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Posted to issues@spark.apache.org by "Marco Gaido (JIRA)" <ji...@apache.org> on 2017/11/17 14:20:00 UTC
[jira] [Commented] (SPARK-22532) Spark SQL function
'drop_duplicates' throws error when passing in a column that is an element
of a struct
[ https://issues.apache.org/jira/browse/SPARK-22532?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16257020#comment-16257020 ]
Marco Gaido commented on SPARK-22532:
-------------------------------------
the reason is that `header.eventId.lo` is not a column name, but it is an `Expression`. It is like you are using any kind of expression to transform a column (eg. `a + b` or `coalesce(a, 1)`) which is not supported by the `dropDuplicates` operation.
> Spark SQL function 'drop_duplicates' throws error when passing in a column that is an element of a struct
> ---------------------------------------------------------------------------------------------------------
>
> Key: SPARK-22532
> URL: https://issues.apache.org/jira/browse/SPARK-22532
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 2.1.0, 2.2.0
> Environment: Attempted on the following versions:
> * Spark 2.1 (CDH 5.9.2 w/ SPARK2-2.1.0.cloudera1-1.cdh5.7.0.p0.120904)
> * Spark 2.1 (installed via homebrew)
> * Spark 2.2 (installed via homebrew)
> Also tried on Spark 1.6 that comes with CDH 5.9.2 and it works correctly; this appears to be a regression.
> Reporter: Nicholas Hakobian
>
> When attempting to use drop_duplicates with a subset of columns that exist within a struct the following error it raised:
> {noformat}
> AnalysisException: u'Cannot resolve column name "header.eventId.lo" among (header);'
> {noformat}
> A complete example (using old sqlContext syntax so the same code can be run with Spark 1.x as well):
> {noformat}
> from pyspark.sql import Row
> from pyspark.sql.functions import *
> data = [
> Row(header=Row(eventId=Row(lo=0, hi=1))),
> Row(header=Row(eventId=Row(lo=0, hi=1))),
> Row(header=Row(eventId=Row(lo=1, hi=2))),
> Row(header=Row(eventId=Row(lo=2, hi=3))),
> ]
> df = sqlContext.createDataFrame(data)
> df.drop_duplicates(['header.eventId.lo', 'header.eventId.hi']).show()
> {noformat}
> produces the following stack trace:
> {noformat}
> ---------------------------------------------------------------------------
> AnalysisException Traceback (most recent call last)
> <ipython-input-1-d44c25c1919c> in <module>()
> 11 df = sqlContext.createDataFrame(data)
> 12
> ---> 13 df.drop_duplicates(['header.eventId.lo', 'header.eventId.hi']).show()
> /usr/local/Cellar/apache-spark/2.2.0/libexec/python/pyspark/sql/dataframe.py in dropDuplicates(self, subset)
> 1243 jdf = self._jdf.dropDuplicates()
> 1244 else:
> -> 1245 jdf = self._jdf.dropDuplicates(self._jseq(subset))
> 1246 return DataFrame(jdf, self.sql_ctx)
> 1247
> /usr/local/Cellar/apache-spark/2.2.0/libexec/python/lib/py4j-0.10.4-src.zip/py4j/java_gateway.py in __call__(self, *args)
> 1131 answer = self.gateway_client.send_command(command)
> 1132 return_value = get_return_value(
> -> 1133 answer, self.gateway_client, self.target_id, self.name)
> 1134
> 1135 for temp_arg in temp_args:
> /usr/local/Cellar/apache-spark/2.2.0/libexec/python/pyspark/sql/utils.py in deco(*a, **kw)
> 67 e.java_exception.getStackTrace()))
> 68 if s.startswith('org.apache.spark.sql.AnalysisException: '):
> ---> 69 raise AnalysisException(s.split(': ', 1)[1], stackTrace)
> 70 if s.startswith('org.apache.spark.sql.catalyst.analysis'):
> 71 raise AnalysisException(s.split(': ', 1)[1], stackTrace)
> AnalysisException: u'Cannot resolve column name "header.eventId.lo" among (header);'
> {noformat}
> This works _correctly_ in Spark 1.6, but fails in 2.1 (via homebrew and CDH) and 2.2 (via homebrew)
> An inconvenient workaround (but it works) is the following:
> {noformat}
> (
> df
> .withColumn('lo', col('header.eventId.lo'))
> .withColumn('hi', col('header.eventId.hi'))
> .drop_duplicates(['lo', 'hi'])
> .drop('lo')
> .drop('hi')
> .show()
> )
> {noformat}
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