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https://issues.apache.org/jira/browse/BEAM-6812?focusedWorklogId=216287&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-216287
]
ASF GitHub Bot logged work on BEAM-6812:
----------------------------------------
Author: ASF GitHub Bot
Created on: 20/Mar/19 16:05
Start Date: 20/Mar/19 16:05
Worklog Time Spent: 10m
Work Description: dmvk commented on pull request #8042: [BEAM-6812]:
Create a custom hash partitioner that deals with arrays during spark combines
URL: https://github.com/apache/beam/pull/8042#discussion_r267398311
##########
File path:
runners/spark/src/main/java/org/apache/beam/runners/spark/translation/GroupCombineFunctions.java
##########
@@ -146,20 +147,40 @@
JavaPairRDD<K, WindowedValue<KV<K, InputT>>> inRddDuplicatedKeyPair =
rdd.mapToPair(TranslationUtils.toPairByKeyInWindowedValue());
- JavaPairRDD<K, SerializableAccumulator<KV<K, AccumT>>> accumulatedResult =
- inRddDuplicatedKeyPair.combineByKey(
- input ->
-
SerializableAccumulator.of(sparkCombineFn.createCombiner(input),
iterAccumCoder),
- (acc, input) ->
- SerializableAccumulator.of(
- sparkCombineFn.mergeValue(input,
acc.getOrDecode(iterAccumCoder)),
- iterAccumCoder),
- (acc1, acc2) ->
- SerializableAccumulator.of(
- sparkCombineFn.mergeCombiners(
- acc1.getOrDecode(iterAccumCoder),
acc2.getOrDecode(iterAccumCoder)),
- iterAccumCoder));
+ JavaPairRDD<K, SerializableAccumulator<KV<K, AccumT>>> accumulatedResult;
+ if (partitioner == null) {
Review comment:
I reckon partitioner can be always `non null` if we tweak logic that
resolves number of partitions little bit
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Issue Time Tracking
-------------------
Worklog Id: (was: 216287)
Time Spent: 1h 40m (was: 1.5h)
> HashPartitioning on Spark with arrays as keys produces unpredictable results
> ----------------------------------------------------------------------------
>
> Key: BEAM-6812
> URL: https://issues.apache.org/jira/browse/BEAM-6812
> Project: Beam
> Issue Type: Bug
> Components: runner-spark
> Reporter: Ankit Jhalaria
> Assignee: Ankit Jhalaria
> Priority: Critical
> Time Spent: 1h 40m
> Remaining Estimate: 0h
>
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