DPE-#### — short for Data Portal Error.
The code names the condition, not the wording. Copy gets improved over time; the code does not
change with it, so it is safe to search for on this page, to bookmark, or to quote to support. The
same codes appear in Data Portal API responses, so a failure reads the same whether you hit it in
the console or from a script.
This page lists every code the product can return, what each one means, and what to do about it.
If you do not have a code in hand, start from Troubleshooting
instead, which routes by symptom.
Alongside the code, each error shows a short reference. That identifies your specific
occurrence rather than the class of problem, so include it when you contact support — it is
what lets us find the exact event in our logs.
How to read an entry
Every entry says what happened and, where you can act on it, what to do next. The category tells you whether acting is worth your time at all:
Some entries go on to give steps for particular kinds of connection, under On and the connection
type — for example On AWS Glue. When your connection is one of those listed, the Data Portal
shows you those steps in place of the general ones.
The first digit groups the code by the area it comes from:
Connections and data sources | Platform | Request validation | Ingestion and tasks | Queries | Schema and table configuration
Connections and data sources
DPE-1041 — Not enough records to sample
The source was reached, but no records came back to sample, so the schema could not be inferred. User correctable — you can correct this. What to do- For a stream, confirm the topic still holds messages: the sample starts at the earliest retained message, so an empty or fully expired topic returns nothing.
- Check Data Format on the Data Setup step matches what producers write. Messages that do not decode are skipped, so a wrong format samples nothing.
- For files, confirm the selected files contain rows, not only a header or empty marker files.
- Then select Show Sample Data again, or Fetch Preview on the dataset’s Schema tab.
- Check the file holds rows below its header; a file with only a header, or an empty one, has nothing to sample.
- For CSV, check Custom Delimiter and Skip File Header on Connection Setup match the file.
- Then upload the file again and select Show Sample Data.
- Confirm the topic still holds messages: the sample starts at the earliest retained message, so an empty or fully expired topic returns nothing.
- Check Data Format on the Data Setup step matches what producers write. Messages that do not decode are skipped, so a wrong format samples nothing.
- Then select Show Sample Data again, or Fetch Preview on the dataset’s Schema tab.
- Confirm the selected files contain rows, not only a header or empty marker files.
- Check Data Format and the Include Glob Pattern on the Data Setup step select the data files.
- Then select Show Sample Data again, or Fetch Preview on the dataset’s Schema tab.
DPE-1042 — Catalog rejected our credentials
The catalog refused to list its databases with the credentials on this connection. User correctable — you can correct this. What to do- For AWS Glue or Amazon S3 Tables, check the Metastore Region is the catalog’s region, and that the Access Key and Secret Key are active or IAM Role ARN names a role that trusts StarTree.
- Grant that identity the catalog actions in the IAM Policy under IAM Policy Creation Steps, such as glue:GetDatabases or s3tables:ListNamespaces.
- For Unity Catalog, replace an expired or revoked Personal Access Token.
- Then select Test Connection, or Edit, Test and Update on the dataset’s Connection tab.
DPE-1043 — Catalog configuration incomplete
This connection was saved without the catalog settings needed to browse it, such as which catalog it points at. User correctable — you can correct this. What to do- Create the connection again with Connect external table: choose the catalog under Select Source Type, fill in Connection Setup and select Test Connection. The form sets the catalog type for you.
- If the connection was created through the API, send catalogType together with that catalog’s catalog.* properties.
DPE-1044 — Kafka credentials rejected
The Kafka brokers rejected the Username and Password on this connection for its SASL mechanism. User correctable — you can correct this. What to do- Check Username and Password for a typo or a rotated password.
- Confirm the brokers accept the selected SASL Mechanism and the user exists for it. SCRAM SHA 256 and SCRAM SHA 512 credentials are created separately, so a user made for one is rejected by the other.
- Correct them on Connection Setup and select Test Connection. For an existing dataset, select Edit on its Connection tab, change them, then Test and Update.
- In Confluent Cloud, open the cluster, then API Keys, and create a key for this cluster.
- Enter it in API Key and API Secret on Connection Setup, or with Edit on the Connections page or the dataset’s Connection tab.
- Click Test, then Update.
DPE-1045 — Could not create the stream consumer
The Kafka client could not be created from this connection’s settings, so the brokers were never contacted. User correctable — you can correct this. What to do- Check Broker URL is a comma-separated list of host:port entries, and that each host name resolves from StarTree.
- If Security Protocol is SSL, paste Server Certificate, Client Certificate and Client Key as complete PEM blocks, including their BEGIN and END lines.
- Correct it on Connection Setup and select Test Connection. For an existing dataset, select Edit on its Connection tab, change it, then Test and Update.
DPE-1046 — The decoder for this data format could not be set up
The settings for the selected Data Format could not be turned into a working message decoder, so no messages were read. User correctable — you can correct this. What to do- For Kafka with AVRO, fill in Schema Registry URL, plus Schema Registry Key and Schema Registry Secret if the registry requires them.
- For PROTOBUF with a Descriptor File, give a Descriptor File Path StarTree can read and the Proto Class Name.
- For Kinesis with AVRO, Schema must be a valid Avro schema in JSON.
- Fix it on the Data Setup step, then select Show Sample Data.
- For AVRO or JSON, check Decoder Class Name, and fill in Schema Registry URL, plus Schema Registry Key and Schema Registry Secret if the registry requires them.
- For PROTOBUF, check Schema Source and the settings it asks for.
- Fix it on the Data Setup step, then select Show Sample Data.
- For AVRO, Schema must be a valid Avro schema in JSON.
- Fix it on the Data Setup step, then select Show Sample Data.
DPE-1047 — Delta table could not be read
The Delta table could not be opened at the configured location. User correctable — you can correct this. What to do- Point the table URI at the Delta table’s root folder, the one that contains _delta_log, using the s3a:// scheme.
- Confirm the access key and secret key, or the role, can list and read that folder, including _delta_log.
- Send the same test or preview request again. Delta Lake is not offered in the Data Portal wizard, so this is checked through the API only.
DPE-1048 — Preview could not read the source data
We reached the source but could not read the data needed to build a preview. User correctable — you can correct this. What to do- Set the data format to the files’ real format: Data Format on the Data Setup step, or inputFormat in the request when calling the API.
- Show details lists the files that could not be decoded and the format that was tried.
- Then run the preview again.
DPE-1049 — Not authorized to preview this table
Your account is not allowed to read the connection or table this preview uses. Informational — not a failure; act only if you want a different outcome. What to do- Ask a workspace administrator for a role that can read this connection and its tables, then reload the page.
DPE-1050 — No files matched the path
There were no data files to sample at the location you chose: the catalog table has no Parquet files yet, or nothing under the path matched. User correctable — you can correct this. What to do- If you picked a catalog table, confirm it holds data. A new or emptied table has no files to preview.
- If you picked a path, choose a Prefix, or an S3 Input Directory URI and Include Glob Pattern, that reaches the Parquet files rather than a parent or sibling folder.
- Then select Show Sample Data again.
DPE-1051 — Preview is busy right now
Too many previews are running in this environment at once, so this one was turned away before it read any data. Nothing is wrong with the connection. Transient — temporary; retrying usually works. What to do- Wait a few seconds, then run the preview again.
DPE-1052 — A setting on this connection was not accepted
A setting on this connection or its data setup was checked and rejected before any data was read: a sampling limit, a file format, or a catalog setting outside what the source accepts. User correctable — you can correct this. What to do- Select Show details: it names the setting and the value it accepts.
- Correct it where it is set: Data Format, Include Glob Pattern or Additional Config on the Data Setup step, or the connection’s own settings for a catalog. If it names a region, set Region to the bucket’s region.
- Then select Show Sample Data, or Test Connection, again.
DPE-1053 — The file could not be read
The file{file} could not be read. It may be incomplete, or it may not be in the selected Data Format ({format}).
User correctable — you can correct this.
What to do
- Set Data Format to the file’s real format, on the Data Setup step (on Connection Setup for Upload File).
- If the folder also holds other files, such as _SUCCESS markers or manifests, add an Include Glob Pattern that matches only the data files, such as one ending in *.parquet. The smallest file is read first, so one stray file fails the preview.
- If Show details mentions Access Denied, grant this connection read access to that path.
- Then select Show Sample Data again.
{file} could not be read. It may be incomplete, or it may not be in the selected Data Format ({format}).
- Set Data Format on Connection Setup to the file’s real format.
- If the format is right, the file may be cut short or damaged; export it again and upload it.
- Then select Show Sample Data again.
DPE-1054 — No files matched that path
Nothing could be read at{path}: no files there matched, or the storage service refused to list it.
User correctable — you can correct this.
What to do
- Check S3 Input Directory URI (or the GCS or ADLS equivalent) for a typo, and that files exist under it.
- On the Data Setup step, check the Include Glob Pattern does not exclude every file.
- If Show details says Access Denied, grant this connection’s identity s3:ListBucket on the bucket. If it says to use the specified endpoint, set Region to the bucket’s region.
- Then select Test Connection or Show Sample Data again.
DPE-1055 — Access was denied while reading this table
The credentials on this connection were refused the{action} permission needed to read the table, so it could not be previewed.
User correctable — you can correct this.
What to do
- Grant
{action}to the identity on this connection: the Metastore credentials for catalog actions, the Storage credentials for s3: and kms: actions. For Unity Catalog, grant it in Databricks to the principal behind this connection. - A new grant can take a minute to apply.
- Then select Show Sample Data, or Fetch Preview on the dataset’s Schema tab. Test Connection only lists the catalog, so it cannot confirm this grant.
DPE-1056 — The storage credentials cannot read that data
The storage credentials on this connection were refused when reading the data file{path}, so the table could not be previewed or created. The catalog listed the table; only reading its files was denied.
User correctable — you can correct this.
What to do
- In AWS IAM, allow s3:GetObject on that bucket and prefix for the Storage identity: the user behind Access Key, the role in IAM Role ARN, or the role in IAM Role Name.
- If the files are encrypted with a KMS key, allow kms:Decrypt on that key for the same identity.
- Then click Show Sample Data again. Test Connection does not read data files, so it can pass while this read is refused.
DPE-1057 — The catalog would not let us sign in
The catalog refused to sign this connection in, so its tables could not be listed. Credentials that expired or were revoked, AWS keys that are no longer accepted, or credentials issued for a different workspace or account than the catalog all end this way. User correctable — you can correct this. What to do- Open the connection from the Connections page or the dataset’s Connection tab and click Edit.
- Under Metastore, re-enter what the authentication type asks for: Personal Access Token, OAuth Client ID and OAuth Client Secret, or Access Key and Secret Key, from the workspace or account that owns the catalog.
- Click Test, then Update.
- Open the connection from the Connections page or the dataset’s Connection tab and click Edit.
- Under Metastore, re-enter the Personal Access Token, or the OAuth Client ID and OAuth Client Secret, from the Databricks workspace that owns the catalog.
- Click Test, then Update.
- Open the connection from the Connections page or the dataset’s Connection tab and click Edit.
- Under Metastore, re-enter the OAuth Client ID and OAuth Client Secret of a principal in the account that owns the catalog.
- Click Test, then Update.
- Open the connection from the Connections page or the dataset’s Connection tab and click Edit.
- Under Metastore, re-enter the Personal Access Token (PAT) of a Snowflake user in the account that owns the catalog.
- Click Test, then Update.
- Open the connection from the Connections page or the dataset’s Connection tab and click Edit.
- Under Metastore, re-enter the Access Key and Secret Key, or the IAM Role ARN, of an identity in the AWS account that owns the catalog.
- Click Test, then Update.
- Open the connection from the Connections page or the dataset’s Connection tab and click Edit.
- Check Table Bucket ARN names a table bucket in the AWS account the connection signs in to, then re-enter the Access Key and Secret Key, or the IAM Role ARN, of an identity in that account.
- Click Test, then Update.
DPE-1058 — The bucket could not be listed
Listing bucket{bucket} was refused for the identity this connection uses, so its folders and files could not be browsed.
User correctable — you can correct this.
What to do
- Allow s3:ListBucket on
{bucket}and s3:GetObject on its objects for the user behind Access Key or the role in IAM Role ARN; for IAM Role, the IAM Policy under IAM Policy Creation Steps lists exactly these. - With IAM Node Role, the role in IAM Role Name is in StarTree’s account, so grant it in the bucket policy. For a GCS bucket, give the HMAC key’s service account read access.
- Then click Test Connection, or Test and Update on a saved connection.
- Check HMAC Access ID and HMAC Secret on the connection are an active key pair; Cloud Storage answers Access denied for a key it does not recognise as well.
- Grant the service account that owns the key storage.objects.list on the bucket and storage.objects.get on its objects, for example through the Storage Object Viewer role.
- Click Test, then Update.
DPE-1059 — The streaming source rejected our credentials
The streaming source refused this connection’s credentials while the topic’s partitions were being read, so no sample could be fetched. User correctable — you can correct this. What to do- Open the connection from the Connections page or the dataset’s Connection tab, click Edit, and re-enter API Key and API Secret (Confluent Cloud) or Username, Password and SASL Mechanism.
- Use a key created for this Kafka cluster rather than a global or Cloud API key, and allow its principal to describe and read the topic.
- Click Test, then Update, then click Show Sample Data again.
DPE-1060 — The storage credentials were rejected
AWS rejected the storage credentials on this connection ({reason}). Keys that are wrong, inactive or temporary, or a role StarTree is not trusted to assume, are refused this way.
User correctable — you can correct this.
What to do
- Edit the connection from the Connections page or the dataset’s Connection tab.
- With Access Key and Secret Key, re-enter both from one active, long-term key pair in AWS IAM.
- With IAM Role, apply the Trust Policy under IAM Policy Creation Steps, with its StarTree Account ID and External ID, to the role in IAM Role ARN.
- Click Test, then Update. If Reuse metastore credentials is Yes, fix them under Metastore.
DPE-1061 — That role could not be assumed
The role named in IAM Role ARN on this connection refused to let StarTree assume it, so the storage behind it could not be read. User correctable — you can correct this. What to do- Check IAM Role ARN is the exact ARN of the role in your AWS account.
- In the AWS console, set that role’s trust policy to the Trust Policy shown under IAM Policy Creation Steps on this connection. It names the StarTree principal and the External ID to require.
- A trust policy change can take a minute to apply.
- Then select Test on the dataset’s Connection tab, or Test Connection in the wizard, rather than waiting for the next ingestion run.
- Check IAM Role ARN is the exact ARN of the role in your AWS account.
- In AWS IAM, set that role’s trust policy to trust the Startree IAM Role ARN shown on the connection form, and to require the External ID shown with it.
- A trust policy change can take a minute to apply; then click Test Connection, or Test then Update on a saved connection.
DPE-1062 — The starting snapshot is not in this table
This dataset is set to start syncing{table} from snapshot {snapshotId}, which that table does not have, so its first sync cannot start. An id copied from another table, or one expired before the first sync, causes this.
User correctable — you can correct this.
What to do
- On the dataset’s Configuration tab, click Edit, remove iceberg.snapshotProcessing.initialSnapshotId and iceberg.snapshotProcessing.initialVersionSelector, then click Apply and Save; the next sync starts from the latest snapshot.
- To start earlier, use an id from this table’s own snapshot history.
- If the dataset was created with SQL, recreate it without snapshot_id.
DPE-1063 — This catalog type is not available in this environment yet
The connection type you picked is newer than the version of StarTree running in this environment, so its storage could not be opened for browsing, previewing or syncing. This is on our side; nothing you entered caused it. Internal — a defect on our side. What to do- Contact StarTree support and quote the reference shown with this error. The environment needs an upgrade before this connection type can be used.
- There is nothing to change on the connection in the meantime. Once the upgrade is in place, click Test on it again.
DPE-1064 — That sign-in needs a one-time passcode
Snowflake refused the sign-in because the Database User on this connection must also enter a one-time passcode, which a stored password cannot supply. User correctable — you can correct this. What to do- In Snowflake, give StarTree a user that signs in with a key pair, ideally a service user with an RSA public key assigned. Key-pair sign-in does not ask for a passcode.
- Open the connection from the Connections page or the dataset’s Connection tab, click Edit, set Database User to that user, choose Key Pair Authentication and paste its Private Key, plus Private Key Password if the key is encrypted.
- Click Test, then Update.
DPE-1065 — No readable Parquet files at that path
No readable Parquet file was found under{path}, so the table’s columns could not be worked out. Only objects whose names end in .parquet are read.
User correctable — you can correct this.
What to do
- On the Select Path step, set Prefix to the folder that holds the table’s .parquet files, as deep as possible, then click Show Sample Data again.
- Confirm the files’ names end in .parquet; files without that extension are skipped.
- If the files are still being written, try again once the writer has finished.
DPE-1066 — That table is no longer in the catalog
The catalog has no table{table}, so it could not be read. A table dropped or renamed at the source, or a connection whose Catalog Name now points at another catalog, causes this.
User correctable — you can correct this.
What to do
- Check in the source catalog that the table still exists under that exact name, and that this connection’s credentials can see it.
- If the connection’s Catalog Name was changed, set it back: Edit the connection, then click Test and Update.
- If the table was renamed or moved, connect it as a new dataset with Connect external table on the Tables page.
- Check in the S3 console that the table bucket holds a table with that exact namespace and name, and that this connection’s credentials can see it.
- Check Table Bucket ARN on the connection names that table bucket: Edit the connection, then click Test and Update.
- If the table was renamed or moved, connect it as a new dataset with Connect external table on the Tables page.
DPE-1067 — That access key is not recognised
AWS does not recognise the Access Key on this connection, so the data could not be read. A key that was deleted or deactivated fails this way, and so does a temporary key (one starting ASIA), which also needs a session token, a field this form lacks. User correctable — you can correct this. What to do- In AWS IAM, check the key is listed as Active for its user, or create a new long-term access key for an IAM user.
- Open the connection from the Connections page or the dataset’s Connection tab, click Edit, and enter the new Access Key and Secret Key.
- Click Test, then Update; the new key reaches every table on this connection that is still in sync.
- In AWS IAM, check the key is listed as Active for its user, or create a new long-term access key for an IAM user.
- Set Authentication Type to Basic, then enter the key in Access Key and Secret Key, on Connection Setup or with Edit on a saved connection.
- Click Test Connection, or Test then Update on a saved connection.
DPE-1068 — Object storage refused the request
Object storage answered Forbidden when we read an object. That answer carries no reason: a missing permission, a bucket policy denial and an inactive key look the same. User correctable — you can correct this. What to do- Grant this connection’s identity s3:GetObject on the files and s3:ListBucket on the bucket. The IAM Policy under IAM Policy Creation Steps (shown for IAM Role) lists both.
- Check no bucket policy denies that identity, and that any Access Key and Secret Key are still active.
- Select Show Sample Data again to confirm. Test Connection only lists the bucket, so it can pass while reads are still refused.
DPE-1069 — That table is not an Iceberg table
The table you picked is in the catalog but cannot be read as Iceberg, so it cannot be used as an external table. Unity Catalog says this of a Delta table without Iceberg reads turned on; AWS Glue of a table not registered as Iceberg. User correctable — you can correct this. What to do- For a Unity Catalog Delta table, enable Iceberg reads (UniForm) on it in Databricks, then pick it again on the Select Table step.
- For AWS Glue, pick a table whose table type is ICEBERG. Plain Parquet files in S3 can be connected through an S3 Data Lake connection instead.
- Views and tables in other formats cannot be used, even though they are listed.
- In Databricks, enable Iceberg reads (UniForm) on this Delta table, then pick it again on the Select Table step.
- Views and tables in other formats cannot be used, even though they are listed.
- Pick a table whose table type is ICEBERG. Plain Parquet files in S3 can be connected through an S3 Data Lake connection instead.
- Views and tables in other formats cannot be used, even though they are listed.
DPE-1070 — The connection test could not run
The test could not start because no file system is set for this connection, so whether its other settings are correct is still unknown. Internal — a defect on our side. What to do- For a Custom connection, Datasource Properties must name the file system in input.fs.className, as the batch ingestion docs show; add it, then click Test Connection.
- For any other source type, contact StarTree support and quote the reference shown with this error. Trying the test again gives the same result.
- Restore the input.fs.className line in Connection Properties as the form filled it in; the quickest way is to start again from Create Connection, which fills it for you.
- Then click Test Connection. For a saved connection, click Edit on the Connections page, restore it, then Test and Update.
DPE-1071 — The source took too long to answer
The source did not answer within 30 seconds while its topics were being listed, so the request stopped before it finished. Transient — temporary; retrying usually works. What to do- Try again in a moment.
- If it times out again, check Broker URL, that Security Protocol matches the listener at that address, and that the cluster accepts traffic from StarTree through its allow-list or private link.
DPE-1072 — The catalog’s reply was cut off
The Iceberg catalog began sending the details of{table}, but the reply stopped partway through, so the table could not be read. When a reply stops at the same point on every attempt, a size limit is the usual cause, and trying again on its own will not help.
Upstream — a service we depend on did not answer as expected.
What to do
- Expire old snapshots on
{table}. The catalog sends the table’s full snapshot history in this reply, and a long history makes it very large. - If a proxy or gateway sits in front of the catalog, check whether it limits the size of responses.
- If the reply is still cut off, contact StarTree support and quote the reference shown with this error.
DPE-1073 — StarTree’s connections can’t be changed
This connection was created by StarTree, so it can’t be edited or deleted. StarTree sets it up again from its own configuration every time the service starts. Informational — not a failure; act only if you want a different outcome. What to do- To use different settings, create a new connection and build your tables from it.
DPE-1074 — Databricks refused the OAuth scope this connection requests
Databricks would not sign this connection in because the scope StarTree requests for Unity Catalog,{scope}, is not assigned to its OAuth client. That happens when the client’s OAuth secret was created for a narrower set of scopes.
