[jira] [Updated] (SPARK-15811) UDFs do not work in Spark 2.0-preview built with scala 2.10

2016-06-15 Thread Davies Liu (JIRA) 

 [ 
https://issues.apache.org/jira/browse/SPARK-15811?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Davies Liu updated SPARK-15811:
---
Priority: Blocker  (was: Critical)

> UDFs do not work in Spark 2.0-preview built with scala 2.10
> ---
>
> Key: SPARK-15811
> URL: https://issues.apache.org/jira/browse/SPARK-15811
> Project: Spark
>  Issue Type: Bug
>  Components: Spark Core
>Affects Versions: 2.0.0
>Reporter: Franklyn Dsouza
>Priority: Blocker
>
> I've built spark-2.0-preview (8f5a04b) with scala-2.10 using the following
> {code}
> ./dev/change-version-to-2.10.sh
> ./dev/make-distribution.sh -DskipTests -Dzookeeper.version=3.4.5 
> -Dcurator.version=2.4.0 -Dscala-2.10 -Phadoop-2.6  -Pyarn -Phive
> {code}
> and then ran the following code in a pyspark shell
> {code}
> from pyspark.sql import SparkSession
> from pyspark.sql.types import IntegerType, StructField, StructType
> from pyspark.sql.functions import udf
> from pyspark.sql.types import Row
> spark = SparkSession.builder.master('local[4]').appName('2.0 
> DF').getOrCreate()
> add_one = udf(lambda x: x + 1, IntegerType())
> schema = StructType([StructField('a', IntegerType(), False)])
> df = spark.createDataFrame([Row(a=1),Row(a=2)], schema)
> df.select(add_one(df.a).alias('incremented')).collect()
> {code}
> This never returns with a result. 



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[jira] [Updated] (SPARK-15811) UDFs do not work in Spark 2.0-preview built with scala 2.10

2016-06-09 Thread Franklyn Dsouza (JIRA) 

 [ 
https://issues.apache.org/jira/browse/SPARK-15811?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Franklyn Dsouza updated SPARK-15811:

Shepherd: Davies Liu

> UDFs do not work in Spark 2.0-preview built with scala 2.10
> ---
>
> Key: SPARK-15811
> URL: https://issues.apache.org/jira/browse/SPARK-15811
> Project: Spark
>  Issue Type: Bug
>  Components: Spark Core
>Affects Versions: 2.0.0
>Reporter: Franklyn Dsouza
>Priority: Critical
>
> I've built spark-2.0-preview (8f5a04b) with scala-2.10 using the following
> {code}
> ./dev/change-version-to-2.10.sh
> ./dev/make-distribution.sh -DskipTests -Dzookeeper.version=3.4.5 
> -Dcurator.version=2.4.0 -Dscala-2.10 -Phadoop-2.6  -Pyarn -Phive
> {code}
> and then ran the following code in a pyspark shell
> {code}
> from pyspark.sql import SparkSession
> from pyspark.sql.types import IntegerType, StructField, StructType
> from pyspark.sql.functions import udf
> from pyspark.sql.types import Row
> spark = SparkSession.builder.master('local[4]').appName('2.0 
> DF').getOrCreate()
> add_one = udf(lambda x: x + 1, IntegerType())
> schema = StructType([StructField('a', IntegerType(), False)])
> df = spark.createDataFrame([Row(a=1),Row(a=2)], schema)
> df.select(add_one(df.a).alias('incremented')).collect()
> {code}
> This never returns with a result. 



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[jira] [Updated] (SPARK-15811) UDFs do not work in Spark 2.0-preview built with scala 2.10

2016-06-08 Thread Sean Owen (JIRA) 

 [ 
https://issues.apache.org/jira/browse/SPARK-15811?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Sean Owen updated SPARK-15811:
--
Target Version/s:   (was: 2.0.0)
Priority: Critical  (was: Blocker)
   Fix Version/s: (was: 2.0.0)

