Fills missing time data points. Used to ensure data fetched with SQL is a correct timeseries for downstream nodes. The SQL language is not timeseries oriented. The GROUP BY timeColumn clause does not create a point if there is no data for a time bucket.

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Inputs

A table with a time index to fill.

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Outputs

The table with the time index filled. No naming constraint for outputKey and outputName.

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Parameters

namedescriptiondefault value
component.timestampThe name of the time index column.timestamp
component.monitoringGranularityGranularity of the time index. In ISO-8601 format. Eg P1D.
component.minTimeInferenceInference strategy for the minimum time constraint.FROM_DATA
component.maxTimeInferenceInference strategy for the maximum time constraint.FROM_DETECTION_TIME
component.lookbackOffset to use for a time inference with lookback. In ISO-8601 format. Eg P7D.
component.fillNullMethodMethod to use to fill null values in the metric column.FILL_WITH_ZEROES
Automatic configuration with macros.minTimeInference, maxTimeInference and lookback are not required if the __timeFilter macro was used to get the input data.
monitoringGranularity is not required if the __timeGroup macro was used to get the input data.

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Available inference strategies for minTimeInference and maxTimeInference

The TimeIndexFiller needs a start and an end to fill the time index. These boundaries can be computed with different strategies.
namedescription
FROM_DATAThe minimum (resp maximum) time for which to fill the index is the minimum (resp maximum) time observed in the input data.
FROM_DETECTION_TIMEThe minimum (resp maximum) time corresponds to the minimum (resp maximum) time used by the detection pipeline run.
FROM_DETECTION_TIME_WITH_LOOKBACKLike above, use the detection pipeline boundaries, but apply an offset. Eg: minTime - lookback.

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Available methods for fillNullMethod

When a missing time point is added, the metric value is unknown. This value can be filled with one the following methods.
namedescription
FILL_WITH_ZEROESReplace null values with zeroes.
KEEP_NULLKeep the null values.
INTERPOLATEAvailable soon. Interpolate a value based on the preceding and next available values.
Note that most of the detectors are not compatible with null values for the moment.

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Examples

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Without macros

    {
      "name": "baselineMissingDataManager",
      "type": "TimeIndexFiller",
      "params": {
        "component.monitoringGranularity": "P1D",
        "component.timestamp": "ts",
        "component.minTimeInference": "FROM_DETECTION_TIME_WITH_LOOKBACK",
        "component.maxTimeInference": "FROM_DETECTION_TIME_WITH_LOOKBACK",
        "component.lookback": "P7D"
      },
      "inputs": [
        {
          "sourcePlanNode": "baselineDataFetcher",
          "sourceProperty": "baselineOutput"
        }
      ],
      "outputs": [
        {
          "outputKey": "filler",
          "outputName": "baselineOutput"
        }
      ]
    }

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With macros

If __timeFilter and __timeGroup macros are used in the upstream DataFetcher node, and if the metric is named metric: 
  {
    "name": "missingDataManager",
    "type": "TimeIndexFiller",
    "params": {
        "component.timestamp": "ts"
      },
    "inputs": [
      {
        "sourcePlanNode": "baselineDataFetcher",
        "sourceProperty": "baselineOutput"
      }
    ],
    "outputs": [
      {
        "outputKey": "filler",
        "outputName": "baselineOutput"
      }
    ]
  }