User correctable — you can correct this.
What to do
- In Databricks, open the service principal whose application ID is this connection’s OAuth Client ID and generate a new OAuth secret that includes the
{scope}scope. - Edit the connection, paste the new secret into OAuth Client Secret, then click Test and Update.
- Alternatively, switch REST Authentication Type to Personal Access Token.
DPE-1075 — This catalog type is not available in this environment yet
The connection type you picked is newer than the version of StarTree running in this environment, so the catalog could not be opened. This is on our side; nothing you entered caused it. Internal — a defect on our side. What to do- Contact StarTree support and quote the reference shown with this error. The environment needs an upgrade before this connection type can be used.
- There is nothing to change on the connection in the meantime. Once the upgrade is in place, click Test on it again.
DPE-1076 — AWS access keys are needed to sign in to this catalog
This connection signs in to AWS with an access key, but its Access Key, Secret Key or Region was empty. It also happens when IAM Role or IAM Node Role is chosen in an environment that cannot yet use a role for this catalog. User correctable — you can correct this. What to do- Edit the connection and, under Metastore, choose the Authentication Type that asks for an Access Key and Secret Key.
- Fill in Access Key, Secret Key and Region, then click Test and Update. If Reuse metastore credentials is set to No, do the same under Storage.
- To sign in with an IAM role instead, contact StarTree support and quote the reference shown with this error.
DPE-1077 — The AWS account ID for this Glue catalog is missing
An AWS Glue catalog is identified by the AWS account that owns it, and this connection did not include that account ID, so the catalog could not be opened. User correctable — you can correct this. What to do- Edit the connection and fill in AWS Account ID with the 12-digit ID of the account that owns the Glue Data Catalog. Connections created with the older Iceberg REST option call this field Warehouse.
- Click Test, then Update.
DPE-1078 — That catalog could not be found
The catalog service found no catalog matching the name saved on this connection, so its databases could not be listed. A misspelled name is the usual cause; a catalog the connection’s identity is not allowed to see can look the same. User correctable — you can correct this. What to do- Check Catalog Name on the connection (Database on Snowflake Horizon Catalog) against the catalog’s exact name in the source system.
- Confirm the Catalog Endpoint URI points at the workspace or account that holds the catalog, and that the connection’s identity has access to it.
- Edit the connection to correct it, then click Test and Update.
- Check Catalog Name on the connection against the catalog’s exact name in the source system.
- Confirm Catalog Endpoint URI points at the workspace or account that holds the catalog, and that the connection’s identity can use it.
- Check Database on the connection against the Snowflake database’s exact name.
- Confirm Catalog Endpoint URI points at the account that holds it.
- Check AWS Account ID on the connection is the numeric ID of the account that owns the Glue Data Catalog.
- Check Region under Metastore is the region of that catalog.
- Check Table Bucket ARN on the connection is the full ARN of the table bucket, copied from the S3 console.
- Check Region under Metastore is the region in that ARN.
DPE-1079 — The source table for this preview was not chosen
The preview did not know which table in the catalog to read: it needs a database and a table name, and at least one was missing, so no rows could be sampled. User correctable — you can correct this. What to do- Go back to Select Table (Select Path for an S3 or GCS data lake), choose the table or folder again, and preview once more. Choosing it fills in both values.
- If you call the API directly, set both the namespace and the table name in the catalog’s table settings. The setup flow uses default for both on an S3 or GCS data lake.
- If the setup flow still shows this, contact StarTree support and quote the reference shown with this error.
DPE-1080 — A decimal column could not be read
Column{column} stores its decimal values in an integer-based encoding that the version of StarTree in this environment cannot read, so the preview stopped. This is on our side; the data itself is fine.
Internal — a defect on our side.
What to do
- Contact StarTree support and quote the reference shown with this error. A newer version reads this encoding, so the fix is an upgrade, not a change to your data.
DPE-1081 — A data file for this table is missing from storage
The preview found{file} in the table’s file list, but storage said the file does not exist when it was opened. A file deleted or moved after it was listed, by a cleanup job, a lifecycle rule or a rewrite in progress, causes this.
User correctable — you can correct this.
What to do
- Check whether that file is still in the bucket.
- If a cleanup job or lifecycle rule removed it, restore the file, or rewrite the table so it no longer lists the file.
- If files under this path are being rewritten right now, wait for the write to finish and preview again.
DPE-1082 — No credentials were available to read the data files
The table’s data files are in a bucket that needs AWS credentials, but no access key or role reached the reader that opens them, so the preview could not read them. User correctable — you can correct this. What to do- Edit the connection and, under Storage, choose the Authentication Type that asks for an Access Key and Secret Key (on AWS Glue and Amazon S3 Tables, first set Reuse metastore credentials to No).
- Enter a key that can read the bucket holding the table’s data files, set Region, then click Test and Update.
- If keys were already set, contact StarTree support and quote the reference shown with this error.
DPE-1083 — The JSON file stops partway through a record
Preview reads about the first 1 MB of a JSON file, and{file} ended partway through a record inside that part. Its records are too large, or are wrapped in one top-level object, to fit there, or the file itself is cut short.
User correctable — you can correct this.
What to do
- Save the data as newline-delimited JSON, one compact record per line without indentation, so whole records fit in the part preview reads.
- Do not wrap the records in a single top-level object. A list of records, or one record per line, both work.
- If the file is under 1 MB, it is incomplete: export it again, replace or re-upload it, and preview the data again.
DPE-1084 — The Kafka sign-in setting is not valid
The connection’s SASL sign-in setting (sasl.jaas.config) does not start with a login module and the word required, so the stream consumer could not be created. User correctable — you can correct this. What to do- If you set sasl.jaas.config under Datasource Properties, give only its value: the login module name, the word required, username and password in double quotes, then a semicolon.
- Remove anything before the module name, such as a pasted property name and equals sign, or a ****** placeholder.
- Or create a new connection with just Username and Password (API Key and API Secret for Confluent Cloud), then run Test Connection.
DPE-1085 — No AWS credentials are set on this connection
The Kinesis connection has no access key or role to sign in to AWS with, so the list of streams could not be read. User correctable — you can correct this. What to do- On the Connection Setup step, or after Edit on the dataset’s Connection tab, set Authentication Type and fill in Access Key and Secret Key, or the IAM Role ARN for StarTree to assume.
- Run Test Connection, or Test then Update on a saved connection; the streams load once AWS accepts the credentials.
- If Authentication Type is already IAM Role, the environment could not get the identity it uses to assume your role: contact StarTree support and quote the reference shown with this error.
DPE-1086 — The AWS identity lacks a Kinesis permission
AWS refused{action} for the user or role this connection signs in with: no policy attached to it allows that action, or one denies it.
User correctable — you can correct this.
What to do
- In AWS IAM, allow
{action}in a policy attached to that user or role. - Allow kinesis:ListShards, kinesis:GetShardIterator and kinesis:GetRecords on the stream as well; ingestion needs them to read it.
- Run Test Connection again once the policy is saved. IAM changes can take a minute to apply.
DPE-1087 — The Google Cloud key is incomplete
The Authentication Json on this connection is not a complete service account key, so the connection could not sign in to Google Cloud. User correctable — you can correct this. What to do- In the Google Cloud console, open IAM & Admin, then Service Accounts, choose the account, and add a new JSON key under Keys.
- Paste the whole downloaded file into Authentication Json without editing it. It must include type, client_id, client_email, private_key and private_key_id; a base64-encoded copy of the file also works.
- Run Test Connection, or Test then Update on a saved connection.
DPE-1088 — That AWS region is not valid
The Region on this connection is not an AWS region code, so the address used to sign in to AWS could not be built. User correctable — you can correct this. What to do- Set Region to the code of the region your bucket or stream is in, in lowercase with hyphens, for example us-east-1 or eu-west-2.
- Run Test Connection before saving.
- Set Region to the code of the region the stream is in, in lowercase with hyphens, for example us-east-1 or eu-west-2.
- Click Test Connection, or Test then Update on a saved connection.
DPE-1089 — The sample data connection could not sign in
The access key behind StarTree’s built-in sample data connection is no longer accepted, so its files could not be listed. This is on our side, not a problem with your settings. Internal — a defect on our side. What to do- If your connection list includes the newer sample connection, s3DemoV4, use it. Datasets built from an older sample connection keep its expired key and need to be created again from the new one.
- Otherwise contact StarTree support and quote the reference shown with this error; your environment needs an update to restore the sample data.
DPE-1090 — The starting snapshot is not in this table
This dataset is set to start syncing{table} from a snapshot id the catalog does not have for this table, so the first sync stops before reading anything. An id copied from another table, or one since expired, causes this.
User correctable — you can correct this.
What to do
- On the Configuration tab, click Edit, remove iceberg.snapshotProcessing.initialSnapshotId and iceberg.snapshotProcessing.initialVersionSelector, then click Apply and Save. The first sync then starts from the latest snapshot.
- To start earlier, use an id from this table’s own snapshot history.
- If the dataset was created with SQL, recreate it without snapshot_id.
DPE-1091 — The catalog refused this table’s sync sign-in
The lakehouse catalog refused the sign-in this table’s sync used. A table keeps its own copy of its connection’s sign-in details and syncs with that copy, so it can be refused even when Test Connection passes for the connection. User correctable — you can correct this. What to do- On the table’s Connection tab, click Edit and re-enter the sign-in details the catalog refused: the Personal Access Token, or the OAuth Client ID and OAuth Client Secret.
- If the tab shows the connection, click Test, then Update; every table in sync with the connection gets the new details. If it shows this table’s own settings, click Save; it tests them first and changes this table only.
- If the sync is still refused, this table’s copy was not reached or still holds an older sign-in: open the Configuration tab, click Edit, and in the ExternalTableSyncTask settings correct the sign-in entries and delete those for a method the connection no longer uses; then Apply and Save.
- Click Sync Now to run the sync again.
- On the table’s Connection tab, click Edit and re-enter the sign-in the catalog refused: the Personal Access Token, or the OAuth Client ID and OAuth Client Secret, whichever the connection uses.
- If the tab shows the connection, click Test, then Update; every table in sync with the connection gets the new details. If it shows this table’s own settings, click Save; it tests them first and changes this table only.
- If the sync is still refused, this table’s copy was not reached or still holds an older sign-in: open the Configuration tab, click Edit, and in the ExternalTableSyncTask settings correct the sign-in entries and delete those for a method the connection no longer uses; then Apply and Save.
- Click Sync Now to run the sync again.
- On the table’s Connection tab, click Edit and re-enter the OAuth Client ID and OAuth Client Secret the catalog refused.
- If the tab shows the connection, click Test, then Update; every table in sync with the connection gets the new details. If it shows this table’s own settings, click Save; it tests them first and changes this table only.
- If the sync is still refused, this table’s copy was not reached or still holds an older sign-in: open the Configuration tab, click Edit, and in the ExternalTableSyncTask settings correct the sign-in entries and delete those for a method the connection no longer uses; then Apply and Save.
- Click Sync Now to run the sync again.
- On the table’s Connection tab, click Edit and re-enter the Personal Access Token (PAT) the catalog refused, with a Snowflake role restriction that matches OAuth Scopes.
- If the tab shows the connection, click Test, then Update; every table in sync with the connection gets the new details. If it shows this table’s own settings, click Save; it tests them first and changes this table only.
- If the sync is still refused, this table’s copy was not reached or still holds an older sign-in: open the Configuration tab, click Edit, and in the ExternalTableSyncTask settings correct the sign-in entries and delete those for a method the connection no longer uses; then Apply and Save.
- Click Sync Now to run the sync again.
DPE-1092 — The catalog refused the requested OAuth scope
The catalog’s sign-in service would not grant the OAuth scope this connection asks for, so the connection could not sign in to the catalog. User correctable — you can correct this. What to do- Set OAuth Scopes on the connection to a scope the catalog grants this client.
- On an existing table, make the change from its Connection tab: click Edit, then, if the tab shows the connection, Test and Update, which reaches every table in sync with it; if it shows this table’s own settings, Save. Then click Sync Now.
- Set OAuth Scopes to PRINCIPAL_ROLE:ALL, or to PRINCIPAL_ROLE: followed by a principal role granted to the client.
- On an existing table, make the change from its Connection tab: click Edit, then, if the tab shows the connection, Test and Update, which reaches every table in sync with it; if it shows this table’s own settings, Save. Then click Sync Now.
- Set OAuth Scopes to session:role: followed by the Snowflake role the PAT is restricted to; the two must name the same role.
- On an existing table, make the change from its Connection tab: click Edit, then, if the tab shows the connection, Test and Update, which reaches every table in sync with it; if it shows this table’s own settings, Save. Then click Sync Now.
- Unity Catalog accepts the all-apis scope. In the connection’s Connection Properties, set catalog.iceberg-rest.auth.rest.oauthScopes back to all-apis, then click Test.
- On an existing table, make the change from its Connection tab: click Edit, then, if the tab shows the connection, Test and Update, which reaches every table in sync with it; if it shows this table’s own settings, Save. Then click Sync Now.
DPE-1093 — The OAuth sign-in address did not issue a token
The URI this connection uses to request OAuth tokens did not answer like an OAuth sign-in endpoint, so the connection could not sign in to the catalog. User correctable — you can correct this. What to do- In the connection’s OAuth settings, enter the full https URI for requesting tokens, not a path.
- On an existing table, make the change from its Connection tab: click Edit, then, if the tab shows the connection, Test and Update, which reaches every table in sync with it; if it shows this table’s own settings, Save. Then click Sync Now.
- Set the URI for requesting OAuth tokens to the workspace URL followed by /oidc/v1/token.
- Do not leave it empty: Unity Catalog has no path of its own for issuing tokens.
- On an existing table, make the change from its Connection tab: click Edit, then, if the tab shows the connection, Test and Update, which reaches every table in sync with it; if it shows this table’s own settings, Save. Then click Sync Now.
- Set the URI for requesting OAuth tokens to the Catalog Endpoint URI followed by /v1/oauth/tokens, such as https://polaris.example.com/api/catalog/v1/oauth/tokens.
- If the catalog signs principals in through a separate identity provider, enter the address where that provider issues tokens instead.
- On an existing table, make the change from its Connection tab: click Edit, then, if the tab shows the connection, Test and Update, which reaches every table in sync with it; if it shows this table’s own settings, Save. Then click Sync Now.
DPE-1094 — AWS rejected the access key and secret key
AWS refused the request because the access key and secret key on this connection do not work together: the secret does not belong to the key, or the key is not recognised. User correctable — you can correct this. What to do- Re-enter the access key and its matching secret wherever this connection uses a pair: under Metastore, under Storage, or both. A key that was rotated or deactivated at the source has to be replaced here as well.
- On an existing table, make the change from its Connection tab: click Edit, then, if the tab shows the connection, Test and Update, which reaches every table in sync with it; if it shows this table’s own settings, Save. Then click Sync Now.
- Re-enter the Access Key and its matching Secret Key under Metastore, and under Storage as well when Reuse metastore credentials is No. A key rotated or deactivated in AWS has to be replaced here too.
- On an existing table, make the change from its Connection tab: click Edit, then, if the tab shows the connection, Test and Update, which reaches every table in sync with it; if it shows this table’s own settings, Save. Then click Sync Now.
- Re-enter the Access Key and its matching Secret Key under Storage. A key rotated or deactivated in AWS has to be replaced here too.
- On an existing table, make the change from its Connection tab: click Edit, then, if the tab shows the connection, Test and Update, which reaches every table in sync with it; if it shows this table’s own settings, Save. Then click Sync Now.
- Re-enter the HMAC Access ID and the HMAC Secret created with it, from the Interoperability settings of Cloud Storage.
- On an existing table, make the change from its Connection tab: click Edit, then, if the tab shows the connection, Test and Update, which reaches every table in sync with it; if it shows this table’s own settings, Save. Then click Sync Now.
DPE-1095 — The Region does not match the catalog’s region
AWS refused the catalog request because it was signed for a different region from the catalog endpoint it was sent to. User correctable — you can correct this. What to do- Set Region to the region of the AWS catalog this connection reads.
- On an existing table, make the change from its Connection tab: click Edit, then, if the tab shows the connection, Test and Update, which reaches every table in sync with it; if it shows this table’s own settings, Save. Then click Sync Now.
- Set Region under Metastore to the region of your AWS Glue Data Catalog.
- AWS Glue connections send catalog requests to the Catalog Endpoint URI in the form’s Connection Properties, which defaults to us-west-1. For a catalog in another region, change the region in that address to match, for example glue.us-east-1.
- On an existing table, make the change from its Connection tab: click Edit, then, if the tab shows the connection, Test and Update, which reaches every table in sync with it; if it shows this table’s own settings, Save. Then click Sync Now.
- Set Region under Metastore to the region in the Table Bucket ARN.
- Amazon S3 Tables connections send catalog requests to the Catalog Endpoint URI in the form’s Connection Properties, which defaults to us-west-1. For a table bucket in another region, change the region in that address to match, for example s3tables.us-east-1.
- On an existing table, make the change from its Connection tab: click Edit, then, if the tab shows the connection, Test and Update, which reaches every table in sync with it; if it shows this table’s own settings, Save. Then click Sync Now.
DPE-1096 — The connection’s AWS identity lacks a permission
AWS refused{action} for the identity this connection uses, so the request could not be completed.
User correctable — you can correct this.
What to do
- Add
{action}to the IAM policy of the role or user this connection uses. Where the connection form offers IAM Policy Creation Steps, Show lists every permission it needs. - With IAM Node Role, grant it to the role shown under IAM Role Name.
- AWS can take a minute to apply a policy change; then try again.
DPE-1097 — The catalog account lacks access to this data
The catalog accepted the sign-in but refused the request, because the account behind it has not been granted the privileges needed to read this catalog, schema or table. User correctable — you can correct this. What to do- Grant the account behind this connection’s sign-in read access to the catalog, schema and table at the source.
- Then test the connection again, or click Sync Now on an existing table.
- In Databricks, grant the user or service principal USE CATALOG on the catalog, USE SCHEMA and EXTERNAL USE SCHEMA on the schema, and SELECT on the table.
- Enable external data access on the metastore if it is off.
- Then test the connection again, or click Sync Now on an existing table.
- Grant the client’s principal role a catalog role that can list namespaces and tables and read table data.
- Then test the connection again, or click Sync Now on an existing table.
- In Snowflake, grant the role the PAT is restricted to USAGE on the database and schema, and SELECT on the table.
- Then test the connection again, or click Sync Now on an existing table.
DPE-1098 — The catalog’s host name could not be found
The host name in Catalog Endpoint URI could not be resolved, so StarTree could not reach the catalog. User correctable — you can correct this. What to do- Check Catalog Endpoint URI for a typo in the host name.
- If the catalog is reachable only on a private network, contact StarTree support about private connectivity.
- On an existing table, make the change from its Connection tab: click Edit, then, if the tab shows the connection, Test and Update, which reaches every table in sync with it; if it shows this table’s own settings, Save. Then click Sync Now.
- Check Catalog Endpoint URI: https://, your workspace host, then /api/2.1/unity-catalog/iceberg-rest.
- If the catalog is reachable only on a private network, contact StarTree support about private connectivity.
- On an existing table, make the change from its Connection tab: click Edit, then, if the tab shows the connection, Test and Update, which reaches every table in sync with it; if it shows this table’s own settings, Save. Then click Sync Now.
- Check Catalog Endpoint URI: https://, your Polaris host, then /api/catalog.
- If the catalog is reachable only on a private network, contact StarTree support about private connectivity.
- On an existing table, make the change from its Connection tab: click Edit, then, if the tab shows the connection, Test and Update, which reaches every table in sync with it; if it shows this table’s own settings, Save. Then click Sync Now.
- Check Catalog Endpoint URI: https://, your Snowflake account host, then /polaris/api/catalog.
- If the catalog is reachable only on a private network, contact StarTree support about private connectivity.
- On an existing table, make the change from its Connection tab: click Edit, then, if the tab shows the connection, Test and Update, which reaches every table in sync with it; if it shows this table’s own settings, Save. Then click Sync Now.
DPE-1099 — The catalog could not be reached
StarTree could not open a connection to the catalog, or the catalog stopped answering before it replied, so the request did not complete. Transient — temporary; retrying usually works. What to do- Try again in a moment. A catalog that is restarting or busy can refuse connections briefly.
- If it keeps failing, check the host and port in Catalog Endpoint URI, and that the catalog accepts traffic from StarTree, for example through an allow-list or private connectivity.
- If the settings are right and it still fails, contact StarTree support and quote the reference shown with this error.
DPE-1100 — The catalog’s TLS certificate was not accepted
The catalog presented a certificate StarTree could not verify: it has expired, it is not issued by a public certificate authority, or it does not name the host in Catalog Endpoint URI. User correctable — you can correct this. What to do- Use the host name the certificate was issued for in Catalog Endpoint URI, rather than an IP address or an alias.
- If the catalog uses a private or self-signed certificate, replace it with one from a public certificate authority, or contact StarTree support.
- If the certificate has expired, renew it on the catalog’s side.
- On an existing table, make the change from its Connection tab: click Edit, then, if the tab shows the connection, Test and Update, which reaches every table in sync with it; if it shows this table’s own settings, Save. Then click Sync Now.
DPE-1101 — The Catalog Endpoint URI is not a catalog address
The address in Catalog Endpoint URI is missing, malformed, or points at a web page rather than the catalog’s Iceberg REST endpoint. User correctable — you can correct this. What to do- Enter the catalog’s full Iceberg REST address in Catalog Endpoint URI, with no spaces.
- On an existing table, make the change from its Connection tab: click Edit, then, if the tab shows the connection, Test and Update, which reaches every table in sync with it; if it shows this table’s own settings, Save. Then click Sync Now.
