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From "Jark Wu" <wuchong...@alibaba-inc.com>
Subject Re: [Discuss] Why different job's tasks can run in the single process.
Date Fri, 01 Jul 2016 02:49:50 GMT
As standalone mode has the disadvantage that the TaskManager JVM can’t isolate different
jobs. Does we have any plan to improve this ? 

- Jark Wu 

> 在 2016年6月30日,下午4:19,Kevin Jacobs <kevin.jacobs@cern.ch> 写道:
> 
> In my opinion the streaming process can be perfectly simulated on a single node. You
can setup a message distribution system like Kafka on a single node, you can run Spark on
a single node and the only thing you need to change when running it on a cluster is that you
need to change the environment. So there is no need to setup a cluster when testing the streaming
process.
> 
> Regards,
> Kevin
> 
> On 30-06-16 09:54, Longda Feng wrote:
>> 
>> This means Standalone mode is just for prototype.
>> But I think we need a lightweight solution for streaming process, standalone is the
best solution. Some times, we need setup a flink cluster on a small cluster. setup a yarn
cluster isn't convenient.
>> (1) in small company, the number of machine is small (2) When a data center is small,
but we still need do some computing in this data center(3) some machines are in the while-list,
they have been authorited to access some special data or machine, but the number of these
machine is small.(4) some machine has critical data, they can't be shared with others, but
the number of these machine is small.(5) when a team start to learn flink, he will setup a
small cluster firstly, maybe he wo't want to setup a huge system, perfer to a small system
>> 
>> 
>> regardsLongda
>> 
>> ------------------------------------------------------------------From:Aljoscha Krettek
<aljoscha@apache.org>Send Time:2016年6月29日(星期三) 21:48To:封仲淹(纪君祥)
<zhongyan.feng@alibaba-inc.com>; dev <dev@flink.apache.org>Subject:Re: [Discuss]
Why different job's tasks can run in the single process.
>> Hi,
>> yes, you are definitely right that allowing to run multiple user code tasks
>> in the same TaskManager JVM is not good for stability. This mode is still
>> there from the very early days of Flink where Yarn was not yet available.
>> In a production environment I would now recommend to always run one
>> Flink-Yarn cluster per job to get good isolation between different jobs.
>> 
>> Cheers,
>> Aljoscha
>> 
>> On Wed, 29 Jun 2016 at 09:18 Longda Feng <zhongyan.feng@alibaba-inc.com>
>> wrote:
>> 
>>>  hi ,
>>>  Sorry for asking the quest here? Any answer will be apprecated.
>>>  Why different job's tasks can run in the single process. (There are some
>>>  different job's tasks  in one TaskManager).It seems Flink-on-Yarn can let
>>>  different job  run on different process. But for standalone mode, this
>>>  problem still exists.
>>>  Why design Flink like this?The advantage What I can thought is as
>>>  following:(1) All task can share bigger memory pool.(2) The communication
>>>  between the tasks in the same process will be fast.
>>>  But this design will impact to the stability. Flink provide
>>>  User-Define-Function interface, if one of the User-Define-Function crash,
>>>  It maybe crack the whole JVM, If the TaskManager crash, all other job's
>>>  task in this TaskManager will be impacted. Even if the JVM don't crash, but
>>>  maybe lead to some other unexpected problem, what's more this will make the
>>>  code too sophisticated。Normal framework like Spark/Storm/Samza won't run
>>>  different job's tasks in the same process。As one normal user, stability has
>>>  the highest priority.
>>> 
>>>  ThanksLongda
>>> 
>>> 
>>> 
>>> 


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