[jira] [Commented] (SPARK-9435) Java UDFs don't work with GROUP BY expressions
[
https://issues.apache.org/jira/browse/SPARK-9435?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15819117#comment-15819117
]
Apache Spark commented on SPARK-9435:
-
User 'HyukjinKwon' has created a pull request for this issue:
https://github.com/apache/spark/pull/16553
> Java UDFs don't work with GROUP BY expressions
> --
>
> Key: SPARK-9435
> URL: https://issues.apache.org/jira/browse/SPARK-9435
> Project: Spark
> Issue Type: Bug
> Components: SQL
>Affects Versions: 1.4.1
> Environment: All
>Reporter: James Aley
> Attachments: IncMain.java, points.txt
>
>
> If you define a UDF in Java, for example by implementing the UDF1 interface,
> then try to use that UDF on a column in both the SELECT and GROUP BY clauses
> of a query, you'll get an error like this:
> {code}
> "SELECT inc(y),COUNT(DISTINCT x) FROM test_table GROUP BY inc(y)"
> org.apache.spark.sql.AnalysisException: expression 'y' is neither present in
> the group by, nor is it an aggregate function. Add to group by or wrap in
> first() if you don't care which value you get.
> {code}
> We put together a minimal reproduction in the attached Java file, which makes
> use of the data in the text file attached.
> I'm guessing there's some kind of issue with the equality implementation, so
> Spark can't tell that those two expressions are the same maybe? If you do the
> same thing from Scala, it works fine.
> Note for context: we ran into this issue while working around SPARK-9338.
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[jira] [Commented] (SPARK-9435) Java UDFs don't work with GROUP BY expressions
[
https://issues.apache.org/jira/browse/SPARK-9435?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15813832#comment-15813832
]
Hyukjin Kwon commented on SPARK-9435:
-
This sill happens in the current master -
{code}
val df = Seq((1, 10), (2, 11), (3, 12)).toDF("x", "y")
val udf = new UDF1[Int, Int] {
override def call(i: Int): Int = i + 1
}
spark.udf.register("inc", udf, IntegerType)
df.createOrReplaceTempView("tmp")
spark.sql("SELECT inc(y) FROM tmp GROUP BY inc(y)").show()
{code}
I tested both Scala and Java ones. and I believe the above one is simpler Scala
one to reproduce the same issue.
> Java UDFs don't work with GROUP BY expressions
> --
>
> Key: SPARK-9435
> URL: https://issues.apache.org/jira/browse/SPARK-9435
> Project: Spark
> Issue Type: Bug
> Components: SQL
>Affects Versions: 1.4.1
> Environment: All
>Reporter: James Aley
> Attachments: IncMain.java, points.txt
>
>
> If you define a UDF in Java, for example by implementing the UDF1 interface,
> then try to use that UDF on a column in both the SELECT and GROUP BY clauses
> of a query, you'll get an error like this:
> {code}
> "SELECT inc(y),COUNT(DISTINCT x) FROM test_table GROUP BY inc(y)"
> org.apache.spark.sql.AnalysisException: expression 'y' is neither present in
> the group by, nor is it an aggregate function. Add to group by or wrap in
> first() if you don't care which value you get.
> {code}
> We put together a minimal reproduction in the attached Java file, which makes
> use of the data in the text file attached.
> I'm guessing there's some kind of issue with the equality implementation, so
> Spark can't tell that those two expressions are the same maybe? If you do the
> same thing from Scala, it works fine.
> Note for context: we ran into this issue while working around SPARK-9338.
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[jira] [Commented] (SPARK-9435) Java UDFs don't work with GROUP BY expressions
[
https://issues.apache.org/jira/browse/SPARK-9435?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15001866#comment-15001866
]
DOAN DuyHai commented on SPARK-9435:
Same error for me:
{code:java}
// Register computeDecade() as a SparkSQL function
sqlContext.udf().register("computeDecade", (Integer year) ->
computeDecade(year), DataTypes.StringType);
final List albums = Arrays.asList(new Album(2000, "1"), new
Album(2000, "2"), new Album(2000, "3"));
final JavaRDD rdd = javaSc.parallelize(albums);
final DataFrame df = sqlContext.createDataFrame(rdd, Album.class);
df.registerTempTable("albums");
final DataFrame dataFrame = sqlContext.sql("SELECT
computeDecade(year),count(title) "+
" FROM albums " +
" GROUP BY computeDecade(year)");
{code}
> Java UDFs don't work with GROUP BY expressions
> --
>
> Key: SPARK-9435
> URL: https://issues.apache.org/jira/browse/SPARK-9435
> Project: Spark
> Issue Type: Bug
> Components: SQL
>Affects Versions: 1.4.1
> Environment: All
>Reporter: James Aley
> Attachments: IncMain.java, points.txt
>
>
> If you define a UDF in Java, for example by implementing the UDF1 interface,
> then try to use that UDF on a column in both the SELECT and GROUP BY clauses
> of a query, you'll get an error like this:
> {code}
> "SELECT inc(y),COUNT(DISTINCT x) FROM test_table GROUP BY inc(y)"
> org.apache.spark.sql.AnalysisException: expression 'y' is neither present in
> the group by, nor is it an aggregate function. Add to group by or wrap in
> first() if you don't care which value you get.
> {code}
> We put together a minimal reproduction in the attached Java file, which makes
> use of the data in the text file attached.
> I'm guessing there's some kind of issue with the equality implementation, so
> Spark can't tell that those two expressions are the same maybe? If you do the
> same thing from Scala, it works fine.
