[jira] [Assigned] (SPARK-12231) Failed to generate predicate Error when using dropna

["Apache Spark (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/SPARK-12231?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Apache Spark reassigned SPARK-12231:
------------------------------------

    Assignee:     (was: Apache Spark)

> Failed to generate predicate Error when using dropna
> ----------------------------------------------------
>
>                 Key: SPARK-12231
>                 URL: https://issues.apache.org/jira/browse/SPARK-12231
>             Project: Spark
>          Issue Type: Bug
>          Components: PySpark, SQL
>    Affects Versions: 1.5.2, 1.6.0
>         Environment: python version: 2.7.9
> os: ubuntu 14.04
>            Reporter: yahsuan, chang
>
> code to reproduce error
> # write.py
> {code}
> import pyspark
> sc = pyspark.SparkContext()
> sqlc = pyspark.SQLContext(sc)
> df = sqlc.range(10)
> df1 = df.withColumn('a', df['id'] * 2)
> df1.write.partitionBy('id').parquet('./data')
> {code}
> # read.py
> {code}
> import pyspark
> sc = pyspark.SparkContext()
> sqlc = pyspark.SQLContext(sc)
> df2 = sqlc.read.parquet('./data')
> df2.dropna().count()
> {code}
> $ spark-submit write.py
> $ spark-submit read.py
> # error message
> {code}
> 15/12/08 17:20:34 ERROR Filter: Failed to generate predicate, fallback to interpreted org.apache.spark.sql.catalyst.errors.package$TreeNodeException: Binding attribute, tree: a#0L
> ...
> {code}
> If write data without partitionBy, the error won't happen



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