https://issues.apache.org/jira/browse/SPARK-8360?jql=project%20%3D%20SPARK%20AND%20text%20~%20Streaming
-Todd
On Thu, Sep 10, 2015 at 10:22 AM, Gurvinder Singh <
gurvinder.si...@uninett.no> wrote:
> On 09/10/2015 07:42 AM, Tathagata Das wrote:
> > Rewriting is necessary. You will have to convert
On 09/10/2015 07:42 AM, Tathagata Das wrote:
> Rewriting is necessary. You will have to convert RDD/DStream operations
> to DataFrame operations. So get the RDDs in DStream, using
> transform/foreachRDD, convert to DataFrames and then do DataFrame
> operations.
Are there any plans for 1.6 or later
to:nb.nos...@gmail.com>
Cc: user<mailto:user@spark.apache.org>
Oggetto: Re: Tungsten and Spark Streaming
Rewriting is necessary. You will have to convert RDD/DStream operations to
DataFrame operations. So get the RDDs in DStream, using transform/foreachRDD,
convert to DataFrames and then do Da
Rewriting is necessary. You will have to convert RDD/DStream operations to
DataFrame operations. So get the RDDs in DStream, using
transform/foreachRDD, convert to DataFrames and then do DataFrame
operations.
On Wed, Sep 9, 2015 at 9:23 PM, N B wrote:
> Hello,
>
> How can we start taking advanta
Hello,
How can we start taking advantage of the performance gains made under
Project Tungsten in Spark 1.5 for a Spark Streaming program?
>From what I understand, this is available by default for Dataframes. But
for a program written using Spark Streaming, would we see any potential
gains "out of