[
https://issues.apache.org/jira/browse/SPARK-13744?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15185656#comment-15185656
]
Stavros Kontopoulos commented on SPARK-13744:
---------------------------------------------
The problem is that ui shows less data than it should when all partitions are
cached in the first place, gradually the size is the right one but not with the
first count after cache.
Why this is not a problem could you elaborate more?
> Dataframe RDD caching increases the input size for subsequent stages
> --------------------------------------------------------------------
>
> Key: SPARK-13744
> URL: https://issues.apache.org/jira/browse/SPARK-13744
> Project: Spark
> Issue Type: Bug
> Components: SQL, Web UI
> Affects Versions: 1.6.0
> Environment: OSX
> Reporter: Justin Pihony
> Priority: Minor
> Attachments: Screen Shot 2016-03-08 at 10.35.51 AM.png
>
>
> Given the below code, you will see that the first run of count shows up as
> ~90KB, and even the next run with cache being set will result in the same
> input size. However, every subsequent run thereafter will result in an input
> size that is MUCH larger (500MB is listed as 38% for a default run). This
> size discrepancy seems to be a bug in the caching of a dataframe's RDD as far
> as I can see.
> {code}
> import sqlContext.implicits._
> case class Person(name:String ="Test", number:Double = 1000.2)
> val people = sc.parallelize(1 to 10000000,50).map { p => Person()}.toDF
> people.write.parquet("people.parquet")
> val parquetFile = sqlContext.read.parquet("people.parquet")
> parquetFile.rdd.count()
> parquetFile.rdd.cache()
> parquetFile.rdd.count()
> parquetFile.rdd.count()
> {code}
--
This message was sent by Atlassian JIRA
(v6.3.4#6332)
---------------------------------------------------------------------
To unsubscribe, e-mail: [email protected]
For additional commands, e-mail: [email protected]
