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Posted to issues@spark.apache.org by "Xiao Li (JIRA)" <ji...@apache.org> on 2018/07/23 20:06:00 UTC
[jira] [Resolved] (SPARK-24339) spark sql can not prune column in
transform/map/reduce query
[ https://issues.apache.org/jira/browse/SPARK-24339?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Xiao Li resolved SPARK-24339.
-----------------------------
Resolution: Fixed
Assignee: Li Yuanjian
Fix Version/s: 2.4.0
> spark sql can not prune column in transform/map/reduce query
> ------------------------------------------------------------
>
> Key: SPARK-24339
> URL: https://issues.apache.org/jira/browse/SPARK-24339
> Project: Spark
> Issue Type: Improvement
> Components: SQL
> Affects Versions: 2.2.0
> Reporter: xdcjie
> Assignee: Li Yuanjian
> Priority: Minor
> Labels: map, reduce, sql, transform
> Fix For: 2.4.0
>
>
> I was using {{TRANSFORM USING}} with branch-2.1/2.2, and noticed that it will scan all column of data, query like:
> {code:java}
> SELECT TRANSFORM(usid, cch) USING 'python test.py' AS (u1, c1, u2, c2) FROM test_table;{code}
> it's physical plan like:
> {code:java}
> == Physical Plan ==
> ScriptTransformation [usid#17, cch#9], python test.py, [u1#784, c1#785, u2#786, c2#787], HiveScriptIOSchema(List(),List(),Some(org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe),Some(org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe),List((field.delim, )),List((field.delim, )),Some(org.apache.hadoop.hive.ql.exec.TextRecordReader),Some(org.apache.hadoop.hive.ql.exec.TextRecordWriter),false)
> +- FileScan parquet [sh#0L,clk#1L,chg#2L,qey#3,ship#4,chgname#5,sid#6,bid#7,dis#8L,cch#9,wch#10,wid#11L,arank#12L,rtag#13,iid#14,uid#15,pid#16,usid#17,wdid#18,bid#19,oqleft#20,oqright#21,poqvalue#22,tm#23,... 367 more fields] Batched: false, Format: Parquet, Location: InMemoryFileIndex[file:/Users/Downloads/part-r-00093-0ef5d59f-2e08-4085-9b46-458a1652932a.g..., PartitionFilters: [], PushedFilters: [], ReadSchema: struct<sh:bigint,clk:bigint,chg:bigint,qey:string,ship:string,chgname:string,s...
> {code}
> In our scenario, parquet has 400 column, this query will take more time.
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