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From "Xiao Li (JIRA)" <j...@apache.org>
Subject [jira] [Updated] (SPARK-23309) Spark 2.3 cached query performance 20-30% worse then spark 2.2
Date Thu, 01 Feb 2018 23:10:00 GMT

     [ https://issues.apache.org/jira/browse/SPARK-23309?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Xiao Li updated SPARK-23309:
----------------------------
    Priority: Blocker  (was: Major)

> Spark 2.3 cached query performance 20-30% worse then spark 2.2
> --------------------------------------------------------------
>
>                 Key: SPARK-23309
>                 URL: https://issues.apache.org/jira/browse/SPARK-23309
>             Project: Spark
>          Issue Type: Bug
>          Components: SQL
>    Affects Versions: 2.3.0
>            Reporter: Thomas Graves
>            Priority: Blocker
>
> I was testing spark 2.3 rc2 and I am seeing a performance regression in sql queries on
cached data.
> The size of the data: 10.4GB input from hive orc files /18.8 GB cached/5592 partitions
> Here is the example query:
> val dailycached = spark.sql("select something from table where dt = '20170301' AND something
IS NOT NULL")
> dailycached.createOrReplaceTempView("dailycached") spark.catalog.cacheTable("dailyCached")
> spark.sql("SELECT COUNT(DISTINCT(something)) from dailycached").show()
>  
> On spark 2.2 I see queries times average 13 seconds
> On the same nodes I see spark 2.3 queries times average 17 seconds
> Note these are times of queries after the initial caching.  so just running the last
line again: 
> spark.sql("SELECT COUNT(DISTINCT(something)) from dailycached").show() multiple times.
>  
> I also ran a query over more data (335GB input/587.5 GB cached) and saw a similar discrepancy
in the performance of querying cached data between spark 2.3 and spark 2.2, where 2.2 was
better by like 20%.  



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