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Posted to issues@spark.apache.org by "Marco Gaido (JIRA)" <ji...@apache.org> on 2018/07/09 08:38:00 UTC

[jira] [Comment Edited] (SPARK-24438) Empty strings and null strings are written to the same partition

    [ https://issues.apache.org/jira/browse/SPARK-24438?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16536682#comment-16536682 ] 

Marco Gaido edited comment on SPARK-24438 at 7/9/18 8:37 AM:
-------------------------------------------------------------

IIRC, Hive has a placeholder string (\_\_HIVE_DEFAULT_PARTITION\_\_) for null value in partitions.


was (Author: mgaido):
IIRC, Hive has a placeholder string (__HIVE_DEFAULT_PARTITION__) for null value in partitions.

> Empty strings and null strings are written to the same partition
> ----------------------------------------------------------------
>
>                 Key: SPARK-24438
>                 URL: https://issues.apache.org/jira/browse/SPARK-24438
>             Project: Spark
>          Issue Type: Bug
>          Components: SQL
>    Affects Versions: 2.3.0
>            Reporter: Mukul Murthy
>            Priority: Major
>
> When you partition on a string column that has empty strings and nulls, they are both written to the same default partition. When you read the data back, all those values get read back as null.
> {code:java}
> import org.apache.spark.sql.types._
> import org.apache.spark.sql.catalyst.encoders.RowEncoder
> val data = Seq(Row(1, ""), Row(2, ""), Row(3, ""), Row(4, "hello"), Row(5, null))
> val schema = new StructType().add("a", IntegerType).add("b", StringType)
> val df = spark.createDataFrame(spark.sparkContext.parallelize(data), schema)
> display(df) 
> => 
> a b
> 1 
> 2 
> 3 
> 4 hello
> 5 null
> df.write.mode("overwrite").partitionBy("b").save("/home/mukul/weird_test_data4")
> val df2 = spark.read.load("/home/mukul/weird_test_data4")
> display(df2)
> => 
> a b
> 4 hello
> 3 null
> 2 null
> 1 null
> 5 null
> {code}
> Seems to affect multiple types of tables.



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