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https://issues.apache.org/jira/browse/SPARK-14066?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15206280#comment-15206280
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KaiXinXIaoLei edited comment on SPARK-14066 at 3/23/16 1:19 AM:
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In the
org.apache.spark.sql.catalyst.analysis.HiveTypeCoercion.FunctionArgumentConversion,
I find in the value `findTightestCommonTypeOfTwo`:
{code}
case (t1: IntegralType, t2: DecimalType) if t2.isWiderThan(t1) =>
Some(t2)
case (t1: DecimalType, t2: IntegralType) if t1.isWiderThan(t2) =>
Some(t1)
{code}
In `array(0,0.2,0.3,1)`, The type of `0` changes `DecimalType(10, 0)`, The type
of `0.2` is `DecimalType(1, 1)`, so the value of `t2.isWiderThan(t1) ` is
false. So the type of numbers will be [int, decimal(1,1), decimal(1,1), int].
And the query run failed.
So I think the `TightestCommonTypeOfTwo` is not reasonable. Thanks.
was (Author: kaixinxiaolei):
In the
org.apache.spark.sql.catalyst.analysis.HiveTypeCoercion.FunctionArgumentConversion,
I find in the value `findTightestCommonTypeOfTwo`:
```
case (t1: IntegralType, t2: DecimalType) if t2.isWiderThan(t1) =>
Some(t2)
case (t1: DecimalType, t2: IntegralType) if t1.isWiderThan(t2) =>
Some(t1)
```
In `array(0,0.2,0.3,1)`, The type of `0` changes `DecimalType(10, 0)`, The type
of `0.2` is `DecimalType(1, 1)`, so the value of `t2.isWiderThan(t1) ` is
false. So the type of numbers will be [int, decimal(1,1), decimal(1,1), int].
And the query run failed.
So I think the `TightestCommonTypeOfTwo` is not reasonable. Thanks.
> Set "spark.sql.dialect=sql", there is a problen in running query "select
> percentile(d,array(0,0.2,0.3,1)) as a from t;"
> -------------------------------------------------------------------------------------------------------------------------
>
> Key: SPARK-14066
> URL: https://issues.apache.org/jira/browse/SPARK-14066
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 1.5.1
> Reporter: KaiXinXIaoLei
>
> In spark 1.5.1, I run "sh bin/spark-sql --conf spark.sql.dialect=sql", and
> run query "select percentile(d,array(0,0.2,0.3,1)) as a from t". There is a
> problem as follows.
> {code}
> spark-sql> select percentile(d,array(0,0.2,0.3,1)) as a from t;
> 16/03/22 17:25:15 INFO HiveMetaStore: 0: get_table : db=default tbl=t
> 16/03/22 17:25:15 INFO audit: ugi=root ip=unknown-ip-addr cmd=get_table
> : db=default tbl=t
> 16/03/22 17:25:16 ERROR SparkSQLDriver: Failed in [select
> percentile(d,array(0,0.2,0.3,1)) as a from t]
> org.apache.spark.sql.AnalysisException: cannot resolve 'array(0,0.2,0.3,1)'
> due to data type mismatch: input to function array should all be the same
> type, but it's [int, decimal(1,1), decimal(1,1), int];
> {code}
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