> UDFs do not work in Spark 2.0-preview built with scala 2.10
> ---
>
> Key: SPARK-15811
> URL: https://issues.apache.org/jira/browse/SPARK-15811
> Project: Spark
>  Issue Type: Bug
>  Components: Spark Core
>Affects Versions: 2.0.0
>Reporter: Franklyn Dsouza
>Priority: Critical
>
> I've built spark-2.0-preview (8f5a04b) with scala-2.10 using the following
> {code}
> ./dev/change-version-to-2.10.sh
> ./dev/make-distribution.sh -DskipTests -Dzookeeper.version=3.4.5 
> -Dcurator.version=2.4.0 -Dscala-2.10 -Phadoop-2.6  -Pyarn -Phive
> {code}
> and then ran the following code in a pyspark shell
> {code}
> from pyspark.sql import SparkSession
> from pyspark.sql.types import IntegerType, StructField, StructType
> from pyspark.sql.functions import udf
> from pyspark.sql.types import Row
> spark = SparkSession.builder.master('local[4]').appName('2.0 
> DF').getOrCreate()
> add_one = udf(lambda x: x + 1, IntegerType())
> schema = StructType([StructField('a', IntegerType(), False)])
> df = spark.createDataFrame([Row(a=1),Row(a=2)], schema)
> df.select(add_one(df.a).alias('incremented')).collect()
> {code}
> This never returns with a result. 



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[jira] [Updated] (SPARK-15811) UDFs do not work in Spark 2.0-preview built with scala 2.10

2016-06-07 Thread Franklyn Dsouza (JIRA) 

 [ 
https://issues.apache.org/jira/browse/SPARK-15811?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Franklyn Dsouza updated SPARK-15811:

Description: 
I've built spark-2.0-preview (8f5a04b) with scala-2.10 using the following
{code}
./dev/change-version-to-2.10.sh
./dev/make-distribution.sh -DskipTests -Dzookeeper.version=3.4.5 
-Dcurator.version=2.4.0 -Dscala-2.10 -Phadoop-2.6  -Pyarn -Phive
{code}
and then ran the following code in a pyspark shell
{code:python}
from pyspark.sql import SparkSession
from pyspark.sql.types import IntegerType, StructField, StructType
from pyspark.sql.functions import udf
from pyspark.sql.types import Row
spark = SparkSession.builder.master('local[4]').appName('2.0 DF').getOrCreate()
add_one = udf(lambda x: x + 1, IntegerType())
schema = StructType([StructField('a', IntegerType(), False)])
df = spark.createDataFrame([Row(a=1),Row(a=2)], schema)
df.select(add_one(df.a).alias('incremented')).collect()
{code}

This never returns with a result. 


  was:
I've built spark-2.0-preview (8f5a04b) with scala-2.10 using the following
{code}
./dev/change-version-to-2.10.sh
./dev/make-distribution.sh -DskipTests -Dzookeeper.version=3.4.5 
-Dcurator.version=2.4.0 -Dscala-2.10 -Phadoop-2.6  -Pyarn -Phive
{code}
and then ran the following code in a pyspark shell
{code:python}
from pyspark.sql import SparkSession
from pyspark.sql.types import IntegerType, StructField, StructType
from pyspark.sql.functions import udf
from pyspark.sql.types import Row
spark = SparkSession.builder.master('local[4]').appName('2.0 DF').getOrCreate()
add_one = udf(lambda x: x + 1, IntegerType())
schema = StructType([StructField('a', IntegerType(), False)])
df = spark.createDataFrame([Row(a=1),Row(a=2)], schema)
df.select(add_one(df.a).alias('incremented')).collect()
{code:xml}
This never returns with a result. 



