[
https://issues.apache.org/jira/browse/SPARK-6201?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Jianshi Huang updated SPARK-6201:
---------------------------------
Description:
Suppose we have the following table:
{code}
sqlc.jsonRDD(sc.parallelize(Seq("{\"a\": \"1\"}}", "{\"a\": \"2\"}}", "{\"a\":
\"3\"}}"))).registerTempTable("d")
{code}
The schema is
{noformat}
root
|-- a: string (nullable = true)
{noformat}
Then,
{code}
sql("select * from d where (d.a = 1 or d.a = 2)").collect
=>
Array([1], [2])
{code}
where d.a and constants 1,2 will be casted to Double first and do the
comparison as you can find it out in the plan:
{noformat}
Filter ((CAST(a#155, DoubleType) = CAST(1, DoubleType)) || (CAST(a#155,
DoubleType) = CAST(2, DoubleType)))
{noformat}
However, if I use
{code}
sql("select * from d where d.a in (1,2)").collect
{code}
The result is empty.
The physical plan shows it's using INSET:
{noformat}
== Physical Plan ==
Filter a#155 INSET (1,2)
PhysicalRDD [a#155], MappedRDD[499] at map at JsonRDD.scala:47
{noformat}
But it seems INSET implementation in SparkSQL doesn't coerce type implicitly,
where Hive does.
Jianshi
was:
Suppose we the following table:
{code}
sqlc.jsonRDD(sc.parallelize(Seq("{\"a\": \"1\"}}", "{\"a\": \"2\"}}", "{\"a\":
\"3\"}}"))).registerTempTable("d")
{code}
The schema is
{noformat}
root
|-- a: string (nullable = true)
{noformat}
Then,
{code}
sql("select * from d where (d.a = 1 or d.a = 2)").collect
=>
Array([1], [2])
{code}
where d.a and constants 1,2 will be casted to Double first and do the
comparison as you can find it out in the plan:
{noformat}
Filter ((CAST(a#155, DoubleType) = CAST(1, DoubleType)) || (CAST(a#155,
DoubleType) = CAST(2, DoubleType)))
{noformat}
However, if I use
{code}
sql("select * from d where d.a in (1,2)").collect
{code}
The result is empty.
The physical plan shows it's using INSET:
{noformat}
== Physical Plan ==
Filter a#155 INSET (1,2)
PhysicalRDD [a#155], MappedRDD[499] at map at JsonRDD.scala:47
{noformat}
But it seems INSET implementation in SparkSQL doesn't coerce type implicitly,
where Hive does.
Jianshi
> INSET should coerce types
> -------------------------
>
> Key: SPARK-6201
> URL: https://issues.apache.org/jira/browse/SPARK-6201
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 1.2.0, 1.3.0, 1.2.1
> Reporter: Jianshi Huang
>
> Suppose we have the following table:
> {code}
> sqlc.jsonRDD(sc.parallelize(Seq("{\"a\": \"1\"}}", "{\"a\": \"2\"}}",
> "{\"a\": \"3\"}}"))).registerTempTable("d")
> {code}
> The schema is
> {noformat}
> root
> |-- a: string (nullable = true)
> {noformat}
> Then,
> {code}
> sql("select * from d where (d.a = 1 or d.a = 2)").collect
> =>
> Array([1], [2])
> {code}
> where d.a and constants 1,2 will be casted to Double first and do the
> comparison as you can find it out in the plan:
> {noformat}
> Filter ((CAST(a#155, DoubleType) = CAST(1, DoubleType)) || (CAST(a#155,
> DoubleType) = CAST(2, DoubleType)))
> {noformat}
> However, if I use
> {code}
> sql("select * from d where d.a in (1,2)").collect
> {code}
> The result is empty.
> The physical plan shows it's using INSET:
> {noformat}
> == Physical Plan ==
> Filter a#155 INSET (1,2)
> PhysicalRDD [a#155], MappedRDD[499] at map at JsonRDD.scala:47
> {noformat}
> But it seems INSET implementation in SparkSQL doesn't coerce type implicitly,
> where Hive does.
> Jianshi
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