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https://issues.apache.org/jira/browse/SPARK-22240?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16202691#comment-16202691
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Arthur Baudry commented on SPARK-22240:
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[~hyukjin.kwon] Yes it is a single file so even counting the # of files
wouldn't work in this particular case.
Spark 2.0.2 has builtin support for multiline without the option so I guess
having only one partition in Spark 2.2 is kind of fail-safe mechanism and we
are just lucky to have never encountered any problems with our files when
reading multiline records in Spark 2.0.2.
If it's any help I also tried with s3n and it's the same thing. Didn't try with
HDFS as I am only interacting with S3 at the moment. If I have a moment I shall
try.
Thanks for your help
> S3 CSV number of partitions incorrectly computed
>
>
> Key: SPARK-22240
> URL: https://issues.apache.org/jira/browse/SPARK-22240
> Project: Spark
> Issue Type: Bug
> Components: Spark Core
>Affects Versions: 2.2.0
> Environment: Running on EMR 5.8.0 with Hadoop 2.7.3 and Spark 2.2.0
>Reporter: Arthur Baudry
>
> Reading CSV out of S3 using S3A protocol does not compute the number of
> partitions correctly in Spark 2.2.0.
> With Spark 2.2.0 I get only partition when loading a 14GB file
> {code:java}
> scala> val input = spark.read.format("csv").option("header",
> "true").option("delimiter", "|").option("multiLine",
> "true").load("s3a://")
> input: org.apache.spark.sql.DataFrame = [PARTY_KEY: string, ROW_START_DATE:
> string ... 36 more fields]
> scala> input.rdd.getNumPartitions
> res2: Int = 1
> {code}
> While in Spark 2.0.2 I had:
> {code:java}
> scala> val input = spark.read.format("csv").option("header",
> "true").option("delimiter", "|").option("multiLine",
> "true").load("s3a://")
> input: org.apache.spark.sql.DataFrame = [PARTY_KEY: string, ROW_START_DATE:
> string ... 36 more fields]
> scala> input.rdd.getNumPartitions
> res2: Int = 115
> {code}
> This introduces obvious performance issues in Spark 2.2.0. Maybe there is a
> property that should be set to have the number of partitions computed
> correctly.
> I'm aware that the .option("multiline","true") is not supported in Spark
> 2.0.2, it's not relevant here.
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