[jira] [Updated] (SPARK-12823) Cannot create UDF with StructType input

2019-05-20 Thread Hyukjin Kwon (JIRA) 


 [ 
https://issues.apache.org/jira/browse/SPARK-12823?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Hyukjin Kwon updated SPARK-12823:
-
Labels: bulk-closed  (was: )

> Cannot create UDF with StructType input
> ---
>
> Key: SPARK-12823
> URL: https://issues.apache.org/jira/browse/SPARK-12823
> Project: Spark
>  Issue Type: Bug
>  Components: SQL
>Affects Versions: 1.5.2
>Reporter: Frank Rosner
>Priority: Major
>  Labels: bulk-closed
>
> h5. Problem
> It is not possible to apply a UDF to a column that has a struct data type. 
> Two previous requests to the mailing list remained unanswered.
> h5. How-To-Reproduce
> {code}
> val sql = new org.apache.spark.sql.SQLContext(sc)
> import sql.implicits._
> case class KV(key: Long, value: String)
> case class Row(kv: KV)
> val df = sc.parallelize(List(Row(KV(1L, "a")), Row(KV(5L, "b".toDF
> val udf1 = org.apache.spark.sql.functions.udf((kv: KV) => kv.value)
> df.select(udf1(df("kv"))).show
> // java.lang.ClassCastException: 
> org.apache.spark.sql.catalyst.expressions.GenericRowWithSchema cannot be cast 
> to $line78.$read$$iwC$$iwC$KV
> val udf2 = org.apache.spark.sql.functions.udf((kv: (Long, String)) => kv._2)
> df.select(udf2(df("kv"))).show
> // org.apache.spark.sql.AnalysisException: cannot resolve 'UDF(kv)' due to 
> data type mismatch: argument 1 requires struct<_1:bigint,_2:string> type, 
> however, 'kv' is of struct type.;
> {code}
> h5. Mailing List Entries
> - 
> https://mail-archives.apache.org/mod_mbox/spark-user/201511.mbox/%3CCACUahd8M=ipCbFCYDyein_=vqyoantn-tpxe6sq395nh10g...@mail.gmail.com%3E
> - https://www.mail-archive.com/user@spark.apache.org/msg43092.html
> h5. Possible Workaround
> If you create a {{UserDefinedFunction}} manually, not using the {{udf}} 
> helper functions, it works. See https://github.com/FRosner/struct-udf, which 
> exposes the {{UserDefinedFunction}} constructor (public from package 
> private). However, then you have to work with a {{Row}}, because it does not 
> automatically convert the row to a case class / tuple.



--
This message was sent by Atlassian JIRA
(v7.6.3#76005)

-
To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org
For additional commands, e-mail: issues-h...@spark.apache.org

[jira] [Updated] (SPARK-12823) Cannot create UDF with StructType input

2016-01-18 Thread Frank Rosner (JIRA) 

 [ 
https://issues.apache.org/jira/browse/SPARK-12823?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Frank Rosner updated SPARK-12823:
-
Description: 
h5. Problem

It is not possible to apply a UDF to a column that has a struct data type. Two 
previous requests to the mailing list remained unanswered.

h5. How-To-Reproduce

{code}
val sql = new org.apache.spark.sql.SQLContext(sc)
import sql.implicits._

case class KV(key: Long, value: String)
case class Row(kv: KV)
val df = sc.parallelize(List(Row(KV(1L, "a")), Row(KV(5L, "b".toDF

val udf1 = org.apache.spark.sql.functions.udf((kv: KV) => kv.value)
df.select(udf1(df("kv"))).show
// java.lang.ClassCastException: 
org.apache.spark.sql.catalyst.expressions.GenericRowWithSchema cannot be cast 
to $line78.$read$$iwC$$iwC$KV

val udf2 = org.apache.spark.sql.functions.udf((kv: (Long, String)) => kv._2)
df.select(udf2(df("kv"))).show
// org.apache.spark.sql.AnalysisException: cannot resolve 'UDF(kv)' due to data 
type mismatch: argument 1 requires struct<_1:bigint,_2:string> type, however, 
'kv' is of struct type.;
{code}

h5. Mailing List Entries

- 
https://mail-archives.apache.org/mod_mbox/spark-user/201511.mbox/%3CCACUahd8M=ipCbFCYDyein_=vqyoantn-tpxe6sq395nh10g...@mail.gmail.com%3E

