Release 1.19 lyft#83
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maheepm-lyft wants to merge 2361 commits intorelease-1.17-lyftfrom
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(cherry picked from commit 95163e8)
…ob is suspended during Restarting phase
suspend and cancel reset the ExecutionGraph in a similar way. I move the common logic into its own method to make this more prominent in the code.
…out for AdaptiveSchedulerTest (apache#24400)
…Builder.cleanupInRocksdbCompactFilter
…3.11 wheel package This closes apache#24439.
…hod construct resource has exception. This closes apache#24462.
…ogs when the task exited. (apache#23922)
…used by multiple writes to the same sink table and shared staging directory This closes apache#24492 * Fix unstable TableSourceITCase#testTableHintWithLogicalTableScanReuse * Moves the staging dir configuration into builder for easier testing --------- Co-authored-by: Matthias Pohl <matthias.pohl@aiven.io> (cherry picked from commit 7d0111d)
…lerTest.testOnReadBufferRequestError
… as stable in docs This closes apache#24518
…ls.sh` script attempt to retrieve the Java Home. This closes apache#24527.
… literal without seconds (apache#26555)
…in adaptive scheduler Also enable this strategy by default via the introduced config option
…on via `CompiledPlan`
Co-authored-by: Matthias Pohl <github@mapohl.com>
…sabled for all connections unexpectedly
…Y type by evaluating Unsafe.arrayBaseOffset(byte[].class) in TM rather than in JM (apache#26592) Fix HashPartitioner codegen for BINARY/VARBINARY type by evaluating BYTE_ARRAY_BASE_OFFSET in TM instead of JM. The issue is, if JM memory is set > 32G while TM memory is set < 32G, this causes JVM to treat the JAVA process > 32G as large heap JVM. This can impact Unsafe behavior. For eg: UNSAFE.arrayBaseOffset(byte[].class) will return 24 for large heap JVM while 16 for others. Due to this, the tasks that run on TM (<32 G while JM > 32G or vice versa) that try to read the byte[] for MurmurHash read wrong memory locations. Signed-off-by: Jiangjie (Becket) Qin <becket.qin@gmail.com>
…es in batch mode (apache#27016) In apache#26433, we removed the EOI marker in the form of Long.MAX_VALUE as the checkpoint id. Since streaming pipelines can continue to checkpoint even after their respective operators have been shut down, it is not safe to use a constant as this can lead to duplicate commits. However, in batch pipelines we only have one commit on job shutdown. Using any checkpoint id should suffice in this scenario. Any pending committables should be processed by the ComitterOperator when the operator shuts down. No further checkpoints will take place. There are various connectors which rely on this behavior. I don't see any drawbacks from keeping this behavior for batch pipelines.
If a resource is lazily created in open, we can only close after checking for null. Otherwise a failure during initialization will trigger secondary failures.
…eckpoint notification is delayed (apache#27157)
Relax Beam dependency
The build-system requires in pyproject.toml still had the upstream range <2.49.0 while setup.py was already relaxed to <2.62.0. This causes macOS sdist builds to fail because no Beam version in the 2.43–2.49 range is available on Artifactory. Matches the relaxation already applied in setup.py (commit 7c2ca50).
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