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https://issues.apache.org/jira/browse/SPARK-3621?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14143933#comment-14143933
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bc Wong commented on SPARK-3621:
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I think this is for the case of a map-side join where one of the tables is
small.
[~xuefuz], if the driver is running in the cluster, then RDD.collect() means it
reading from HDFS and then broadcast the data to everyone. Right? That seems
reasonable. I don't see another way to "broadcast" something. Alternatively,
it's probably better for each executor to individually read that small HDFS
file into its memory.
> Provide a way to broadcast an RDD (instead of just a variable made of the
> RDD) so that a job can access
> -------------------------------------------------------------------------------------------------------
>
> Key: SPARK-3621
> URL: https://issues.apache.org/jira/browse/SPARK-3621
> Project: Spark
> Issue Type: Improvement
> Components: Spark Core
> Affects Versions: 1.0.0, 1.1.0
> Reporter: Xuefu Zhang
>
> In some cases, such as Hive's way of doing map-side join, it would be
> benefcial to allow client program to broadcast RDDs rather than just
> variables made of these RDDs. Broadcasting a variable made of RDDs requires
> all RDD data be collected to the driver and that the variable be shipped to
> the cluster after being made. It would be more performing if driver just
> broadcasts the RDDs and uses the corresponding data in jobs (such building
> hashmaps at executors).
> Tez has a broadcast edge which can ship data from previous stage to the next
> stage, which doesn't require driver side processing.
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