[
https://issues.apache.org/jira/browse/SPARK-17108?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Herman van Hovell updated SPARK-17108:
--------------------------------------
Description:
I have a Hive table with the following definition:
{noformat}
create table testforerror (
my_column MAP<BIGINT, ARRAY<String>>
);
{noformat}
The table has the following records
{noformat}
hive> select * from testforerror;
OK
{11001:["0034111000a4WaAAA2"]}
{11001:["0034111000orWiWAAU"]}
{11001:["","0034111000VgrHdAAJ"]}
{11001:["0034110000cS4rDAAS"]}
{12001:["0037110001a7ofsAAA"]}
Time taken: 0.067 seconds, Fetched: 5 row(s)
{noformat}
I have a query which filters records with key of the my_column. The query is as
follows
{noformat}
select * from testforerror where my_column[11001] is not null;
{noformat}
This query is executing fine from hive/beeline shell and producing the
following records:
{noformat}
hive> select * from testforerror where my_column[11001] is not null;
OK
{11001:["0034111000a4WaAAA2"]}
{11001:["0034111000orWiWAAU"]}
{11001:["","0034111000VgrHdAAJ"]}
{11001:["0034110000cS4rDAAS"]}
Time taken: 2.224 seconds, Fetched: 4 row(s)
{noformat}
But however I get an error when trying to execute from spark sqlContext. The
following is the error message:
{noformat}
scala> val errorquery = "select * from testforerror where my_column[11001] is
not null"
errorquery: String = select * from testforerror where my_column[11001] is not
null
scala> sqlContext.sql(errorquery).show()
org.apache.spark.sql.AnalysisException: cannot resolve 'my_column[11001]' due
to data type mismatch: argument 2 requires bigint type, however, '11001' is of
int type.; line 1 pos 43
at
org.apache.spark.sql.catalyst.analysis.package$AnalysisErrorAt.failAnalysis(package.scala:42)
at
org.apache.spark.sql.catalyst.analysis.CheckAnalysis$$anonfun$checkAnalysis$1$$anonfun$apply$2.applyOrElse(CheckAnalysis.scala:65)
at
org.apache.spark.sql.catalyst.analysis.CheckAnalysis$$anonfun$checkAnalysis$1$$anonfun$apply$2.applyOrElse(CheckAnalysis.scala:57)
at
org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformUp$1.apply(TreeNode.scala:335)
at
org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformUp$1.apply(TreeNode.scala:335)
at
org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:69)
at
org.apache.spark.sql.catalyst.trees.TreeNode.transformUp(TreeNode.scala:334)
at
org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$5.apply(TreeNode.scala:332)
at
org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$5.apply(TreeNode.scala:332)
at
org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$4.apply(TreeNode.scala:281)
at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
at scala.collection.Iterator$class.foreach(Iterator.scala:727)
at scala.collection.AbstractIterator.foreach(Iterator.scala:1157)
at scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:48)
at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:103)
at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:47)
{noformat}
was:
I have a Hive table with the following definition:
create table testforerror (
my_column MAP<BIGINT, ARRAY<String>>
);
The table has the following records
hive> select * from testforerror;
OK
{11001:["0034111000a4WaAAA2"]}
{11001:["0034111000orWiWAAU"]}
{11001:["","0034111000VgrHdAAJ"]}
{11001:["0034110000cS4rDAAS"]}
{12001:["0037110001a7ofsAAA"]}
Time taken: 0.067 seconds, Fetched: 5 row(s)
I have a query which filters records with key of the my_column. The query is as
follows
select * from testforerror where my_column[11001] is not null;
This query is executing fine from hive/beeline shell and producing the
following records:
hive> select * from testforerror where my_column[11001] is not null;
OK
{11001:["0034111000a4WaAAA2"]}
{11001:["0034111000orWiWAAU"]}
{11001:["","0034111000VgrHdAAJ"]}
{11001:["0034110000cS4rDAAS"]}
Time taken: 2.224 seconds, Fetched: 4 row(s)
But however I get an error when trying to execute from spark sqlContext. The
following is the error message:
scala> val errorquery = "select * from testforerror where my_column[11001] is
not null"
errorquery: String = select * from testforerror where my_column[11001] is not
null
scala> sqlContext.sql(errorquery).show()
org.apache.spark.sql.AnalysisException: cannot resolve 'my_column[11001]' due
to data type mismatch: argument 2 requires bigint type, however, '11001' is of
int type.; line 1 pos 43
at
org.apache.spark.sql.catalyst.analysis.package$AnalysisErrorAt.failAnalysis(package.scala:42)
