[
https://issues.apache.org/jira/browse/SPARK-11145?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14991314#comment-14991314
]
Jeff Zhang commented on SPARK-11145:
------------------------------------
I ran it on the master, seems it has been resolved.
> Cannot filter using a partition key and another column
> ------------------------------------------------------
>
> Key: SPARK-11145
> URL: https://issues.apache.org/jira/browse/SPARK-11145
> Project: Spark
> Issue Type: Bug
> Components: PySpark, SQL
> Affects Versions: 1.5.1
> Reporter: Julien Buret
>
> A Dataframe, loaded from partitionned parquet files, cannot be filtered by a
> predicate comparing a partition key and another column.
> In this case all records are returned
> Example
> {code}
> from pyspark.sql import SQLContext
> sqlContext = SQLContext(sc)
> d = [
> {'name': 'a', 'YEAR': 2015, 'year_2': 2014, 'statut': 'a'},
> {'name': 'b', 'YEAR': 2014, 'year_2': 2014, 'statut': 'a'},
> {'name': 'c', 'YEAR': 2013, 'year_2': 2011, 'statut': 'a'},
> {'name': 'd', 'YEAR': 2014, 'year_2': 2013, 'statut': 'a'},
> {'name': 'e', 'YEAR': 2016, 'year_2': 2017, 'statut': 'p'}
> ]
> rdd = sc.parallelize(d)
> df = sqlContext.createDataFrame(rdd)
> df.write.partitionBy('YEAR').mode('overwrite').parquet('data')
> df2 = sqlContext.read.parquet('data')
> df2.filter(df2.YEAR == df2.year_2).show()
> {code}
> return
> {code}
> +----+------+------+----+
> |name|statut|year_2|YEAR|
> +----+------+------+----+
> | d| a| 2013|2014|
> | b| a| 2014|2014|
> | c| a| 2011|2013|
> | e| p| 2017|2016|
> | a| a| 2014|2015|
> +----+------+------+----+
> {code}
--
This message was sent by Atlassian JIRA
(v6.3.4#6332)
---------------------------------------------------------------------
To unsubscribe, e-mail: [email protected]
For additional commands, e-mail: [email protected]
