[FLINK-5890] [gelly] GatherSumApply broken when object reuse enabled #3515
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The initial fix for this ticket is not working on larger data sets. Reduce supports returning the left input, right input, a new object, or a locally reused object. The trouble with the initial fix was that the returned local object was reusing fields from the input tuples. The problem is with ReduceDriver#run managing two values (reuse1 and reuse2) and with a third, local value returned by GatherSumApplyIteration.SumUDF. After the first grouping value.f1 == reuse1.f1. Following UDF calls may swap value.f1 and reuse2.f1, which causes reuse1.f1 == reuse2.f1. With an odd number of swaps the next grouping will reduce with reuse1 and reuse2 sharing a field and deserialization will overwrite stored values. The simple fix is to only use and return the provided inputs.
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@StephanEwen deja vu FLINK-2883 / FLINK-3340. I'm also looking to run the FLINK-4949 IT tests with object reuse both enabled and disabled which would have highlighted this issue as the unit test input was too small. |
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I think having the IT test makes sense here. You can try to artificially reduce the memory to trigger spilling situations earlier. |
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Not an issue of spilling memory but at least three elements are required to trigger two reduces and the error condition depends on which value is returned. @StephanEwen is this a +1? |
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It is a +1 :-) |
kateri1
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Mar 26, 2017
The initial fix for this ticket is not working on larger data sets. Reduce supports returning the left input, right input, a new object, or a locally reused object. The trouble with the initial fix was that the returned local object was reusing fields from the input tuples. The problem is with ReduceDriver#run managing two values (reuse1 and reuse2) and with a third, local value returned by GatherSumApplyIteration.SumUDF. After the first grouping value.f1 == reuse1.f1. Following UDF calls may swap value.f1 and reuse2.f1, which causes reuse1.f1 == reuse2.f1. With an odd number of swaps the next grouping will reduce with reuse1 and reuse2 sharing a field and deserialization will overwrite stored values. The simple fix is to only use and return the provided inputs. This closes apache#3515
p16i
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Apr 16, 2017
The initial fix for this ticket is not working on larger data sets. Reduce supports returning the left input, right input, a new object, or a locally reused object. The trouble with the initial fix was that the returned local object was reusing fields from the input tuples. The problem is with ReduceDriver#run managing two values (reuse1 and reuse2) and with a third, local value returned by GatherSumApplyIteration.SumUDF. After the first grouping value.f1 == reuse1.f1. Following UDF calls may swap value.f1 and reuse2.f1, which causes reuse1.f1 == reuse2.f1. With an odd number of swaps the next grouping will reduce with reuse1 and reuse2 sharing a field and deserialization will overwrite stored values. The simple fix is to only use and return the provided inputs. This closes apache#3515
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The initial fix for this ticket is not working on larger data sets.
Reduce supports returning the left input, right input, a new object, or a locally reused object. The trouble with the initial fix was that the returned local object was reusing fields from the input tuples.
The problem is with ReduceDriver#run managing two values (reuse1 and reuse2) and with a third, local value returned by GatherSumApplyIteration.SumUDF. After the first grouping value.f1 == reuse1.f1. Following UDF calls may swap value.f1 and reuse2.f1, which causes reuse1.f1 == reuse2.f1. With an odd number of swaps the next grouping will reduce with reuse1 and reuse2 sharing a field and deserialization will overwrite stored values.
The simple fix is to only use and return the provided inputs.