[jira] [Created] (SPARK-22052) Incorrect Metric reported in MetricsReporter.scala

["Jason Taaffe (JIRA)" <ji...@apache.org>]

Jason Taaffe created SPARK-22052:
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             Summary: Incorrect Metric reported 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


The wrong metric is being sent in MetricsReporter.scala

The current implementation for processingRate-total uses the wrong metric:
Look at the first and second registerGauge. The second one mistakenly uses inputRowsPerSecond instead of processedRowsPerSecond.

{code:java}
package org.apache.spark.sql.execution.streaming

import java.{util => ju}

import scala.collection.mutable

import com.codahale.metrics.{Gauge, MetricRegistry}

import org.apache.spark.internal.Logging
import org.apache.spark.metrics.source.{Source => CodahaleSource}
import org.apache.spark.util.Clock

/**
 * Serves metrics from a [[org.apache.spark.sql.streaming.StreamingQuery]] to
 * Codahale/DropWizard metrics
 */
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. 





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