- https://www.mail-archive.com/user@spark.apache.org/msg43092.html

h5. Possible Workaround

If you create a {{UserDefinedFunction}} manually, not using the {{udf}} helper 
functions, it works. See https://github.com/FRosner/struct-udf, which exposes 
the {{UserDefinedFunction}} constructor (public from package private). However, 
then you have to work with Row, because it does not automatically convert the 
row to a case class / tuple.

  was:
h5. Problem

It is not possible to apply a UDF to a column that has a struct data type. Two 
previous requests to the mailing list remained unanswered.

h5. How-To-Reproduce

{code}
val sql = new org.apache.spark.sql.SQLContext(sc)
import sql.implicits._

case class KV(key: Long, value: String)
case class Row(kv: KV)
val df = sc.parallelize(List(Row(KV(1L, "a")), Row(KV(5L, "b".toDF

val udf1 = org.apache.spark.sql.functions.udf((kv: KV) => kv.value)
df.select(udf1(df("kv"))).show
// java.lang.ClassCastException: 
org.apache.spark.sql.catalyst.expressions.GenericRowWithSchema cannot be cast 
to $line78.$read$$iwC$$iwC$KV

val udf2 = org.apache.spark.sql.functions.udf((kv: (Long, String)) => kv._2)
df.select(udf2(df("kv"))).show
// org.apache.spark.sql.AnalysisException: cannot resolve 'UDF(kv)' due to data 
type mismatch: argument 1 requires struct<_1:bigint,_2:string> type, however, 
'kv' is of struct type.;
{code}

h5. Mailing List Entries

- 
https://mail-archives.apache.org/mod_mbox/spark-user/201511.mbox/%3CCACUahd8M=ipCbFCYDyein_=vqyoantn-tpxe6sq395nh10g...@mail.gmail.com%3E

- https://www.mail-archive.com/user@spark.apache.org/msg43092.html

h5. Possible Workaround

If you create a {{UserDefinedFunction}} manually, not using the {{udf}} helper 
functions, it works. See https://github.com/FRosner/struct-udf, which exposes 
the {{UserDefinedFunction}} constructor (public from package private).


> Cannot create UDF with StructType input
> ---
>
> Key: SPARK-12823
> URL: https://issues.apache.org/jira/browse/SPARK-12823
> Project: Spark
>  Issue Type: Bug
>  Components: SQL
>Affects Versions: 1.5.2
>Reporter: Frank Rosner
>
> h5. Problem
> It is not possible to apply a UDF to a column that has a struct data type. 
> Two previous requests to the mailing list remained unanswered.
> h5. How-To-Reproduce
> {code}
> val sql = new org.apache.spark.sql.SQLContext(sc)
> import sql.implicits._
> case class KV(key: Long, value: String)
> case class Row(kv: KV)
> val df = sc.parallelize(List(Row(KV(1L, "a")), Row(KV(5L, "b".toDF
> val udf1 = org.apache.spark.sql.functions.udf((kv: KV) => kv.value)
> df.select(udf1(df("kv"))).show
> // java.lang.ClassCastException: 
> org.apache.spark.sql.catalyst.expressions.GenericRowWithSchema cannot be cast 
> to $line78.$read$$iwC$$iwC$KV
> val udf2 = org.apache.spark.sql.functions.udf((kv: (Long, String)) => kv._2)
> df.select(udf2(df("kv"))).show
> // org.apache.spark.sql.AnalysisException: cannot resolve 'UDF(kv)' due to 
> data type mismatch: argument 1 requires struct<_1:bigint,_2:string> type, 
> however, 'kv' is of struct type.;
> {code}
> h5. Mailing List Entries
> - 
> https://mail-archives.apache.org/mod_mbox/spark-user/201511.mbox/%3CCACUahd8M=ipCbFCYDyein_=vqyoantn-tpxe6sq395nh10g...@mail.gmail.com%3E
> - https://www.mail-archive.com/user@spark.apache.org/msg43092.html
> h5. Possible Workaround
> If you create a {{UserDefinedFunction}} manually, not using the {{udf}} 
> helper functions, it works. See https://github.com/FRosner/struct-udf,

