Hi Stephan,Fabian
Thank you for your reply! I will run the flink on yarn actually . It is
feasible to isolate different tasks in one job by starting new yarn session.
And it means every job will have a yarn seesion, and one taskManager just has
one slot. If I want to run all jobs in one yarn cluster in pipelined mode, and
one taskManager can run many tasks, another way is to use process mode, that
means every task will be a process not thread, so isolation is natural. Do you
think it is feasible to modify flink runtime to realize this? Or if we want to
do that, are there any suggestions? Thank you!
------------------------------------------------------------------发件人：Stephan
Ewen <se...@apache.org>发送时间：2015年8月3日(星期一) 00:36收件人：user
<user@flink.apache.org>抄 送：wangzhijiang999 <wangzhijiang...@aliyun.com>主 题：Re:
thread model issue in TaskManagerHere are some additional things you can do: -
For isolation between parallel tasks (within a job), start your YARN job such
that each TaskManager has one slot, and start many TaskManagers. That is a bit
less efficient (but not much) than fewer TaskManagers with more slots. (*) -
If you need to isolate successor tasks in a job against predecessor tasks, you
can select "batch" execution mode. By default, the system uses "pipelined"
execution mode. In a MapReduce case, this means that mappers and reducers run
concurrently. With "batch" mode, reducers run only after all mappers
finished.Greetings,Stephan(*) The reason why multiple slots in one TaskManager
are more efficient is that TaskManagers multiplex multiple data exchanges of a
shuffle through a TCP connection, reducing per-exchange overhead and usually
increasing throughput.As Fabian suggested, YARN is a good way to go for
isolation (it actually isolates more than a JVM, which is very nice).On Thu,
Jul 30, 2015 at 12:10 PM, Fabian Hueske <fhue...@gmail.com> wrote:Hi,it is
currently not possible to isolate tasks that consume a lot of JVM heap memory
and schedule them to a specific slot (or TaskManager).If you operate in a YARN
setup, you can isolate different jobs from each other by starting a new YARN
session for each job, but tasks within the same job cannot be isolated from
each other right now.Cheers, Fabian2015-07-30 4:02 GMT+02:00 wangzhijiang999
<wangzhijiang...@aliyun.com>:As I know, flink uses thread model in TaskManager,
that means one taskmanager process may run many different operator threads，and
these threads will compete the memory of the process. I know that flink has
memoryManage component in each taskManager， and it will control the
localBufferPool of InputGate, ResultPartition for each task，but if UDF consume
much memory, it will use jvm heap memory， so it can not be controlled by flink.
If I use flink as common platform, some users will consume much memory in UDF,
and it may influence other threads in the process, especially for OOM. I know
that it has sharedslot or isolated slot properties , but it just limit the task
schedule in one taskmanager, can i schedule task in separate taskmanger if i
consume much memory and donot want to influence other tasks. Or are there any
suggestions for the issue of thread model. As I know spark is also thread
model, but hadoop2 use process model.Thank you for any suggestions in advance!
