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https://issues.apache.org/jira/browse/FLINK-3322?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15503225#comment-15503225
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ASF GitHub Bot commented on FLINK-3322:
---------------------------------------
Github user ggevay commented on a diff in the pull request:
https://github.com/apache/flink/pull/2510#discussion_r79376690
--- Diff:
flink-runtime/src/main/java/org/apache/flink/runtime/operators/JoinDriver.java
---
@@ -128,17 +130,22 @@ public void prepare() throws Exception{
ConfigConstants.DEFAULT_RUNTIME_HASH_JOIN_BLOOM_FILTERS);
// create and return joining iterator according to provided
local strategy.
- if (objectReuseEnabled) {
- switch (ls) {
- case INNER_MERGE:
- this.joinIterator = new
ReusingMergeInnerJoinIterator<>(in1, in2,
+ if (reset) {
+ resetForIterativeTasks(in1, in2, serializer1,
serializer2, comparator1, comparator2, pairComparatorFactory);
+ reset = false;
+ }
+ if (joinIterator == null) {
--- End diff --
This solution here with the `reset` flag is very hacky. I would like to
point your attention to the `initialize` method of `ResettableDriver`, which is
called once before the first iteration step. Instead of controlling with flags
what `prepare` does, you should cleanly separate its work into `initialize` and
`reset`. (If they have overlapping parts, then these can go to a new private
method that both of them call.)
> MemoryManager creates too much GC pressure with iterative jobs
> --------------------------------------------------------------
>
> Key: FLINK-3322
> URL: https://issues.apache.org/jira/browse/FLINK-3322
> Project: Flink
> Issue Type: Bug
> Components: Local Runtime
> Affects Versions: 1.0.0
> Reporter: Gabor Gevay
> Assignee: ramkrishna.s.vasudevan
> Priority: Critical
> Fix For: 1.0.0
>
> Attachments: FLINK-3322.docx, FLINK-3322_reusingmemoryfordrivers.docx
>
>
> When taskmanager.memory.preallocate is false (the default), released memory
> segments are not added to a pool, but the GC is expected to take care of
> them. This puts too much pressure on the GC with iterative jobs, where the
> operators reallocate all memory at every superstep.
> See the following discussion on the mailing list:
> http://apache-flink-mailing-list-archive.1008284.n3.nabble.com/Memory-manager-behavior-in-iterative-jobs-tt10066.html
> Reproducing the issue:
> https://github.com/ggevay/flink/tree/MemoryManager-crazy-gc
> The class to start is malom.Solver. If you increase the memory given to the
> JVM from 1 to 50 GB, performance gradually degrades by more than 10 times.
> (It will generate some lookuptables to /tmp on first run for a few minutes.)
> (I think the slowdown might also depend somewhat on
> taskmanager.memory.fraction, because more unused non-managed memory results
> in rarer GCs.)
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