- Set Catalog Endpoint URI to https://, your workspace host, then /api/2.1/unity-catalog/iceberg-rest, with no spaces.
- On an existing table, make the change from its Connection tab: click Edit, then, if the tab shows the connection, Test and Update, which reaches every table in sync with it; if it shows this table’s own settings, Save. Then click Sync Now.
- Set Catalog Endpoint URI to https://, your Polaris host, then /api/catalog, with no spaces.
- On an existing table, make the change from its Connection tab: click Edit, then, if the tab shows the connection, Test and Update, which reaches every table in sync with it; if it shows this table’s own settings, Save. Then click Sync Now.
- Set Catalog Endpoint URI to https://, your Snowflake account host, then /polaris/api/catalog, with no spaces.
- On an existing table, make the change from its Connection tab: click Edit, then, if the tab shows the connection, Test and Update, which reaches every table in sync with it; if it shows this table’s own settings, Save. Then click Sync Now.
DPE-1102 — The connection needs a Region
No region is set for the storage or catalog this connection uses, so its requests could not be signed or routed. User correctable — you can correct this. What to do- Set Region to the AWS region of the bucket that holds the data. It is required even when the catalog vends storage credentials, because vended credentials carry no region.
- With IAM Role as the Authentication Type, the role cannot be assumed until the region is set.
- On an existing table, make the change from its Connection tab: click Edit, then, if the tab shows the connection, Test and Update, which reaches every table in sync with it; if it shows this table’s own settings, Save. Then click Sync Now.
- Set Region under Storage to the AWS region of the bucket that holds the table’s data. It is required even when the catalog vends storage credentials, because those carry no region.
- On an existing table, make the change from its Connection tab: click Edit, then, if the tab shows the connection, Test and Update, which reaches every table in sync with it; if it shows this table’s own settings, Save. Then click Sync Now.
- Set Region under Metastore to the catalog’s region, and under Storage as well when Reuse metastore credentials is No.
- On an existing table, make the change from its Connection tab: click Edit, then, if the tab shows the connection, Test and Update, which reaches every table in sync with it; if it shows this table’s own settings, Save. Then click Sync Now.
- Set Region to the region of the bucket.
- On an existing table, make the change from its Connection tab: click Edit, then, if the tab shows the connection, Test and Update, which reaches every table in sync with it; if it shows this table’s own settings, Save. Then click Sync Now.
DPE-1103 — The Bucket Name is missing or malformed
The connection’s Bucket Name is empty or is not a plain bucket name, so the files in it could not be listed. User correctable — you can correct this. What to do- Enter only the bucket’s name in Bucket Name, for example sales-data, without s3:// or gs://, slashes or a path. Put the folder in the prefix, without a trailing slash.
- When browsing, stay within the connection’s bucket; to read another bucket, create a connection for it.
- On an existing table, make the change from its Connection tab: click Edit, then, if the tab shows the connection, Test and Update, which reaches every table in sync with it; if it shows this table’s own settings, Save. Then click Sync Now.
- Enter only the bucket’s name in Bucket Name, for example sales-data, without s3://, slashes or a path. Put the folder in the prefix, without a trailing slash.
- On an existing table, make the change from its Connection tab: click Edit, then, if the tab shows the connection, Test and Update, which reaches every table in sync with it; if it shows this table’s own settings, Save. Then click Sync Now.
- Enter only the bucket’s name in Bucket Name, for example sales-data, without gs://, slashes or a path. Put the folder in the prefix, without a trailing slash.
- On an existing table, make the change from its Connection tab: click Edit, then, if the tab shows the connection, Test and Update, which reaches every table in sync with it; if it shows this table’s own settings, Save. Then click Sync Now.
DPE-1104 — The storage Endpoint is not a valid address
The Endpoint on this connection is not a complete https address, so the object store could not be contacted. User correctable — you can correct this. What to do- Enter the full address of the object store in Endpoint, starting with https:// and with no spaces.
- On an existing table, make the change from its Connection tab: click Edit, then, if the tab shows the connection, Test and Update, which reaches every table in sync with it; if it shows this table’s own settings, Save. Then click Sync Now.
- Set Endpoint to https://storage.googleapis.com, the default.
- On an existing table, make the change from its Connection tab: click Edit, then, if the tab shows the connection, Test and Update, which reaches every table in sync with it; if it shows this table’s own settings, Save. Then click Sync Now.
DPE-1105 — The HMAC keys could not be read from Secret Manager
This connection reads its HMAC keys from GCP Secret Manager, and they could not be read: a secret name may be wrong, have no enabled version, or be unreadable with the configured service account. User correctable — you can correct this. What to do- Check that Access ID Secret Name and Secret Key Secret Name match secrets in the project set in GCP Project ID, and that each has an enabled version.
- Grant the service account in Service Account Key Path the Secret Manager Secret Accessor role on both secrets.
- Or switch Authentication Type to Inline HMAC Keys and enter the HMAC Access ID and the HMAC Secret directly.
- On an existing table, make the change from its Connection tab: click Edit, then, if the tab shows the connection, Test and Update, which reaches every table in sync with it; if it shows this table’s own settings, Save. Then click Sync Now.
DPE-1106 — The bucket does not exist
The object store reports that the bucket named on this connection does not exist. User correctable — you can correct this. What to do- Check Bucket Name for a typo, and enter only the name, without s3:// or a path.
- If the bucket was deleted or renamed, point the connection at the bucket that now holds the data.
- On an existing table, make the change from its Connection tab: click Edit, then, if the tab shows the connection, Test and Update, which reaches every table in sync with it; if it shows this table’s own settings, Save. Then click Sync Now.
DPE-1107 — The bucket is in a different region
The bucket that holds this data is in a different AWS region from the one set on the connection, so the object store redirected or refused the request instead of answering it. User correctable — you can correct this. What to do- Set the Region in the connection’s storage settings to the bucket’s region, shown in the S3 console’s list of buckets.
- On an existing table, make the change from its Connection tab: click Edit, then, if the tab shows the connection, Test and Update, which reaches every table in sync with it; if it shows this table’s own settings, Save. Then click Sync Now.
- Set Region under Storage to the bucket’s region, shown in the S3 console’s list of buckets.
- On an existing table, make the change from its Connection tab: click Edit, then, if the tab shows the connection, Test and Update, which reaches every table in sync with it; if it shows this table’s own settings, Save. Then click Sync Now.
- Set Region under Storage to the bucket’s region, shown in the S3 console’s list of buckets. If Reuse metastore credentials is Yes, set it to No first, so the storage Region can differ from the catalog’s.
- On an existing table, make the change from its Connection tab: click Edit, then, if the tab shows the connection, Test and Update, which reaches every table in sync with it; if it shows this table’s own settings, Save. Then click Sync Now.
- Set Region to the bucket’s region, shown in the S3 console’s list of buckets.
- On an existing table, make the change from its Connection tab: click Edit, then, if the tab shows the connection, Test and Update, which reaches every table in sync with it; if it shows this table’s own settings, Save. Then click Sync Now.
DPE-1108 — The storage Region does not match the bucket
Bucket{bucket} is in {actualRegion}, but the connection’s storage Region is set to {configuredRegion}.
User correctable — you can correct this.
What to do
- Set the Region in the connection’s storage settings to
{actualRegion}. - On an existing table, make the change from its Connection tab: click Edit, then, if the tab shows the connection, Test and Update, which reaches every table in sync with it; if it shows this table’s own settings, Save. Then click Sync Now.
- Set Region under Storage to
{actualRegion}. - On an existing table, make the change from its Connection tab: click Edit, then, if the tab shows the connection, Test and Update, which reaches every table in sync with it; if it shows this table’s own settings, Save. Then click Sync Now.
- Set Region under Storage to
{actualRegion}. If Reuse metastore credentials is Yes, set it to No first, so the storage Region can differ from the catalog’s. - On an existing table, make the change from its Connection tab: click Edit, then, if the tab shows the connection, Test and Update, which reaches every table in sync with it; if it shows this table’s own settings, Save. Then click Sync Now.
- Set Region to
{actualRegion}. - On an existing table, make the change from its Connection tab: click Edit, then, if the tab shows the connection, Test and Update, which reaches every table in sync with it; if it shows this table’s own settings, Save. Then click Sync Now.
DPE-1109 — Tables stored outside Amazon S3 cannot be read yet
This table’s data files are in Google Cloud Storage or Azure storage, and an external table backed by a catalog can read data files only from Amazon S3 today. User correctable — you can correct this. What to do- Pick a table whose data files are stored in Amazon S3. The support matrix lists the storage each catalog can use.
- For Parquet files in Google Cloud Storage that no catalog manages, use a GCS Data Lake connection instead.
DPE-1110 — The source table has no data yet
The table exists in the catalog but has no snapshot with data files yet, so there is nothing to preview or sync. Informational — not a failure; act only if you want a different outcome. What to do- Write data to the table at the source, then preview it again.
- An existing table picks the data up on its next sync; nothing needs to change in StarTree.
DPE-1111 — The table changed while it was being read
The table snapshot being read was expired at the source before the read finished, which happens when snapshot retention is short or expiry runs often. Transient — temporary; retrying usually works. What to do- Try again: the next attempt reads the latest snapshot, and an existing table’s sync recovers on its next run.
- If it keeps happening, keep snapshots longer at the source, or expire them less often.
DPE-1112 — A data file the table lists is missing
A Parquet file that the table points to no longer exists in storage, usually because compaction, vacuum or file-retention cleanup removed it while it was still referenced. User correctable — you can correct this. What to do- Make sure cleanup at the source, such as VACUUM, orphan-file removal or compaction, keeps every file the table still reads. Then try again once a fresh snapshot is written.
- If the file was removed by mistake, restore it at the same path, then click Sync Now.
- Files removed or rewritten by compaction cannot be read again from a data lake source. Read sources that compact through a catalog such as AWS Glue or Unity Catalog, or recreate the table.
- If the file was removed by mistake, restore it at the same path, then click Sync Now.
- Make sure cleanup at the source, such as VACUUM or orphan-file removal, keeps every file the current snapshots still use. Then try again once a fresh snapshot is written.
- If the file was removed by mistake, restore it at the same path, then click Sync Now.
DPE-1113 — A source file is not readable Parquet
A file under the source path is not a Parquet file the reader can open: it is in another format, incomplete, corrupt, or encrypted. User correctable — you can correct this. What to do- Keep only Parquet data files under the table’s path, or narrow the prefix so other files, such as _SUCCESS markers, CSV files or a _delta_log folder, are left out.
- Parquet files with encrypted footers cannot be read; rely on bucket encryption instead.
- To let a sync skip unreadable files instead of failing, set continueOnFileError to true in the ExternalTableSyncTask settings on the table’s Configuration tab.
DPE-1114 — Reading the source files took too long
Reading data from the source files did not finish in time, so the sample could not be built. Transient — temporary; retrying usually works. What to do- Try again in a moment; object storage can be slow to answer under load.
- If it fails the same way every time, check that the Region in the connection’s storage settings matches the bucket’s region; a mismatch can show up like this.
- If it still fails, contact StarTree support and quote the reference shown with this error.
DPE-1115 — A column in the source could not be decoded
Column{column} holds values in a form the reader could not decode, so the sample could not be built.
Internal — a defect on our side.
What to do
- Contact StarTree support and quote the reference shown with this error and the column name; the type mapping may not cover how this column is encoded yet.
DPE-1116 — The catalog returned an error
The catalog answered with a server error, said it was unavailable, or asked StarTree to slow down, so the request did not complete. This is on the catalog’s side. Transient — temporary; retrying usually works. What to do- Try again in a moment.
- If it keeps failing, check the catalog’s status page or service health, then contact StarTree support and quote the reference shown with this error.
DPE-1117 — The catalog rejected the connection’s settings
The catalog rejected a request built from this connection’s settings as malformed, usually because the catalog name, prefix or table bucket it names is not valid there. User correctable — you can correct this. What to do- Check the settings that name where the catalog is against the catalog: Catalog Name, AWS Account ID, Prefix or Table Bucket ARN, whichever the form shows.
- On an existing table, make the change from its Connection tab: click Edit, then, if the tab shows the connection, Test and Update, which reaches every table in sync with it; if it shows this table’s own settings, Save. Then click Sync Now.
- Check Catalog Name and Prefix against the catalog in Snowflake Open Catalog.
- On an existing table, make the change from its Connection tab: click Edit, then, if the tab shows the connection, Test and Update, which reaches every table in sync with it; if it shows this table’s own settings, Save. Then click Sync Now.
- Check Catalog Name against the catalog’s exact name at the source.
- On an existing table, make the change from its Connection tab: click Edit, then, if the tab shows the connection, Test and Update, which reaches every table in sync with it; if it shows this table’s own settings, Save. Then click Sync Now.
- Check Database against the Snowflake database’s exact name.
- On an existing table, make the change from its Connection tab: click Edit, then, if the tab shows the connection, Test and Update, which reaches every table in sync with it; if it shows this table’s own settings, Save. Then click Sync Now.
- Check Table Bucket ARN is the full ARN of the table bucket, copied from the S3 console.
- On an existing table, make the change from its Connection tab: click Edit, then, if the tab shows the connection, Test and Update, which reaches every table in sync with it; if it shows this table’s own settings, Save. Then click Sync Now.
- Check AWS Account ID is the numeric ID of the account that owns the Glue Data Catalog.
- On an existing table, make the change from its Connection tab: click Edit, then, if the tab shows the connection, Test and Update, which reaches every table in sync with it; if it shows this table’s own settings, Save. Then click Sync Now.
DPE-1118 — That namespace is no longer in the catalog
The catalog no longer has the namespace being browsed; it may have been renamed or dropped since the list was loaded. User correctable — you can correct this. What to do- Go back to the list of namespaces, reload it, and pick the namespace again.
DPE-1119 — No AWS credentials were available
The connection asked to use AWS credentials from the environment, but none were available where the request ran. User correctable — you can correct this. What to do- Set Authentication Type to IAM Role, with the IAM Role ARN of a role that trusts this environment, or to access keys with a Secret Key.
- IAM Node Role works only where the cluster’s servers have an AWS identity; if you expected it to, contact StarTree support and quote the reference shown with this error.
- On an existing table, make the change from its Connection tab: click Edit, then, if the tab shows the connection, Test and Update, which reaches every table in sync with it; if it shows this table’s own settings, Save. Then click Sync Now.
DPE-1120 — The IAM Role ARN is not valid
AWS rejected the IAM Role ARN on this connection because it is not a well-formed role ARN. User correctable — you can correct this. What to do- Copy the role’s ARN from the role’s summary page in the IAM console into IAM Role ARN, whole and without spaces; a role name or a policy ARN is not accepted.
- On an existing table, make the change from its Connection tab: click Edit, then, if the tab shows the connection, Test and Update, which reaches every table in sync with it; if it shows this table’s own settings, Save. Then click Sync Now.
DPE-1121 — The storage address could not be found
The object store’s address for this bucket could not be resolved, usually because the Region is misspelled or the Endpoint is wrong. User correctable — you can correct this. What to do- Check the Region in the connection’s storage settings is a real AWS region name, written with hyphens, for example us-east-1.
- On an existing table, make the change from its Connection tab: click Edit, then, if the tab shows the connection, Test and Update, which reaches every table in sync with it; if it shows this table’s own settings, Save. Then click Sync Now.
- Keep Endpoint as https://storage.googleapis.com, and check Region; the default auto works for most buckets.
- On an existing table, make the change from its Connection tab: click Edit, then, if the tab shows the connection, Test and Update, which reaches every table in sync with it; if it shows this table’s own settings, Save. Then click Sync Now.
DPE-1122 — Object storage did not answer the request
The object store was busy, asked StarTree to slow down, or could not be reached, so the files could not be listed or read this time. Transient — temporary; retrying usually works. What to do- Try again in a moment; an existing table’s next sync retries on its own.
- If it keeps failing, contact StarTree support and quote the reference shown with this error.
DPE-1123 — The temporary AWS credentials expired
The temporary AWS credentials used for this request expired before it finished. Transient — temporary; retrying usually works. What to do- Try again; fresh credentials are requested on the next attempt, and an existing table’s next sync does so on its own.
- If it keeps happening with an IAM Role, raise the role’s maximum session duration in AWS.
DPE-1124 — A file name under the source cannot be read
A file under the source path has a name with a space or another character that is not allowed in a storage address, so the sync cannot read past it. User correctable — you can correct this. What to do- Rename or move files whose names contain spaces, percent signs, or # and ? characters at the source, or narrow the prefix so they are left out.
- Click Sync Now.
DPE-1125 — The table’s namespace is not set
The table’s sync settings name a table but no namespace, so the catalog could not look it up. User correctable — you can correct this. What to do- Open the table’s Configuration tab, click Edit, and in the ExternalTableSyncTask settings set the namespace (the database or schema) the table belongs to; then Apply and Save.
- Click Sync Now.
DPE-1126 — The preview needed more memory than was available
Reading the sample rows needed more memory than the cluster had free, so the preview stopped. This is on our side, not your configuration. Upstream — a service we depend on did not answer as expected. What to do- Try again in a moment.
- If the table is very wide and it keeps failing, contact StarTree support and quote the reference shown with this error.
DPE-1131 — Some tables are no longer linked to this connection
The update named tables that aren’t linked to this connection:{tables}. Nothing was changed. A table may have been deleted, unlinked or moved to another connection since this page loaded.
User correctable — you can correct this.
What to do
- Reload the page so the Associated Tables list is current.
- Update the connection again.
DPE-1132 — A table can’t be both updated and unlinked
The update asked to both update and unlink{tables}. Nothing was changed.
User correctable — you can correct this.
What to do
- Reload the page and update the connection again.
DPE-1133 — This table’s ingestion settings can’t be edited here
Table{table} doesn’t ingest from a source type that has connection settings, so there is no settings form to apply.
User correctable — you can correct this.
What to do
- Edit the table’s ingestion config on its Configuration tab instead.
DPE-1134 — The brokers do not offer that SASL Mechanism
The Kafka brokers do not accept the{mechanism} mechanism, so they never checked the Username and Password. They offer {enabled}.
User correctable — you can correct this.
What to do
- Set SASL Mechanism on Connection Setup to one the brokers offer:
{enabled}. Confluent Cloud brokers offer Plain. - For a saved connection, click Edit on the Connections page or the dataset’s Connection tab, change SASL Mechanism, then Test and Update.
DPE-1135 — An AWS policy explicitly denies this action
AWS refused{action} because a {policy} explicitly denies it for this identity. An explicit deny overrides any permission granted elsewhere, so adding {action} to the connection’s IAM policy does not help.
User correctable — you can correct this.
What to do
- Ask whoever manages that
{policy}in your AWS account or organization to exempt this connection’s identity, or the bucket, from the deny. - Then click Test Connection, or Test then Update on a saved connection.
DPE-1136 — The uploaded file is no longer available
The preview reads an uploaded file from a temporary copy on the server, and that copy is gone, so there was nothing to read. The copy does not survive a restart of the service that holds it. User correctable — you can correct this. What to do- Go back to Connection Setup and upload the file again with Upload File.
- Then select Show Sample Data, and continue to the step you were on.
DPE-1141 — A file name pattern excludes the uploaded file
A file name pattern in the Connection Properties does not match the uploaded file, so no file was read. User correctable — you can correct this. What to do- Remove includeFileNamePattern and excludeFileNamePattern from the Connection Properties; an upload does not need them.
- If you keep a pattern, match the file name exactly, including the case of its extension.
DPE-1142 — That file format is not supported
The file format of this upload is missing or is not one that can be read. User correctable — you can correct this. What to do- Upload a CSV, JSON, Avro, Parquet, ORC or Protobuf file, and set Data Format to match it.
- The format is taken from the file extension, so give the file the extension of its real format.
DPE-1143 — A file setting is not valid for this format
One of the file settings is not valid for this file format, so the file could not be opened. User correctable — you can correct this. What to do- Set Custom Delimiter to a single character, such as a comma or a pipe.
- Remove any property added in the Connection Properties that this file format does not support.
- Use a quote character that differs from the delimiter.
DPE-1144 — The uploaded file needs a name with an extension
The uploaded file has no name or no extension, so its format could not be determined. User correctable — you can correct this. What to do- Rename the file so it ends with the extension of its format, such as data.csv, and upload it again.
DPE-1145 — The Databricks workspace blocks StarTree’s address
The Databricks workspace’s IP access list does not allow{sourceIp}, the address StarTree connected from, so Databricks refused the request. This is a network rule on the workspace, not a problem with this connection’s credentials.
User correctable — you can correct this.
What to do
- Ask a Databricks workspace admin to add
{sourceIp}to an allow list in the workspace’s IP access lists. Databricks manages these with its CLI or the IP Access Lists API; a change takes a few minutes to apply. - If the workspace also uses context-based ingress, allow the address there too: a request has to pass both.
- If a later attempt names a different address, add that one as well. StarTree support can confirm every address your environment connects from.
- Then click Test on the connection, from the Connections page or the dataset’s Connection tab, or click Sync Now on an existing table.
DPE-1146 — No source location was set for the preview
The preview has no folder or file location to read from, so no rows could be sampled. User correctable — you can correct this. What to do- For Amazon S3, Google Cloud Storage or ADLS, fill in S3 Input Directory URI, GCS Input directory URI or ADLS Input Directory URI on Connection Setup, then select Show Sample Data.
- For Upload File, choose the file under Upload File on Connection Setup again, then select Show Sample Data.
- If you are calling the API directly, set inputDirURI in the table config’s FileIngestionTask.
DPE-1147 — The CSV file’s first line is not its header
The first line of{file} has no Custom Delimiter in it but the lines below it do, so its column names could not be read. A title, account or note line above the column names ends this way, as does a header separated by a different character than the rows.
User correctable — you can correct this.
