[SPARK-22052] Incorrect Metric assigned in MetricsReporter.scala

Current implementation for processingRate-total uses wrong metric:
mistakenly uses inputRowsPerSecond instead of processedRowsPerSecond

## What changes were proposed in this pull request?
Adjust processingRate-total from using inputRowsPerSecond to processedRowsPerSecond

## How was this patch tested?

Built spark from source with proposed change and tested output with correct parameter. Before change the csv metrics file for inputRate-total and processingRate-total displayed the same values due to the error. After changing MetricsReporter.scala the processingRate-total csv file displayed the correct metric.
<img width="963" alt="processed rows per second" src="https://user-images.githubusercontent.com/32072374/30554340-82eea12c-9ca4-11e7-8370-8168526ff9a2.png">

Please review http://spark.apache.org/contributing.html before opening a pull request.

Author: Taaffy <32072374+Taaffy@users.noreply.github.com>

Closes #19268 from Taaffy/patch-1.

(cherry picked from commit 1bc17a6)
Signed-off-by: Sean Owen <sowen@cloudera.com>

sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/MetricsReporter.scala

@@ -40,7 +40,7 @@ class MetricsReporter(
   // 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("processingRate-total", () => stream.lastProgress.processedRowsPerSecond)
   registerGauge("latency", () => stream.lastProgress.durationMs.get("triggerExecution").longValue())
 
   private def registerGauge[T](name: String, f: () => T)(implicit num: Numeric[T]): Unit = {