Hi Rohit,

Can you point which thread has this statement? Maybe the additional
context would help us disambiguate the original idea.

TD

On Tue, Jul 29, 2014 at 6:15 PM, Tobias Pfeiffer <[email protected]> wrote:
> Hi,
>
> that quoted statement doesn't make too much sense for me, either. Maybe if
> you had a link for us that shows the context (Google doesn't reveal anything
> but this conversation), we could evaluate that statement better.
>
> Tobias
>
>
> On Tue, Jul 29, 2014 at 5:53 PM, Sean Owen <[email protected]> wrote:
>>
>> I'm not sure I understand this, maybe because the context is missing.
>> An RDD is immutable, so there is no such thing as writing to an RDD.
>> I'm not sure which aspect is being referred to as single-threaded. Is
>> this the Spark Streaming driver?
>>
>> What is the difference between "streaming into Spark" and "reading
>> from the stream"? Streaming data into Spark means Spark reads the
>> stream.
>>
>> A mini batch of data is exposed as an RDD, but the stream processing
>> continues while it is operated on. Saving the RDDs is one of the most
>> basic operations exposed by streaming:
>>
>> http://spark.apache.org/docs/latest/streaming-programming-guide.html#output-operations
>>  No, you do not stop the stream processing to persist it. In fact you
>> couldn't.
>>
>> On that basis, no, this sounds fairly wrong.
>>
>> On Tue, Jul 29, 2014 at 1:37 AM, Rohit Pujari <[email protected]>
>> wrote:
>> > Hello folks:
>> >
>> > I came across a thread that said
>> >
>> > "A Spark RDD read/write access is driven by a context object and is
>> > single
>> > threaded.  You cannot stream into Spark and read from the stream at the
>> > same
>> > time.  You have to stop the stream processing, snapshot the RDD and
>> > continue"
>> >
>> > Can you please offer some insights?
>> >
>> >
>> > Thanks,
>> > Rohit Pujari
>> > Solutions Engineer, Hortonworks
>> > [email protected]
>> > 716-430-6899
>> >
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