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Posted to issues@spark.apache.org by "Li Jin (Jira)" <ji...@apache.org> on 2020/10/02 20:16:00 UTC
[jira] [Updated] (SPARK-33057) Cannot use filter with window
operations
[ https://issues.apache.org/jira/browse/SPARK-33057?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Li Jin updated SPARK-33057:
---------------------------
Description:
Current, trying to use filter with a window operations will fail:
{code:java}
df = spark.range(100)
win = Window.partitionBy().orderBy('id')
df.filter(F.rank().over(win) > 10).show()
{code}
Error:
{code:java}
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/Users/icexelloss/opt/miniconda3/envs/ibis-dev-spark-3/lib/python3.8/site-packages/pyspark/sql/dataframe.py", line 1461, in filter
jdf = self._jdf.filter(condition._jc)
File "/Users/icexelloss/opt/miniconda3/envs/ibis-dev-spark-3/lib/python3.8/site-packages/pyspark/python/lib/py4j-0.10.9-src.zip/py4j/java_gateway.py", line 1304, in __call__
File "/Users/icexelloss/opt/miniconda3/envs/ibis-dev-spark-3/lib/python3.8/site-packages/pyspark/sql/utils.py", line 134, in deco
raise_from(converted)
File "<string>", line 3, in raise_from
pyspark.sql.utils.AnalysisException: It is not allowed to use window functions inside WHERE clause;{code}
Although the code is same as the code below, which works:
{code:java}
df = spark.range(100)
win = Window.partitionBy().orderBy('id')
df = df.withColumn('rank', F.rank().over(win))
df = df[df['rank'] > 10]
df = df.drop('rank'){code}
was:
Current, trying to use filter with a window operations will fail:
{code:java}
df = spark.range(100)
win = Window.partitionBy().orderBy('id')
df.filter(F.rank().over(win) > 10).show()
{code}
Error:
{code:java}
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/Users/icexelloss/opt/miniconda3/envs/ibis-dev-spark-3/lib/python3.8/site-packages/pyspark/sql/dataframe.py", line 1461, in filter
jdf = self._jdf.filter(condition._jc)
File "/Users/icexelloss/opt/miniconda3/envs/ibis-dev-spark-3/lib/python3.8/site-packages/pyspark/python/lib/py4j-0.10.9-src.zip/py4j/java_gateway.py", line 1304, in __call__
File "/Users/icexelloss/opt/miniconda3/envs/ibis-dev-spark-3/lib/python3.8/site-packages/pyspark/sql/utils.py", line 134, in deco
raise_from(converted)
File "<string>", line 3, in raise_from
pyspark.sql.utils.AnalysisException: It is not allowed to use window functions inside WHERE clause;{code}
Although the code is same as:
{code:java}
df = spark.range(100)
win = Window.partitionBy().orderBy('id')
df = df.withColumn('rank', F.rank().over(win))
df = df[df['rank'] > 10]
df = df.drop('rank'){code}
> Cannot use filter with window operations
> ----------------------------------------
>
> Key: SPARK-33057
> URL: https://issues.apache.org/jira/browse/SPARK-33057
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 3.0.1
> Reporter: Li Jin
> Priority: Major
>
> Current, trying to use filter with a window operations will fail:
>
> {code:java}
> df = spark.range(100)
> win = Window.partitionBy().orderBy('id')
> df.filter(F.rank().over(win) > 10).show()
> {code}
> Error:
> {code:java}
> Traceback (most recent call last):
> File "<stdin>", line 1, in <module>
> File "/Users/icexelloss/opt/miniconda3/envs/ibis-dev-spark-3/lib/python3.8/site-packages/pyspark/sql/dataframe.py", line 1461, in filter
> jdf = self._jdf.filter(condition._jc)
> File "/Users/icexelloss/opt/miniconda3/envs/ibis-dev-spark-3/lib/python3.8/site-packages/pyspark/python/lib/py4j-0.10.9-src.zip/py4j/java_gateway.py", line 1304, in __call__
> File "/Users/icexelloss/opt/miniconda3/envs/ibis-dev-spark-3/lib/python3.8/site-packages/pyspark/sql/utils.py", line 134, in deco
> raise_from(converted)
> File "<string>", line 3, in raise_from
> pyspark.sql.utils.AnalysisException: It is not allowed to use window functions inside WHERE clause;{code}
> Although the code is same as the code below, which works:
> {code:java}
> df = spark.range(100)
> win = Window.partitionBy().orderBy('id')
> df = df.withColumn('rank', F.rank().over(win))
> df = df[df['rank'] > 10]
> df = df.drop('rank'){code}
>
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