Broadcast vars should work fine in Spark streaming. Broadcast vars are
immutable however. If you have some info to cache which might change
from batch to batch, you should be able to load it at the start of
your 'foreachRDD' method or equivalent. That's simple and works
assuming your batch interval isn't so short and data so big that
loading it every time is a burden.

On Wed, Nov 5, 2014 at 11:30 PM, spr <s...@yarcdata.com> wrote:
> My use case has one large data stream (DS1) that obviously maps to a DStream.
> The processing of DS1 involves filtering it for any of a set of known
> values, which will change over time, though slowly by streaming standards.
> If the filter data were static, it seems to obviously map to a broadcast
> variable, but it's dynamic.  (And I don't think it works to implement it as
> a DStream, because the new values need to be copied redundantly to all
> executors, not partitioned among the executors.)
>
> Looking at the Spark and Spark Streaming documentation, I have two
> questions:
>
> 1) There's no mention in the Spark Streaming Programming Guide of broadcast
> variables.  Do they coexist properly?
>
> 2) Once I have a broadcast variable in place in the "periodic function" that
> Spark Streaming executes, how can I update its value?  Obviously I can't
> literally update the value of that broadcast variable, which is immutable,
> but how can I get a new version of the variable established in all the
> executors?
>
> (And the other ever-present implicit question...)
>
> 3) Is there a better way to implement this?
>
>
>
> --
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