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https://issues.apache.org/jira/browse/SPARK-1962?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Taeyun Kim updated SPARK-1962:
------------------------------
Description:
It would be nice if the RDD cache() method incorporate a reference counting
information.
That is,
{code}
void test()
{
JavaRDD<...> rdd = ...;
rdd.cache(); // to depth 1. actual caching happens.
rdd.cache(); // to depth 2. Nop as long as the storage level is the same.
Else, exception.
...
rdd.uncache(); // to depth 1. Nop.
rdd.uncache(); // to depth 0. Actual unpersist happens.
}
{code}
This can be useful when writing code in modular way.
When a function receives an rdd as an argument, it doesn't necessarily know the
cache status of the rdd.
But it could want to cache the rdd, since it will use the rdd multiple times.
But with the current RDD API, it cannot determine whether it should unpersist
it or leave it alone (so that caller can continue to use that rdd without
rebuilding).
> Add RDD cache reference counting
> --------------------------------
>
> Key: SPARK-1962
> URL: https://issues.apache.org/jira/browse/SPARK-1962
> Project: Spark
> Issue Type: New Feature
> Reporter: Taeyun Kim
> Priority: Minor
>
> It would be nice if the RDD cache() method incorporate a reference counting
> information.
> That is,
> {code}
> void test()
> {
> JavaRDD<...> rdd = ...;
> rdd.cache(); // to depth 1. actual caching happens.
> rdd.cache(); // to depth 2. Nop as long as the storage level is the same.
> Else, exception.
> ...
> rdd.uncache(); // to depth 1. Nop.
> rdd.uncache(); // to depth 0. Actual unpersist happens.
> }
> {code}
> This can be useful when writing code in modular way.
> When a function receives an rdd as an argument, it doesn't necessarily know
> the cache status of the rdd.
> But it could want to cache the rdd, since it will use the rdd multiple times.
> But with the current RDD API, it cannot determine whether it should unpersist
> it or leave it alone (so that caller can continue to use that rdd without
> rebuilding).
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