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https://issues.apache.org/jira/browse/BEAM-5865?focusedWorklogId=238479&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-238479
]
ASF GitHub Bot logged work on BEAM-5865:
----------------------------------------
Author: ASF GitHub Bot
Created on: 07/May/19 13:50
Start Date: 07/May/19 13:50
Worklog Time Spent: 10m
Work Description: mxm commented on pull request #8499: [BEAM-5865] Create
optional auto-balancing sharding function for Flink
URL: https://github.com/apache/beam/pull/8499#discussion_r281631096
##########
File path:
runners/flink/src/main/java/org/apache/beam/runners/flink/FlinkStreamingPipelineTranslator.java
##########
@@ -222,7 +282,117 @@ boolean canTranslate(T transform,
FlinkStreamingTranslationContext context) {
@Override
public Map<PValue, ReplacementOutput> mapOutputs(
Map<TupleTag<?>, PValue> outputs, WriteFilesResult<DestinationT>
newOutput) {
- return Collections.emptyMap();
+ return ReplacementOutputs.tagged(outputs, newOutput);
+ }
+ }
+
+ /**
+ * Flink has a known problem of unevenly assigning keys to key groups (and
then workers) for cases
+ * that number of keys is not >> key groups. This is typical scenario when
writing files, where
+ * one do not want to end up with too many small files. This {@link
ShardingFunction} implements
+ * what was suggested on Flink's <a
+ *
href="http://mail-archives.apache.org/mod_mbox/flink-dev/201901.mbox/%3CCAOUjMkygmFMDbOJNCmndrZ0bYug=iQJmVz6QvMW7C87n=pw...@mail.gmail.com%3E";>mailing
+ * list</a> and properly chooses shard keys in a way that they are
distributed evenly among
+ * workers by Flink.
+ */
+ private static class FlinkAutoBalancedShardKeyShardingFunction<UserT,
DestinationT>
+ implements ShardingFunction<UserT, DestinationT> {
+
+ private final int parallelism;
+ private final int maxParallelism;
+ private final Coder<DestinationT> destinationCoder;
+ private final Map<CacheKey, ShardedKey<Integer>> cache = new HashMap<>();
+ private final Set<Integer> usedSalts = new HashSet<>();
+
+ private int shardNumber = -1;
+
+ private FlinkAutoBalancedShardKeyShardingFunction(
+ int parallelism, int maxParallelism, Coder<DestinationT>
destinationCoder) {
+ this.parallelism = parallelism;
+ this.maxParallelism = maxParallelism;
+ this.destinationCoder = destinationCoder;
+ }
+
+ @Override
+ public ShardedKey<Integer> assignShardKey(
+ DestinationT destination, UserT element, int shardCount) throws
Exception {
+
+ if (shardNumber == -1) {
+ shardNumber = ThreadLocalRandom.current().nextInt(shardCount);
+ } else {
+ shardNumber = (shardNumber + 1) % shardCount;
+ }
+
+ int destinationKey =
+ Arrays.hashCode(CoderUtils.encodeToByteArray(destinationCoder,
destination));
+ // we need to ensure that keys are always stable no matter at which
worker they
+ // are created and what is an order of observed shard numbers
+ if (cache.size() < shardNumber) {
+ for (int i = 0; i < shardNumber; i++) {
+ generateInternal(new CacheKey(destinationKey, i));
+ }
+ }
Review comment:
Could be refactored to a method named `generateInitialShardedKeys` which
only takes care of the initial generation.
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Issue Time Tracking
-------------------
Worklog Id: (was: 238479)
Time Spent: 1h 40m (was: 1.5h)
> Auto sharding of streaming sinks in FlinkRunner
> -----------------------------------------------
>
> Key: BEAM-5865
> URL: https://issues.apache.org/jira/browse/BEAM-5865
> Project: Beam
> Issue Type: Improvement
> Components: runner-flink
> Reporter: Maximilian Michels
> Assignee: Jozef Vilcek
> Priority: Major
> Time Spent: 1h 40m
> Remaining Estimate: 0h
>
> The Flink Runner should do auto-sharding of streaming sinks, similar to
> BEAM-1438. That way, the user doesn't have to set shards manually which
> introduces additional shuffling and might cause skew in the distribution of
> data.
> As per discussion:
> https://lists.apache.org/thread.html/7b92145dd9ae68da1866f1047445479f51d31f103d6407316bb4114c@%3Cuser.beam.apache.org%3E
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