What to do
- Open the file and delete any lines above the column names, so the first line is the header.
- On the Data Setup step, check Custom Delimiter is the character between the column names, such as a comma or a semicolon.
- Replace the file at the source, or leave it out with an Include Glob Pattern, then select Show Sample Data again.
- Open the file and delete any lines above the column names, so the first line is the header.
- On Connection Setup, check Custom Delimiter is the character between the column names, such as a comma or a semicolon.
- Upload the file again under Upload File, then select Show Sample Data.
DPE-1148 — The ADLS Access Key is not a storage account key
The Access Key on this connection is not an Azure storage account access key, so it could not be used to sign requests to Azure storage. A storage account key is 88 characters of base64 text; a connection string, a shared access signature or an ID pasted in its place ends this way. User correctable — you can correct this. What to do- In the Azure portal, open the storage account, then Security + networking, then Access keys. Select Show keys and copy the Key under key1 or key2, not the connection string.
- Paste it into Access Key, with Authentication Type set to Access Key, on Connection Setup, or with Edit on the Connections page.
- To sign in with a service principal instead, set Authentication Type to Azure Active Directory and enter Client Id, Client Secret and Tenant Id.
- Then select Test Connection, or Test and then Update on a saved connection.
DPE-1149 — Snowflake did not recognise the account address
Snowflake Account does not hold an account identifier on its own, so the address built from it does not lead to the account. The connection adds .snowflakecomputing.com to Snowflake Account itself, so a value that already ends in that domain, starts with https:// or holds a page path ends this way. User correctable — you can correct this. What to do- Set Snowflake Account to the account identifier only: the organization and account names joined by a hyphen, such as myorg-myaccount, or the account locator with its region, such as xy12345.eu-central-1.
- Leave out https://, .snowflakecomputing.com and anything after a slash: for https://myorg-myaccount.snowflakecomputing.com, enter myorg-myaccount.
- Then select Test Connection, or Test and then Update on a saved connection.
DPE-1150 — A file pattern setting needs a list
includeFileNamePatterns or excludeFileNamePatterns holds a single glob pattern, but each takes a list of patterns, so the files to preview could not be chosen. User correctable — you can correct this. What to do- On the Data Setup step, turn on Glob Patterns and enter each pattern under Include Glob Pattern or Exclude Glob Pattern, instead of in Additional Config.
- If you keep it in Additional Config, write the value as a list: the pattern in double quotes inside square brackets, such as [“glob:**/*.csv”].
- Then select Show Sample Data again.
DPE-1151 — Snowflake refused the user name or password
Snowflake would not sign in Database User with the Database Password on this connection. A mistyped user name or password, a password changed in Snowflake after the connection was saved, or a user that signs in only through single sign-on ends this way. User correctable — you can correct this. What to do- Check that Database User is the Snowflake login name, then enter Database Password again.
- If the user signs in through single sign-on or must use a key pair, choose Key Pair Authentication under Authentication Type and enter its Private Key instead.
- Then select Test Connection, or Test and then Update on a saved connection.
DPE-1152 — No Delta table was found at the Table URI
There is no Delta table at{uri}: the folder has no _delta_log folder in it. A folder of plain Parquet files, a folder inside the table rather than its root, or a mistyped path ends this way.
User correctable — you can correct this.
What to do
- Set Table URI to the Delta table’s root folder, the one that holds its _delta_log folder, such as s3://example-bucket/path/to/table.
- If the folder holds plain Parquet files rather than a Delta table, use an S3 connection with PARQUET as Data Format instead.
- Then select Show Sample Data again.
DPE-1153 — The SQL Query has no time filter to fill in
The SQL Query must filter on the Time Column with BETWEEN END, so that each read can fill in its own time range, and no filter in that form was found. Quotes around END, a column named differently from Time Column, no WHERE clause, or a filter inside a subquery ends this way. User correctable — you can correct this. What to do- On the Data Setup step, end the SQL Query with a filter such as WHERE event_time BETWEEN END, naming the column exactly as in Time Column, with the same letter case.
- Leave END without quotes: they are replaced with the times being read, in the Time Column Format and quoted where that format needs it.
- Keep the filter in the main query’s WHERE clause, not in a subquery, and write it with BETWEEN rather than >= and <.
- Then select Show Sample Data again.
DPE-1154 — Kafka did not return the topic’s offsets in time
Kafka did not answer a request for the topic’s offsets within{timeoutMs} ms, so reading the topic could not start. Overloaded brokers, a partition with no leader, or brokers that advertise addresses StarTree cannot reach end this way.
Transient — temporary; retrying usually works.
What to do
- Try again in a moment: select Show Sample Data again, or Submit on the Validate step if the dataset was being created.
- If it keeps failing, check in your Kafka cluster that every partition of the topic has a leader, and that the brokers’ advertised listeners are addresses StarTree can reach rather than internal ones.
DPE-1155 — The preview was asked to use rows it was not sent
The preview request turned on skipSourceSampling, which previews the rows sent with the request instead of reading the source, but it sent no sourceRows. User correctable — you can correct this. What to do- Send the rows to preview in sourceRows, or set config.sampling.skipSourceSampling to false so the preview reads rows from the source, then send the request again.
DPE-1156 — The Kafka brokers’ certificate is not trusted
The secure connection to the Kafka brokers failed because their certificate does not chain to an authority StarTree trusts, as with a certificate from a private or self-signed certificate authority. User correctable — you can correct this. What to do- If the brokers use a private certificate authority, set Security Protocol to SSL on Connection Setup and paste that authority’s certificate into Server Certificate, then select Test Connection.
- With Security Protocol SASL SSL there is no Server Certificate field: ask your Kafka administrator for a listener whose certificate comes from a public certificate authority, or contact StarTree support and quote the reference shown with this error.
- On a saved connection, make the change with Edit on the Connections page, then Test and Update.
DPE-1157 — The Delta Lake connection has no Table URI
Sample rows are read from the Delta table that Table URI points to, and this connection has no Table URI, so there was no table to read. User correctable — you can correct this. What to do- Set Table URI on the connection to the Delta table’s root folder, the one that holds its _delta_log folder, such as s3://example-bucket/path/to/table.
- If you are calling the API directly, include delta.ingestion.table.uri in the connection’s properties.
- Then select Show Sample Data again.
Platform
DPE-0000 — Something went wrong on our side
This action did not complete because of an unexpected problem on our side. Internal — a defect on our side. What to do- Retry the action.
- If it happens again, contact StarTree support and quote the reference shown with this error.
DPE-5101 — The system is busy
We could not complete your request because the service is at capacity right now. Transient — temporary; retrying usually works. What to do- Wait a moment and try again. If you were creating or changing something, first check whether the change was saved, so you do not apply it twice.
- If it keeps failing for more than a few minutes, contact StarTree support and quote the reference shown with this error.
DPE-5102 — The system is busy
A database operation could not complete right now. Transient — temporary; retrying usually works. What to do- Wait a moment and try again. If you were creating or changing something, first check whether the change was saved, so you do not apply it twice.
- If it keeps failing for more than a few minutes, contact StarTree support and quote the reference shown with this error.
DPE-5103 — The system is busy
A database operation could not complete right now. Transient — temporary; retrying usually works. What to do- Wait a moment and try again. If you were creating or changing something, first check whether the change was saved, so you do not apply it twice.
- If it keeps failing for more than a few minutes, contact StarTree support and quote the reference shown with this error.
DPE-5104 — A service we depend on is unavailable
A service this action depends on could not be reached. This is on our side, not your configuration. Upstream — a service we depend on did not answer as expected. What to do- Retry in a few minutes.
- If it persists, contact StarTree support and quote the reference shown with this error.
DPE-5105 — A service we depend on is unavailable
A service this action depends on did not respond. This is on our side, not your configuration. Upstream — a service we depend on did not answer as expected. What to do- Retry in a few minutes.
- If it persists, contact StarTree support and quote the reference shown with this error.
DPE-5106 — The cluster is not reachable
We could not reach the cluster that stores this dataset. This is on our side, not your configuration. Upstream — a service we depend on did not answer as expected. What to do- Retry in a few minutes.
- If it persists, contact StarTree support and quote the reference shown with this error.
DPE-5107 — The cluster is at capacity
Too many requests to the cluster were already in progress, so this one was held back to protect the cluster and was not sent. Upstream — a service we depend on did not answer as expected. What to do- Retry in a few minutes.
DPE-5108 — Something went wrong on our side
The cluster returned an error we could not interpret, so the action did not complete. Internal — a defect on our side. What to do- Retry the action.
- If it happens again, contact StarTree support and quote the reference shown with this error.
DPE-5109 — The request could not be read
The request body could not be read: it was missing, was not well-formed JSON, or a field held a value of the wrong type or outside its allowed options. Nothing was changed. User correctable — you can correct this. What to do- Reload the page and repeat the action.
- If you are calling the API directly, send a well-formed JSON body whose fields use the types and values the API reference lists; Show details has the parser’s own message.
- If it happens again in Data Portal, contact StarTree support and quote the reference shown with this error.
DPE-5110 — A service we depend on is unavailable
A service this action depends on could not be reached or did not answer in time. This is on our side, not your configuration. Upstream — a service we depend on did not answer as expected. What to do- Retry in a few minutes.
- If it persists, contact StarTree support and quote the reference shown with this error.
DPE-5111 — That action is not available here
This request used a method this address does not accept, so nothing was changed. Internal — a defect on our side. What to do- Reload the page and try again.
- If you are calling the API directly, use the method the API reference lists for this path.
- If it happens again in Data Portal, contact StarTree support and quote the reference shown with this error.
DPE-5112 — That address does not exist
Nothing on this service answers that address, so the request was not processed. Internal — a defect on our side. What to do- Reload the page and try again.
- If you are calling the API directly, check the path, including its version prefix, against the API reference.
- If it happens again in Data Portal, contact StarTree support and quote the reference shown with this error.
DPE-5117 — A stored setting could not be read
One of the connection settings this request carried is incomplete, such as a dropdown value sent without its list of options, so it could not be read. Internal — a defect on our side. What to do- If you are calling the API directly, send each setting with its complete options list, as the properties endpoint returns it.
- In Data Portal, reload the page and repeat the action. If it keeps happening on a saved connection, open it from Connections, select Edit, then Update, which saves its settings again in full.
- If that does not help, contact StarTree support and quote the reference shown with this error.
DPE-5118 — The request was cancelled
The request ended before a reply could be sent, usually because the page was closed or navigated away from. Informational — not a failure; act only if you want a different outcome.DPE-5119 — Cluster health is not available right now
The cluster answered the health request without any detail, so there is nothing to show yet. Upstream — a service we depend on did not answer as expected. What to do- Try again in a few moments.
- If it stays empty, contact StarTree support and quote the reference shown with this message.
DPE-5120 — Something went wrong on our side
This action did not complete because a database request could not be carried out. Internal — a defect on our side. What to do- Retry the action.
- If it happens again, contact StarTree support and quote the reference shown with this message.
DPE-5121 — The cluster is not reachable
We could not get an answer from the cluster, so this action could not finish. This is on our side, not your configuration. Upstream — a service we depend on did not answer as expected. What to do- Retry in a few minutes; this usually means the cluster was restarting or briefly unavailable.
- If it still fails after about 15 minutes, contact StarTree support and quote the reference shown with this error.
DPE-5122 — A service we depend on returned an error
An internal service this action needs returned an error, so the action could not complete. Upstream — a service we depend on did not answer as expected. What to do- Try again in a moment.
- If it keeps happening, contact StarTree support and quote the reference shown with this error.
DPE-5123 — An answer from the cluster could not be read
The cluster replied in a shape this action did not expect, so the result could not be read. Internal — a defect on our side. What to do- Retry the action.
- If it happens again, contact StarTree support and quote the reference shown with this error.
DPE-5124 — That data source type is not recognised
This environment has no data source type with that id. This usually happens when the page was opened before the environment was updated, or when the id came from another environment. User correctable — you can correct this. What to do- Reload the page, then try again. If you were adding a table or connection, choose the data source type again from the refreshed list.
- If you are calling the API directly, get the id from GET /api/datasources/types in this environment. Don’t reuse an id from another environment or release.
- If the type you need is missing from the list after reloading, contact StarTree support and quote the reference shown with this message.
DPE-5125 — The change is still being applied
This sync registered new data for{table}, but the servers had not finished loading it when the sync’s waiting time ran out, so the run stopped. The servers keep loading it, so the new data may take longer to appear.
Upstream — a service we depend on did not answer as expected.
What to do
- Check the dataset’s Monitoring tab after the next sync, which waits for this data again; to start one now, select Retry Sync there.
- If it stops this way again, open the Storage tab, then Segments, select Bad, tick the segments listed, select Reset and confirm.
- If no segments are Bad, contact StarTree support and quote the reference shown with this error.
DPE-5126 — That file is not served here
A browser asked this service for a static file it does not serve. Nothing the reader did caused it and nothing is affected. Informational — not a failure; act only if you want a different outcome. What to do- No action is needed.
DPE-5127 — Some copies of this data are in an error state
Some of this dataset’s segments failed to load on the servers holding them and stay failed until they are reset, so this sync stopped rather than leave the dataset half-updated. Queries may return partial results until then. Upstream — a service we depend on did not answer as expected. What to do- On the dataset’s Storage tab, open Segments, select Bad, tick the segments listed, select Reset and confirm. Then select Retry Sync on the Monitoring tab.
- If they turn Bad again after the reset, or many segments are Bad at once, contact StarTree support and quote the reference shown with this error; the servers holding them need attention.
DPE-5128 — The change stopped making progress
This sync registered new data, but the servers made no progress loading it for longer than the sync waits, so the run was stopped rather than left waiting indefinitely. Upstream — a service we depend on did not answer as expected. What to do- Select Retry Sync on the dataset’s Monitoring tab, or wait for the next scheduled sync; it waits for the same data again and completes once the servers catch up.
- If it stops this way again, contact StarTree support and quote the reference shown with this error; the servers loading this data need attention.
DPE-5129 — The API reference could not be generated
The page that describes this service’s API could not be built because of a fault on our side. The API itself is unaffected. Internal — a defect on our side. What to do- Keep using the API as normal — only the reference page is affected.
- If you need the reference page, contact StarTree support and quote the reference shown with this error.
DPE-5130 — A service component failed to load
Part of the service that reads this source could not be loaded on our side, so the request stopped before any data was read. Your connection and data are not the cause. Internal — a defect on our side. What to do- Contact StarTree support and quote the reference shown with this error; this needs a fix on our side.
- Your connection settings do not need to change.
DPE-5131 — New data could not be registered in time
This sync prepared its new data, but the cluster took longer than allowed to accept it, so the run stopped. Large runs on a busy cluster can exceed that limit. Upstream — a service we depend on did not answer as expected. What to do- No action is needed if the next sync succeeds; it picks up any files this run did not finish.
- Check the dataset’s Monitoring tab after the next scheduled run.
- If several runs in a row stop this way, contact StarTree support and quote the reference shown with this error: the cluster needs more time or capacity for runs of this size.
DPE-5132 — Table health results could not be saved
The background check that tracks table health could not record its latest results, so health alert emails are held back until it succeeds. This is on our side, not your configuration. Internal — a defect on our side. What to do- No action is needed on your side.
- If health alert emails stop arriving, contact StarTree support and quote the reference shown with this error.
DPE-5133 — Table health tracking skipped one round
A table was removed while the background table health check was saving its results, so that round was set aside. The next round starts from the current list of tables, so no health alert is lost. Informational — not a failure; act only if you want a different outcome. What to do- No action is needed.
DPE-5134 — The preview request was missing its settings
Some of the connection or data setup settings this preview needs did not arrive with the request, so the sample data could not be built. This is a fault on our side, not in your data. Internal — a defect on our side. What to do- Go back to Select Data Source, choose the source again, fill in Connection Setup and select Show Sample Data.
- If you are calling the preview API directly, send each settings object with its complete properties list, as the properties endpoints return it.
- If it happens again, contact StarTree support and quote the reference shown with this error.
DPE-5135 — This source type has no Data Setup step
The Data Setup step was opened for a source type that does not use one, so there was nothing to load. This is a fault on our side, not in your connection. Internal — a defect on our side. What to do- Upload File, Custom and Databricks skip Data Setup: after Connection Setup, select Show Sample Data, then continue to Data Modeling.
- To load a file, select Create table on the Tables page and choose Upload File under Select Data Source.
- If you call the API directly, these types have no data setup properties to request.
- If it happens again, contact StarTree support and quote the reference shown with this error.
DPE-5136 — Your account cannot access this table in the cluster
The cluster’s access control did not allow this request for your account. Informational — not a failure; act only if you want a different outcome. What to do- Ask a workspace administrator to grant your account access to this table.
- If access was granted just now, sign out and in again so a fresh session is used.
DPE-5137 — The cluster is not reachable
We could not reach the cluster that stores this dataset. This is on our side, not your configuration. Upstream — a service we depend on did not answer as expected. What to do- Retry in a few minutes.
- If it persists, contact StarTree support and quote the reference shown with this error.
DPE-5138 — This table’s ingestion status cannot be read
Data Portal’s record of this table does not say which cluster the table is on, so its ingestion status and details could not be read from the cluster. The table and its data are not affected. Internal — a defect on our side. What to do- Keep querying the table as usual from Query Console; only the ingestion status and details shown in Data Portal are affected.
- Contact StarTree support and quote the reference shown with this error, so the table’s record can be repaired.
Request validation
DPE-5201 — Ingestion type not recognised
This table was created outside Data Portal with a stream type that Data Portal does not recognise, so its ingestion details could not be read. User correctable — you can correct this. What to do- Keep querying and managing the table as usual; only the ingestion details shown in Data Portal are affected.
- If you need those details, contact StarTree support and quote the reference shown with this error.
DPE-5202 — A required value was missing
The request did not name a{param}. This environment hosts several workspaces, so every request has to say which one it is for.
User correctable — you can correct this.
What to do
- Choose a workspace in the Workspace selector at the top of the page, then repeat the action.
- If the selector offers no workspace, ask an administrator to give you access to one.
- If you are calling the API directly, send a Workspace header with the workspace id; Copy Workspace Id in the Workspace selector gives it.
DPE-5203 — You do not have access to this
Your account is not authorized for this action in this workspace. Informational — not a failure; act only if you want a different outcome. What to do- Ask an administrator to assign you a role that allows this action, under Settings > Security Manager > Role Assignments, then reload the page.
DPE-5204 — You do not have access to this
Your account is missing the{action} permission, which this needs.
Informational — not a failure; act only if you want a different outcome.
What to do
- Ask an administrator to grant
{action}through a role assigned to you, under Settings > Security Manager, then reload the page.
DPE-5205 — You do not have access to this
Your account is not authorized for this action in this workspace. Informational — not a failure; act only if you want a different outcome. What to do- Ask an administrator to assign you a role that allows this action, under Settings > Security Manager > Role Assignments, then reload the page.
DPE-5206 — Connection not found
The connection this refers to no longer exists: it was deleted, or the page or link that named it is out of date. User correctable — you can correct this. What to do- Open Connections and pick the connection from the list; a deleted connection is no longer listed.
- If this appeared while creating a table, go back to Connection Setup and choose one under Existing Connections, or set one up under New Connection and run Test Connection.
- If it appears on a table’s page although its connection still exists, contact StarTree support and quote the reference shown with this error.
DPE-5207 — Uploaded file could not be read
The upload could not be read: the request ended before the whole file arrived, or it was not sent as a multipart form. User correctable — you can correct this. What to do- Upload the file again; an interrupted upload cannot be resumed.
- Keep the file under 30 MB. For a larger file, put it in object storage such as Amazon S3 and create the table from there instead of uploading it.
- If you are calling the API directly, send multipart/form-data with a file part and a request part, and let your HTTP client set the boundary.
DPE-5208 — Uploaded file was empty
The preview request carried no file contents, so there was nothing to read. User correctable — you can correct this. What to do- If you are calling POST /api/v1/data-manager/datasources/preview-ingestion with ingestionType UPLOAD, put the file’s contents, base64-encoded, in payloadBase64.
- For preview-ingestion-v2, put them in the locator under upload.payloadBase64.
- In Data Portal, choose Upload File as the source when creating a table; the page sends the file for you.
DPE-5209 — Setting not recognised
This environment has no setting by that name. That happens when Data Portal is newer than the service behind it, or when a request names a setting that does not exist. User correctable — you can correct this. What to do- Nothing needs changing in Data Portal; the setting becomes available once this environment is updated.
- If you are calling the API directly, use a key listed by GET /api/v1/app-settings.
DPE-5210 — That dataset could not be found
The dataset{srn} no longer exists, or it was renamed while this page was open.
User correctable — you can correct this.
What to do
- Reload the page and open the dataset again from the Tables list.
- If it is not in the list, it was deleted — nothing further is needed.
- If you reached this from a bookmark or a shared link, the name in the link is out of date.
DPE-5211 — You do not have access to that
Your account does not have permission to{action}.
Informational — not a failure; act only if you want a different outcome.
What to do
- Ask an administrator to assign you a role that allows this, under Settings > Security Manager > Role Assignments.
- Reload the page once it is granted; permissions are read when the page loads.
DPE-5212 — That value is not valid here
The value supplied for{param} is not one this request accepts.
User correctable — you can correct this.
What to do
- If you are calling the API directly, send
{param}in the form the endpoint documents: a number where it takes a numeric id, or one of its listed values where it takes a fixed set. - For example, GET /api/datasources/<id> takes a numeric data source type id, not a connection reference; list connections with GET /api/datasources instead.
- If this appeared in Data Portal, reload the page and repeat the action from its list.
DPE-5213 — A required value was not supplied
{field} is required, and the request did not include it.
User correctable — you can correct this.