> UDFs do not work in Spark 2.0-preview built with scala 2.10
> ---
>
> Key: SPARK-15811
> URL: https://issues.apache.org/jira/browse/SPARK-15811
> Project: Spark
>  Issue Type: Bug
>  Components: Spark Core
>Affects Versions: 2.0.0
>Reporter: Franklyn Dsouza
>Priority: Blocker
> Fix For: 2.0.0
>
>
> I've built spark-2.0-preview (8f5a04b) with scala-2.10 using the following
> {code}
> ./dev/change-version-to-2.10.sh
> ./dev/make-distribution.sh -DskipTests -Dzookeeper.version=3.4.5 
> -Dcurator.version=2.4.0 -Dscala-2.10 -Phadoop-2.6  -Pyarn -Phive
> {code}
> and then ran the following code in a pyspark shell
> {code:python}
> from pyspark.sql import SparkSession
> from pyspark.sql.types import IntegerType, StructField, StructType
> from pyspark.sql.functions import udf
> from pyspark.sql.types import Row
> spark = SparkSession.builder.master('local[4]').appName('2.0 
> DF').getOrCreate()
> add_one = udf(lambda x: x + 1, IntegerType())
> schema = StructType([StructField('a', IntegerType(), False)])
> df = spark.createDataFrame([Row(a=1),Row(a=2)], schema)
> df.select(add_one(df.a).alias('incremented')).collect()
> {code}
> This never returns with a result. 



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[jira] [Updated] (SPARK-15811) UDFs do not work in Spark 2.0-preview built with scala 2.10

2016-06-07 Thread Franklyn Dsouza (JIRA) 

 [ 
https://issues.apache.org/jira/browse/SPARK-15811?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Franklyn Dsouza updated SPARK-15811:

Description: 
I've built spark-2.0-preview (8f5a04b) with scala-2.10 using the following
{code}
./dev/change-version-to-2.10.sh
./dev/make-distribution.sh -DskipTests -Dzookeeper.version=3.4.5 
-Dcurator.version=2.4.0 -Dscala-2.10 -Phadoop-2.6  -Pyarn -Phive
{code}
and then ran the following code in a pyspark shell
{code:python}
from pyspark.sql import SparkSession
from pyspark.sql.types import IntegerType, StructField, StructType
from pyspark.sql.functions import udf
from pyspark.sql.types import Row
spark = SparkSession.builder.master('local[4]').appName('2.0 DF').getOrCreate()
add_one = udf(lambda x: x + 1, IntegerType())
schema = StructType([StructField('a', IntegerType(), False)])
df = spark.createDataFrame([Row(a=1),Row(a=2)], schema)
df.select(add_one(df.a).alias('incremented')).collect()
{code:xml}
This never returns with a result. 


  was:
I've built spark-2.0-preview (8f5a04b) with scala-2.10 using the following

./dev/change-version-to-2.10.sh
./dev/make-distribution.sh -DskipTests -Dzookeeper.version=3.4.5 
-Dcurator.version=2.4.0 -Dscala-2.10 -Phadoop-2.6  -Pyarn -Phive

and then ran the following code in a pyspark shell

from pyspark.sql import SparkSession
from pyspark.sql.types import IntegerType, StructField, StructType
from pyspark.sql.functions import udf
from pyspark.sql.types import Row
spark = SparkSession.builder.master('local[4]').appName('2.0 DF').getOrCreate()
add_one = udf(lambda x: x + 1, IntegerType())
schema = StructType([StructField('a', IntegerType(), False)])
df = spark.createDataFrame([Row(a=1),Row(a=2)], schema)
df.select(add_one(df.a).alias('incremented')).collect()

This never returns with a result. 



> UDFs do not work in Spark 2.0-preview built with scala 2.10
> ---
>
> Key: SPARK-15811
> URL: https://issues.apache.org/jira/browse/SPARK-15811
> Project: Spark
>  Issue Type: Bug
>  Components: Spark Core
>Affects Versions: 2.0.0
>Reporter: Franklyn Dsouza
>Priority: Blocker
> Fix For: 2.0.0
>
>
> I've built spark-2.0-preview (8f5a04b) with scala-2.10 using the following
> {code}
> ./dev/change-version-to-2.10.sh
> ./dev/make-distribution.sh -DskipTests -Dzookeeper.version=3.4.5 
> -Dcurator.version=2.4.0 -Dscala-2.10 -Phadoop-2.6  -Pyarn -Phive
> {code}
> and then ran the following code in a pyspark shell
> {code:python}
> from pyspark.sql import SparkSession
> from pyspark.sql.types import IntegerType, StructField, StructType
> from pyspark.sql.functions import udf
> from pyspark.sql.types import Row
> spark = SparkSession.builder.master('local[4]').appName('2.0 
> DF').getOrCreate()
> add_one = udf(lambda x: x + 1, IntegerType())
> schema = StructType([StructField('a', IntegerType(), False)])
> df = spark.createDataFrame([Row(a=1),Row(a=2)], schema)
> df.select(add_one(df.a).alias('incremented')).collect()
> {code:xml}
> This never returns with a result. 



