Return-Path: X-Original-To: apmail-cassandra-user-archive@www.apache.org Delivered-To: apmail-cassandra-user-archive@www.apache.org Received: from mail.apache.org (hermes.apache.org [140.211.11.3]) by minotaur.apache.org (Postfix) with SMTP id 6608511BF3 for ; Tue, 16 Sep 2014 12:33:19 +0000 (UTC) Received: (qmail 20513 invoked by uid 500); 16 Sep 2014 12:33:15 -0000 Delivered-To: apmail-cassandra-user-archive@cassandra.apache.org Received: (qmail 20474 invoked by uid 500); 16 Sep 2014 12:33:15 -0000 Mailing-List: contact user-help@cassandra.apache.org; run by ezmlm Precedence: bulk List-Help: List-Unsubscribe: List-Post: List-Id: Reply-To: user@cassandra.apache.org Delivered-To: mailing list user@cassandra.apache.org Received: (qmail 20464 invoked by uid 99); 16 Sep 2014 12:33:15 -0000 Received: from athena.apache.org (HELO athena.apache.org) (140.211.11.136) by apache.org (qpsmtpd/0.29) with ESMTP; Tue, 16 Sep 2014 12:33:15 +0000 X-ASF-Spam-Status: No, hits=1.5 required=5.0 tests=HTML_MESSAGE,RCVD_IN_DNSWL_LOW,SPF_PASS X-Spam-Check-By: apache.org Received-SPF: pass (athena.apache.org: domain of gsterg@gmail.com designates 209.85.216.171 as permitted sender) Received: from [209.85.216.171] (HELO mail-qc0-f171.google.com) (209.85.216.171) by apache.org (qpsmtpd/0.29) with ESMTP; Tue, 16 Sep 2014 12:33:11 +0000 Received: by mail-qc0-f171.google.com with SMTP id x13so3577153qcv.30 for ; Tue, 16 Sep 2014 05:32:51 -0700 (PDT) DKIM-Signature: v=1; a=rsa-sha256; c=relaxed/relaxed; d=gmail.com; s=20120113; h=mime-version:in-reply-to:references:date:message-id:subject:from:to :content-type; bh=VQ66Nt4f6/LKyu2d45/Cj6M8KY207B9YQdvO0UsPIOY=; b=SPZZv00oTHlcByWkTk17sVHr7n8dvn3NWK1lBbE62TapbdKR+iCiA4FFyfX9S/sBeU tuFb2YhqQDhOaF/DAh071Bi7/EYQ6Ngd8NgjvMZrlVlKr1p+F4FBa82AXjpBrycCa1Aj VYd8BVaJHBtianqfa1nWNeo9xzQQjvoSve0DU9fS6hQ5F3dtdgalUY/br/cGAewQ8gr6 Hqps41rEc7V1AG7NQLH6qty9A+XCEVuYMs+glJhiWyV55rU7xlcRhh83I/DeSNvAezbE ryuU9P4TaIH0cZlZzBS/dWaiSG9A7YR2B/h5g3FLWG0fWK10QNCi337iXroIIjl7fFWj lHBw== MIME-Version: 1.0 X-Received: by 10.140.17.9 with SMTP id 9mr44183010qgc.47.1410870771047; Tue, 16 Sep 2014 05:32:51 -0700 (PDT) Received: by 10.229.53.133 with HTTP; Tue, 16 Sep 2014 05:32:50 -0700 (PDT) In-Reply-To: References: Date: Tue, 16 Sep 2014 08:32:50 -0400 Message-ID: Subject: Re: Cassandra, vnodes, and spark From: George Stergiou To: user@cassandra.apache.org Content-Type: multipart/alternative; boundary=001a11c0b36a21e10205032df3ea X-Virus-Checked: Checked by ClamAV on apache.org --001a11c0b36a21e10205032df3ea Content-Type: text/plain; charset=UTF-8 Run into this performance report https://github.com/datastax/spark-cassandra-connector/issues/200 Does spark connector in its current state issue one CQL per vnode or task per vnode? Regards. On Tue, Sep 16, 2014 at 2:05 AM, DuyHai Doan wrote: > Look into the source code of the Spark connector. CassandraRDD try to find > all token ranges (even when using vnodes) for each node (endpoint) and > create RDD partition to match this distribution of token ranges. Thus data > locality is guaranteed > > On Tue, Sep 16, 2014 at 4:39 AM, Eric Plowe wrote: > >> Interesting. The way I understand the spark connector is that it's >> basically a client executing a cql query and filling a spark rdd. Spark >> will then handle the partitioning of data. Again, this is my understanding, >> and it maybe incorrect. >> >> >> On Monday, September 15, 2014, Robert Coli wrote: >> >>> On Mon, Sep 15, 2014 at 4:57 PM, Eric Plowe >>> wrote: >>> >>>> Based on this stackoverflow question, vnodes effect the number of >>>> mappers Hadoop needs to spawn. Which in then affect performance. >>>> >>>> With the spark connector for cassandra would the same situation happen? >>>> Would vnodes affect performance in a similar situation to Hadoop? >>>> >>> >>> I don't know what specifically Spark does here, but if it has the same >>> locality expectations as Hadoop generally, my belief would be : "yes." >>> >>> =Rob >>> >>> > --001a11c0b36a21e10205032df3ea Content-Type: text/html; charset=UTF-8 Content-Transfer-Encoding: quoted-printable
Does spark connector in its current state issue one CQL = per vnode or task per vnode?

Regards.
<= div class=3D"gmail_extra">
On Tue, Sep 16, 20= 14 at 2:05 AM, DuyHai Doan <doanduyhai@gmail.com> wrote:<= br>
Look into the source cod= e of the Spark connector. CassandraRDD try to find all token ranges (even w= hen using vnodes) for each node (endpoint) and create RDD partition to matc= h this distribution of token ranges. Thus data locality is guaranteed

On Tue, Sep 1= 6, 2014 at 4:39 AM, Eric Plowe <eric.plowe@gmail.com> wro= te:
Interesting. The way I understand the= spark connector is that it's basically a client executing a cql query = and filling a spark rdd. Spark will then handle the partitioning of data. A= gain, this is my understanding, and it maybe incorrect.


On Monday, September 15, 2014, Robert Coli <rcoli@eventbrite.com> wrote= :
On Mon, Sep 15, 2014 at 4:57 PM, Eric Plowe= <eric.plowe@gmail.com> wrote:
Based=C2=A0on this stackoverflow question,= =C2=A0vnodes effect the number of mappers Hadoop needs to spawn. Which in t= hen affect performance.

With the spark connector f= or cassandra would the same situation happen? Would vnodes affect performan= ce in a similar situation to Hadoop?

I don't know wh= at specifically Spark does here, but if it has the same locality expectatio= ns as Hadoop generally, my belief would be : "yes."

=3DRob



--001a11c0b36a21e10205032df3ea--