[jira] [Created] (SPARK-17386) Default trigger interval causes excessive RPC calls

["Frederick Reiss (JIRA)" <ji...@apache.org>]

Frederick Reiss created SPARK-17386:
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             Summary: Default trigger interval causes excessive RPC calls
                 Key: SPARK-17386
                 URL: https://issues.apache.org/jira/browse/SPARK-17386
             Project: Spark
          Issue Type: Bug
          Components: Streaming
            Reporter: Frederick Reiss


The default trigger interval for a Structured Streaming query is `ProcessingTime(0)`, i.e. "trigger new microbatches as fast as possible". When the trigger is set to this default value, the scheduler in `StreamExecution` will spin in a tight loop calling `getOffset()` on every `Source` until new data arrives.

In test cases, where most of the sources are `MemoryStream` or `TextSocketSource`, this spinning leads to excessive CPU usage.

In a production environment, this spinning could take down critical infrastructure. Most sources in Spark clusters will be `FileStreamSource` or the not-yet-written Kafka 0.10 Source. The `getOffset()` method of `FileStreamSource` performs a directory listing of an HDFS directory. If the scheduler calls `FileStreamSource.getOffset()` in a tight loop, Spark will make several hundred RPC calls per second to the HDFS NameNode. This overhead could disrupt service to other systems using HDFS, including Spark itself. A similar situation will exist with the Kafka source, the `getOffset()` method of which will presumably call Kafka's `Consumer.poll()` method.



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