[jira] [Updated] (SPARK-12823) Cannot create UDF with StructType input

2016-01-18 Thread Frank Rosner (JIRA) 

 [ 
https://issues.apache.org/jira/browse/SPARK-12823?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Frank Rosner updated SPARK-12823:
-
Description: 
h5. Problem

It is not possible to apply a UDF to a column that has a struct data type. Two 
previous requests to the mailing list remained unanswered.

h5. How-To-Reproduce

{code}
val sql = new org.apache.spark.sql.SQLContext(sc)
import sql.implicits._

case class KV(key: Long, value: String)
case class Row(kv: KV)
val df = sc.parallelize(List(Row(KV(1L, "a")), Row(KV(5L, "b".toDF

val udf1 = org.apache.spark.sql.functions.udf((kv: KV) => kv.value)
df.select(udf1(df("kv"))).show
// java.lang.ClassCastException: 
org.apache.spark.sql.catalyst.expressions.GenericRowWithSchema cannot be cast 
to $line78.$read$$iwC$$iwC$KV

val udf2 = org.apache.spark.sql.functions.udf((kv: (Long, String)) => kv._2)
df.select(udf2(df("kv"))).show
// org.apache.spark.sql.AnalysisException: cannot resolve 'UDF(kv)' due to data 
type mismatch: argument 1 requires struct<_1:bigint,_2:string> type, however, 
'kv' is of struct type.;
{code}

h5. Mailing List Entries

- 
https://mail-archives.apache.org/mod_mbox/spark-user/201511.mbox/%3CCACUahd8M=ipCbFCYDyein_=vqyoantn-tpxe6sq395nh10g...@mail.gmail.com%3E

- https://www.mail-archive.com/user@spark.apache.org/msg43092.html

h5. Possible Workaround

If you create a {{UserDefinedFunction}} manually, not using the {{udf}} helper 
functions, it works. See https://github.com/FRosner/struct-udf, which exposes 
the {{UserDefinedFunction}} constructor (public from package private). However, 
then you have to work with a {{Row}}, because it does not automatically convert 
the row to a case class / tuple.

  was:
h5. Problem

It is not possible to apply a UDF to a column that has a struct data type. Two 
previous requests to the mailing list remained unanswered.

h5. How-To-Reproduce

{code}
val sql = new org.apache.spark.sql.SQLContext(sc)
import sql.implicits._

case class KV(key: Long, value: String)
case class Row(kv: KV)
val df = sc.parallelize(List(Row(KV(1L, "a")), Row(KV(5L, "b".toDF

val udf1 = org.apache.spark.sql.functions.udf((kv: KV) => kv.value)
df.select(udf1(df("kv"))).show
// java.lang.ClassCastException: 
org.apache.spark.sql.catalyst.expressions.GenericRowWithSchema cannot be cast 
to $line78.$read$$iwC$$iwC$KV

val udf2 = org.apache.spark.sql.functions.udf((kv: (Long, String)) => kv._2)
df.select(udf2(df("kv"))).show
// org.apache.spark.sql.AnalysisException: cannot resolve 'UDF(kv)' due to data 
type mismatch: argument 1 requires struct<_1:bigint,_2:string> type, however, 
'kv' is of struct type.;
{code}

h5. Mailing List Entries

- 
https://mail-archives.apache.org/mod_mbox/spark-user/201511.mbox/%3CCACUahd8M=ipCbFCYDyein_=vqyoantn-tpxe6sq395nh10g...@mail.gmail.com%3E

- https://www.mail-archive.com/user@spark.apache.org/msg43092.html

h5. Possible Workaround

If you create a {{UserDefinedFunction}} manually, not using the {{udf}} helper 
functions, it works. See https://github.com/FRosner/struct-udf, which exposes 
the {{UserDefinedFunction}} constructor (public from package private). However, 
then you have to work with Row, because it does not automatically convert the 
row to a case class / tuple.


