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From "Chaozhong Yang (JIRA)" <j...@apache.org>
Subject [jira] [Comment Edited] (HIVE-15872) The PERCENTILE UDAF does not work with empty set
Date Fri, 10 Feb 2017 08:25:42 GMT

    [ https://issues.apache.org/jira/browse/HIVE-15872?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15860908#comment-15860908
] 

Chaozhong Yang edited comment on HIVE-15872 at 2/10/17 8:25 AM:
----------------------------------------------------------------

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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