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https://issues.apache.org/jira/browse/FLINK-2716?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15060402#comment-15060402
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ASF GitHub Bot commented on FLINK-2716:
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GitHub user greghogan opened a pull request:
https://github.com/apache/flink/pull/1462
[FLINK-2716] [gelly java scala] New checksum method on DataSet and Graph
This implementation aggregates using `Object.hashCode`. As noted in
FLINK-2716, `TypeComparator` has a hash function, which simply calls `hashCode`
for basic types. For composite types (pojo, tuples, and case classes) the hash
is computed over the keyed subset of fields, as noted by @StephanEwen. The
differences between `hashCode` and `hash` are immaterial for this use case.
Should this be added to the Python API? I am not finding count() on
Python's `DataSet`.
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/greghogan/flink
2716_checksum_method_for_dataset_and_graph
Alternatively you can review and apply these changes as the patch at:
https://github.com/apache/flink/pull/1462.patch
To close this pull request, make a commit to your master/trunk branch
with (at least) the following in the commit message:
This closes #1462
----
commit 8ac28776a81bd70918b872d159f0a21c889d081d
Author: Greg Hogan <[email protected]>
Date: 2015-12-15T19:25:54Z
[FLINK-2716] [gelly java scala] New checksum method on DataSet and Graph
----
> Checksum method for DataSet and Graph
> -------------------------------------
>
> Key: FLINK-2716
> URL: https://issues.apache.org/jira/browse/FLINK-2716
> Project: Flink
> Issue Type: Improvement
> Components: Gelly, Java API, Scala API
> Affects Versions: 0.10.0
> Reporter: Greg Hogan
> Assignee: Greg Hogan
> Priority: Minor
>
> {{DataSet.count()}}, {{Graph.numberOfVertices()}}, and
> {{Graph.numberOfEdges()}} provide measures of the number of distributed data
> elements. New {{DataSet.checksum()}} and {{Graph.checksum()}} methods will
> summarize the content of data elements and support algorithm validation,
> integration testing, and benchmarking.
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