at
org.apache.spark.sql.catalyst.analysis.CheckAnalysis$$anonfun$checkAnalysis$1$$anonfun$apply$2.applyOrElse(CheckAnalysis.scala:65)
at
org.apache.spark.sql.catalyst.analysis.CheckAnalysis$$anonfun$checkAnalysis$1$$anonfun$apply$2.applyOrElse(CheckAnalysis.scala:57)
at
org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformUp$1.apply(TreeNode.scala:335)
at
org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformUp$1.apply(TreeNode.scala:335)
at
org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:69)
at
org.apache.spark.sql.catalyst.trees.TreeNode.transformUp(TreeNode.scala:334)
at
org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$5.apply(TreeNode.scala:332)
at
org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$5.apply(TreeNode.scala:332)
at
org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$4.apply(TreeNode.scala:281)
at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
at scala.collection.Iterator$class.foreach(Iterator.scala:727)
at scala.collection.AbstractIterator.foreach(Iterator.scala:1157)
at scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:48)
at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:103)
at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:47)
> BIGINT and INT comparison failure in spark sql
> ----------------------------------------------
>
> Key: SPARK-17108
> URL: https://issues.apache.org/jira/browse/SPARK-17108
> Project: Spark
> Issue Type: Bug
> Reporter: Sai Krishna Kishore Beathanabhotla
>
> I have a Hive table with the following definition:
> {noformat}
> create table testforerror (
> my_column MAP<BIGINT, ARRAY<String>>
> );
> {noformat}
> The table has the following records
> {noformat}
> hive> select * from testforerror;
> OK
> {11001:["0034111000a4WaAAA2"]}
> {11001:["0034111000orWiWAAU"]}
> {11001:["","0034111000VgrHdAAJ"]}
> {11001:["0034110000cS4rDAAS"]}
> {12001:["0037110001a7ofsAAA"]}
> Time taken: 0.067 seconds, Fetched: 5 row(s)
> {noformat}
> I have a query which filters records with key of the my_column. The query is
> as follows
> {noformat}
> select * from testforerror where my_column[11001] is not null;
> {noformat}
> This query is executing fine from hive/beeline shell and producing the
> following records:
> {noformat}
> hive> select * from testforerror where my_column[11001] is not null;
> OK
> {11001:["0034111000a4WaAAA2"]}
> {11001:["0034111000orWiWAAU"]}
> {11001:["","0034111000VgrHdAAJ"]}
> {11001:["0034110000cS4rDAAS"]}
> Time taken: 2.224 seconds, Fetched: 4 row(s)
> {noformat}
> But however I get an error when trying to execute from spark sqlContext. The
> following is the error message:
> {noformat}
> scala> val errorquery = "select * from testforerror where my_column[11001] is
> not null"
> errorquery: String = select * from testforerror where my_column[11001] is not
> null
> scala> sqlContext.sql(errorquery).show()
> org.apache.spark.sql.AnalysisException: cannot resolve 'my_column[11001]' due
> to data type mismatch: argument 2 requires bigint type, however, '11001' is
> of int type.; line 1 pos 43
> at
> org.apache.spark.sql.catalyst.analysis.package$AnalysisErrorAt.failAnalysis(package.scala:42)
> at
> org.apache.spark.sql.catalyst.analysis.CheckAnalysis$$anonfun$checkAnalysis$1$$anonfun$apply$2.applyOrElse(CheckAnalysis.scala:65)
> at
> org.apache.spark.sql.catalyst.analysis.CheckAnalysis$$anonfun$checkAnalysis$1$$anonfun$apply$2.applyOrElse(CheckAnalysis.scala:57)
> at
> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformUp$1.apply(TreeNode.scala:335)
> at
> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformUp$1.apply(TreeNode.scala:335)
> at
> org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:69)
> at
> org.apache.spark.sql.catalyst.trees.TreeNode.transformUp(TreeNode.scala:334)
> at
> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$5.apply(TreeNode.scala:332)
> at
> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$5.apply(TreeNode.scala:332)
> at
> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$4.apply(TreeNode.scala:281)
> at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
> at scala.collection.Iterator$class.foreach(Iterator.scala:727)
> at scala.collection.AbstractIterator.foreach(Iterator.scala:1157)
> at
> scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:48)
> at
> scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:103)
> at
> scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:47)
> {noformat}
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