[jira] [Created] (FLINK-3477) Add hash-based combine strategy for ReduceFunction

["Fabian Hueske (JIRA)" <ji...@apache.org>]

Fabian Hueske created FLINK-3477:
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             Summary: Add hash-based combine strategy for ReduceFunction
                 Key: FLINK-3477
                 URL: https://issues.apache.org/jira/browse/FLINK-3477
             Project: Flink
          Issue Type: Sub-task
          Components: Local Runtime
            Reporter: Fabian Hueske


This issue is about adding a hash-based combine strategy for ReduceFunctions.
The interface of the {{reduce()}} method is as follows:

{code}
public T reduce(T v1, T v2)
{code}

Input type and output type are identical and the function returns only a single value. A Reduce function is incrementally applied to compute a final aggregated value. This allows to hold the preaggregated value in a hash-table and update it with each function call. 

The hash-based strategy requires special implementation of an in-memory hash table. The hash table should support in place updates of elements (if the updated value has the same size as the new value) but also appending updates with invalidation of the old value (if the binary length of the new value differs). The hash table needs to be able to evict and emit all elements if it runs out-of-memory.



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