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[HUDI-4980] Calculate avg record size using commit only #6864

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Merged
codope merged 1 commit into from
Oct 5, 2022
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[HUDI-4980] Calculate avg record size using commit only #6864

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16 changes: 12 additions & 4 deletions ...udi-spark-client/src/main/java/org/apache/hudi/table/action/commit/UpsertPartitioner.java
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Original file line number Diff line number Diff line change
Expand Up @@ -29,13 +29,15 @@
import org.apache.hudi.common.model.HoodieWriteStat;
import org.apache.hudi.common.table.timeline.HoodieInstant;
import org.apache.hudi.common.table.timeline.HoodieTimeline;
import org.apache.hudi.common.util.CollectionUtils;
import org.apache.hudi.common.util.NumericUtils;
import org.apache.hudi.common.util.Option;
import org.apache.hudi.common.util.collection.Pair;
import org.apache.hudi.config.HoodieWriteConfig;
import org.apache.hudi.table.HoodieTable;
import org.apache.hudi.table.WorkloadProfile;
import org.apache.hudi.table.WorkloadStat;

import org.apache.log4j.LogManager;
import org.apache.log4j.Logger;
import org.apache.spark.api.java.JavaRDD;
Expand All @@ -54,6 +56,8 @@

import scala.Tuple2;

import static org.apache.hudi.common.table.timeline.HoodieTimeline.COMMIT_ACTION;

/**
* Packs incoming records to be upserted, into buckets (1 bucket = 1 RDD partition).
*/
Expand Down Expand Up @@ -158,13 +162,17 @@ private List<SmallFile> filterSmallFilesInClustering(final Set<String> pendingCl
private void assignInserts(WorkloadProfile profile, HoodieEngineContext context) {
// for new inserts, compute buckets depending on how many records we have for each partition
Set<String> partitionPaths = profile.getPartitionPaths();
long averageRecordSize =
averageBytesPerRecord(table.getMetaClient().getActiveTimeline().getCommitTimeline().filterCompletedInstants(),
config);
/*
* NOTE: we only use commit instants to calculate average record size because replacecommit can be
* created by clustering, which has smaller average record size, which affects assigning inserts and
* may result in OOM by making spark underestimate the actual input record sizes.
*/
long averageRecordSize = averageBytesPerRecord(table.getMetaClient().getActiveTimeline()
.getTimelineOfActions(CollectionUtils.createSet(COMMIT_ACTION)).filterCompletedInstants(), config);
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@codope codope Oct 4, 2022

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The change looks good. Is it possible to reproduce a workload for this kind of scenario?

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@xushiyan xushiyan Oct 5, 2022 •
edited
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simulated the scenario: COW inserts created small files, and then cluster created larger files.

Clustered file

4.4M Oct  5 18:33 9b3b96be-95ca-4e93-9a08-ab49640bd113-0_2-99-376_20221005183355230.parquet

// cat .hoodie/xxx.replacecommit
      "numWrites" : 39781,
      "totalWriteBytes" : 4664174,
// avg ≈ 117

Inserted file

863K Oct  5 18:33 d88007a8-f5d9-4c97-a5f1-56907b99d4a1-0_23-77-286_20221005183349960.parquet

// cat .hoodie/xxx.commit
      "numWrites" : 3588,
      "totalWriteBytes" : 818456,
// avg ≈ 228

so using replacecommit tends to underestimate avg rec size

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@codope codope Oct 5, 2022

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Cool. Thanks for sharing.

LOG.info("AvgRecordSize => " + averageRecordSize);

Map<String, List<SmallFile>> partitionSmallFilesMap =
getSmallFilesForPartitions(new ArrayList<String>(partitionPaths), context);
getSmallFilesForPartitions(new ArrayList<>(partitionPaths), context);

Map<String, Set<String>> partitionPathToPendingClusteringFileGroupsId = getPartitionPathToPendingClusteringFileGroupsId();

Expand Down