Olivier Girardot created SPARK-8038:
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Summary: PySpark SQL when functions is broken on Column
Key: SPARK-8038
URL: https://issues.apache.org/jira/browse/SPARK-8038
Project: Spark
Issue Type: Bug
Affects Versions: 1.4.0
Environment: Spark 1.4.0 RC3
Reporter: Olivier Girardot
Priority: Blocker
{code}
In [1]: df = sqlCtx.createDataFrame([(1, "1"), (2, "2"), (1, "2"), (1, "2")],
["key", "value"])
In [2]: from pyspark.sql import functions as F
In [8]: df.select(df.key, F.when(df.key > 1, 0).when(df.key == 0,
2).otherwise(1)).show()
+---+---------------------------------+
| key |CASE WHEN (key = 0) THEN 2 ELSE 1|
+---+---------------------------------+
| 1| 1|
| 2| 1|
| 1| 1|
| 1| 1|
+---+---------------------------------+
{code}
When in Scala I get the expected expression and behaviour :
{code}
scala> val df = sqlContext.createDataFrame(List((1, "1"), (2, "2"), (1, "2"),
(1, "2"))).toDF("key", "value")
scala> import org.apache.spark.sql.functions._
scala> df.select(df("key"), when(df("key") > 1, 0).when(df("key") === 2,
2).otherwise(1)).show()
+---+-------------------------------------------------------+
|key|CASE WHEN (key > 1) THEN 0 WHEN (key = 2) THEN 2 ELSE 1|
+---+-------------------------------------------------------+
| 1| 1|
| 2| 0|
| 1| 1|
| 1| 1|
+---+-------------------------------------------------------+
{code}
This is coming from the "column.py" file with the Column class definition of
**when** and the fix is coming.
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