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https://issues.apache.org/jira/browse/HIVE-15527?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15818027#comment-15818027
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Rui Li commented on HIVE-15527:
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Hi [~csun], it seems the current solution relies on how the iterators are used
- the inner iterator must be consumed before moving forward the outer iterator.
Is there any guarantee this assumption will hold? Even if it works at the
moment, I'm afraid changes in Hive or Spark can easily break it.
> Memory usage is unbound in SortByShuffler for Spark
> ---------------------------------------------------
>
> Key: HIVE-15527
> URL: https://issues.apache.org/jira/browse/HIVE-15527
> Project: Hive
> Issue Type: Improvement
> Components: Spark
> Affects Versions: 1.1.0
> Reporter: Xuefu Zhang
> Assignee: Chao Sun
> Attachments: HIVE-15527.0.patch, HIVE-15527.0.patch,
> HIVE-15527.1.patch, HIVE-15527.2.patch, HIVE-15527.3.patch,
> HIVE-15527.4.patch, HIVE-15527.5.patch, HIVE-15527.6.patch,
> HIVE-15527.7.patch, HIVE-15527.patch
>
>
> In SortByShuffler.java, an ArrayList is used to back the iterator for values
> that have the same key in shuffled result produced by spark transformation
> sortByKey. It's possible that memory can be exhausted because of a large key
> group.
> {code}
> @Override
> public Tuple2<HiveKey, Iterable<BytesWritable>> next() {
> // TODO: implement this by accumulating rows with the same key
> into a list.
> // Note that this list needs to improved to prevent excessive
> memory usage, but this
> // can be done in later phase.
> while (it.hasNext()) {
> Tuple2<HiveKey, BytesWritable> pair = it.next();
> if (curKey != null && !curKey.equals(pair._1())) {
> HiveKey key = curKey;
> List<BytesWritable> values = curValues;
> curKey = pair._1();
> curValues = new ArrayList<BytesWritable>();
> curValues.add(pair._2());
> return new Tuple2<HiveKey, Iterable<BytesWritable>>(key,
> values);
> }
> curKey = pair._1();
> curValues.add(pair._2());
> }
> if (curKey == null) {
> throw new NoSuchElementException();
> }
> // if we get here, this should be the last element we have
> HiveKey key = curKey;
> curKey = null;
> return new Tuple2<HiveKey, Iterable<BytesWritable>>(key,
> curValues);
> }
> {code}
> Since the output from sortByKey is already sorted on key, it's possible to
> backup the value iterable using the same input iterator.
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