Flink:RewriteDataFiles support filter in plan #13669
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pvary
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Jul 25, 2025
.../v2.0/flink/src/test/java/org/apache/iceberg/flink/maintenance/api/TestRewriteDataFiles.java
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pvary
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Jul 25, 2025
...link/src/main/java/org/apache/iceberg/flink/maintenance/operator/DataFileRewritePlanner.java
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pvary
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Jul 25, 2025
...link/src/main/java/org/apache/iceberg/flink/maintenance/operator/DataFileRewritePlanner.java
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@mxm: Your thoughts? |
mxm
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Jul 29, 2025
| .maxFileSizeBytes(2_000_000L) | ||
| .minFileSizeBytes(500_000L) | ||
| .minInputFiles(2) | ||
| .filter(Expressions.in("id", 1, 2)) |
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It's always nice to add a comment at the test-relevant parameters (here: the filter).
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Ok, I have add it .
| } | ||
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| @Test | ||
| void testRewriteUnPartitionedWithFilter() throws Exception { |
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Is "Unpartitioned" relevant for this test? If not, we could rename the test to testRewriteWithFilter.
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It is not relevant. I have rename totestRewriteWithFilter
mxm
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Jul 29, 2025
pvary
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Jul 29, 2025
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Merged to main. |
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Background
When an existing table is migrated to the Flink implementation of RewriteDataFiles and its historical data has not been compacted thoroughly,or modify the targetFileSize, the Flink maintenance job must first rewrite the entire table before it can follow the user’s intended schedule. This initial compaction can run for a very long time, while new data cannot trigger compaction, resulting in degraded query performance.
Purpose
This PR introduces an optional filter parameter to Flink’s RewriteDataFiles. Users can define predicates (e.g. data whose time is greater than a given timestamp) so that only the necessary subset of data is compacted, allowing historical data to be skipped.