[jira] [Resolved] (SPARK-22052) Incorrect Metric assigned in MetricsReporter.scala

["Sean Owen (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/SPARK-22052?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Sean Owen resolved SPARK-22052.
-------------------------------
       Resolution: Fixed
    Fix Version/s: 2.1.2
                   2.3.0
                   2.2.1

Issue resolved by pull request 19268
[https://github.com/apache/spark/pull/19268]

> Incorrect Metric assigned in MetricsReporter.scala
> --------------------------------------------------
>
>                 Key: SPARK-22052
>                 URL: https://issues.apache.org/jira/browse/SPARK-22052
>             Project: Spark
>          Issue Type: Bug
>          Components: Input/Output, Structured Streaming
>    Affects Versions: 2.2.0, 2.3.0
>         Environment: Spark 2.2 
> MetricsReporter.scala
>            Reporter: Jason Taaffe
>            Priority: Minor
>             Fix For: 2.2.1, 2.3.0, 2.1.2
>
>         Attachments: Processed Rows Per Second.png
>
>
> The wrong metric is being sent in MetricsReporter.scala
> The current implementation for processingRate-total is assigned the wrong metric:
> Look at the first and second registerGauge. The second one mistakenly uses inputRowsPerSecond instead of processedRowsPerSecond.
> {code:java}
> class MetricsReporter(
>     stream: StreamExecution,
>     override val sourceName: String) extends CodahaleSource with Logging {
>   override val metricRegistry: MetricRegistry = new MetricRegistry
>   // Metric names should not have . in them, so that all the metrics of a query are identified
>   // together in Ganglia as a single metric group
>   registerGauge("inputRate-total", () => stream.lastProgress.inputRowsPerSecond)
>   registerGauge("processingRate-total", () => stream.lastProgress.inputRowsPerSecond)
>   registerGauge("latency", () => stream.lastProgress.durationMs.get("triggerExecution").longValue())
>   private def registerGauge[T](name: String, f: () => T)(implicit num: Numeric[T]): Unit = {
>     synchronized {
>       metricRegistry.register(name, new Gauge[T] {
>         override def getValue: T = f()
>       })
>     }
>   }
> }
> {code}
> [https://github.com/apache/spark/blob/master/sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/MetricsReporter.scala]
> After adjusting the line and rebuilding from source I tested the change by checking the csv files produced via the metrics properties file. Previously inputRate-total and processingRate-total were identical due to the same metric being used. After the change the processingRate-total file held the right value. 
> Please check the attached file "Processed Rows Per Second".
> After altering the code the correct values are displayed in column B. 
> They match the data from the INFO StreamExecution displayed during streaming



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