Hi,
Sorry it's not clear to me if you want help moving the data to the cluster
or in defining the best structure of your files on the cluster for
efficient processing. Are you on standalone or using hdfs?
On Tuesday, May 23, 2017, docdwarf wrote:
> tesmai4 wrote
> > I am converting my Java base
Ah that's right. I didn't mention it: I have 10 executors in my cluster,
and so when I do .coalesce(10) and right after that saving orc to s3 - does
coalescing really affects parallelism? To me it looks like no, because we
went from 100 tasks that are executed in parallel by 10 executors to 10
task
Spark is doing operations on each partition in parallel. If you decrease number
of partitions, you’re potentially doing less work in parallel depending on your
cluster setup.
> On May 23, 2017, at 4:23 PM, Andrii Biletskyi
> wrote:
>
>
> No, I didn't try to use repartition, how exactly it
No, I didn't try to use repartition, how exactly it impacts the parallelism?In
my understanding coalesce simply "unions" multiple partitions located on same
executor "one on on top of the other", while repartition does hash-based
shuffle decreasing the number of output partitions. So how this e
Hi all,
I am running a Spark (v1.6.1) application using the ./bin/spark-submit
script. I made some changes to the HttpBroadcast module. However, after the
application finishes completely, the spark master program hangs at the end
of the application. The ShutdownHook is supposed to be called at thi
No, I didn't try to use repartition, how exactly it impacts the parallelism?
In my understanding coalesce simply "unions" multiple partitions located on
same executor "one on on top of the other", while repartition does
hash-based shuffle decreasing the number of output partitions. So how this
exac
Thanks a lot Michael! I am not sure why Google search doesn't take me to
databricks blog when I typed in relevant keywords on various things.
Perhaps the blog needs some metadata for the search engine to index or
Google is more focused on Ads than relevant docs?!
On Tue, May 23, 2017 at 12:17 P
coalesce is nice because it does not shuffle, but the consequence of
avoiding a shuffle is it will also reduce parallelism of the preceding
computation. Have you tried using repartition instead?
On Tue, May 23, 2017 at 12:14 PM, Andrii Biletskyi <
andrii.bilets...@yahoo.com.invalid> wrote:
> Hi
There is an example in this post:
https://databricks.com/blog/2017/04/04/real-time-end-to-end-integration-with-apache-kafka-in-apache-sparks-structured-streaming.html
On Tue, May 23, 2017 at 11:35 AM, kant kodali wrote:
> Hi All,
>
> Are there any Kafka forEachSink examples preferably in Java b
Mark is right. I will cut another RC as soon as the known issues are
resolve. In the mean time it would be very helpful for people to test RC2
and report issues.
On Tue, May 23, 2017 at 11:10 AM, Mark Hamstra
wrote:
> I heard that once we reach release candidates it's not a question of time
>
Hi all,
I'm trying to understand the impact of coalesce operation on spark job
performance.
As a side note: were are using emrfs (i.e. aws s3) as source and a target
for the job.
Omitting unnecessary details job can be explained as: join 200M records
Dataframe stored in orc format on emrfs with
Hi All,
Are there any Kafka forEachSink examples preferably in Java but Scala is
fine too?
Thanks!
I heard that once we reach release candidates it's not a question of time
or a target date, but only whether blockers are resolved and the code is
ready to release.
On Tue, May 23, 2017 at 11:07 AM, kant kodali wrote:
> Heard its end of this month (May)
>
> On Tue, May 23, 2017 at 9:41 AM, mojha
Heard its end of this month (May)
On Tue, May 23, 2017 at 9:41 AM, mojhaha kiklasds
wrote:
> Hello,
>
> I could see a RC2 candidate for Spark 2.2, but not sure about the expected
> release timeline on that.
> Would be great if somebody can confirm it.
>
> Thanks,
> Mhojaha
>
Thanks !
On Mon, May 22, 2017 at 5:58 PM kant kodali wrote:
> Well there are few things here.
