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https://issues.apache.org/jira/browse/HIVE-15872?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15860908#comment-15860908
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Chaozhong Yang edited comment on HIVE-15872 at 2/10/17 8:25 AM:
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According to SQL-standard, percentile_approx should return null for zero
elements rather than throws IndexOutOfBoundsException in reduce.
@Override
public Object terminate(AggregationBuffer agg) throws HiveException {
PercentileAggBuf myagg = (PercentileAggBuf) agg;
if (myagg.histogram.getUsedBins() < 1) { // SQL standard - return null
for zero elements
return null;
} else {
assert(myagg.quantiles != null);
return new DoubleWritable(myagg.histogram.quantile(myagg.quantiles[0]));
}
}
was (Author: debugger87):
According to SQL-standard, percentile_approx should return null for zero
elements rather than throws IndexOutOfBoundsException in reduce.
@Override
public Object terminate(AggregationBuffer agg) throws HiveException {
PercentileAggBuf myagg = (PercentileAggBuf) agg;
if (myagg.histogram.getUsedBins() < 1) { // SQL standard - return null
for zero elements
return null;
} else {
assert(myagg.quantiles != null);
return new DoubleWritable(myagg.histogram.quantile(myagg.quantiles[0]));
}
}
> The PERCENTILE UDAF does not work with empty set
> ------------------------------------------------
>
> Key: HIVE-15872
> URL: https://issues.apache.org/jira/browse/HIVE-15872
> Project: Hive
> Issue Type: Bug
> Components: UDF
> Reporter: Chaozhong Yang
> Assignee: Chaozhong Yang
> Fix For: 2.1.2
>
> Attachments: HIVE-15872.patch
>
>
> 1. Original SQL:
> select
> percentile_approx(
> column0,
> array(0.50, 0.70, 0.90, 0.95, 0.99)
> )
> from
> my_table
> where
> date = '20170207'
> and column1 = 'value1'
> and column2 = 'value2'
> and column3 = 'value3'
> and column4 = 'value4'
> and column5 = 'value5'
> 2. Exception StackTrace:
> Error: java.lang.RuntimeException:
> org.apache.hadoop.hive.ql.metadata.HiveException: Hive Runtime Error while
> processing row (tag=0) {"key":{},"value":{"_col0":[0.0,10000.0]}} at
> org.apache.hadoop.hive.ql.exec.mr.ExecReducer.reduce(ExecReducer.java:256) at
> org.apache.hadoop.mapred.ReduceTask.runOldReducer(ReduceTask.java:453) at
> org.apache.hadoop.mapred.ReduceTask.run(ReduceTask.java:401) at
> org.apache.hadoop.mapred.YarnChild$2.run(YarnChild.java:163) at
> java.security.AccessController.doPrivileged(Native Method) at
> javax.security.auth.Subject.doAs(Subject.java:422) at
> org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1671)
> at org.apache.hadoop.mapred.YarnChild.main(YarnChild.java:158) Caused by:
> org.apache.hadoop.hive.ql.metadata.HiveException: Hive Runtime Error while
> processing row (tag=0) {"key":{},"value":{"_col0":[0.0,10000.0]}} at
> org.apache.hadoop.hive.ql.exec.mr.ExecReducer.reduce(ExecReducer.java:244)
> ... 7 more Caused by: org.apache.hadoop.hive.ql.metadata.HiveException:
> java.lang.IndexOutOfBoundsException: Index: 2, Size: 2 at
> org.apache.hadoop.hive.ql.exec.GroupByOperator.process(GroupByOperator.java:766)
> at
> org.apache.hadoop.hive.ql.exec.mr.ExecReducer.reduce(ExecReducer.java:235)
> ... 7 more Caused by: java.lang.IndexOutOfBoundsException: Index: 2, Size: 2
> at java.util.ArrayList.rangeCheck(ArrayList.java:653) at
> java.util.ArrayList.get(ArrayList.java:429) at
> org.apache.hadoop.hive.ql.udf.generic.NumericHistogram.merge(NumericHistogram.java:134)
> at
> org.apache.hadoop.hive.ql.udf.generic.GenericUDAFPercentileApprox$GenericUDAFPercentileApproxEvaluator.merge(GenericUDAFPercentileApprox.java:318)
> at
> org.apache.hadoop.hive.ql.udf.generic.GenericUDAFEvaluator.aggregate(GenericUDAFEvaluator.java:188)
> at
> org.apache.hadoop.hive.ql.exec.GroupByOperator.updateAggregations(GroupByOperator.java:612)
> at
> org.apache.hadoop.hive.ql.exec.GroupByOperator.processAggr(GroupByOperator.java:851)
> at
> org.apache.hadoop.hive.ql.exec.GroupByOperator.processKey(GroupByOperator.java:695)
> at
> org.apache.hadoop.hive.ql.exec.GroupByOperator.process(GroupByOperator.java:761)
> ... 8 more
> 3. review data:
> select
> column0
> from
> my_table
> where
> date = '20170207'
> and column1 = 'value1'
> and column2 = 'value2'
> and column3 = 'value3'
> and column4 = 'value4'
> and column5 = 'value5'
> After run this sql, we found the result is NULL.
> 4. what's the meaning of [0.0, 10000.0] in stacktrace?
> In GenericUDAFPercentileApproxEvaluator, the method `merge` should process an
> ArrayList which name is partialHistogram. Normally, the basic structure of
> partialHistogram is [npercentiles, percentile0, percentile1..., nbins,
> bin0.x, bin0.y, bin1.x, bin1.y,...]. However, if we are process NULL(empty
> set) column values, the partialHistoram will only contains [npercentiles(0),
> nbins(10000)]. That's the reason why the stacktrace shows a strange row data:
> {"key":{},"value":{"_col0":[0.0,10000.0]}}
> Before we call histogram#merge (on-line hisgoram algorithm from paper:
> http://www.jmlr.org/papers/volume11/ben-haim10a/ben-haim10a.pdf ), the
> partialHistogram should remove elements which store percentiles like
> `partialHistogram.subList(0, nquantiles+1).clear();`. In the case of empty
> set, GenericUDAFPercentileApproxEvaluator will not remove percentiles.
> Consequently, NumericHistogram will merge a list which contains only 2
> elements([0, 10000.0]) and throws IndexOutOfBoundsException.
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