Ingo,
Q: In your Parquet/S3 testing, what does your current cluster
configuration look like? (I.e., how many partitions have you configured
it with - physical storage partitions that is?) Even though your S3
data isn't stored inside AsterixDB in this case, the system still uses
that info to decide how many parallel threads to use at the base of its
query plans. (Obviously there is room for improvement on that behavior
for use cases involving external storage. :-))
Cheers,
Mike
On 8/9/21 12:28 PM, Müller Ingo wrote:
Hi Dmitry,
Thanks a lot for checking! Indeed, my queries do not have an exchange. However,
the number of I/O devices has indeed worked well in many cases: when I tried
the various VM instance sizes, I always created as many I/O devices as there
were physical cores (i.e., half the number of logical CPUs). For internal
storage as well as HDFS (both using the hdfs:// and the file:// protocol), I
saw the full system being utilized. However, just for the case of Parquet on
S3, I cannot seem to make it use more than 16 cores.
Cheers,
Ingo
-----Original Message-----
From: Dmitry Lychagin <[email protected]>
Sent: Monday, August 9, 2021 9:10 PM
To: [email protected]
Subject: Re: Increasing degree of parallelism when reading Parquet files
Hi Ingo,
I checked the code and it seems that when scanning external datasource we're
using the same number of cores as there are configured storage partitions (I/O
devices).
Therefore, if you want 96 cores to be used when scanning Parquet files then you
need to configure 96 I/O devices.
Compiler.parallelism setting is supposed to affect how many cores we use after
the first EXCHANGE operator. However, if your query doesn't have any
EXCHANGEs then it'll use the number of cores assigned for the initial data scan
operator (number of I/O devices)
Thanks,
-- Dmitry
On 8/9/21, 11:42 AM, "Müller Ingo" <[email protected]> wrote:
EXTERNAL EMAIL: Use caution when opening attachments or clicking on links
Dear Dmitry,
Thanks a lot for the quick reply! I had not though of this. However, I
have tried
out both ways just now (per query and in the cluster configuration) and did not
see any changes. Is there any way I can control that the setting was applied
successfully? I have also tried setting compiler.parallelism to 4 and still
observed
16 cores being utilized.
Note that the observed degree of parallelism does not correspond to
anything
related to the data set (I tried with every power of two files between 1 and
128)
or the cluster (I tried with every power of two cores between 2 and 64, as well
as 48 and 96) and I always see 16 cores being used (or fewer, if the system has
fewer). To me, this makes it unlikely that the system really uses the semantics
for p=0 or p<0, but looks more like some hard-coded value.
Cheers,
Ingo
> -----Original Message-----
> From: Dmitry Lychagin <[email protected]>
> Sent: Monday, August 9, 2021 7:25 PM
> To: [email protected]
> Subject: Re: Increasing degree of parallelism when reading Parquet files
>
> Ingo,
>
>
>
> We have `compiler.parallelism` parameter that controls how many cores are
> used for query execution.
>
> See
>
https://ci.apache.org/projects/asterixdb/sqlpp/manual.html#Parallelism_param
> eter
>
<https://ci.apache.org/projects/asterixdb/sqlpp/manual.html#Parallelism_para
> meter>
>
> You can either set it per query (e.g. SET `compiler.parallelism` "-1";) ,
>
> or globally in the cluster configuration:
>
> https://github.com/apache/asterixdb/blob/master/asterixdb/asterix-
> app/src/main/resources/cc2.conf#L57
>
>
>
> Thanks,
>
> -- Dmitry
>
>
>
>
>
> From: Müller Ingo <[email protected]>
> Reply-To: "[email protected]" <[email protected]>
> Date: Monday, August 9, 2021 at 10:05 AM
> To: "[email protected]" <[email protected]>
> Subject: Increasing degree of parallelism when reading Parquet files
>
>
>
> EXTERNAL EMAIL: Use caution when opening attachments or clicking on
links
>
>
>
>
>
> Dear AsterixDB devs,
>
>
>
> I am currently trying out the new support for Parquet files on S3 (still
in the
> context of my High-energy Physics use case [1]). This works great so far
and
has
> generally decent performance. However, I realized that it does not use
more
> than 16 cores, even though 96 logical cores are available and even
though I
run
> long-running queries (several minutes) on large data sets with a large
number of
> files (I tried 128 files of 17GB each). Is this an arbitrary/artificial
limitation
that
> can be changed somehow (potentially with a small patch+recompiling) or is
> there more serious development required to lift it? FYI, I am currently
using
> 03fd6d0f, which should include all S3/Parquet commits on master.
>
>
>
> Cheers,
>
> Ingo
>
>
>
>
>
> [1] https://arxiv.org/abs/2104.12615
>
>
