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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