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https://issues.apache.org/jira/browse/HIVE-15527?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15791783#comment-15791783
]
Hive QA commented on HIVE-15527:
--------------------------------
Here are the results of testing the latest attachment:
https://issues.apache.org/jira/secure/attachment/12845257/HIVE-15527.2.patch
{color:red}ERROR:{color} -1 due to no test(s) being added or modified.
{color:red}ERROR:{color} -1 due to 8 failed/errored test(s), 10883 tests
executed
*Failed tests:*
{noformat}
TestDerbyConnector - did not produce a TEST-*.xml file (likely timed out)
(batchId=233)
TestMiniLlapLocalCliDriver - did not produce a TEST-*.xml file (likely timed
out) (batchId=151)
[smb_mapjoin_15.q,insert_values_partitioned.q,selectDistinctStar.q,bucket4.q,vectorized_distinct_gby.q,vector_groupby_mapjoin.q,insert_values_dynamic_partitioned.q,vector_nvl.q,join_nullsafe.q,vectorized_mapjoin.q,vectorized_shufflejoin.q,tez_smb_1.q,cbo_union.q,tez_vector_dynpart_hashjoin_1.q,vector_coalesce_2.q,filter_join_breaktask2.q,table_access_keys_stats.q,vector_data_types.q,multiMapJoin2.q,filter_join_breaktask.q,schema_evol_orc_nonvec_part.q,alter_merge_2_orc.q,vectorization_3.q,union4.q,auto_sortmerge_join_8.q,stats_based_fetch_decision.q,vectorized_date_funcs.q,auto_sortmerge_join_10.q,vector_varchar_simple.q,vector_decimal_udf2.q]
org.apache.hadoop.hive.cli.TestMiniLlapCliDriver.testCliDriver[orc_ppd_basic]
(batchId=134)
org.apache.hadoop.hive.cli.TestMiniLlapCliDriver.testCliDriver[orc_ppd_schema_evol_3a]
(batchId=135)
org.apache.hadoop.hive.cli.TestMiniLlapLocalCliDriver.testCliDriver[offset_limit_ppd_optimizer]
(batchId=150)
org.apache.hadoop.hive.cli.TestMiniTezCliDriver.testCliDriver[explainanalyze_1]
(batchId=92)
org.apache.hadoop.hive.cli.TestMiniTezCliDriver.testCliDriver[explainanalyze_2]
(batchId=93)
org.apache.hadoop.hive.cli.TestSparkCliDriver.testCliDriver[vectorized_ptf]
(batchId=121)
{noformat}
Test results: https://builds.apache.org/job/PreCommit-HIVE-Build/2756/testReport
Console output: https://builds.apache.org/job/PreCommit-HIVE-Build/2756/console
Test logs: http://104.198.109.242/logs/PreCommit-HIVE-Build-2756/
Messages:
{noformat}
Executing org.apache.hive.ptest.execution.TestCheckPhase
Executing org.apache.hive.ptest.execution.PrepPhase
Executing org.apache.hive.ptest.execution.ExecutionPhase
Executing org.apache.hive.ptest.execution.ReportingPhase
Tests exited with: TestsFailedException: 8 tests failed
{noformat}
This message is automatically generated.
ATTACHMENT ID: 12845257 - PreCommit-HIVE-Build
> 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.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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