>
> 1. What is the Spark Version?
>
cdh 1.6
2. You said there is OOM error but what is the cause that appears in the
> log message or stack trace? OOM can happen for various reasons and JVM
> usually s
Hello,
I could see a RC2 candidate for Spark 2.2, but not sure about the expected
release timeline on that.
Would be great if somebody can confirm it.
Thanks,
Mhojaha
unsubscribe
tesmai4 wrote
> I am converting my Java based NLP parser to execute it on my Spark
> cluster. I know that Spark can read multiple text files from a directory
> and convert into RDDs for further processing. My input data is not only in
> text files, but in a multitude of different file formats.
>
On Tue, May 23, 2017 at 7:48 AM, Xiangyu Li wrote:
> Thank you for the answer.
>
> So basically it is not recommended to install Spark to your local maven
> repository? I thought if they wanted to enforce scalastyle for better open
> source contributions, they would have fixed all the scalastyle
Thank you for the answer.
So basically it is not recommended to install Spark to your local maven
repository? I thought if they wanted to enforce scalastyle for better open
source contributions, they would have fixed all the scalastyle warnings.
On a side note, my posts on Nabble never got accept
Thank you for the answer.
So basically it is not recommended to install Spark to your local maven
repository? I thought if they wanted to enforce scalastyle for better open
source contributions, they would have fixed all the scalastyle warnings.
On a side note, my posts on Nabble never got accept
From: Arun [mailto:arunbm...@gmail.com]
Sent: Saturday, May 20, 2017 9:48 PM
To: user@spark.apache.org
Subject: Rmse recomender system
hi all..
I am new to machine learning.
i am working on recomender system. for training dataset RMSE is 0.08 while on
test data its is 2.345
From: Abir Chakraborty [mailto:abi...@247-inc.com]
Sent: Sunday, May 21, 2017 4:17 AM
To: user@spark.apache.org
Subject: unsubscribe
unsubscribe
From: Bibudh Lahiri [mailto:bibudhlah...@gmail.com]
Sent: Sunday, May 21, 2017 9:34 AM
To: user
Subject: unsubscribe
unsubscribe
user-unsubscr...@spark.apache.org
From: 萝卜丝炒饭 [mailto:1427357...@qq.com]
Sent: Sunday, May 21, 2017 8:15 PM
To: user
Subject: Are tachyon and akka removed from 2.1.1 please
HI all,
Iread some paper about source code, the paper base on version 1.2. they
refer the tachyon and akka. When
Hi
I just joined a project that runs on spark-1.6.1 and I have no prior spark
experience.
The project build is quite fragile when it comes to runtime dependencies.
Often the project builds fine but after deployment we end up with
ClassNotFoundException's or NoSuchMethodError's when submitting a j
Hi all,
I read some paper about the stage, l know the narrow dependency and shuffle
dependency.
About the belowing RDD DAG, how deos spark generate the stage DAG please?
And is this RDD DAG legal please?<>
-
To unsubscrib
Hi Xiangrui,
We are also getting same exception while running our Spark application both
in local mode and distributed mode.
Do you have any insights on how to fix this?
Any help is highly appreciated.
TIA!
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View this message in context:
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thanks gromakowski and chin wei.
---Original---
From: "vincent gromakowski"
Date: 2017/5/23 00:54:33
To: "Chin Wei Low";
Cc: "user";"??"<1427357...@qq.com>;"Gene
Pang";
Subject: Re: Are tachyon and akka removed from 2.1.1 please
Akka has been replaced by netty in 1.6
Le 22 mai 2017
thanks Gene.
---Original---
From: "Gene Pang"
Date: 2017/5/22 22:19:47
To: "??"<1427357...@qq.com>;
Cc: "user";
Subject: Re: Are tachyon and akka removed from 2.1.1 please
Hi,
Tachyon has been renamed to Alluxio. Here is the documentation for running
Alluxio with Spark.
Hope this
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