Excellent. Is there an example of this somewhere?

Sent from my iPhone

> On Nov 6, 2014, at 1:43 AM, Sean Owen <so...@cloudera.com> wrote:
> 
> 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?
>> 
>> 
>> 
>> --
>> View this message in context: 
>> http://apache-spark-user-list.1001560.n3.nabble.com/how-to-blend-a-DStream-and-a-broadcast-variable-tp18227.html
>> Sent from the Apache Spark User List mailing list archive at Nabble.com.
>> 
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