> Cannot create UDF with StructType input
> ---
>
> Key: SPARK-12823
> URL: https://issues.apache.org/jira/browse/SPARK-12823
> Project: Spark
>  Issue Type: Bug
>  Components: SQL
>Affects Versions: 1.5.2
>Reporter: Frank Rosner
>
> h5. Problem
> It is not possible to apply a UDF to a column that has a struct data type. 
> Two previous requests to the mailing list remained unanswered.
> h5. How-To-Reproduce
> {code}
> val sql = new org.apache.spark.sql.SQLContext(sc)
> import sql.implicits._
> case class KV(key: Long, value: String)
> case class Row(kv: KV)
> val df = sc.parallelize(List(Row(KV(1L, "a")), Row(KV(5L, "b".toDF
> val udf1 = org.apache.spark.sql.functions.udf((kv: KV) => kv.value)
> df.select(udf1(df("kv"))).show
> // java.lang.ClassCastException: 
> org.apache.spark.sql.catalyst.expressions.GenericRowWithSchema cannot be cast 
> to $line78.$read$$iwC$$iwC$KV
> val udf2 = org.apache.spark.sql.functions.udf((kv: (Long, String)) => kv._2)
> df.select(udf2(df("kv"))).show
> // org.apache.spark.sql.AnalysisException: cannot resolve 'UDF(kv)' due to 
> data type mismatch: argument 1 requires struct<_1:bigint,_2:string> type, 
> however, 'kv' is of struct type.;
> {code}
> h5. Mailing List Entries
> - 
> https://mail-archives.apache.org/mod_mbox/spark-user/201511.mbox/%3CCACUahd8M=ipCbFCYDyein_=vqyoantn-tpxe6sq395nh10g...@mail.gmail.com%3E
> - https://www.mail-archive.com/user@spark.apache.org/msg43092.html
> h5. Possible Workaround
> If you create a

[jira] [Updated] (SPARK-12823) Cannot create UDF with StructType input

2016-01-18 Thread Frank Rosner (JIRA) 

 [ 
https://issues.apache.org/jira/browse/SPARK-12823?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Frank Rosner updated SPARK-12823:
-
Description: 
h5. Problem

It is not possible to apply a UDF to a column that has a struct data type. Two 
previous requests to the mailing list remained unanswered.

h5. How-To-Reproduce

{code}
val sql = new org.apache.spark.sql.SQLContext(sc)
import sql.implicits._

case class KV(key: Long, value: String)
case class Row(kv: KV)
val df = sc.parallelize(List(Row(KV(1L, "a")), Row(KV(5L, "b".toDF

val udf1 = org.apache.spark.sql.functions.udf((kv: KV) => kv.value)
df.select(udf1(df("kv"))).show
// java.lang.ClassCastException: 
org.apache.spark.sql.catalyst.expressions.GenericRowWithSchema cannot be cast 
to $line78.$read$$iwC$$iwC$KV

val udf2 = org.apache.spark.sql.functions.udf((kv: (Long, String)) => kv._2)
df.select(udf2(df("kv"))).show
// org.apache.spark.sql.AnalysisException: cannot resolve 'UDF(kv)' due to data 
type mismatch: argument 1 requires struct<_1:bigint,_2:string> type, however, 
'kv' is of struct type.;
{code}

h5. Mailing List Entries

- 
https://mail-archives.apache.org/mod_mbox/spark-user/201511.mbox/%3CCACUahd8M=ipCbFCYDyein_=vqyoantn-tpxe6sq395nh10g...@mail.gmail.com%3E

- https://www.mail-archive.com/user@spark.apache.org/msg43092.html

h5. Possible Workaround

If you create a {{UserDefinedFunction}} manually, not using the {{udf}} helper 
functions, it works. See https://github.com/FRosner/struct-udf, which exposes 
the UserDefinedFunction constructor (public from package private).

  was:
h5. Problem

It is not possible to apply a UDF to a column that has a struct data type. Two 
previous requests to the mailing list remained unanswered.

h5. How-To-Reproduce

{code}
val sql = new org.apache.spark.sql.SQLContext(sc)
import sql.implicits._

case class KV(key: Long, value: String)
case class Row(kv: KV)
val df = sc.parallelize(List(Row(KV(1L, "a")), Row(KV(5L, "b".toDF

val udf1 = org.apache.spark.sql.functions.udf((kv: KV) => kv.value)
df.select(udf1(df("kv"))).show
// java.lang.ClassCastException: 
org.apache.spark.sql.catalyst.expressions.GenericRowWithSchema cannot be cast 
to $line78.$read$$iwC$$iwC$KV

val udf2 = org.apache.spark.sql.functions.udf((kv: (Long, String)) => kv._2)
df.select(udf2(df("kv"))).show
// org.apache.spark.sql.AnalysisException: cannot resolve 'UDF(kv)' due to data 
type mismatch: argument 1 requires struct<_1:bigint,_2:string> type, however, 
'kv' is of struct type.;
{code}

h5. Mailing List Entries

- 
https://mail-archives.apache.org/mod_mbox/spark-user/201511.mbox/%3CCACUahd8M=ipCbFCYDyein_=vqyoantn-tpxe6sq395nh10g...@mail.gmail.com%3E

