spark-issues mailing list archives

Site index · List index
Message view « Date » · « Thread »
Top « Date » · « Thread »
From "Apache Spark (JIRA)" <j...@apache.org>
Subject [jira] [Assigned] (SPARK-11258) Remove quadratic runtime complexity for converting a Spark DataFrame into an R data.frame
Date Thu, 22 Oct 2015 08:51:27 GMT

     [ https://issues.apache.org/jira/browse/SPARK-11258?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Apache Spark reassigned SPARK-11258:
------------------------------------

    Assignee:     (was: Apache Spark)

> Remove quadratic runtime complexity for converting a Spark DataFrame into an R data.frame
> -----------------------------------------------------------------------------------------
>
>                 Key: SPARK-11258
>                 URL: https://issues.apache.org/jira/browse/SPARK-11258
>             Project: Spark
>          Issue Type: Improvement
>          Components: SparkR
>    Affects Versions: 1.5.1
>            Reporter: Frank Rosner
>
> h4. Introduction
> We tried to collect a DataFrame with > 1 million rows and a few hundred columns in
SparkR. This took a huge amount of time (much more than in the Spark REPL). When looking into
the code, I found that the {{org.apache.spark.sql.api.r.SQLUtils.dfToCols}} method has quadratic
run time complexity (it goes through the complete data set _m_ times, where _m_ is the number
of columns.
> h4. Problem
> The {{dfToCols}} method is transposing the row-wise representation of the Spark DataFrame
(array of rows) into a column wise representation (array of columns) to then be put into a
data frame. This is done in a very inefficient way, yielding to huge performance (and possibly
also memory) problems when collecting bigger data frames.
> h4. Solution
> Directly transpose the row wise representation to the column wise representation with
one pass through the data. I will create a pull request for this.
> h4. Runtime comparison
> On a test data frame with 1 million rows and 22 columns, the old `dfToCols` method takes
average 2267 ms to complete. My implementation takes only 554 ms on average. This effect gets
even bigger, the more columns you have.



--
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


Mime
View raw message