Ryan Williams created SPARK-11156:
-------------------------------------
Summary: Web UI doesn't count or show info about replicated blocks
Key: SPARK-11156
URL: https://issues.apache.org/jira/browse/SPARK-11156
Project: Spark
Issue Type: Bug
Components: Web UI
Affects Versions: 1.5.1
Reporter: Ryan Williams
When executors receive a replica of a block, they [notify the driver with a
{{UpdateBlockInfo}}
message|https://github.com/apache/spark/blob/4ee2cea2a43f7d04ab8511d9c029f80c5dadd48e/core/src/main/scala/org/apache/spark/storage/BlockManagerMaster.scala#L59-L61]
which [sends a {{SparkListenerBlockUpdated}} event to
SparkListeners|https://github.com/apache/spark/blob/4ee2cea2a43f7d04ab8511d9c029f80c5dadd48e/core/src/main/scala/org/apache/spark/storage/BlockManagerMasterEndpoint.scala#L67].
However, the web UI (via its BlockStatusListener) [ignores
{{SparkListenerBlockUpdated}} events for non-streaming
blocks|https://github.com/apache/spark/blob/4ee2cea2a43f7d04ab8511d9c029f80c5dadd48e/core/src/main/scala/org/apache/spark/storage/BlockStatusListener.scala#L57-L60].
As a result, in non-streaming apps:
* The "Executors" column on RDD Page doesn't show executors housing replicas;
it can only show the executor that initially computed (and initiated
replication of) the block.
* The executor-memory-usage and related stats displayed throughout the web
interface are undercounting due to ignorance of the existence of block replicas.
For example, here is the Storage tab for a simple app with 3 identical RDDs
cached with replication equal to 1, 2, and 3:
!http://f.cl.ly/items/3m3B2v2k2J23350I3t1c/Screen%20Shot%202015-10-16%20at%2012.30.54%20AM.png!
These were generated with:
{code}
val bar1 = sc.parallelize(1 to 100000000, 100).map(_ % 100 ->
1).reduceByKey(_+_, 100).setName("bar1").persist(StorageLevel(false, true,
false, true, 1))
bar1.count
val bar2 = sc.parallelize(1 to 100000000, 100).map(_ % 100 ->
1).reduceByKey(_+_, 100).setName("bar2").persist(StorageLevel(false, true,
false, true, 2))
bar2.count
val bar3 = sc.parallelize(1 to 100000000, 100).map(_ % 100 ->
1).reduceByKey(_+_, 100).setName("bar3").persist(StorageLevel(false, true,
false, true, 3))
bar3.count
{code}
Note the identically-reported memory usage across the three.
Here is the RDD page for the 3x-replicated RDD above:
!http://f.cl.ly/items/0t0H1o2S2g140s1A0X0k/Screen%20Shot%202015-10-16%20at%2012.31.24%20AM.png!
Note that only one executor is listed for each partition.
--
This message was sent by Atlassian JIRA
(v6.3.4#6332)
---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org
For additional commands, e-mail: issues-h...@spark.apache.org