- https://www.mail-archive.com/user@spark.apache.org/msg43092.html


> Cannot create UDF with StructType input
> ---
>
> Key: SPARK-12823
> URL: https://issues.apache.org/jira/browse/SPARK-12823
> Project: Spark
>  Issue Type: Bug
>  Components: SQL
>Affects Versions: 1.5.2
>Reporter: Frank Rosner
>
> h5. Problem
> It is not possible to apply a UDF to a column that has a struct data type. 
> Two previous requests to the mailing list remained unanswered.
> h5. How-To-Reproduce
> {code}
> val sql = new org.apache.spark.sql.SQLContext(sc)
> import sql.implicits._
> case class KV(key: Long, value: String)
> case class Row(kv: KV)
> val df = sc.parallelize(List(Row(KV(1L, "a")), Row(KV(5L, "b".toDF
> val udf1 = org.apache.spark.sql.functions.udf((kv: KV) => kv.value)
> df.select(udf1(df("kv"))).show
> // java.lang.ClassCastException: 
> org.apache.spark.sql.catalyst.expressions.GenericRowWithSchema cannot be cast 
> to $line78.$read$$iwC$$iwC$KV
> val udf2 = org.apache.spark.sql.functions.udf((kv: (Long, String)) => kv._2)
> df.select(udf2(df("kv"))).show
> // org.apache.spark.sql.AnalysisException: cannot resolve 'UDF(kv)' due to 
> data type mismatch: argument 1 requires struct<_1:bigint,_2:string> type, 
> however, 'kv' is of struct type.;
> {code}
> h5. Mailing List Entries
> - 
> https://mail-archives.apache.org/mod_mbox/spark-user/201511.mbox/%3CCACUahd8M=ipCbFCYDyein_=vqyoantn-tpxe6sq395nh10g...@mail.gmail.com%3E
> - https://www.mail-archive.com/user@spark.apache.org/msg43092.html
> h5. Possible Workaround
> If you create a {{UserDefinedFunction}} manually, not using the {{udf}} 
> helper functions, it works. See https://github.com/FRosner/struct-udf, which 
> exposes the UserDefinedFunction constructor (public from package private).



--
This message was sent by Atlassian JIRA
(v6.3.4#6332)

-
To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org
For additional commands, e-mail: issues-h...@spark.apache.org

[jira] [Updated] (SPARK-12823) Cannot create UDF with StructType input

2016-01-18 Thread Frank Rosner (JIRA) 

 [ 
https://issues.apache.org/jira/browse/SPARK-12823?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Frank Rosner updated SPARK-12823:
-
Description: 
h5. Problem

It is not possible to apply a UDF to a column that has a struct data type. Two 
previous requests to the mailing list remained unanswered.

h5. How-To-Reproduce

{code}
val sql = new org.apache.spark.sql.SQLContext(sc)
import sql.implicits._

case class KV(key: Long, value: String)
case class Row(kv: KV)
val df = sc.parallelize(List(Row(KV(1L, "a")), Row(KV(5L, "b".toDF

val udf1 = org.apache.spark.sql.functions.udf((kv: KV) => kv.value)
df.select(udf1(df("kv"))).show
// java.lang.ClassCastException: 
org.apache.spark.sql.catalyst.expressions.GenericRowWithSchema cannot be cast 
to $line78.$read$$iwC$$iwC$KV

val udf2 = org.apache.spark.sql.functions.udf((kv: (Long, String)) => kv._2)
df.select(udf2(df("kv"))).show
// org.apache.spark.sql.AnalysisException: cannot resolve 'UDF(kv)' due to data 
type mismatch: argument 1 requires struct<_1:bigint,_2:string> type, however, 
'kv' is of struct type.;
{code}

h5. Mailing List Entries

- 
https://mail-archives.apache.org/mod_mbox/spark-user/201511.mbox/%3CCACUahd8M=ipCbFCYDyein_=vqyoantn-tpxe6sq395nh10g...@mail.gmail.com%3E