> Note for context: we ran into this issue while working around SPARK-9338.
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[jira] [Commented] (SPARK-9435) Java UDFs don't work with GROUP BY expressions
[
https://issues.apache.org/jira/browse/SPARK-9435?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15002126#comment-15002126
]
DOAN DuyHai commented on SPARK-9435:
Work-around: *define the UDF using the Scala API instead*
{code:java}
public static final class ComputeDecadeFn extends
AbstractFunction1 implements Serializable {
@Override
public String apply(Integer year) {
return computeDecade(year);
}
}
sqlContext.udf().register("computeDecade", new ComputeDecadeFn(),
JavaApiHelper.getTypeTag(String.class),
JavaApiHelper.getTypeTag(Integer.class));
{code}
You cannot use the lambda expression because the UDF function should be
serializable.
> Java UDFs don't work with GROUP BY expressions
> --
>
> Key: SPARK-9435
> URL: https://issues.apache.org/jira/browse/SPARK-9435
> Project: Spark
> Issue Type: Bug
> Components: SQL
>Affects Versions: 1.4.1
> Environment: All
>Reporter: James Aley
> Attachments: IncMain.java, points.txt
>
>
> If you define a UDF in Java, for example by implementing the UDF1 interface,
> then try to use that UDF on a column in both the SELECT and GROUP BY clauses
> of a query, you'll get an error like this:
> {code}
> "SELECT inc(y),COUNT(DISTINCT x) FROM test_table GROUP BY inc(y)"
> org.apache.spark.sql.AnalysisException: expression 'y' is neither present in
> the group by, nor is it an aggregate function. Add to group by or wrap in
> first() if you don't care which value you get.
> {code}
> We put together a minimal reproduction in the attached Java file, which makes
> use of the data in the text file attached.
> I'm guessing there's some kind of issue with the equality implementation, so
> Spark can't tell that those two expressions are the same maybe? If you do the
> same thing from Scala, it works fine.
> Note for context: we ran into this issue while working around SPARK-9338.
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[jira] [Commented] (SPARK-9435) Java UDFs don't work with GROUP BY expressions
[
https://issues.apache.org/jira/browse/SPARK-9435?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=14992633#comment-14992633
]
Utkarsh Sengar commented on SPARK-9435:
---
I am running into this problem too.
Query:
sqlContext.sql("SELECT properties.time FROM allEvents WHERE event='abc' AND
isSingleSearch(properties.ids) GROUP BY listToSingleId(properties.ids)")
UDF:
sqlContext.udf.register("listToSingleId", (ids : List[Long]) => ids(0))
Trying the nested select now, but is this a bug or expected outcome when using
UDF with group by?
> Java UDFs don't work with GROUP BY expressions
> --
>
> Key: SPARK-9435
> URL: https://issues.apache.org/jira/browse/SPARK-9435
> Project: Spark
> Issue Type: Bug
> Components: SQL
>Affects Versions: 1.4.1
> Environment: All
>Reporter: James Aley
> Attachments: IncMain.java, points.txt
>
>
> If you define a UDF in Java, for example by implementing the UDF1 interface,
> then try to use that UDF on a column in both the SELECT and GROUP BY clauses
> of a query, you'll get an error like this:
> {code}
> "SELECT inc(y),COUNT(DISTINCT x) FROM test_table GROUP BY inc(y)"
> org.apache.spark.sql.AnalysisException: expression 'y' is neither present in
> the group by, nor is it an aggregate function. Add to group by or wrap in
> first() if you don't care which value you get.
> {code}
> We put together a minimal reproduction in the attached Java file, which makes
> use of the data in the text file attached.
> I'm guessing there's some kind of issue with the equality implementation, so
> Spark can't tell that those two expressions are the same maybe? If you do the
> same thing from Scala, it works fine.
> Note for context: we ran into this issue while working around SPARK-9338.
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[jira] [Commented] (SPARK-9435) Java UDFs don't work with GROUP BY expressions
[
https://issues.apache.org/jira/browse/SPARK-9435?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=14735416#comment-14735416
]
Michael Armbrust commented on SPARK-9435:
-
>From a quick glance, the problem is likely that the {{equals}} function on
>Java UDFs is working correctly. As a workaround you could probably calculate
>the udf in a nested select.
> Java UDFs don't work with GROUP BY expressions
> --
>
> Key: SPARK-9435
> URL: https://issues.apache.org/jira/browse/SPARK-9435
> Project: Spark
> Issue Type: Bug
> Components: SQL
>Affects Versions: 1.4.1
> Environment: All
>Reporter: James Aley
> Attachments: IncMain.java, points.txt
>
>
> If you define a UDF in Java, for example by implementing the UDF1 interface,
> then try to use that UDF on a column in both the SELECT and GROUP BY clauses
> of a query, you'll get an error like this:
> {code}
> "SELECT inc(y),COUNT(DISTINCT x) FROM test_table GROUP BY inc(y)"
> org.apache.spark.sql.AnalysisException: expression 'y' is neither present in
> the group by, nor is it an aggregate function. Add to group by or wrap in
> first() if you don't care which value you get.
> {code}
> We put together a minimal reproduction in the attached Java file, which makes
> use of the data in the text file attached.
> I'm guessing there's some kind of issue with the equality implementation, so
> Spark can't tell that those two expressions are the same maybe? If you do the
> same thing from Scala, it works fine.
> Note for context: we ran into this issue while working around SPARK-9338.
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