Class StreamingQueryProgress
- All Implemented Interfaces:
- Serializable
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.
 
 param:  id A unique query id that persists across restarts. See StreamingQuery.id().
 param:  runId A query id that is unique for every start/restart. See StreamingQuery.runId().
 param:  name User-specified name of the query, null if not specified.
 param:  timestamp Beginning time of the trigger in ISO8601 format, i.e. UTC timestamps.
 param:  batchId 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.
 param:  batchDuration The process duration of each batch.
 param:  durationMs The amount of time taken to perform various operations in milliseconds.
 param:  eventTime 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
                 - Since:
- 2.1.0
- See Also:
- 
Method SummaryModifier and TypeMethodDescriptionlonglongbatchId()id()doubleThe aggregate (across all sources) rate of data arriving.json()The compact JSON representation of this progress.name()longThe aggregate (across all sources) number of records processed in a trigger.The pretty (i.e.doubleThe aggregate (across all sources) rate at which Spark is processing data.runId()sink()sources()toString()
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Method Details- 
id
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runId
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name
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timestamp
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batchIdpublic long batchId()
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batchDurationpublic long batchDuration()
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durationMs
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eventTime
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stateOperators
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sources
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sink
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observedMetrics
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numInputRowspublic long numInputRows()The aggregate (across all sources) number of records processed in a trigger.
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inputRowsPerSecondpublic double inputRowsPerSecond()The aggregate (across all sources) rate of data arriving.
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processedRowsPerSecondpublic double processedRowsPerSecond()The aggregate (across all sources) rate at which Spark is processing data.
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jsonThe compact JSON representation of this progress.
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prettyJsonThe pretty (i.e. indented) JSON representation of this progress.
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toString
 
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