What to do
- Fill in
{field}on the step or form that asks for it, then try again; required fields are marked with an asterisk. - If Data Portal shows no field by that name, reload the page and repeat the action; the page sent an incomplete request.
- If you are calling the API directly, include
{field}in the request body; it has no default.
DPE-5214 — A required value was not supplied
The request was missing a value it needs, so it was not processed. User correctable — you can correct this. What to do- Reload the page and repeat the action.
- If a field on screen is empty, fill it in; required fields are marked with an asterisk.
- If you are calling the API directly, the error’s technical detail names the missing value; add it to the request.
- If it keeps happening in Data Portal, contact StarTree support and quote the reference shown with this error.
DPE-5215 — Choose a source type
The request did not set ingestionType, so it is not known which kind of source it is for. User correctable — you can correct this. What to do- Set ingestionType in the request body to one of:
{types}. - In Data Portal, start from Create table on the Tables page and pick the source under Select Data Source; the wizard sets the type for you.
DPE-5216 — That name is already taken
Another connection in this workspace already uses this name, and connection names must be unique within a workspace. User correctable — you can correct this. What to do- Change Source Name (Connection Name on a catalog connection) to a name no other connection in this workspace uses, then try again.
- To reuse the existing connection instead, choose it under Existing Connections when creating a table.
DPE-5217 — That dataset belongs to a different workspace
The dataset named in the request is not in the workspace the request was made against. User correctable — you can correct this. What to do- Choose the dataset’s workspace in the Workspace selector at the top of the page, then open the dataset again from Tables.
- A link saved in another workspace keeps failing here, because the workspace is part of the dataset’s address. If that workspace is not offered, ask an administrator for access to it.
- If you are calling the API directly, send the Workspace header for the workspace in the dataset reference.
DPE-5218 — That value is not one of the accepted options
The setting with id{parameter} accepts only values from a fixed list, and the request sent a value that is not on it, or none at all.
User correctable — you can correct this.
What to do
- In Data Portal, open the connection or data setup form, choose a value from each dropdown again, and retry; a value saved by an earlier version may no longer be offered.
- If you are calling the API directly, set the property whose id is
{parameter}to one of the option values listed for it, matching case exactly. - If it persists in Data Portal, contact StarTree support and quote the reference shown with this error.
DPE-5219 — That data source type is not available here
This environment does not offer that data source type. Which types are offered can differ between environments and releases. User correctable — you can correct this. What to do- Reload the page, then choose a data source type from the list. The list shows only the types this environment offers.
- If you are calling the API directly, use a type listed by GET /api/datasources/types in this environment.
- If you expect this type to be available, contact StarTree support and quote the reference shown with this message.
DPE-5220 — A required setting is missing
The connection has no value for{property}, which this source needs before it can connect.
User correctable — you can correct this.
What to do
- On a Kinesis connection, fill in Region with the AWS region the stream is in, such as us-east-1, then test the connection again.
- If you are calling the API directly, include
{property}in the connection properties.
- Open the connection from the Connections page, click Edit, and fill in Region with the AWS region the stream is in, such as us-east-1.
- Click Test, then Update.
DPE-5221 — Ingestion settings are needed to preview rows
Sample rows are read through the table’s ingestion task, and this table has none: its data is loaded another way, or its source has not been set up yet. User correctable — you can correct this. What to do- While creating a table, complete Data Setup under Configure Connection, then preview again.
- On an existing table’s Schema tab, carry on without the preview: a table with no ingestion task has no source rows to sample, and its schema can still be edited.
DPE-5222 — A source in the list is no longer there
The tables that use this connection could not be listed because the connection no longer exists; it was deleted, or the page that asked for it is out of date. Informational — not a failure; act only if you want a different outcome. What to do- Reload Connections and pick the connection from the list; if it is not listed, it was deleted.
DPE-5223 — Notification preferences need a recipient or a dataset
Listing notification preferences needs a recipientEmail or a tableKey query parameter, and the request had neither. User correctable — you can correct this. What to do- On GET /api/v1/table-health-check-notifications/preferences, add recipientEmail=<address> to list one recipient’s preferences, or tableKey=<table name> to list one table’s.
- To find who is subscribed, call GET /api/v1/table-health-check-notifications/preferences/recipients first.
- In Data Portal, open Monitoring > Health Dashboard > Settings and pick a recipient; the page sends the address for you.
DPE-5224 — That data source belongs to a different workspace
This connection belongs to another workspace, so it cannot be opened or changed from the workspace selected now. User correctable — you can correct this. What to do- Choose the connection’s workspace in the Workspace selector at the top of the page, then open the connection again from Connections.
- To use the same system from this workspace, create a connection here with Create Connection on the Connections page.
- If you are calling the API directly, send the Workspace header for the workspace the connection belongs to.
DPE-5225 — That recipient has no preferences set
No notification preferences that you can see are saved for this recipient. You see your own, plus those in workspaces where you can manage notifications. Informational — not a failure; act only if you want a different outcome. What to do- To subscribe them, open Monitoring > Health Dashboard > Settings and click Add recipient, or call PUT /api/v1/table-health-check-notifications/preferences/scopes.
DPE-5226 — That name is reserved for a StarTree connection
A connection created by StarTree already uses this name. StarTree’s connections appear in every workspace, so the name can’t be used for another connection. User correctable — you can correct this. What to do- Enter a different name for the connection.
DPE-5227 — A task plan chart setting was out of range
The task plan chart request’s{param} {rule}.
User correctable — you can correct this.
What to do
- In Data Portal, reload the Tasks page and pick the time range again; the page sends valid values for you.
- If you are calling GET /api/tasks/plans/histogram directly, send from and to as epoch milliseconds with from before to, bucketMs between one minute and one year giving at most 500 buckets, and tzOffsetMs within 18 hours of UTC.
DPE-5228 — You do not have permission to create this dataset
Your account is not allowed to create datasets in this cluster. Informational — not a failure; act only if you want a different outcome. What to do- Ask a workspace administrator to grant you permission to create tables.
DPE-5229 — That file is larger than the upload limit
The file is larger than the 30 MB an upload accepts, so it was not read. User correctable — you can correct this. What to do- Upload a file under 30 MB.
- For a larger file, put it in object storage such as Amazon S3 and create the table from there, with S3, GCS or ADLS under Select Data Source.
DPE-5230 — The upload did not include its file
The request had no{part} part, so there was nothing to read.
User correctable — you can correct this.
What to do
- Reload the page and upload the file again.
- If you are calling the API directly, send multipart/form-data with a file part and a request part.
DPE-5232 — The dataset request is incomplete
The request to create the dataset is missing information it needs. User correctable — you can correct this. What to do- Complete each step of the wizard in order, then create the dataset again.
- If you are calling the API, send name, tableType, tableConfigString and a valid dataSourceTypeId.
DPE-5233 — The topic or stream to read was not named
This request is for a streaming table, and it did not name the Kafka topic or the Kinesis stream to read, so the table’s ingestion settings could not be worked out. User correctable — you can correct this. What to do- In Data Portal, start from Create table on the Tables page; the Data Setup step asks for Topic Name and sends it for you.
- If you are calling POST /api/v1/data-manager/datasources/infer-config directly, set ingestionLocator to the topic name for Kafka, or to the stream name for Kinesis.
- On infer-config-v2, put the topic under stream.kafka.topicName in ingestionLocator for Kafka, or the stream under streamName for Kinesis.
DPE-5234 — That connection has no saved settings to use
The connection this request names has no connection settings saved, so there is nothing to test it with or read sample rows from. This is the case for the cluster connection created by StarTree, and for a connection whose saved settings could not be loaded. User correctable — you can correct this. What to do- In Data Portal, go back to Connection Setup and choose another connection under Existing Connections, or set the source up again under New Connection and click Test Connection.
- If you are calling POST /api/table/preview or POST /api/datasources/test directly, set dataSourceSrn to a source connection listed by GET /api/datasources, or send dataSourceProperties with the settings to use. The cluster connection that a table create names is not a source connection.
DPE-5235 — The notification subscription request is incomplete
A request to add, change or remove notification subscriptions has to name the recipient and list each workspace, dataset and health check it applies to. Adding or changing one also has to say whether notifications are on and whether they are muted. This request left one of those out. User correctable — you can correct this. What to do- In Data Portal, manage subscriptions from Monitoring > Health Dashboard > Settings with Add recipient, or with Mute on a health check; the page sends every part for you.
- If you are calling PUT /api/v1/table-health-check-notifications/preferences/scopes directly, send recipientEmail, notificationsEnabled and notificationsMuted as true or false, and scopes with workspaceId, tableKey and tableHealthCheckKey on every entry. Use * for every dataset or every check, and a real workspace id rather than *.
- Removing subscriptions with DELETE on the same path takes recipientEmail and scopes the same way, up to 1000 scopes per request.
DPE-5236 — The schema in the request is not in the expected shape
The schema sent with this request could not be read because its{field} field has the wrong shape.
User correctable — you can correct this.
What to do
- If you are calling the API directly, send the schema as a string holding schema, the table schema itself; mappings, an object from each column name to the source field it reads; and dateTimeMappings, a list.
- In Data Portal, create the table from Create table on the Tables page instead; the wizard builds the schema for you.
DPE-5237 — This older endpoint does not support that source type
The{type} source type cannot be used with this endpoint, which predates it. The current connection and table endpoints support every source type this environment offers.
User correctable — you can correct this.
What to do
- In Data Portal, use Connections, or Create table on the Tables page; they test, preview and create every source type offered here.
- If you are calling the API directly, test a connection with POST /api/datasources/test and a dataSourceTypeId from GET /api/datasources/types, and preview it with POST /api/table/preview.
DPE-5238 — The connection test did not say what to test
A connection test needs either a saved connection to test or the settings of a new one, and this request sent neither. User correctable — you can correct this. What to do- In Data Portal, open the connection from Connections and click Test, or in Create table choose it under Existing Connections on the Connection Setup step and click Test Connection.
- To test settings you have not saved yet, fill in the form under New Connection and click Test Connection.
- If you are calling POST /api/datasources/test directly, send dataSourceTypeId with dataSourceSrn to test a saved connection, or with dataSourceProperties to test new settings.
Ingestion and tasks
DPE-3104 — No ingestion runs yet
This dataset has no ingestion task scheduled, so there is no run history to show. Informational — not a failure; act only if you want a different outcome. What to do- Schedule an ingestion task to get started.
DPE-3105 — No ingestion runs yet
No ingestion run has been recorded for this dataset yet, so there is no progress to report. Informational — not a failure; act only if you want a different outcome. What to do- Schedule an ingestion task, then check back once the first run starts.
DPE-3106 — No files matched this run
The ingestion task ran but found no new input files matching the configured path, so nothing was scheduled. Informational — not a failure; act only if you want a different outcome. What to do- Confirm the input path and file pattern point at the files you expect.
- If files were already ingested, this is expected — each file is processed once.
DPE-3107 — Ingestion service unavailable
We could not reach the service that reports ingestion progress. This is on our side, not your configuration. Upstream — a service we depend on did not answer as expected. What to do- Retry in a few minutes.
- If it persists, contact StarTree support and quote the reference shown with this error.
DPE-3108 — Preview is not available for this dataset
Sample rows can be fetched only for a dataset that loads its data through file ingestion, a SQL connector, Delta Lake or a catalog sync. This dataset’s table config names{taskType} instead, so there is no source to sample. The dataset itself is unaffected; only the preview is.
Informational — not a failure; act only if you want a different outcome.
What to do
- To look at its rows, query the dataset from the Query Console.
DPE-3109 — Task configuration missing
Setting, pausing or resuming a schedule changes the{taskType} entry in this dataset’s table config, and the table config has no such entry. It was removed after this page loaded, or it never existed.
User correctable — you can correct this.
What to do
- Reload the dataset’s page; without that entry there is no schedule to change, so Pause Sync and Resume Sync are no longer offered.
- To run on a schedule again, restore the entry under task on the Configuration tab (Edit, Apply, then Save). If you do not have the settings it held, contact StarTree support and quote the reference shown with this error.
DPE-3110 — Ingestion task scheduling failed
The request to start this ingestion run did not get a usable answer from the cluster’s task scheduler, so it is not known whether the run started. This is on our side, not your configuration. Upstream — a service we depend on did not answer as expected. What to do- Wait a minute, then look for a new run on the dataset’s Tasks tab, or on the Monitoring tab for a catalog table; it may have started anyway.
- If none appears, select Run Now (Sync Now for a catalog table) again.
- If it keeps failing, contact StarTree support and quote the reference shown with this error.
DPE-3111 — Cluster state for this dataset is missing
The cluster has no record of how this dataset’s data is placed across its servers. That is expected for a moment while a dataset is being created or deleted; if it lasts, the cluster’s state for this dataset is incomplete. This is on our side, not your configuration. Upstream — a service we depend on did not answer as expected. What to do- Refresh the page in a minute; if the dataset was just created or deleted, this clears on its own.
- If it persists, contact StarTree support and quote the reference shown with this error.
DPE-3112 — Could not read ingestion progress
We could not read this dataset’s stream ingestion progress from the cluster, so it cannot be shown right now. This is on our side, not your configuration. Upstream — a service we depend on did not answer as expected. What to do- Wait a moment, then refresh the page.
- If it persists, contact StarTree support and quote the reference shown with this error.
DPE-3113 — Could not reach the ingestion service
We could not reach the service that reports this dataset’s ingestion runs, so their status cannot be shown right now. This is on our side, not your configuration. Upstream — a service we depend on did not answer as expected. What to do- Wait a moment and refresh.
- If it keeps happening, contact StarTree support and quote the reference shown with this error.
DPE-3115 — The source path could not be listed
Listing the files under{uri} failed, so the run had nothing to ingest. The connection could not list that location: a missing list permission, a wrong bucket, path or region, or credentials that no longer work.
User correctable — you can correct this.
What to do
- On the dataset’s Connection tab, select Test. If it fails, select Edit, correct the input directory URI, region or credentials, then Test and Update.
- If the settings are right, let the connection’s credentials list that location, not only read files: on AWS, s3:ListBucket on the bucket.
- Then select Run Now at the top of the dataset’s page, or wait for the next scheduled run.
DPE-3116 — Ingestion could not be scheduled
The cluster could not prepare an ingestion run for{table}, so no run was started and no data was read. The reason it gave is not one we recognise; it is recorded with the reference shown with this error.
Upstream — a service we depend on did not answer as expected.
What to do
- Try again in a moment.
- If it persists, contact StarTree support and quote the reference shown with this error.
DPE-3117 — Ingestion status is unavailable
The service that reports ingestion progress did not return this dataset’s task details, so its status cannot be shown right now. This is on our side, not your configuration. Upstream — a service we depend on did not answer as expected. What to do- Wait a moment and refresh.
- If it keeps happening, contact StarTree support and quote the reference shown with this error.
DPE-3118 — Ingestion run failed
One or more input files in the latest ingestion run failed to load, so their rows are not in the dataset yet. The run recorded which files failed and why. Upstream — a service we depend on did not answer as expected. What to do- At the top of the dataset’s page, select the icon beside Sync Status to see the failed files and the error; the run’s Task plan on the Tasks tab holds its full log.
- If the error is about a file’s content or format, fix or replace the file at the source, then select Run Now to load it again.
- If it reports running out of disk space or memory, or every file fails, contact StarTree support.
DPE-3119 — You do not have access to task details
Reading task details for this dataset requires a permission this account does not have. Informational — not a failure; act only if you want a different outcome. What to do- Ask a workspace administrator for access to view this dataset’s ingestion tasks.
DPE-3120 — Pinot answered with nothing
The cluster answered that it has nothing to return for this yet, and gave no reason. The usual case is cluster health results asked for before the first scheduled health check has finished. Upstream — a service we depend on did not answer as expected. What to do- Try again in a few minutes; the result appears once the cluster has produced it.
- If it keeps happening, contact StarTree support and quote the reference shown with this error.
DPE-3121 — No new ingestion run was needed
The scheduled check ran and found nothing new to ingest since the previous run, so no run was started. Informational — not a failure; act only if you want a different outcome. What to do- Nothing to do — the next scheduled check starts a run once there is new data.
DPE-3122 — Streaming ingestion has stalled
One stream partition of this dataset stopped being read after the server reading it hit an error, so its new records are not arriving. The cluster usually restarts it within about an hour; if the stream refuses the read, it stops again. Upstream — a service we depend on did not answer as expected. What to do- Watch Ingestion delay on the dataset’s Monitoring tab; once it falls again, reading has resumed and nothing else is needed.
- If it stays stopped, check the topic still exists and the credentials still work: on the dataset’s Connection tab, click Test.
- If the connection passes, contact StarTree support and quote the reference shown with this error.
DPE-3123 — A source file could not be ingested
The sync stopped at{file}, which could not be turned into data. The time column is the usual culprit: missing, empty, or a legacy INT96 timestamp. Otherwise the file is damaged or a column type differs from the schema.
User correctable — you can correct this.
What to do
- On the dataset’s Monitoring tab, click View full error to see what failed, and fix the file at the source.
- If its time column is missing or empty, set segmentTimeValueCheck to false under ingestionConfig on the Configuration tab (Edit, Apply, Save).
- To skip unreadable files instead, set continueOnFileError to true in the ExternalTableSyncTask settings there. Then click Retry Sync.
DPE-3124 — Ingestion paused while capacity frees up
No run was started for this dataset: the cluster holds back new ingestion while a capacity limit is reached, either disk usage on the servers that hold it or, for an external table, the number of segments it or the environment may have. Informational — not a failure; act only if you want a different outcome. What to do- Runs start again on their own once usage is back under the limit, and the next run picks up what arrived meanwhile.
- If it lasts, contact StarTree support to review this environment’s capacity, and quote the reference shown with this error.
DPE-3125 — Some rows have timestamps out of range
Data was refused because its time range,{range}, falls outside what StarTree accepts, {allowed}. A placeholder date or a timestamp read in the wrong unit causes this.
User correctable — you can correct this.
What to do
- Correct or remove those rows at the source. A unit mismatch is the usual cause: seconds read as milliseconds land in 1970, the reverse far in the future.
- If the dates are right, set segmentTimeValueCheck to false under ingestionConfig on the Configuration tab (Edit, Apply, Save).
- Then run the ingestion again: Retry Sync on the Monitoring tab for an external table, otherwise Run Now or the next scheduled run.
DPE-3126 — This dataset has no data to show
This dataset holds no data. It was loaded from an uploaded file, and data whose timestamps are all older than the retention period is removed automatically. User correctable — you can correct this. What to do- Check the newest timestamp in the uploaded file; if it is older than the retention period, the data was removed.
- Raising retentionTimeValue under segmentsConfig on the Configuration tab does not bring back removed data.
- To load the file again, use Upload File, which creates a new dataset; raise retention at its Validate step first.
- If the timestamps are recent, contact StarTree support and quote the reference shown with this error.
DPE-3127 — The source warehouse is suspended
The source Snowflake account’s free trial has ended, so Snowflake has suspended all of its warehouses and refuses the reads this ingestion needs. User correctable — you can correct this. What to do- Add billing details to that Snowflake account in the Snowflake web interface; its warehouses stay suspended until then.
- Nothing in StarTree needs changing: the next scheduled run ingests as usual, and Next Run at the top of the dataset’s page shows when.
DPE-3128 — Preview needs exactly one task in the table config
Sample rows are read through the table config’s ingestion task, and this table config lists more than one task, or none, so the preview cannot tell which one reads the source. The dataset’s ingestion is not affected. User correctable — you can correct this. What to do- While creating a dataset: on the Validate step’s Table Config tab, select Edit configuration, keep only the ingestion task under task, then Apply Changes. Add other tasks on the Configuration tab once the dataset exists.
- On an existing dataset, keep its tasks; only Fetch Preview on the Schema tab is affected. To look at its rows, query the dataset from the Query Console.
DPE-3129 — Ingestion tasks could not be generated
The cluster could not prepare this dataset’s next ingestion run, so nothing was started. The full error names the reason; most often the source could not be listed or read with the connection’s settings. Upstream — a service we depend on did not answer as expected. What to do- At the top of the dataset’s page, click the icon next to Sync Status to read the full error.
- If it points at the source, open the dataset’s Connection tab and click Test; correct the settings with Edit, then Update.
- The next scheduled run retries on its own. If runs keep failing, contact StarTree support and quote the reference shown with this error.
DPE-3130 — Another run is already being prepared
Task generation for this dataset is already in progress elsewhere in the cluster, so this attempt stopped rather than duplicating it. Informational — not a failure; act only if you want a different outcome. What to do- No action is needed: the run already being prepared continues normally.
- It appears on the dataset’s Tasks tab, or on the Monitoring tab for an external table; use Run Now or Sync Now again only if no new run shows up there.
DPE-3131 — The ingestion schedule is not firing correctly
This dataset’s next scheduled run time has passed without the run starting, so its schedule has stopped firing. This is a fault in the cluster’s scheduler, not in your settings. User correctable — you can correct this. What to do- On the Configuration tab click Edit, change the schedule value under the dataset’s ingestion task (a minute’s shift is enough), then Apply and Save. Saving it unchanged does not restart the schedule.
- Next Run at the top of the dataset’s page then shows the coming run. If it falls behind again, contact StarTree support and quote the reference shown with this error.
DPE-3132 — That file could not be read
The dataset was not created because a record in the uploaded file could not be read or converted to its column’s type. Where the file’s reader reports a line, Show details names it. User correctable — you can correct this. What to do- At the Data Setup step, check Data Format matches the file; for CSV also check Custom Delimiter and Skip File Header.
- At the Data Modeling step, check each column’s type fits every value: text in a number column fails the whole file.
- Correct or remove the records that differ and create the dataset again, or set continueOnError to true under ingestionConfig at the Validate step to skip them.