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[jira] [Updated] (SPARK-15811) UDFs do not work in Spark 2.0-preview built with scala 2.10

2016-06-07 Thread Franklyn Dsouza (JIRA) 

 [ 
https://issues.apache.org/jira/browse/SPARK-15811?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Franklyn Dsouza updated SPARK-15811:

Description: 
I've built spark-2.0-preview (8f5a04b) with scala-2.10 using the following

{code}
./dev/change-version-to-2.10.sh
./dev/make-distribution.sh -DskipTests -Dzookeeper.version=3.4.5 
-Dcurator.version=2.4.0 -Dscala-2.10 -Phadoop-2.6  -Pyarn -Phive
{code}

and then ran the following code in a pyspark shell

{code}
from pyspark.sql import SparkSession
from pyspark.sql.types import IntegerType, StructField, StructType
from pyspark.sql.functions import udf
from pyspark.sql.types import Row
spark = SparkSession.builder.master('local[4]').appName('2.0 DF').getOrCreate()
add_one = udf(lambda x: x + 1, IntegerType())
schema = StructType([StructField('a', IntegerType(), False)])
df = spark.createDataFrame([Row(a=1),Row(a=2)], schema)
df.select(add_one(df.a).alias('incremented')).collect()
{code}

This never returns with a result. 


  was:
I've built spark-2.0-preview (8f5a04b) with scala-2.10 using the following
{code}
./dev/change-version-to-2.10.sh
./dev/make-distribution.sh -DskipTests -Dzookeeper.version=3.4.5 
-Dcurator.version=2.4.0 -Dscala-2.10 -Phadoop-2.6  -Pyarn -Phive
{code}
and then ran the following code in a pyspark shell
{code:python}
from pyspark.sql import SparkSession
from pyspark.sql.types import IntegerType, StructField, StructType
from pyspark.sql.functions import udf
from pyspark.sql.types import Row
spark = SparkSession.builder.master('local[4]').appName('2.0 DF').getOrCreate()
add_one = udf(lambda x: x + 1, IntegerType())
schema = StructType([StructField('a', IntegerType(), False)])
df = spark.createDataFrame([Row(a=1),Row(a=2)], schema)
df.select(add_one(df.a).alias('incremented')).collect()
{code}

This never returns with a result. 



> UDFs do not work in Spark 2.0-preview built with scala 2.10
> ---
>
> Key: SPARK-15811
> URL: https://issues.apache.org/jira/browse/SPARK-15811
> Project: Spark
>  Issue Type: Bug
>  Components: Spark Core
>Affects Versions: 2.0.0
>Reporter: Franklyn Dsouza
>Priority: Blocker
> Fix For: 2.0.0
>
>
> I've built spark-2.0-preview (8f5a04b) with scala-2.10 using the following
> {code}
> ./dev/change-version-to-2.10.sh
> ./dev/make-distribution.sh -DskipTests -Dzookeeper.version=3.4.5 
> -Dcurator.version=2.4.0 -Dscala-2.10 -Phadoop-2.6  -Pyarn -Phive
> {code}
> and then ran the following code in a pyspark shell
> {code}
> from pyspark.sql import SparkSession
> from pyspark.sql.types import IntegerType, StructField, StructType
> from pyspark.sql.functions import udf
> from pyspark.sql.types import Row
> spark = SparkSession.builder.master('local[4]').appName('2.0 
> DF').getOrCreate()
> add_one = udf(lambda x: x + 1, IntegerType())
> schema = StructType([StructField('a', IntegerType(), False)])
> df = spark.createDataFrame([Row(a=1),Row(a=2)], schema)
> df.select(add_one(df.a).alias('incremented')).collect()
> {code}
> This never returns with a result. 



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