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

["Hyukjin Kwon (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/SPARK-24438?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Hyukjin Kwon resolved SPARK-24438.
----------------------------------
    Resolution: Won't Fix

I checked that and it looks treating empty string like that intentionally and I checked that {{__HIVE_DEFAULT_PARTITION__}} too.

Workaround should be easy anyway since we can just do one projection right before write out. Let me leave this resolved for now.

> 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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