- https://www.mail-archive.com/user@spark.apache.org/msg43092.html

h5. Possible Workaround

If you create a {{UserDefinedFunction}} manually, not using the {{udf}} helper 
functions, it works. See https://github.com/FRosner/struct-udf, which exposes 
the {{UserDefinedFunction}} constructor (public from package private).

  was:
h5. Problem

It is not possible to apply a UDF to a column that has a struct data type. Two 
previous requests to the mailing list remained unanswered.

h5. How-To-Reproduce

{code}
val sql = new org.apache.spark.sql.SQLContext(sc)
import sql.implicits._

case class KV(key: Long, value: String)
case class Row(kv: KV)
val df = sc.parallelize(List(Row(KV(1L, "a")), Row(KV(5L, "b".toDF

val udf1 = org.apache.spark.sql.functions.udf((kv: KV) => kv.value)
df.select(udf1(df("kv"))).show
// java.lang.ClassCastException: 
org.apache.spark.sql.catalyst.expressions.GenericRowWithSchema cannot be cast 
to $line78.$read$$iwC$$iwC$KV

val udf2 = org.apache.spark.sql.functions.udf((kv: (Long, String)) => kv._2)
df.select(udf2(df("kv"))).show
// org.apache.spark.sql.AnalysisException: cannot resolve 'UDF(kv)' due to data 
type mismatch: argument 1 requires struct<_1:bigint,_2:string> type, however, 
'kv' is of struct type.;
{code}

h5. Mailing List Entries

- 
https://mail-archives.apache.org/mod_mbox/spark-user/201511.mbox/%3CCACUahd8M=ipCbFCYDyein_=vqyoantn-tpxe6sq395nh10g...@mail.gmail.com%3E

- https://www.mail-archive.com/user@spark.apache.org/msg43092.html

h5. Possible Workaround

If you create a {{UserDefinedFunction}} manually, not using the {{udf}} helper 
functions, it works. See https://github.com/FRosner/struct-udf, which exposes 
the UserDefinedFunction constructor (public from package private).


> Cannot create UDF with StructType input
> ---
>
> Key: SPARK-12823
> URL: https://issues.apache.org/jira/browse/SPARK-12823
> Project: Spark
>  Issue Type: Bug
>  Components: SQL
>Affects Versions: 1.5.2
>Reporter: Frank Rosner
>
> h5. Problem
> It is not possible to apply a UDF to a column that has a struct data type. 
> Two previous requests to the mailing list remained unanswered.
> h5. How-To-Reproduce
> {code}
> val sql = new org.apache.spark.sql.SQLContext(sc)
> import sql.implicits._
> case class KV(key: Long, value: String)
> case class Row(kv: KV)
> val df = sc.parallelize(List(Row(KV(1L, "a")), Row(KV(5L, "b".toDF
> val udf1 = org.apache.spark.sql.functions.udf((kv: KV) => kv.value)
> df.select(udf1(df("kv"))).show
> // java.lang.ClassCastException: 
> org.apache.spark.sql.catalyst.expressions.GenericRowWithSchema cannot be cast 
> to $line78.$read$$iwC$$iwC$KV
> val udf2 = org.apache.spark.sql.functions.udf((kv: (Long, String)) => kv._2)
> df.select(udf2(df("kv"))).show
> // org.apache.spark.sql.AnalysisException: cannot resolve 'UDF(kv)' due to 
> data type mismatch: argument 1 requires struct<_1:bigint,_2:string> type, 
> however, 'kv' is of struct type.;
> {code}
> h5. Mailing List Entries
> - 
> https://mail-archives.apache.org/mod_mbox/spark-user/201511.mbox/%3CCACUahd8M=ipCbFCYDyein_=vqyoantn-tpxe6sq395nh10g...@mail.gmail.com%3E
> - https://www.mail-archive.com/user@spark.apache.org/msg43092.html
> h5. Possible Workaround
> If you create a {{UserDefinedFunction}} manually, not using the {{udf}} 
> helper functions, it works. See https://github.com/FRosner/struct-udf, which 
> exposes the {{UserDefinedFunction}} constructor (public from package private).



--
This message was sent by