[ 
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 8:30 AM:
----------------------------------------------------------------

According to SQL-standard, percentile_approx should return null for zero 
elements rather than throws IndexOutOfBoundsException in reducer.


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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