DPE-3133 — The time column is missing from the uploaded data
The data could not be stored because it carries no time range for{timeColumn}, the dataset’s time column. That happens when the column is missing from the source files or holds no usable values.
User correctable — you can correct this.
What to do
- Make sure every source file has
{timeColumn}, with values, in the type the schema expects. - To store such data anyway, set segmentTimeValueCheck to false under ingestionConfig on the Configuration tab (Edit, Apply, Save); without a time range, retention will not remove it.
- Then run the ingestion again: Retry Sync on the Monitoring tab for an external table, otherwise the next scheduled run.
DPE-3134 — Preview is not available for this dataset
Sample rows cannot be fetched for a dataset that ingests both batch and streaming data. The dataset itself is unaffected; only the preview is. Informational — not a failure; act only if you want a different outcome. What to do- To look at its rows, query the dataset from the Query Console.
DPE-3135 — Two of this dataset’s tasks cannot be used together
The table config turns on both{task} and {conflictingTask}. They rewrite the same data, so only one of them may be configured and the configuration was not saved.
User correctable — you can correct this.
What to do
- Open the table config JSON — the Configuration tab of an existing dataset (Edit) or, while creating one, the Validate step’s Table Config tab (Edit configuration) — delete one of the two entries under task, and apply the change.
- If one is UpsertCompactionTask or UpsertCompactMergeTask and the other refreshes segments, keep the refresh task: it already does the compaction work.
DPE-3136 — The last scheduled run did not start
The schedule’s last run time passed with no record of a run being prepared for it, so nothing was ingested then. Usually an earlier run was still in progress, or the run was held back by a capacity limit or another run being prepared. Upstream — a service we depend on did not answer as expected. What to do- Open the dataset’s Tasks tab: if a run is still in progress there, nothing is wrong and the schedule resumes once it finishes.
- To ingest now, use Run Now at the top of the dataset’s page where offered; its message says why no run started.
- If runs keep being skipped with nothing in progress, contact StarTree support and quote the reference shown with this error.
DPE-3137 — Your access could not be checked
The cluster tried to check whether your account may do this, but the check itself failed, so the request was refused without a decision. This is not a missing permission; it is on our side. Upstream — a service we depend on did not answer as expected. What to do- Reload the page and try again; a check that fails once usually succeeds on the next attempt.
- If it keeps failing, contact StarTree support and quote the reference shown with this error. No permission change is needed on your side.
DPE-3138 — The file took too long to load
Loading the file did not finish within the time allowed, so the dataset was not created. User correctable — you can correct this. What to do- Upload a smaller file, or split it into smaller files.
- For a large file, put it in object storage and create the dataset from that connection instead of uploading it.
DPE-3139 — The table configuration has no file ingestion settings
The table configuration has no FileIngestionTask, which the upload needs in order to read the file. User correctable — you can correct this. What to do- On the Validate step’s Table Config tab, keep FileIngestionTask under task.taskTypeConfigsMap with its inputFormat.
DPE-3140 — No stream ingestion for this dataset
The cluster holds no stream ingestion for{table}, so there is no live progress to show.
Informational — not a failure; act only if you want a different outcome.
What to do
- Refresh the page, then open the dataset from the list.
- If it should be ingesting from a stream, contact StarTree support and quote the reference shown with this message.
DPE-3141 — A sync setting needs a feature the source lacks
The table’s sync settings turn on{flag}, but its catalog or source does not support it, so the sync stopped before reading any data.
User correctable — you can correct this.
What to do
- Open the table’s Configuration tab, click Edit, and in its ExternalTableSyncTask settings set
{flag}to false or remove it; then Apply and Save. - Click Sync Now to run the sync again.
DPE-3142 — The starting snapshot setting is not valid
The table’s sync settings ask to start from a snapshot this source cannot select. S3 and GCS Data Lake sources read only the latest files; Iceberg sources accept LATEST, EARLIEST or a numeric snapshot ID. User correctable — you can correct this. What to do- Open the Configuration tab, click Edit, and in the ExternalTableSyncTask settings set the initial version selector to LATEST, or for an Iceberg source to EARLIEST, or to SNAPSHOT_ID together with a numeric initial snapshot ID; then Apply and Save.
- Click Sync Now.
- Open the Configuration tab, click Edit, and in the ExternalTableSyncTask settings set the initial version selector to LATEST; then Apply and Save.
- Click Sync Now.
- Open the Configuration tab, click Edit, and in the ExternalTableSyncTask settings set the initial version selector to LATEST or EARLIEST, or to SNAPSHOT_ID together with a numeric initial snapshot ID; then Apply and Save.
- Click Sync Now.
DPE-3143 — A sync setting has a value out of range
One of the table’s numeric sync settings, such as the files scanned per run, the batch size or a wait time, has a value the sync cannot use. User correctable — you can correct this. What to do- Open the Configuration tab, click Edit, and in the ExternalTableSyncTask settings check the value the error names: the maximum files scanned per run must be at least the batch size, and wait and poll times must be positive numbers of milliseconds. Then Apply and Save.
- Click Sync Now.
DPE-3144 — The table’s source type changed after it was created
The table’s saved sync progress belongs to a different kind of source from the one its settings now name, so the sync cannot continue from where it stopped. User correctable — you can correct this. What to do- Change the catalog settings back in the table’s Configuration tab, or, to read from the new source, delete the table and create it again from Data & AI, Tables, Connect external table.
DPE-3145 — The sync could not save or read its progress
The cluster could not read or record how far this table’s sync has got, so the run stopped without losing any data. Transient — temporary; retrying usually works. What to do- Click Sync Now to run it again; the next run continues from the last saved point.
- If it keeps happening, contact StarTree support and quote the reference shown with this error.
DPE-3146 — Servers did not finish loading the new data
The sync built and uploaded the new data, but some servers did not report it ready in the time allowed, so the new snapshot was not made visible to queries. Transient — temporary; retrying usually works. What to do- Click Sync Now to try again. Servers that were busy usually finish on a later run, and queries keep returning the previous snapshot meanwhile.
- If it keeps happening, contact StarTree support and quote the reference shown with this error; the servers may need more capacity.
DPE-3147 — The sync could not upload the segments it built
The sync built segments from the source files but could not upload them to the cluster’s storage, so the run stopped. This is on our side, not your configuration. Upstream — a service we depend on did not answer as expected. What to do- Click Sync Now to try again.
- If it keeps happening, contact StarTree support and quote the reference shown with this error.
DPE-3148 — The cluster ran out of disk space during the sync
The sync ran out of local disk space while building segments, so the run stopped. This is on our side, not your configuration. Upstream — a service we depend on did not answer as expected. What to do- Contact StarTree support and quote the reference shown with this error; the cluster needs more disk.
- Click Sync Now once support confirms the capacity.
DPE-3149 — One file stopped a grouped sync
This table groups files into shared segments, which needs every file in the run to convert, and only{succeeded} of {total} did.
User correctable — you can correct this.
What to do
- Find the failing file in the earlier errors for this run, and fix or remove it at the source.
- Or turn off segment groups in the table’s Configuration tab, so the sync can proceed file by file.
- Click Sync Now.
DPE-3150 — The table’s definition was missing during the sync
The sync could not read the table’s schema or configuration while it ran, so it stopped. This is on our side, unless the table was being deleted at the time. Upstream — a service we depend on did not answer as expected. What to do- If the table still exists, click Sync Now to run the sync again.
- If it keeps happening, contact StarTree support and quote the reference shown with this error.
DPE-3151 — External table sync is not available on this cluster
The cluster could not start a sync for this table because external table sync is not running there. This is on our side, not your configuration. Upstream — a service we depend on did not answer as expected. What to do- Contact StarTree support and quote the reference shown with this error.
- Queries on data that has already synced keep working meanwhile.
DPE-3152 — The sync status is unavailable right now
The cluster could not report this table’s sync status just now. Transient — temporary; retrying usually works. What to do- Refresh the page in a moment.
- If it keeps happening, contact StarTree support and quote the reference shown with this error.
DPE-3153 — This table has no sync settings
The table’s configuration has no ExternalTableSyncTask settings, so its sync cannot be paused, resumed or started. Tables created with an older sync task lack them. User correctable — you can correct this. What to do- Open the Configuration tab and look for an ExternalTableSyncTask entry in the task settings. If the table uses an older task instead, create it again from Data & AI, Tables, Connect external table, then delete the old one.
- If the entry was removed by an edit, restore it, or contact StarTree support and quote the reference shown with this error.
DPE-3154 — The last sync failed without a recorded reason
The table’s last sync run failed in its{phase} step, and the cluster recorded no reason for it.
Upstream — a service we depend on did not answer as expected.
What to do
- LISTING_FILES usually means the storage credentials or path; GENERATING_SEGMENTS a data type that does not match the schema; COMPRESSING_SEGMENTS server resources; UPLOADING_SEGMENTS the cluster’s storage.
- Click Sync Now to run it again; the run records its reason if it fails again.
- If it keeps happening, contact StarTree support and quote the reference shown with this error.
DPE-3155 — The sync is still running
Sync Now runs the sync while the page waits, and this one took longer than the page waits for. It keeps running in the background. Informational — not a failure; act only if you want a different outcome. What to do- Follow its progress on the table’s Monitoring tab.
- Do not click Sync Now again until it finishes; a second request waits for the first.
DPE-3156 — The table’s storage quota is full
The table’s storage quota has no room for the segments this sync built, so the cluster refused them. User correctable — you can correct this. What to do- Raise the storage value under quota in the table’s Configuration tab, or remove it; then Apply and Save.
- Click Sync Now.
DPE-3157 — The sync could not read the table’s data files
Object storage refused to let the sync read the table’s files, so no data was loaded. Storage gives no reason with that refusal: a missing read permission, a bucket policy, files owned by another account and an encryption key the identity cannot use all look the same. User correctable — you can correct this. What to do- Grant the identity in the connection’s storage settings read access to the table’s data files, and use of the encryption key if the bucket encrypts them with one.
- Check that no bucket policy denies that identity.
- Click Sync Now to run the sync again. To use other credentials instead, change them from the table’s Connection tab: click Edit, then, if the tab shows the connection, Test and Update; if it shows this table’s own settings, Save.
- Grant the identity under Storage on the connection s3:GetObject on the table’s data files, and kms:Decrypt on the key if the bucket uses AWS KMS. If the catalog hands out its own storage credentials, grant the same to the storage credential it uses for this table.
- Check that no bucket policy denies that identity.
- Click Sync Now to run the sync again. To use other credentials instead, change them from the table’s Connection tab: click Edit, then, if the tab shows the connection, Test and Update; if it shows this table’s own settings, Save.
- Grant the identity under Storage s3:GetObject on the table’s data files, and kms:Decrypt on the key if the bucket uses AWS KMS. When Reuse metastore credentials is Yes, that is the identity under Metastore.
- Check that no bucket policy denies that identity.
- Click Sync Now to run the sync again. To use other credentials instead, change them from the table’s Connection tab: click Edit, then, if the tab shows the connection, Test and Update; if it shows this table’s own settings, Save.
- Grant the identity under Storage s3tables:GetTableData on the table bucket, and kms:Decrypt on the key if the bucket uses AWS KMS. When Reuse metastore credentials is Yes, that is the identity under Metastore.
- Click Sync Now to run the sync again. To use other credentials instead, change them from the table’s Connection tab: click Edit, then, if the tab shows the connection, Test and Update; if it shows this table’s own settings, Save.
- Grant the connection’s identity s3:GetObject on the files under its bucket and prefix, and kms:Decrypt on the key if the bucket uses AWS KMS.
- Check that no bucket policy denies that identity, and that the files belong to the bucket owner’s account.
- Click Sync Now to run the sync again. To use other credentials instead, change them from the table’s Connection tab: click Edit, then, if the tab shows the connection, Test and Update; if it shows this table’s own settings, Save.
- Grant the service account that owns the connection’s HMAC key storage.objects.get on the bucket, for example through the Storage Object Viewer role.
- Click Sync Now to run the sync again. To use other credentials instead, change them from the table’s Connection tab: click Edit, then, if the tab shows the connection, Test and Update; if it shows this table’s own settings, Save.
DPE-3160 — Preview cannot read through that task
Sample rows are read through the table config’s ingestion task, and its task,{taskType}, is not one preview can read, so no rows could be sampled.
User correctable — you can correct this.
What to do
- While creating the dataset, choose Edit configuration on the Validate step’s Table Config tab, put the ingestion task back under task, such as FileIngestionTask for files, then Apply Changes.
- Add other tasks on the Configuration tab once the dataset exists.
DPE-3161 — The uploaded file is not kept for another run
This dataset was created from an uploaded file, and the file is not kept once the dataset exists, so Run Now has nothing to read. User correctable — you can correct this. What to do- To add data, select Upload File next to the dataset’s name and upload the file again.
- Run Now and scheduled runs do not apply to an uploaded file; there is nothing to fix on the connection.
DPE-3162 — The previous run is still finishing
Run Now did not start a new run because tasks from the previous run, or from before the last configuration change, are still finishing. Nothing is wrong with the dataset. Informational — not a failure; act only if you want a different outcome. What to do- Select Run Now again in a few minutes, or wait for the next scheduled run.
DPE-3163 — The Protobuf descriptor file could not be used
The Protobuf descriptor file named in the file settings could not be loaded, so the records could not be decoded and nothing was ingested. User correctable — you can correct this. What to do- Check that the descriptor file setting names the right file and that StarTree can read it.
- Use a compiled descriptor set made with protoc —descriptor_set_out, not the .proto source file.
- Put the message type of the records first: the first message type of the first file in the set is the one read.
DPE-3164 — The time column values cannot name a segment
The time column holds text values with characters such as : or / that a segment name cannot contain, so the data could not be stored. User correctable — you can correct this. What to do- Make the time column a TIMESTAMP or LONG column on the Data Modeling step, then upload again.
- If it has to stay text, give it a SIMPLE_DATE_FORMAT format such as yyyy-MM-dd so that segments are named by date.
DPE-3165 — Some timestamps in the file are out of range
The time column of the file spans{range}, outside the range StarTree accepts (1971 to 2071), so the dataset was not created.
User correctable — you can correct this.
What to do
- Check the unit of the time column on the Data Modeling step: seconds read as milliseconds land in 1970, milliseconds read as seconds far in the future.
- Correct or remove the rows that carry placeholder dates, then upload again.
- If those rows are expected, set segmentTimeValueCheck to false under ingestionConfig on the Validate step’s Table Config tab before creating the dataset.
DPE-3166 — The file was read but its data could not be stored
The file was read, but storing its data failed, so the dataset was not created. The cluster does not say why: it may have been busy, or it may have refused the data. Upstream — a service we depend on did not answer as expected. What to do- Create the dataset again in a few minutes.
- If it fails again, check the storage quota (quota.storage) on the Validate step’s Table Config tab; data larger than it is refused.
- Check that the values of the time column fall between 1971 and 2071.
- If neither applies, contact StarTree support and quote the reference shown with this error.
DPE-3167 — File sync cannot resume from the saved progress
This dataset re-ingests a file whenever it changes (Enable Sync), which needs its saved ingestion progress to hold one record per file. Some of its saved records each cover several files, written by an ingestion run that had Enable Sync off, so no new run can be prepared. Retrying does not clear this. User correctable — you can correct this. What to do- To keep the dataset and its data, contact StarTree support and quote the reference shown with this error: the dataset’s saved ingestion progress has to be reset before syncing can resume.
- To resume without waiting, delete the dataset with Delete at the top of its page and create it again from the same folder with Create table on the Tables page. A new dataset starts with no saved progress and ingests every file again.
- When you run a File Ingestion Task by hand from Monitoring, Tasks, Create task plan on this dataset, keep Enable Sync under Advanced Options set to true.
Queries
DPE-4301 — Query could not be parsed
The SQL could not be read, so nothing was run. User correctable — you can correct this. What to do- Select Run in the Query Console to see the line and column where Pinot stopped reading the statement; a query that cannot be parsed does not run.
- Fix what is at that spot: often an unclosed quote, bracket or comment, or a missing comma between columns.
- Wrap any table or column name that is also an SQL keyword, such as timestamp or date, in double quotes.
- If part of the editor text is selected, only that part is analyzed; clear the selection or select one whole statement, then choose Analyze Query again.
DPE-4302 — Query took too long
The query did not finish within the time allowed and was stopped. Transient — temporary; retrying usually works. What to do- Narrow the time range or add a filter, then run it again.
DPE-4303 — Table not found for this query
The query names a table this workspace does not have, so it was not analyzed. The analyzer matches table names exactly, including upper and lower case, even where the query itself runs. Informational — not a failure; act only if you want a different outcome. What to do- Type the table name exactly as it appears under Tables on the left of the Query Console, matching upper and lower case, then choose Analyze Query again.
DPE-4304 — Query analysis is not set up
Query analysis is switched on for this environment, but the service that performs it has no endpoint or credential configured, so no analysis can run. Nothing about the query caused this. Upstream — a service we depend on did not answer as expected. What to do- Contact StarTree support to finish enabling query analysis for this environment.
- On a self-managed install, ask its administrator to set QUERY_ANALYZER_LLM_API_URL and QUERY_ANALYZER_LLM_API_KEY for Data Manager; Show details names the one that is missing.
DPE-4305 — That query could not be parsed
The SQL could not be read, so nothing was run. User correctable — you can correct this. What to do- Select Run in the Query Console to see the line and column where Pinot stopped reading the statement; a query that cannot be parsed does not run.
- Fix what is at that spot: often an unclosed quote, bracket or comment, or a missing comma between columns.
- Wrap any table or column name that is also an SQL keyword, such as timestamp or date, in double quotes.
- If part of the editor text is selected, only that part is analyzed; clear the selection or select one whole statement, then choose Analyze Query again.
DPE-4306 — Query analysis usage limit reached
Query analysis has used up its usage limit for this environment, so it cannot analyze queries until the limit resets. Nothing about the query caused this. Informational — not a failure; act only if you want a different outcome. What to do- Run the analysis again once the limit resets; the details give the reset time when the limit is weekly.
- Contact StarTree support if you need query analysis before then.
DPE-4307 — Query analysis is temporarily unavailable
The service that performs query analysis could not complete this request, so no recommendations were produced. This is on our side, not the query. Upstream — a service we depend on did not answer as expected. What to do- Run the analysis again in a few minutes.
- If it keeps happening, contact StarTree support and quote the reference shown with this error.
DPE-4308 — Analysis of this query was too large to finish
The analysis of this query ran past the most the analysis service can return, so it was cut off and discarded. Analyzing the same query again is likely to be cut off the same way. User correctable — you can correct this. What to do- Select one subquery or join in the Query Console editor, then choose Analyze Query; only the selected text is analyzed, so the analysis is shorter.
- If you chose High Effort Analysis, choose Low Effort Analysis, which reports less detail for each finding.
- Contact StarTree support to raise the analysis output limit if you need the whole query analyzed.
DPE-4309 — Query analysis service refused access
The service that performs query analysis did not accept the credentials StarTree set up for this environment, so no analysis can run. This is on our side; workspace permissions do not affect it. Upstream — a service we depend on did not answer as expected. What to do- Contact StarTree support and quote the reference shown with this error so the credentials can be restored.
DPE-4310 — Query analysis request was rejected
The service that performs query analysis rejected the request we sent for this query, so nothing was analyzed. This is a problem on our side, not in the query. Internal — a defect on our side. What to do- Contact StarTree support and quote the reference shown with this error.
DPE-4311 — Query analysis is turned off for this organization
Query analysis runs only after your organization turns it on in Settings, and it is currently off, so nothing was analyzed. This is a setting, not a permission on your account. Informational — not a failure; act only if you want a different outcome. What to do- Open Settings and turn on Query Analyzer. It shows what query analysis sends to the model before you confirm.
- If the switch is unavailable to you, ask someone who can change settings to turn it on.
DPE-4312 — Query too large to analyze
This query, the metadata of every table it reads and, for High Effort Analysis, its execution statistics are more than the analysis service can take in at once, so nothing was analyzed. Analyzing the same query again stops at the same point. User correctable — you can correct this. What to do- Select one subquery or join that reads fewer tables in the Query Console editor, then choose Analyze Query; only the selected text is analyzed.
- If you chose High Effort Analysis, choose Low Effort Analysis, which does not send execution statistics.
- Contact StarTree support if you need the whole query analyzed.
DPE-4318 — The query has nothing to analyze
Everything in the query is a comment, so there is no statement to run or explain. A comment that starts with — runs to the end of its line, so a statement written after it on the same line is part of the comment too. User correctable — you can correct this. What to do- In Query Console, put the statement you want analyzed on its own line, outside any — or /* */ comment.
- Then click Analyze Query and choose High Effort Analysis or Low Effort Analysis again.
- If you are calling the analysis API directly, send the statement itself in sql, not only comments.
Schema and table configuration
DPE-2201 — Dataset name not allowed
A dataset name may use only letters, numbers, hyphens and underscores, and this one is empty or contains another character, such as a space or a symbol. User correctable — you can correct this. What to do- Set Table Name on the Additional Configuration step using letters, numbers, hyphens and underscores only, then submit again.
- If you are calling the API directly, apply the same rule to the name in the request.
- Choose with care: a dataset cannot be renamed once it exists.
DPE-2202 — Dataset name is required
The request to create a dataset did not include a name, so the dataset could not be created. User correctable — you can correct this. What to do- Fill in Table Name on the Additional Configuration step, then submit again.
- If you are calling the API directly, set the dataset name in the request; letters, numbers, hyphens and underscores are accepted.
DPE-2203 — Double underscore not allowed in name
Dataset names cannot contain a double underscore, which Pinot reserves for internal naming. User correctable — you can correct this. What to do- Change Table Name on the Additional Configuration step so it has no double underscore; a single underscore is fine.
- The schema takes the same name, so one change fixes both.
