[
https://issues.apache.org/jira/browse/SPARK-12231?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15049498#comment-15049498
]
kevin yu commented on SPARK-12231:
----------------------------------
Hello Michael: Thanks for the suggestion. Yes, I can recreate the problem in
spark 1.6.
> 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
> 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
--
This message was sent by Atlassian JIRA
(v6.3.4#6332)
---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org
For additional commands, e-mail: issues-h...@spark.apache.org
