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https://issues.apache.org/jira/browse/HIVE-15527?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15793967#comment-15793967
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liyunzhang_intel edited comment on HIVE-15527 at 1/3/17 2:53 AM:
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[~xuefuz] and [~lirui]: HiveKVResultCache will write key value pair to disk if
buffer is full and this will do some limits to the memory usage. But is there
anything to show that the ArrayList use a lot of memory? test this by memory
analysis tool?
was (Author: kellyzly):
[~xuefuz] and [~lirui]: HiveKVResultCache will write key value pair if buffer
is full and this will do some limits to the memory usage. But is there anything
to show that the ArrayList use a lot of memory? test this by memory analysis
tool?
> 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: Xuefu Zhang
> Attachments: HIVE-15527.1.patch, HIVE-15527.2.patch,
> HIVE-15527.3.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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