[jira] [Created] (SPARK-13021) Fail fast when custom RDD's violate RDD.partition's API contract

["Josh Rosen (JIRA)" <ji...@apache.org>]

Josh Rosen created SPARK-13021:
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             Summary: Fail fast when custom RDD's violate RDD.partition's API contract
                 Key: SPARK-13021
                 URL: https://issues.apache.org/jira/browse/SPARK-13021
             Project: Spark
          Issue Type: Bug
          Components: Spark Core
            Reporter: Josh Rosen
            Assignee: Josh Rosen


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: https://rawgit.com/JoshRosen/e520fb9a64c1c97ec985/raw/5e8a5aa8d2a18910a1607f0aa4190104adda3424/Violating%2520RDD.partitions%2520contract.html

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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