Hi Ingo, Were you reading from an actual S3 bucket? or was it a local S3 mock server? The reason I ask is because reading from a remote bucket is slow (the fastest I have seen was ~60MB/s). If your HDFS server(s) are backed by NVMe drives, then the read speed could be in GBs/s. For the remote S3 bucket case, other cores would be idle as they will be waiting for the data to arrive.
On Mon, Aug 9, 2021 at 12:28 PM Müller Ingo <[email protected]> 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 > > > > > > > > > > -- *Regards,* Wail Alkowaileet
