Package org.apache.druid.data.input
Class InputRowSchema
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- org.apache.druid.data.input.InputRowSchema
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Constructor Summary
Constructors Constructor Description InputRowSchema(TimestampSpec timestampSpec, DimensionsSpec dimensionsSpec, ColumnsFilter columnsFilter)InputRowSchema(TimestampSpec timestampSpec, DimensionsSpec dimensionsSpec, ColumnsFilter columnsFilter, Set<String> metricNames)
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Method Summary
All Methods Instance Methods Concrete Methods Modifier and Type Method Description ColumnsFiltergetColumnsFilter()AColumnsFilterthat can filter down the list of columns that must be read after flattening.DimensionsSpecgetDimensionsSpec()@NotNull Set<String>getMetricNames()TimestampSpecgetTimestampSpec()
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Constructor Detail
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InputRowSchema
public InputRowSchema(TimestampSpec timestampSpec, DimensionsSpec dimensionsSpec, ColumnsFilter columnsFilter)
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InputRowSchema
public InputRowSchema(TimestampSpec timestampSpec, DimensionsSpec dimensionsSpec, ColumnsFilter columnsFilter, Set<String> metricNames)
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Method Detail
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getTimestampSpec
public TimestampSpec getTimestampSpec()
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getDimensionsSpec
public DimensionsSpec getDimensionsSpec()
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getColumnsFilter
public ColumnsFilter getColumnsFilter()
AColumnsFilterthat can filter down the list of columns that must be read after flattening. Logically, Druid applies ingestion spec components in a particular order: first flattenSpec (if any), then timestampSpec, then transformSpec, and finally dimensionsSpec and metricsSpec. If a flattenSpec is provided, this method returns a filter that should be applied after flattening. So, it will be based on what needs to pass between the flattenSpec and everything beyond it.
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