DPE-2204 — Column name not allowed
A column name contains a forward slash or a backslash. Those two characters are reserved because column names become path segments internally. User correctable — you can correct this. What to do- On the Schema tab choose Edit, open the column with its Edit (pencil) action, and change Column Name so it has no forward slash or backslash.
- Choose Update Column, then Save.
- Spaces are refused too; letters, numbers and underscores are always safe.
DPE-2205 — Schema is not backward-compatible
The updated schema removes or changes a column the dataset already has, so it cannot replace the current schema. User correctable — you can correct this. What to do- On the Schema tab choose Reset All to restore the saved schema, then make only additions and Save.
- Adding columns is always allowed. Removing a column, or changing an existing column’s Data Type or Multi Value setting, or the primary key, is refused.
- To change one of those, create a new dataset with the schema you want and load the data into it; stored data cannot be reinterpreted in place.
DPE-2206 — Table configuration rejected
The table configuration for this dataset could not be read: a value has the wrong type, a required section is missing, or the JSON is malformed. User correctable — you can correct this. What to do- Choose Show details on this message to see the field that could not be read.
- On the Configuration tab choose Edit, correct that field, then Apply and Save. While creating, use Edit configuration under Table Config on the Validate step.
- Look for text where a number or true/false is expected, or a missing offline or realtime section; in a pasted config, also a trailing comma.
DPE-2207 — Datetime format not recognised
The Format on a datetime column is missing, or does not match the values in the source data. User correctable — you can correct this. What to do- Open the column with its Edit (pencil) action on the Data Modeling step or the Schema tab, and set Format to match the source values exactly.
- Epoch numbers use EPOCH|MILLISECONDS (or SECONDS); text dates use SIMPLE_DATE_FORMAT| followed by their pattern, such as yyyy-MM-dd.
- Choose Fetch Preview to check the values now parse.
DPE-2208 — This dataset already exists
A dataset with this name already exists in the workspace. User correctable — you can correct this. What to do- Choose a different dataset name.
- To change the existing dataset instead, open it from the Tables list — creating it again is not needed.
- A deleted dataset’s name is free again only once its removal finishes.
DPE-2209 — Dataset not found
This dataset is no longer available. It may have been deleted, or the link may be out of date. Informational — not a failure; act only if you want a different outcome. What to do- Refresh the page, then open the dataset from the list.
DPE-2210 — Dataset not found
This dataset is no longer available. It may have been deleted, or the link may be out of date. Informational — not a failure; act only if you want a different outcome. What to do- Refresh the page, then open the dataset from the list.
DPE-2211 — Transform refers to a field that does not exist
The transform function for{columnName} reads {property}, but no value of that name reaches the script.
User correctable — you can correct this.
What to do
- Open
{columnName}with its Edit (pencil) action on the Data Modeling step or the Schema tab, and check its Transform Function. - In a Groovy transform, list every field the script reads after the script, as in Groovy({a + b}, a, b); names are case-sensitive.
- If
{property}sits inside a field that arrives as JSON text, read it with jsonPathString instead of a dot. - Choose Fetch Preview to check the column now resolves.
DPE-2212 — Transform expression could not be evaluated
A column’s transform function failed on the source data, or two transforms depend on each other. User correctable — you can correct this. What to do- Open the column named in the details with its Edit (pencil) action on the Data Modeling step or the Schema tab, and check its Transform Function.
- Confirm every field it reads exists in the source with the type it expects, and that no two transforms read each other’s output.
- If only some records fail, set continueOnError to true under Ingestion Configuration in the Json view and Apply; those values are then left empty.
DPE-2213 — Column value did not match its type
A value in column{columnName} could not be converted to the column’s Data Type, so the rows could not be loaded.
User correctable — you can correct this.
What to do
- While creating, open
{columnName}with its Edit (pencil) action on the Data Modeling step and choose a Data Type its values fit, such as STRING for a dimension with mixed values. - Or correct the values at the source; an empty string or text in a numeric column is the usual cause.
- To keep loading and leave such values empty, set continueOnError to true under Ingestion Configuration in the Json view, then Apply.
DPE-2214 — Dataset not found in Pinot
This dataset does not exist in the cluster. It may have been deleted, or never finished creating. Informational — not a failure; act only if you want a different outcome. What to do- Refresh the page, then open the dataset from the list.
DPE-2215 — That identifier is not valid
One of the identifiers in this request is not in a form this service recognises. User correctable — you can correct this. What to do- Reload the page and repeat the action from the list rather than from a saved link.
- If you are calling the API directly, the identifier must be the full reference the list endpoint returns, not just a name.
DPE-2216 — Dataset removed
The dataset{table} was removed. Its entry here will clear on its own shortly.
Informational — not a failure; act only if you want a different outcome.
What to do
- Refresh the list in a moment.
DPE-2217 — Dimension table needs a primary key
A dimension table has to declare at least one primary key column, and this one declares none. User correctable — you can correct this. What to do- While creating, pick at least one column in Primary Key Columns under Table Type Dimension on the Additional Configuration step.
- For an existing dataset, open the Schema tab, choose Edit, switch to Json, add the column names to primaryKeyColumns under Column Configuration, then Apply and Save.
- If it should not be a dimension table, choose Table Type Fact instead, or set isDimTable to false on the Configuration tab.
DPE-2218 — That server tenant does not exist
The server tenant this dimension table names has no servers at all, so the table has nowhere to be placed and the configuration was rejected. User correctable — you can correct this. What to do- On the Tenants step of Additional Configuration, choose another Server Tenant; its list shows the server tenants this cluster has.
- For an existing dataset, set tenants.server in the Configuration tab (Edit, then Apply) to a tenant that has servers. The name is case-sensitive.
- If this is the tenant you expect to use, ask a workspace administrator to assign servers to it.
DPE-2219 — A dataset of that name already exists
{table} already exists, so it cannot be created again.
User correctable — you can correct this.
What to do
- Choose a different name for the new dataset.
- To change the existing one, open it from the Tables list and edit it instead of creating it again.
- If no dataset of that name is listed, an earlier failed attempt may have left its schema behind: choose a different name, or ask an administrator to remove the schema.
DPE-2220 — That setting cannot be changed after creation
This edit changes{fields}. Those settings cannot change on an existing dataset, because the data already stored depends on the current value. Each item shows the current value, then the one you entered.
User correctable — you can correct this.
What to do
- In the Configuration tab, choose Edit, set each setting listed back to the value before the arrow, then Apply; your other changes can then save.
- To use the new value, create a new dataset with it and load the data into that; an existing dataset cannot be converted in place.
DPE-2221 — A value in the configuration has the wrong type
The default null value{value} is not a valid {targetType}, the data type of its column, so the configuration could not be read.
User correctable — you can correct this.
What to do
- Edit the column whose Default Null Value is
{value}(Data Modeling step, or the Schema tab after Edit), enter a{targetType}value or clear the field, then choose Update Column. - A number column takes a number such as 0 or -1, not text like N/A; to keep a text placeholder, set Data Type to STRING.
- In the Json view, the same setting is defaultNullValue on that column.
DPE-2222 — The configuration could not be read
Part of the dataset configuration is not in the expected structure, so it could not be read and nothing was changed. Usually a column sits in the list for another field type, a fieldType value is misspelled, or a required section such as tenants was removed. User correctable — you can correct this. What to do- In the Json view (Data Modeling step, or the Schema tab after Edit), keep each column in the list matching its fieldType, such as a DIMENSION in dimensionFieldSpecs.
- To change a column’s field type, use Field Type in the Table view; it moves the column for you.
- In the Configuration tab, restore any section you removed, then Apply.
DPE-2223 — A timestamp did not match its declared format
The time value{value} could not be read with this SQL source’s Time Column Format. That setting takes millisecondsSinceEpoch, secondsSinceEpoch or hoursSinceEpoch for epoch numbers, or a date pattern such as yyyy-MM-dd HH:mm:ss for text.
User correctable — you can correct this.
What to do
- On the Data Setup step, enter the Time Column Format that matches the column, and give Start Time in that same format.
- The size:unit:EPOCH form, such as 1:MILLISECONDS:EPOCH, is not accepted here, and there is no microsecond option; expose the column in milliseconds or seconds through a view at the source.
DPE-2224 — No servers are assigned to that tenant
No servers are assigned to{tag} for this kind of data, so the dataset could not be placed on it and the configuration was rejected. A tenant can have servers for batch data but not streaming, or the reverse.
User correctable — you can correct this.
What to do
- Choose another Server Tenant on the Tenants step of Additional Configuration; for an existing dataset, set tenants.server in the Configuration tab (Edit, then Apply).
- If a storage tier uses
{tag}, change Tier Server Tag on the Storage step, or serverTag under tierConfigs in the Configuration tab. - If
{tag}is the tenant you expect, ask a workspace administrator to assign servers to it.
DPE-2225 — Granularity value not recognised
The granularity in this configuration is not a value the cluster accepts, so the configuration was rejected and nothing was changed. User correctable — you can correct this. What to do- Set Granularity on the Datetime column to a size and a unit, such as 1:DAYS or DAYS|1. It is required, so it cannot be left empty.
- Units are NANOSECONDS, MICROSECONDS, MILLISECONDS, SECONDS, MINUTES, HOURS or DAYS, in capitals. A value such as 1:MILLISECONDS:EPOCH belongs in Format, not Granularity.
- Enter only the value: a field that also holds the property name is the most common cause. Edit it on the column’s row, on the Data Modeling step or the Schema tab.
DPE-2226 — The two halves name different time columns
A dataset that ingests both batch and streaming data must use one time column on both halves. This one names{offline} on the batch half and {realtime} on the streaming half, so the configuration was rejected.
User correctable — you can correct this.
What to do
- In the Configuration tab, choose Edit, set timeColumnName under segmentsConfig to the same column in both the offline and realtime sections, then Apply.
- Choose a Datetime column that both batch and streaming data fill; a query spans the two halves on that column.
DPE-2227 — The dataset still has tasks running
It could not be deleted because{tasks} task(s) are still running on it. Its schedules have been cleared, so no further tasks will start.
Transient — temporary; retrying usually works.
What to do
- Wait for the running tasks to finish, then send the delete again.
- To delete it now, add ignoreActiveTasks=true to the delete request; Delete on the dataset’s page in Data Portal already does this and does not wait for running tasks.
DPE-2228 — The primary key names a column that is not there
The schema sent to infer a configuration lists{column} as a primary key column but defines no column of that name, so no configuration was produced.
User correctable — you can correct this.
What to do
- In the infer-config request, make every name in the schema’s primaryKeyColumns match one of its columns exactly, including case. A dimension table needs at least one.
- Or create the dataset in Data Portal: Primary Key Columns, on the Details step of Additional Configuration, offers only columns that exist.
DPE-2229 — The dataset has neither batch nor streaming settings
A dataset configuration has to contain an offline section for batch data, a realtime section for streaming data, or both. This one contains neither, so it could not be checked. User correctable — you can correct this. What to do- Add the offline or realtime section, holding the table configuration, next to tableName and schema, and send it again.
- In Data Portal, open the Configuration tab, choose Edit, restore the offline or realtime section, then Apply.
- For a new dataset, use Create table on the Tables page; the source you pick fills in the right section.
DPE-2230 — The time column is not in the schema
The table config uses{column} as its time column, but the schema has no Datetime column of that name, so the change could not be saved. Either timeColumnName names a column the schema does not have, or the column was removed, renamed or given another Field Type.
User correctable — you can correct this.
What to do
- If you changed timeColumnName, set it on the Configuration tab (Edit, then Apply) to a Datetime column the schema has.
- If the schema changed, set
{column}back to Field Type Datetime on the Schema tab or the Data Modeling step; on the Schema tab, Cancel drops the whole edit.
DPE-2231 — The star-tree index names a column that is not there
The star-tree index lists{column} as a dimension, but the schema has no column with that name, so the configuration could not be saved.
User correctable — you can correct this.
What to do
- On the Indexes tab choose Edit, open the star-tree index with its pencil icon, remove
{column}from Dimension Split Order or pick an existing column, then Update and Save. - Or add
{column}first: on the Schema tab choose Edit, then Add Column, then Save. - For a time bucket such as DAY, add no column: give the base column a timestamp index with that granularity on the Configuration tab instead.
DPE-2232 — The schema is missing a column the table config uses
The table configuration for{table} still uses {column}, in an index or a field setting, but the schema has no column of that name.
User correctable — you can correct this.
What to do
- To keep
{column}, add it back: on the Schema tab, Cancel discards an unsaved deletion, or choose Edit, then Add Column, then Save. While creating, use Add Column on the Data Modeling step. - To drop it, first remove every mention of
{column}on the Configuration tab: choose Edit, delete it from the index and field settings, then Apply and Save. Then delete the column. - Names must match exactly, including case.
DPE-2233 — Dimension table storage quota is above the limit
A dimension table is copied in full to every server, so its storage quota may not exceed{allowed} bytes. This configuration sets it to {requested} bytes.
User correctable — you can correct this.
What to do
- On the Configuration tab choose Edit, lower storage under quota to the limit or remove it so the limit applies, then Apply and Save. While creating, do this under Table Config on the Validate step.
- If the data needs more room, make it a fact table instead: Table Type Fact on the Additional Configuration step.
- Ask StarTree support if this workspace needs a higher dimension-table limit.
DPE-2234 — Every column needs raw encoding
An external table reads its data in place from the source files, so every column must use raw encoding, without a dictionary. These columns have no field config and would default to a dictionary:{columns}.
User correctable — you can correct this.
What to do
- In the Configuration tab, choose Edit, add a fieldConfigList entry with encodingType RAW for each column listed, then Apply. While creating, use Edit configuration on the Table Config step.
- If a listed column is not needed, delete it on the Schema tab instead.
DPE-2235 — A transform expression could not be read
The Transform Function on{column} could not be parsed, so the configuration was rejected and nothing was changed.
User correctable — you can correct this.
What to do
- Edit
{column}(Data Modeling step, or the Schema tab after Edit) and check Transform Function for an unclosed quote or bracket, the usual cause. - A single quote inside a quoted argument ends it early; write it as two single quotes. Function names need parentheses, even with no arguments.
- Use Fetch Preview to confirm the expression now works.
DPE-2236 — A transform writes to a column that is not there
A transform writes to{column}, which is not one of this dataset’s columns and is not read by another transform, so its value would have nowhere to go.
User correctable — you can correct this.
What to do
- Open the Json view (Data Modeling step, or the Schema tab after Edit). Under Ingestion Configuration, change that transform’s columnName to an existing column or remove the entry, then Apply.
- To keep
{column}, add it first with Add Column; the name must match exactly, including case.
DPE-2237 — Dataset creation interrupted by a concurrent update
Another part of the service recorded a dataset with this name at the same moment, so this creation could not be saved and was undone. Transient — temporary; retrying usually works. What to do- Create the dataset again in a moment; the name does not need to change.
DPE-2238 — The schema was missing from the request
The table configuration could not be worked out because the request carried no schema for the new dataset. User correctable — you can correct this. What to do- In the infer-config request, set outputSchema’s schema to an object holding the Pinot schema under schema and its column mappings under mappings, not to the Pinot schema on its own.
- Or create the dataset in Data Portal with Create table on the Tables page; it does not use this request.
DPE-2239 — That function is not available when data is ingested
The Transform Function for{column} calls {function}, which ingestion cannot run. Ingestion has fewer functions than queries, and some query functions go by another name there.
User correctable — you can correct this.
What to do
- To read a value out of JSON, use jsonPathString(col, ‘.path’, ‘STRING’), or jsonPathLong or jsonPathDouble for numbers.
- For any other function, check its name and argument count against the ingestion transformation functions; both mistakes are reported this way.
- Fix it in Transform Function (Data Modeling step, Edit on the column), then use Fetch Preview.
DPE-2240 — A transform reads the column it writes to
The Transform Function for{column} takes {column} as one of its inputs. A transform has to write to a column other than the ones it reads, so the configuration was rejected and nothing was changed.
User correctable — you can correct this.
What to do
- Keep
{column}as the source: on the Data Modeling step choose Add Column, give the new column its own name, and enter the expression that reads{column}as its Transform Function. - Then clear the Transform Function on
{column}itself. If you only need the new column, delete{column}: the new column’s transform still reads it from the source.
DPE-2241 — This request did not name a dataset
The request refers to a dataset, but the dataset name in it is blank, so there is nothing to look up. User correctable — you can correct this. What to do- Refresh the page, then open the dataset from the list.
- If you are calling the API directly, end the dataset reference with the dataset name exactly as the list endpoint returns it: lowercase letters, numbers, hyphens and underscores.
DPE-2242 — The ingestion filter calls a function it cannot use
The ingestion filter calls{function}, which ingestion cannot run, or calls it with the wrong number of arguments. IN and NOT IN lists are among the forms it cannot use, so the configuration was rejected.
User correctable — you can correct this.
What to do
- Write a list as strcmp comparisons: for col NOT IN (‘A’, ‘B’) use strcmp(col, ‘A’) != 0 AND strcmp(col, ‘B’) != 0; for IN, join strcmp(col, ‘A’) = 0 terms with OR.
- Compare other text with strcmp too; for any other function, check its name and argument count.
- Edit filterFunction in Ingestion Configuration (Data Modeling step, Json view) and Apply; rows for which the filter is true are left out.
DPE-2243 — The ingestion filter could not be read
The ingestion filter is not a valid expression, so the configuration was rejected and nothing was changed. User correctable — you can correct this. What to do- Test equality with a single =, not ==, and inequality with != or <>; join conditions with AND, OR and NOT.
- Put text in single quotes and close every quote and bracket; a quote inside text is written twice.
- Compare text through strcmp, as in strcmp(col, ‘value’) = 0; a plain = on text fails once rows are read.
- Edit filterFunction in Ingestion Configuration (Data Modeling step, Json view) and Apply. Rows for which the filter is true are left out.
DPE-2244 — The datetime format is not written correctly
The datetime format{format} is not in a form the cluster can read, so the configuration was rejected and nothing was changed.
User correctable — you can correct this.
What to do
- For numbers counted from 1970, write EPOCH|unit, optionally |size: EPOCH|SECONDS or EPOCH|MILLISECONDS|1. The unit is NANOSECONDS, MICROSECONDS, MILLISECONDS, SECONDS, MINUTES, HOURS or DAYS.
- For dates written as text, write SIMPLE_DATE_FORMAT|pattern, such as SIMPLE_DATE_FORMAT|yyyy-MM-dd HH:mm:ss. MM is the month and mm the minute.
- For a TIMESTAMP column, write TIMESTAMP.
- Set it in the column’s Format: Data Modeling step, Edit on the column, or the Schema tab after Edit.
DPE-2245 — Text was compared as a number during ingestion
An ingestion filter or transform compares{column} with a text value using =, != or a similar operator. During ingestion those operators compare numbers, so the text could not be compared and the rows could not be read.
User correctable — you can correct this.
What to do
- Compare text through strcmp, which returns 0 when the values match: strcmp(
{column}, ‘value’) != 0 in place of{column}!= ‘value’, and strcmp({column}, ‘value’) = 0 in place of{column}= ‘value’. - Edit the filter in Ingestion Configuration (Data Modeling step, Json view) or the column’s Transform Function, then preview the rows again.
DPE-2246 — That retention unit is not accepted
Retention Time Unit is set to{unit}, but retention has to be given in days or a smaller unit such as hours, so the configuration was not saved.
User correctable — you can correct this.
What to do
- On the Storage step of Additional Configuration, set Retention Time Unit to DAYS and enter the period in days in Retention Time Value: 365 for one year, 730 for two.
- For an existing dataset, open the Configuration tab, choose Edit, set retentionTimeUnit to DAYS with retentionTimeValue in days, and choose Apply.
- YEARS is listed as a unit but is not accepted yet, so convert years to days.
DPE-2247 — A column is set to both raw and dictionary encoding
Column{column} is listed in noDictionaryColumns, so it is stored raw, but its fieldConfigList entry sets encodingType to DICTIONARY. The two disagree, so the configuration was not saved.
User correctable — you can correct this.
What to do
- Open the table config JSON: the Configuration tab of an existing dataset (Edit) or, while creating one, the Validate step’s Table Config tab (Edit configuration).
- To keep a dictionary, remove
{column}from noDictionaryColumns (and noDictionaryConfig, if present) under tableIndexConfig. To store it raw, set encodingType to RAW in its fieldConfigList entry instead. Then apply the change.
DPE-2248 — A range index on a text column needs a dictionary
Column{column} is not numeric and has no dictionary, and a range index can only be built on such a column through its dictionary, so the configuration was not saved.
User correctable — you can correct this.
What to do
- On the Indexes tab, choose Edit, then either set the Encoding of
{column}to Dictionary or remove its range index, and choose Save. - In the table config JSON (the Validate step’s Table Config tab while creating, or the Configuration tab), remove
{column}from noDictionaryColumns and set its encodingType to DICTIONARY, or drop range from its indexes.
DPE-2249 — A primary key column is not in the schema
The schema lists a primary key column that is not one of its columns, or that is a built-in name starting with $, so the configuration was not saved. User correctable — you can correct this. What to do- Choose the key again in Primary Key Columns, on the Ingestion Type step for an upsert or deduplication dataset or the Details step for a dimension table. That list offers only columns that exist.
- If you edited the schema JSON, make every name in primaryKeyColumns match a column exactly, including case.
DPE-2250 — An upsert dataset cannot have a star-tree index
This dataset uses upsert and also declares a star-tree index, or turns on the default one. The two cannot be combined, so the configuration was not saved. User correctable — you can correct this. What to do- On the Indexes tab, choose Edit, delete each row under StarTree Index, and choose Save.
