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Title:
Spark 3.4: Multiple shuffle partitions per file in compaction by aokolnychyi · Pull Request #7897 · apache/iceberg · GitHub
Description:
This PR adds a new compaction option called shuffle-partitions-per-file for shuffle-based file rewriters. By default, our shuffling file rewriters assume each shuffle partition would become a separ...
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aokolnychyi, file, contributor, shuffle, author, szehonho, spark, partitions, partition, member, issues, files, commented, output, singhpk, compaction, data, size, sign, iceberg, public, shufflepartitionsperfile, separate, cluster, view, reviewed, case, sort, order, resources, pull, multiple, merged, conversation, memory, parameter, operation, sorted, test, sparkvsparksrcmainjavaorgapacheicebergsparkactionssparkshufflingdatarewriterjava, comment, assert, plan, bit, docs, skip, navigation, apache, projects, security,
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ensions/src/test/java/org/apache/iceberg/spark/extensions/testrewritedatafilesprocedure 4/spark/src/main/java/org/apache/iceberg/spark/actions/sparkshufflingdatarewriter 4/spark/src/main/scala/org/apache/spark/sql/execution/orderawarecoalesceexec member szehon-ho left contributor singhpk234 left member szehon-ho contributor singhpk234 shuffle-based file rewriters case class orderawarecoalesceexec import org view reviewed rodmeneses/iceberg sort-based optimizations supported options sorted partitions back spark memory spark/v3 multiple shuffle partitions iceberg partition bit dynamic depending separate output file target file size single sorted file zstd parquet data java outdated pull request test set shuffle-partitions max partition size memory resources custom coalesce operation conversation spark iceberg //iceberg 2gb files 👍 1 fix 512mb files apache java scala output file 8 shuffle partitions shuffle partitions shuffle-partitions aokolnychyi comment lgtm single file separate pr comprehensive list
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- Also wouldn't it make more sense to have 128MB as a conf (shuffle-threshold), otherwise its always a bit dynamic depending on the max partition size?
- Not to block this change, but did we consider having shuffle-threshold?
- This is nice, but did we also add a test that assert the sort order is preserved within partition?
- This works for sorted data, because we always use range partitioning for sort, right?
- Will we still shuffle to four partitions in this case and coalesce at end, unnecessarily?
- You mean like switching to a local sort if the size of the data to compact is small?
- Should we also assert that OrderAwareCoaleseExec is inserted by inspecting the plan ?
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