You are viewing a plain text version of this content. The canonical link for it is here.
Posted to issues@spark.apache.org by "Hyukjin Kwon (Jira)" <ji...@apache.org> on 2019/09/18 14:35:00 UTC
[jira] [Resolved] (SPARK-29101) CSV datasource returns incorrect
.count() from file with malformed records
[ https://issues.apache.org/jira/browse/SPARK-29101?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Hyukjin Kwon resolved SPARK-29101.
----------------------------------
Fix Version/s: 3.0.0
Resolution: Fixed
Issue resolved by pull request 25820
[https://github.com/apache/spark/pull/25820]
> CSV datasource returns incorrect .count() from file with malformed records
> --------------------------------------------------------------------------
>
> Key: SPARK-29101
> URL: https://issues.apache.org/jira/browse/SPARK-29101
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 2.4.4
> Reporter: Stuart White
> Assignee: Sandeep Katta
> Priority: Minor
> Fix For: 3.0.0
>
>
> Spark 2.4 introduced a change to the way csv files are read. See [Upgrading From Spark SQL 2.3 to 2.4|https://spark.apache.org/docs/2.4.0/sql-migration-guide-upgrade.html#upgrading-from-spark-sql-23-to-24] for more details.
> In that document, it states: _To restore the previous behavior, set spark.sql.csv.parser.columnPruning.enabled to false._
> I am configuring Spark 2.4.4 as such, yet I'm still getting results inconsistent with pre-2.4. For example:
> Consider this file (fruit.csv). Notice it contains a header record, 3 valid records, and one malformed record.
> {noformat}
> fruit,color,price,quantity
> apple,red,1,3
> banana,yellow,2,4
> orange,orange,3,5
> xxx
> {noformat}
>
> With Spark 2.1.1, if I call .count() on a DataFrame created from this file (using option DROPMALFORMED), "3" is returned.
> {noformat}
> (using Spark 2.1.1)
> scala> spark.read.option("header", "true").option("mode", "DROPMALFORMED").csv("fruit.csv").count
> 19/09/16 14:28:01 WARN CSVRelation: Dropping malformed line: xxx
> res1: Long = 3
> {noformat}
> With Spark 2.4.4, I set the "spark.sql.csv.parser.columnPruning.enabled" option to false to restore the pre-2.4 behavior for handling malformed records, then call .count() and "4" is returned.
> {noformat}
> (using spark 2.4.4)
> scala> spark.conf.set("spark.sql.csv.parser.columnPruning.enabled", false)
> scala> spark.read.option("header", "true").option("mode", "DROPMALFORMED").csv("fruit.csv").count
> res1: Long = 4
> {noformat}
> So, using the *spark.sql.csv.parser.columnPruning.enabled* option did not actually restore previous behavior.
> How can I, using Spark 2.4+, get a count of the records in a .csv which excludes malformed records?
--
This message was sent by Atlassian Jira
(v8.3.4#803005)
---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscribe@spark.apache.org
For additional commands, e-mail: issues-help@spark.apache.org