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[66.87.138.247]) by smtp.gmail.com with ESMTPSA id q145sm161396663pfq.22.2017.01.06.10.27.10 for (version=TLS1_2 cipher=ECDHE-RSA-AES128-GCM-SHA256 bits=128/128); Fri, 06 Jan 2017 10:27:10 -0800 (PST) From: Chen Qin Content-Type: multipart/alternative; boundary=Apple-Mail-B24DCC45-49F7-4EF1-B880-4219FC50661E Content-Transfer-Encoding: 7bit Mime-Version: 1.0 (1.0) Date: Fri, 6 Jan 2017 10:27:09 -0800 Subject: Re: Increasing parallelism skews/increases overall job processing time linearly Message-Id: <86871029-C414-4201-BA45-80022E0D6A7A@gmail.com> References: In-Reply-To: To: user@flink.apache.org X-Mailer: iPhone Mail (14C92) archived-at: Fri, 06 Jan 2017 18:27:22 -0000 --Apple-Mail-B24DCC45-49F7-4EF1-B880-4219FC50661E Content-Type: text/plain; charset=us-ascii Content-Transfer-Encoding: quoted-printable Just noticed there are only two partitions per topic. Regardless of how larg= e parallelism set. Only two of those will get partition assigned at most. Sent from my iPhone > On Jan 6, 2017, at 02:40, Chakravarthy varaga w= rote: >=20 > Hi All, >=20 > Any updates on this? >=20 > Best Regards > CVP >=20 >> On Thu, Jan 5, 2017 at 1:21 PM, Chakravarthy varaga wrote: >>=20 >> Hi All, >>=20 >> I have a job as attached. >>=20 >> I have a 16 Core blade running RHEL 7. The taskmanager default number of s= lots is set to 1. The source is a kafka stream and each of the 2 sources(top= ic) have 2 partitions each. >> What I notice is that when I deploy a job to run with #parallelism=3D2 th= e total processing time doubles the time it took when the same job was deplo= yed with #parallelism=3D1. It linearly increases with the parallelism. >>=20 >> Since the numberof slots is set to 1 per TM, I would assume that the job w= ould be processed in parallel in 2 different TMs and that each consumer in e= ach TM is connected to 1 partition of the topic. This therefore should have k= ept the overall processing time the same or less !!! >>=20 >> The co-flatmap connects the 2 streams & uses ValueState (checkpointed in = FS). I think this is distributed among the TMs. My understanding is that the= search of values state could be costly between TMs. Do you sense something= wrong here? >>=20 >> Best Regards >> CVP >>=20 >>=20 >>=20 >>=20 >=20 --Apple-Mail-B24DCC45-49F7-4EF1-B880-4219FC50661E Content-Type: text/html; charset=utf-8 Content-Transfer-Encoding: quoted-printable
Just noticed there are only two partit= ions per topic. Regardless of how large parallelism set. Only two of those w= ill get partition assigned at most.

Sent from my iPhone
On Jan 6, 2017, at 02:40, Chakravarthy varaga <chakravarthyvp@gmail.com> wrote:

Hi All,

    Any updates on this?

Best Regards
CVP

On= Thu, Jan 5, 2017 at 1:21 PM, Chakravarthy varaga <chakravarthyvp@gma= il.com> wrote:

Hi All,

I have a job as a= ttached.

I have a 16 Core blade running RHEL 7. The t= askmanager default number of slots is set to 1. The source is a kafka stream= and each of the 2 sources(topic) have 2 partitions each.
What I= notice is that when I deploy a job to run with #parallelism=3D2 the total p= rocessing time doubles the time it took when the same job was deployed with #= parallelism=3D1. It linearly increases with the parallelism.

Since the numberof slots is set to 1 per TM, I would assume that the j= ob would be processed in parallel in 2 different TMs and that each consumer i= n each TM is connected to 1 partition of the topic. This therefore should ha= ve kept the overall processing time the same or less !!!

The co-flatm= ap connects the 2 streams & uses ValueState (checkpointed in FS). I thin= k this is distributed among the TMs. My understanding is that the search of v= alues state could be costly between TMs.  Do you sense something wrong h= ere?

Best Regards
CVP

<= /b>




= --Apple-Mail-B24DCC45-49F7-4EF1-B880-4219FC50661E--