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From "Yin Huai (JIRA)" <>
Subject [jira] [Resolved] (SPARK-13021) Fail fast when custom RDD's violate RDD.partition's API contract
Date Wed, 27 Jan 2016 21:28:39 GMT


Yin Huai resolved SPARK-13021.
       Resolution: Fixed
    Fix Version/s: 2.0.0

Issue resolved by pull request 10932

> Fail fast when custom RDD's violate RDD.partition's API contract
> ----------------------------------------------------------------
>                 Key: SPARK-13021
>                 URL:
>             Project: Spark
>          Issue Type: Bug
>          Components: Spark Core
>            Reporter: Josh Rosen
>            Assignee: Josh Rosen
>             Fix For: 2.0.0
> Spark's {{Partition}} and {{RDD.partitions}} APIs have a contract which requires custom
implementations of {{RDD.partitions}} to ensure that for all {{x}}, {{rdd.partitions\(x).index
== x}}; in other words, the {{index}} reported by a repartition needs to match its position
in the partitions array.
> If a custom RDD implementation violates this contract, then Spark has the potential to
become stuck in an infinite recomputation loop when recomputing a subset of an RDD's partitions,
since the tasks that are actually run will not correspond to the missing output partitions
that triggered the recomputation. Here's a link to a notebook which demonstrates this problem:
> In order to guard against this infinite loop behavior, I think that Spark should fail-fast
and refuse to compute RDDs' whose {{partitions}} violate the API contract.

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