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Posted to issues@spark.apache.org by "Alexander Petrossian (PAF) (Jira)" <ji...@apache.org> on 2023/11/14 13:51:00 UTC
[jira] [Comment Edited] (SPARK-45876) Filters are not pushed down across lateral view
[ https://issues.apache.org/jira/browse/SPARK-45876?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17785897#comment-17785897 ]
Alexander Petrossian (PAF) edited comment on SPARK-45876 at 11/14/23 1:50 PM:
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So far localized problem here...
ScanOperation.unapply(plan) returns simply plan, but FileSourceStrategy#apply expects LogicalRelation.
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Probably because I've used "expand()", not sure (yet).
was (Author: neopaf):
So far localized problem here...
FileSourceStrategy#apply expects LogicalRelation as a result of ScanOperation.unapply
...but because I've used "expand()" ScanOperation.unapply returns Generate (child of Filter).
match case in 151 line fails.
!Снимок экрана 2023-11-14 в 16.33.48.png!
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No idea on how to improve this (yet).
> Filters are not pushed down across lateral view
> -----------------------------------------------
>
> Key: SPARK-45876
> URL: https://issues.apache.org/jira/browse/SPARK-45876
> Project: Spark
> Issue Type: Bug
> Components: Spark Core
> Affects Versions: 3.5.0
> Reporter: Alexander Petrossian (PAF)
> Priority: Major
> Attachments: Снимок экрана 2023-11-14 в 16.33.48.png, Снимок экрана 2023-11-14 в 16.35.56.png
>
>
> {code:python}
> from pyspark.sql import SparkSession
> spark = SparkSession.builder.config("spark.sql.catalogImplementation", "hive").appName("Write ORC File").getOrCreate()
> spark.sql('drop TABLE if exists test').show()
> spark.sql('CREATE EXTERNAL TABLE test (request struct<characteristic:array<struct<id:string,value:string>>>)'
> 'ROW FORMAT SERDE "org.apache.hadoop.hive.ql.io.orc.OrcSerde" '
> 'STORED AS INPUTFORMAT "org.apache.hadoop.hive.ql.io.orc.OrcInputFormat" '
> 'OUTPUTFORMAT "org.apache.hadoop.hive.ql.io.orc.OrcOutputFormat" '
> 'LOCATION "testfolder"').show()
> spark.sql("select request from test lateral view explode(request.characteristic) cTable as c where c.value='79640000000'").explain()
> {code}
> shows
> {code}
> == Physical Plan ==
> *(1) Project [request#2]
> +- *(1) Filter (isnotnull(c#4.value) AND (c#4.value = 79640000000))
> +- *(1) Generate explode(request#2.characteristic), [request#2], false, [c#4]
> +- *(1) ColumnarToRow
> +- FileScan orc spark_catalog.default.test[request#2] Batched: true, DataFilters: [], Format: ORC, Location: InMemoryFileIndex(1 paths)[file:/Users/paf/Downloads/spark-warehouse/testfolder], PartitionFilters: [], PushedFilters: [], ReadSchema: struct<request:struct<characteristic:array<struct<id:string,value:string>>>>
> {code}
> Which is extremely slow.
> Suppose I search for a column value, which is totally out of min/max statistics range.
> Search could have been much faster, but no.
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