- If enableDefaultStarTree is true, or while creating the dataset, edit the JSON instead (the Validate step’s Table Config tab, or the Configuration tab): empty starTreeIndexConfigs and set enableDefaultStarTree to false under tableIndexConfig.
- If the star-tree index matters more than upsert, create the dataset again with Ingestion Type set to Append.
DPE-2251 — A column’s index settings could not be read
One column’s index settings could not be read, usually because the same index is declared twice: in a list under tableIndexConfig and in that column’s fieldConfigList entry. User correctable — you can correct this. What to do- Open the table config JSON: the Configuration tab of an existing dataset (Edit) or, while creating one, the Validate step’s Table Config tab (Edit configuration).
- For each column with an indexes block in fieldConfigList, remove that index from the lists under tableIndexConfig (such as invertedIndexColumns or rangeIndexColumns) and keep every value under indexes an object. Then apply the change.
DPE-2252 — The schema name was changed before the dataset was named
Until the dataset is named, its schema keeps the temporary name preview_table. The schema JSON was edited to name it{schemaName}, so it no longer matches and the change was not applied.
User correctable — you can correct this.
What to do
- On the Data Modeling step, open the Json view and either choose Cancel to drop the edit, or set schemaName under Column Configuration back to preview_table and choose Apply.
- Give the dataset its name in Table Name on the Details step of Additional Configuration. The schema takes that name automatically.
DPE-2253 — Stream settings are declared in two places
This streaming configuration has stream settings both in tableIndexConfig.streamConfigs and in ingestionConfig.streamIngestionConfig. Only one may hold them, so the configuration was not saved. User correctable — you can correct this. What to do- Delete streamConfigs from tableIndexConfig and keep the settings in ingestionConfig.streamIngestionConfig.streamConfigMaps, moving across any key you still need, such as a flush threshold.
- In Data Portal, edit it on the Validate step’s Table Config tab (Edit configuration, then Apply Changes), or on an existing dataset’s Configuration tab (Edit, then Apply).
DPE-2254 — That column name is reserved
{column} is the name of a built-in column every dataset already has, so a column of your own cannot use it and the configuration was not saved.
User correctable — you can correct this.
What to do
- On the Data Modeling step, open the Table view and delete the
{column}row, then continue. - If you need its values, rename the column in the source data, for example without the leading $, and preview again.
DPE-2255 — A dataset with this name already stores data elsewhere
A dataset named{table} already exists and keeps its data at a fixed storage location. This configuration points that storage somewhere else, which would cut off the data already stored, so it was not saved.
User correctable — you can correct this.
What to do
- If you are creating a new dataset, go back to Additional Configuration and choose a different Table Name.
- If you are editing
{table}, put bucket and pathPrefix under tierConfigs back to their saved values. - To keep the name but store the data somewhere new, delete
{table}and create it again.
DPE-2256 — The dataset was deleted, but we could not confirm it
The cluster removed{table}, but its confirmation came back in a form we could not read, so the request was reported as failed. This is on our side. The dataset’s entry in the list clears on its own within a few minutes.
Internal — a defect on our side.
What to do
- Refresh the Tables list in a few minutes; the dataset should no longer be listed. Deleting it again is not needed and would show this same message.
- If it is still listed after 10 minutes, contact StarTree support and quote the reference shown with this error.
DPE-2257 — No brokers are assigned to that tenant
The broker tenant{tenant} has no brokers assigned to it, so this dataset could not be placed on it and the configuration was rejected.
User correctable — you can correct this.
What to do
- Choose a tenant that has brokers: Broker Tenant on the Tenants step of Additional Configuration lists only those; in the JSON, set tenants.broker on the Validate step’s Table Config tab or the Configuration tab.
- Until a tenant is chosen, the Data Modeling step checks against the default tenant. If this appeared there, or
{tenant}is the one you want, ask a workspace administrator to assign brokers to{tenant}.
DPE-2258 — Batch and streaming settings could not be checked
This dataset has both a batch and a streaming half. When columns are edited, Data Portal checks the change with a temporary time column standing in for the streaming half’s, and the batch half’s time column does not match it. The mismatch comes from that placeholder, not from your settings. Internal — a defect on our side. What to do- To change this dataset’s columns now, open Cluster Manager > Pinot Components, select the dataset on the Tables tab, choose Edit Schema, make the change and choose Save.
- Contact StarTree support and quote the reference shown with this error so the check can be corrected.
DPE-2259 — That function cannot be used in a streaming transform
The Transform Function on{column} calls {function}, which can return a different value each time it runs. A streaming dataset must get the same result every time a record is read, so its transforms may only use functions whose result depends on their inputs.
User correctable — you can correct this.
What to do
- Choose Edit on
{column}, on the Data Modeling step or on the Schema tab after Edit, and remove{function}from its Transform Function. - To record arrival time, map the column from a timestamp carried in the source records instead.
- Clock functions such as now() and ago() are refused; string, math and date-conversion functions are fine.
DPE-2260 — Time Column Format not accepted for this source
The Start Time or End Time{value} could not be read with the Time Column Format {format}. For a SQL source that setting takes millisecondsSinceEpoch, secondsSinceEpoch or hoursSinceEpoch for epoch numbers, or a date pattern such as yyyy-MM-dd HH:mm:ss for text.
User correctable — you can correct this.
What to do
- On the Data Setup step, write Start Time, and End Time if set, in the Time Column Format: 2020-04-01 00:00:00 for yyyy-MM-dd HH:mm:ss, or a number such as 1585699200000 for millisecondsSinceEpoch.
- If the format itself is wrong, set Time Column Format to the column’s own: millisecondsSinceEpoch, secondsSinceEpoch, hoursSinceEpoch, or a date pattern.
- The 1:MILLISECONDS:EPOCH form is not accepted here, and there is no microsecond option; expose the column in milliseconds or seconds through a view at the source.
DPE-2261 — The Transform Function holds JSON, not an expression
The Transform Function for{column} contains configuration text, such as a transformFunction key or a whole column entry in braces, instead of the expression on its own, so it could not be read and nothing was changed.
User correctable — you can correct this.
What to do
- Edit
{column}on the Data Modeling step and leave only the expression in Transform Function, with no key, surrounding double quotes or braces: for example jsonPathString(source_column, ‘$.field’). - The result is written to the column you are editing. To write it to a different column, choose Add Column and give the new column that name.
DPE-2262 — External tables run only the sync task
The table configuration includes the{taskType} task, which an external table cannot run; only ExternalTableSyncTask is allowed.
User correctable — you can correct this.
What to do
- In the Configuration tab, click Edit and remove the
{taskType}entry from the task settings, keeping ExternalTableSyncTask; then Apply and Save.
DPE-2263 — That setting is not supported on external tables
External tables do not support{detail}, which this configuration sets.
User correctable — you can correct this.
What to do
- Remove it in the Indexes tab or the Configuration tab; the external table indexes page lists what is supported.
- Save the configuration again.
DPE-2264 — A star-tree index cannot be used with deletion vectors
The configuration has a star-tree index and enables deletion vectors, and external tables cannot combine the two. User correctable — you can correct this. What to do- In the Configuration tab, remove the star-tree index settings, including enableDefaultStarTree, or set enableDeletionVectors to false; then Apply and Save.
DPE-2265 — External tables cannot transform columns
The configuration adds a derived column or an ingestion transform, which an external table cannot apply because it reads the source files as they are. User correctable — you can correct this. What to do- Remove transform functions from the schema and transformConfigs from ingestionConfig in the Configuration tab, and compute derived values in queries instead.
DPE-2266 — The table’s sync settings are incomplete
The table’s ExternalTableSyncTask settings are missing a value the sync needs, such as the catalog type or one of the catalog’s settings. User correctable — you can correct this. What to do- Open the Configuration tab and compare the ExternalTableSyncTask settings with the connection’s: catalogType and the settings for that catalog must be present. Restore any value an edit removed, then Apply and Save.
DPE-2267 — A sync setting must be true or false
Setting{key} is set to {value}, which is neither true nor false.
User correctable — you can correct this.
What to do
- In the Configuration tab set
{key}to true or false; then Apply and Save.
DPE-2268 — The table’s storage tier settings are incomplete
An external table keeps its segments in a cloud storage tier, and this configuration’s tier settings are missing or incomplete. User correctable — you can correct this. What to do- Restore the tier settings that Connect external table generated for this table, rather than writing them by hand; each tier needs its storage backend properties.
DPE-2269 — A storage tier’s location cannot be changed
The change would move the table’s storage tier to another backend or location, which would leave the segments already stored there unreachable. User correctable — you can correct this. What to do- Keep the existing tier settings. To keep the table’s data somewhere else, create a new table and delete this one.
DPE-2270 — The segment group settings are not valid
The table’s segmentGroupConfig is not valid JSON or has a value out of range. User correctable — you can correct this. What to do- In the Configuration tab, make segmentGroupConfig valid JSON with minSegmentsPerGroup and maxSegmentsPerGroup of at least 1; then Apply and Save.
DPE-2271 — That index needs a dictionary on the column
An inverted, FST, IFST or star-tree index on column{column} needs a dictionary, and the column has none.
User correctable — you can correct this.
What to do
- Add a dictionary to column
{column}alongside the index, in the Indexes tab or the Configuration tab, keeping its forward index raw if the table requires raw encoding; then save.
DPE-2272 — This table uses a retired sync task
The table was created with an older sync task that this cluster no longer runs, so changes to it are rejected. User correctable — you can correct this. What to do- Create the table again from Data & AI, Tables, Connect external table, so it uses the current sync, then delete this one.
- If you need to keep this table, contact StarTree support and quote the reference shown with this error.
DPE-2273 — A table with this name is still being removed
A table with the same name was deleted moments ago and the cluster is still cleaning it up, so a new one cannot be created yet. Transient — temporary; retrying usually works. What to do- Wait a few minutes, then create the table again.
- If it still fails after ten minutes, contact StarTree support and quote the reference shown with this error.
DPE-2274 — Data from an earlier table with this name remains
Parts of an earlier table with the same name were not fully cleaned up, so a new table with that name cannot be created. User correctable — you can correct this. What to do- If a table with this name is still listed under Data & AI, Tables, delete it again, then create the new one.
- If none is listed, create the table under a different name, or contact StarTree support and quote the reference shown with this error.
DPE-2275 — Materialized views depend on this table
The table cannot be deleted while materialized views read from it:{views}.
User correctable — you can correct this.
What to do
- Drop the dependent materialized views, then delete the table again.
- The table’s sync schedule was cleared by this attempt; if you keep the table, click Resume Sync to restore it.
DPE-2276 — The cluster could not read the new table back
The table was submitted, but the cluster could not read its configuration back, so it was not created. This is on our side, not your configuration. Upstream — a service we depend on did not answer as expected. What to do- Try creating the table again in a few minutes.
- If it keeps happening, contact StarTree support and quote the reference shown with this error.
DPE-2277 — The cluster’s restart settings rejected the change
The cluster is set up to restart servers in batches, and that setting rejected this table change. This is on our side, not your configuration. Upstream — a service we depend on did not answer as expected. What to do- Try again in a few minutes; the setting can be unavailable just after a restart.
- If it keeps happening, contact StarTree support and quote the reference shown with this error.
DPE-2278 — The configuration was saved; nothing was reloaded
The new configuration was saved, but no loaded segments were found to reload, so it applies to segments as they are next loaded. Informational — not a failure; act only if you want a different outcome. What to do- No action is needed for a new table, which has no segments yet.
- If the table has data and servers were restarting, reload it later from the table’s Storage tab, or save the configuration again.
DPE-2279 — The task schedule is not a valid cron expression
The schedule set for the{task} task is not a cron expression the scheduler accepts.
User correctable — you can correct this.
What to do
- In the Configuration tab, set the task’s schedule to a Quartz cron expression, which starts with a seconds field and uses ? for the day of the month or week: for example 0 */5 * ? * * * runs every five minutes. Then Apply and Save.
DPE-2282 — A hidden credential could not be filled in
The table configuration hides a stored credential in{field}, and there is no single stored value to fill it in from: the configuration names no saved connection, that connection holds nothing for the field or holds two different values for it, the table’s saved configuration holds nothing for it in that place (a stream or task configuration added or renamed), or more than one saved stream configuration could be the one it stands for.
User correctable — you can correct this.
What to do
- If you are creating a table, go back to the connection step, choose the saved connection again, then repeat the preview or create the table.
- If you edited the configuration directly, keep each stream and task configuration where it was saved, or enter the credential in
{field}yourself. - If you are calling the API directly, name the saved connection in ingestionDataSourceSrn.
DPE-2283 — A stored credential can’t be used with a changed setting
The table configuration hides a stored credential in{field}, but changes {setting}, which decides where that credential is sent or which identity it is used with, from the value the saved connection has. A connection’s stored credential is only filled in alongside the settings it was saved with, unless you can edit the connection.
User correctable — you can correct this.
What to do
- Set
{setting}back to the value the saved connection has. - To use a different
{setting}, enter the credential in{field}yourself as well, or change it on the connection itself, or ask for edit access to the connection.
DPE-2284 — A time value is not a number
A number in the Data Setup settings could not be read:{value}. Usually it is Start Time or End Time, which have to be numbers when Time Column Format counts time since the epoch.
User correctable — you can correct this.
What to do
- When Time Column Format is millisecondsSinceEpoch, secondsSinceEpoch or hoursSinceEpoch, write Start Time and End Time as numbers in that unit, such as 1585699200000 for milliseconds.
- Otherwise check the other number fields on the Data Setup step for text.
- Then select Show Sample Data again.
DPE-2285 — That date pattern must start with the year
A Datetime column’s text has to sort in the same order as the dates it holds, so its pattern must run year, month, day, then time.{format} puts the parts in another order, so it cannot be used, even though it matches the values.
User correctable — you can correct this.
What to do
- Keep the column as text: on the Data Modeling step or the Schema tab, set its Field Type back to Dimension with Data Type STRING.
- To use it as time, add a LONG column with Add Column, Field Type Datetime and Format EPOCH|MILLISECONDS, whose Transform Function is fromDateTime applied to the text column with its pattern.
- Or have the source write dates year first, such as yyyy-MM-dd.
DPE-2286 — The schema name does not match the dataset name
The schema is named{schemaName}, but the dataset is {table}. The two must match, so the change was not applied.
User correctable — you can correct this.
What to do
- Set schemaName back to
{table}: on the Validate step’s Schema Config tab (Edit configuration, then Apply Changes), or in the Schema tab’s Json view on an existing dataset. - To rename the dataset, change Table Name on the Details step of Additional Configuration instead; the schema takes that name.
DPE-2287 — Groovy transforms are turned off here
The Transform Function on{column} uses Groovy, which this environment does not allow when data is ingested, so the configuration was rejected.
User correctable — you can correct this.
What to do
- Rewrite the Transform Function on
{column}with built-in functions instead, such as upper, concat, arithmetic, jsonPathString or fromDateTime. - Edit it on the Data Modeling step, or on the Schema tab after Edit, then Apply.
DPE-2288 — A dimension table needs batch ingestion settings
A dimension table is replaced whole on each load, so its table config needs batch ingestion settings with segmentIngestionType REFRESH, and this one has none. User correctable — you can correct this. What to do- On the Configuration tab choose Edit, add batchIngestionConfig under ingestionConfig with segmentIngestionType REFRESH and segmentIngestionFrequency DAILY, then Apply and Save.
- If it should not be a dimension table, set isDimTable back to false instead.
DPE-2289 — The preview failed on the file’s rows
The preview failed while reading the uploaded file’s rows, and the server did not report why. When the schema and table config are accepted and only the preview fails, the usual cause is a column’s Data Type, a filter or a transform that does not fit the values in the file. Internal — a defect on our side. What to do- On the Data Modeling step, check each column’s Data Type against the file: a text value in an INT, LONG, FLOAT or DOUBLE column fails here.
- In the Json view’s Ingestion Configuration, check filterConfig and transformConfigs: a filter that compares text with a number, or two transforms that read each other, fail only on the rows.
- Undo your last change and select Fetch Preview to find the one that fails. If the preview fails with the settings the wizard filled in, contact StarTree support and quote the reference shown with this error.
DPE-2290 — A column received several values where one is expected
Column{columnName} holds one value per row, but at least one row has several values for it, so the data could not be loaded.
User correctable — you can correct this.
What to do
- If
{columnName}should hold several values, edit it on the Data Modeling step, make it a Dimension column (only Dimension columns can hold several values), turn on Multi Value, and upload again. - If it should hold one value, correct the rows that have several. In a CSV file, the multi-value delimiter inside a value splits it into several values: a semicolon, unless the FileIngestionTask on the Validate step’s Table Config tab sets recordReader.prop.multiValueDelimiter to another character. Replace that character in those values.
DPE-2291 — The table configuration is not valid
The cluster rejected this table configuration, so it was not created or saved. Show details names the setting it objected to and why. User correctable — you can correct this. What to do- Read Show details for the setting and the reason.
- While creating a dataset, correct it on the Validate step’s Table Config tab with Edit configuration, then Apply Changes; for an external table, on the Table Config step. On an existing dataset, correct it on the Configuration tab with Edit, then Apply.
- If you edited the JSON by hand, check for a trailing comma or a value of the wrong type.
DPE-2292 — No task workers carry the tag this task asks for
A scheduled task in this table config asks to run on workers tagged{tag}, and this workspace has no workers with that tag, so the configuration was rejected.
User correctable — you can correct this.
What to do
- Remove minionInstanceTag from that task’s settings under task in the JSON so it runs on the workspace’s default workers: on the Validate step’s Table Config tab select Edit configuration, then Apply Changes; on an existing dataset’s Configuration tab select Edit, then Apply and Save.
- If
{tag}is the tag the task needs, contact StarTree support and quote the reference shown with this error so workers with that tag can be added.
DPE-2293 — Groovy filters are turned off here
The ingestion filter is written in Groovy, which this environment does not allow when data is ingested, so the configuration was rejected. User correctable — you can correct this. What to do- Rewrite the filter with built-in functions. Rows for which the filter is true are left out, so keep the same logic.
- Compare text through strcmp, which returns 0 when the values match; a plain = or != on text fails once rows are read. A Groovy !([‘A’, ‘B’].contains(col)) becomes strcmp(col, ‘A’) != 0 AND strcmp(col, ‘B’) != 0, and [‘A’, ‘B’].contains(col) becomes strcmp(col, ‘A’) = 0 OR strcmp(col, ‘B’) = 0.
- Edit filterFunction in Ingestion Configuration (Data Modeling step, Json view) and Apply, or on the Configuration tab after Edit, then Apply.
DPE-2294 — Only one flush threshold can be set
This streaming dataset sets more than one flush threshold, and only one may be above 0: realtime.segment.flush.threshold.rows, realtime.segment.flush.threshold.segment.rows or realtime.segment.flush.threshold.segment.size. Check all three, including the 200M size threshold Data Portal adds when you do not set one. User correctable — you can correct this. What to do- To flush by size, the default, remove realtime.segment.flush.threshold.segment.rows, and remove realtime.segment.flush.threshold.rows or set it to 0.
- To flush by row count, keep that key and set realtime.segment.flush.threshold.segment.size to 0.
- Change it where the key was added: Additional Config on the Data Setup step, streamConfigMaps in Ingestion Configuration (Data Modeling step, Json view), or the Configuration tab after Edit, then Apply.
DPE-2295 — A storage tier setting is not valid
A storage tier on this dataset has a segment selector type, segment age or storage type that is not accepted, so the configuration was rejected. The selector type must be time, with a segment age such as 7d, and the storage type must be pinot_server. User correctable — you can correct this. What to do- While creating a batch dataset, on the Additional Configuration step under Storage with Enable Tier Storage on, set Tier Segment Selector Type to time, Tier Segment Age to a period such as 7d or 24h, and Tier Storage Type to pinot_server.
- On an existing dataset, correct segmentSelectorType, segmentAge or storageType under tierConfigs on the Configuration tab (Edit, then Apply).
- For a table created through Connect external table, put its tier settings back to the values it was created with rather than writing them by hand.
DPE-2296 — A JSON column cannot hold several values
A column with Data Type JSON is set to Multi Value, so the schema was rejected. A JSON column holds one JSON value per row, and that value can itself be an array. User correctable — you can correct this. What to do- On the Data Modeling step, or on the Schema tab after Edit, open the JSON column with its pencil icon, clear Multi Value and choose Update Column; on the Schema tab, then Save.
- In the Json view, remove singleValueField false from that column, then Apply.
- To keep a list of plain values instead, give the column Data Type STRING or a number type and keep Multi Value.
DPE-2297 — The peer download scheme is missing or not valid
segmentsConfig.peerSegmentDownloadScheme must be http or https. Pauseless ingestion, turned on by pauselessConsumptionEnabled under streamIngestionConfig, requires it whenever the dataset keeps more than one replica, so the configuration was rejected. User correctable — you can correct this. What to do- If you did not mean to turn on pauseless ingestion, set pauselessConsumptionEnabled under streamIngestionConfig back to false.
- To keep it on, set peerSegmentDownloadScheme under segmentsConfig to http or https; StarTree Support can confirm which one this environment’s servers use.
- Make the change on the Configuration tab (Edit, then Apply), or while creating the dataset on the Validate step’s Table Config tab (Edit configuration, then Apply Changes).
DPE-2298 — The table asks for more servers than are available
The table’s instance assignment asks for{asked} servers from a pool that has {available}, so the table could not be placed on servers.
User correctable — you can correct this.
What to do
- On the Validate step, open Table Config and click Edit configuration.
- Under instanceAssignmentConfigMap, in replicaGroupPartitionConfig, lower numInstancesPerReplicaGroup, or numInstances when there are no replica groups, so the servers asked for are no more than
{available}. Set it to 0 to use every server available. - Click Apply Changes, then Submit.
- On an existing dataset, make the same change on the Configuration tab (Edit, Apply, Save).