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In this recipe we’ll learn how to combine the data from fields in our data source into a single column in Apache Pinot.
Pinot Version0.10.0
Codestartreedata/pinot-recipes/combine-fields

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Prerequisites

To follow the code examples in this guide, you must install Docker locally and download recipes.
  1. If you haven’t already, download recipes.
  2. In terminal, go to the recipe by running the following command:
cd pinot-recipes/recipes/combine-fields

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Launch Pinot Cluster

You can spin up a Pinot Cluster by running the following command: 
docker-compose up
This command will run a single instance of the Pinot Controller, Pinot Server, Pinot Broker, and Zookeeper. You can find the docker-compose.yml file on GitHub.

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Dataset

We’re going to import the following JSON file: 
{"name":"Pete", "surname": "Smith"}
{"name":"John", "surname": "Jones"}
data/movies.json

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Pinot Schema and Table

Now let’s create a Pinot Schema and Table. First, the schema: 
{
  "schemaName": "people",
  "dimensionFieldSpecs": [
    {
      "name": "fullName",
      "dataType": "STRING"
    }
  ]
}
config/schema.json You can create the schema by running the following command: 
docker exec -it pinot-controller-json bin/pinot-admin.sh AddSchema \
  -schemaFile /config/schema.json \
  -exec
We’ll also have the following table config: 
{
  "tableName": "people",
  "tableType": "OFFLINE",
  "segmentsConfig": {
    "replication": 1,
    "schemaName": "people"
  },
  "ingestionConfig": {
    "transformConfigs": [
      {
        "columnName": "fullName",
        "transformFunction": "concat(name, surname, ' ')"
      }
    ],
    "batchIngestionConfig": {
      "segmentIngestionType": "APPEND",
      "segmentIngestionFrequency": "DAILY"
    }
  },
  "tenants": {
    "broker": "DefaultTenant",
    "server": "DefaultTenant"
  },
  "tableIndexConfig": {
    "loadMode": "MMAP"
  },
  "metadata": {}
}
config/table.json The highlighted section contains a transformation function that concatenates the name and surname fields, separated by a space. You can create the table by running the following command:` 
docker exec -it pinot-controller-json bin/pinot-admin.sh AddTable \
  -tableConfigFile /config/table.json \
  -exec

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Ingestion Job

Now we’re going to import the JSON file into Pinot. We’ll do this with the following ingestion spec: 
executionFrameworkSpec:
  name: 'standalone'
  segmentGenerationJobRunnerClassName: 'org.apache.pinot.plugin.ingestion.batch.standalone.SegmentGenerationJobRunner'
  segmentTarPushJobRunnerClassName: 'org.apache.pinot.plugin.ingestion.batch.standalone.SegmentTarPushJobRunner'
jobType: SegmentCreationAndTarPush
inputDirURI: '/data'
includeFileNamePattern: 'glob:**/import.json'
outputDirURI: '/opt/pinot/data/people/'
overwriteOutput: true
pinotFSSpecs:
  - scheme: file
    className: org.apache.pinot.spi.filesystem.LocalPinotFS
recordReaderSpec:
  dataFormat: 'json'
  className: 'org.apache.pinot.plugin.inputformat.json.JSONRecordReader'
tableSpec:
  tableName: 'people'
pinotClusterSpecs:
  - controllerURI: 'http://pinot-controller-combine:9000'
pushJobSpec:
  pushAttempts: 2
  pushRetryIntervalMillis: 1000
config/job-spec.yml You can run the following command to run the import: 
docker exec -it pinot-controller-json bin/pinot-admin.sh LaunchDataIngestionJob \
  -jobSpecFile /config/job-spec.yml

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Querying

Once that’s completed, navigate to localhost:9000/#/query and click on the people table or copy/paste the following query: 
select * 
from people
You will see the following output:
fullName
Pete Smith
John Jones
Query Results We can see that the name and surname fields from our JSON file have been combined into a single fullName column for each person.
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