Class

org.apache.spark.sql.streaming

StreamingQueryProgress

Related Doc: package streaming

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class StreamingQueryProgress extends Serializable

Information about progress made in the execution of a StreamingQuery during a trigger. Each event relates to processing done for a single trigger of the streaming query. Events are emitted even when no new data is available to be processed.

Annotations
@Evolving()
Source
progress.scala
Since

2.1.0

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Serializable, Serializable, AnyRef, Any
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  1. StreamingQueryProgress
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Value Members

  1. final def !=(arg0: Any): Boolean

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  2. final def ##(): Int

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  3. final def ==(arg0: Any): Boolean

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  4. final def asInstanceOf[T0]: T0

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  5. val batchId: Long

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    A unique id for the current batch of data being processed.

    A unique id for the current batch of data being processed. Note that in the case of retries after a failure a given batchId my be executed more than once. Similarly, when there is no data to be processed, the batchId will not be incremented.

  6. def clone(): AnyRef

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    @throws( ... )
  7. val durationMs: Map[String, Long]

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    The amount of time taken to perform various operations in milliseconds.

  8. final def eq(arg0: AnyRef): Boolean

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  9. def equals(arg0: Any): Boolean

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  10. val eventTime: Map[String, String]

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    Statistics of event time seen in this batch.

    Statistics of event time seen in this batch. It may contain the following keys:

    "max" -> "2016-12-05T20:54:20.827Z"  // maximum event time seen in this trigger
    "min" -> "2016-12-05T20:54:20.827Z"  // minimum event time seen in this trigger
    "avg" -> "2016-12-05T20:54:20.827Z"  // average event time seen in this trigger
    "watermark" -> "2016-12-05T20:54:20.827Z"  // watermark used in this trigger

    All timestamps are in ISO8601 format, i.e. UTC timestamps.

  11. def finalize(): Unit

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    @throws( classOf[java.lang.Throwable] )
  12. final def getClass(): Class[_]

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  13. def hashCode(): Int

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  14. val id: UUID

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    A unique query id that persists across restarts.

    A unique query id that persists across restarts. See StreamingQuery.id().

  15. def inputRowsPerSecond: Double

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    The aggregate (across all sources) rate of data arriving.

  16. final def isInstanceOf[T0]: Boolean

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  17. def json: String

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    The compact JSON representation of this progress.

  18. val name: String

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    User-specified name of the query, null if not specified.

  19. final def ne(arg0: AnyRef): Boolean

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  20. final def notify(): Unit

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  21. final def notifyAll(): Unit

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  22. def numInputRows: Long

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    The aggregate (across all sources) number of records processed in a trigger.

  23. def prettyJson: String

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    The pretty (i.e.

    The pretty (i.e. indented) JSON representation of this progress.

  24. def processedRowsPerSecond: Double

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    The aggregate (across all sources) rate at which Spark is processing data.

  25. val runId: UUID

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    A query id that is unique for every start/restart.

    A query id that is unique for every start/restart. See StreamingQuery.runId().

  26. val sink: SinkProgress

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  27. val sources: Array[SourceProgress]

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    detailed statistics on data being read from each of the streaming sources.

  28. val stateOperators: Array[StateOperatorProgress]

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    Information about operators in the query that store state.

  29. final def synchronized[T0](arg0: ⇒ T0): T0

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  30. val timestamp: String

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    Beginning time of the trigger in ISO8601 format, i.e.

    Beginning time of the trigger in ISO8601 format, i.e. UTC timestamps.

  31. def toString(): String

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    StreamingQueryProgress → AnyRef → Any
  32. final def wait(): Unit

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    @throws( ... )
  33. final def wait(arg0: Long, arg1: Int): Unit

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  34. final def wait(arg0: Long): Unit

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Inherited from Serializable

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