You are viewing a plain text version of this content. The canonical link for it is here.
Posted to issues@spark.apache.org by "Rowan Chattaway (JIRA)" <ji...@apache.org> on 2015/05/14 17:04:00 UTC
[jira] [Commented] (SPARK-7637) StructType.merge slow with large
nenormalised tables O(N2)
[ https://issues.apache.org/jira/browse/SPARK-7637?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14543770#comment-14543770 ]
Rowan Chattaway commented on SPARK-7637:
----------------------------------------
I have made the changes and will submit a PR shortly. Can this jira be assigned to me please?
> StructType.merge slow with large nenormalised tables O(N2)
> ----------------------------------------------------------
>
> Key: SPARK-7637
> URL: https://issues.apache.org/jira/browse/SPARK-7637
> Project: Spark
> Issue Type: Improvement
> Components: SQL
> Affects Versions: 1.3.1
> Reporter: Rowan Chattaway
> Priority: Minor
> Original Estimate: 24h
> Remaining Estimate: 24h
>
> StructType.merge does a linear scan through the left schema and for each element scans the right schema. This results in a O(N2) algorithm.
> I have found this to be very slow when dealing with large denormalised parquet files.
> I would like to make a small change to this function to map the fields of both the left and right schemas resulting in O(N).
> This has a sizable increase in performance for large denormalised schemas.
> 10000x10000 column merge
> 2891ms Original
> 32ms with mapped field approach.
--
This message was sent by Atlassian JIRA
(v6.3.4#6332)
---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscribe@spark.apache.org
For additional commands, e-mail: issues-help@spark.apache.org