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From Tim Armstrong <tarmstr...@cloudera.com>
Subject Re: Estimate peak memory VS used peak memory
Date Fri, 23 Feb 2018 18:08:39 GMT
I think the previous answers have been good. I wanted to add a couple of
side notes for context since I've been doing a lot of work in this area of
Impala. I could talk about this stuff for hours.

We do have mechanisms, like spilling data to disk or reducing # of threads,
that kick in to keep queries under the mem_limit. This has existed in some
form since Impala 2.0, but Impala 2.10 included some architectural changes
to make this more robust, and we have further improvements in the pipeline.
The end goal, which we're getting much closer to, is that queries should
reliably run to completion instead of getting killed after they are
admitted.

That support is going to enable future enhancements to memory-based
admission control to make it easier for cluster admins like yourself to
configure admission control. It is definitely tricky to pick a good value
for mem_limit when pools can contain a mix of queries and I think Impala
can do better at making these decisions automatically.

- Tim

On Fri, Feb 23, 2018 at 9:05 AM, Alexander Behm <alex.behm@cloudera.com>
wrote:

> For a given query the logic for determining the memory that will be
> required from admission is:
> - if the query has mem_limit use that
> - otherwise, use memory estimates from the planner
>
> A query may be assigned a mem_limit by:
> - taking the default mem_limit from the pool it was submitted to (this is
> the recommended practice)
> - manually setting one for the query (in case you want to override the
> pool default for a single query)
>
> In that setup, the memory estimates from the planner are irrelevant for
> admission decisions and only serve for informational purposes.
> Please do not read too much into the memory estimates from the planner.
> They can be totally wrong (like your 8TB example).
>
>
> On Fri, Feb 23, 2018 at 3:47 AM, Jeszy <jeszyb@gmail.com> wrote:
>
>> Again, the 8TB estimate would not be relevant if the query had a
>> mem_limit set.
>> I think all that we discussed is covered in the docs, but if you feel
>> like specific parts need clarification, please file a jira.
>>
>> On 23 February 2018 at 11:51, Fawze Abujaber <fawzeaj@gmail.com> wrote:
>> > Sorry for  asking many questions, but i see your answers are closing the
>> > gaps that i cannot find in the documentation.
>> >
>> > So how we can explain that there was an estimate for 8T per node and
>> impala
>> > decided to submit this query?
>> >
>> > My goal that each query running beyond the actual limit per node to
>> fail (
>> > and this is what i setup in the default memory per node per pool) an
>> want
>> > all other queries to be queue and not killed, so what i understand that
>> i
>> > need to setup the max queue query to unlimited and the queue timeout to
>> > hours.
>> >
>> > And in order to reach that i need to setup the default memory per node
>> for
>> > each pool and setting either max concurrency or the max memory per pool
>> that
>> > will help to measure the max concurrent queries that can run in specific
>> > pool.
>> >
>> > I think reaching this goal will close all my gaps.
>> >
>> >
>> >
>> > On Fri, Feb 23, 2018 at 11:49 AM, Jeszy <jeszyb@gmail.com> wrote:
>> >>
>> >> > Do queuing query or not is based on the prediction which based on the
>> >> > estimate and of course the concurrency that can run in a pool.
>> >>
>> >> Yes, it is.
>> >>
>> >> > If I have memory limit per pool and memory limit per node for a
>> pool, so
>> >> > it
>> >> > can be used to estimate number of queries that can run concurrently,
>> is
>> >> > this
>> >> > also based on the prediction and not the actual use.
>> >>
>> >> Also on prediction.
>> >
>> >
>>
>
>

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