[ https://issues.apache.org/jira/browse/SPARK-12231?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Michael Armbrust updated SPARK-12231: ------------------------------------- Affects Version/s: 1.6.0 > 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 -- 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