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From Jonathan Yom-Tov <jon.yom...@metismart.com>
Subject Re: Accumulo performance on various hardware configurations
Date Wed, 29 Aug 2018 16:37:45 GMT
I'm not 100% sure it's slow. Coming from RDBMS it seems it might be, but I
wanted the opinion of others since I'm not experienced with Accumulo. From
your reply I assume you think it's reasonable?

On Wed, Aug 29, 2018 at 6:33 PM, Jeremy Kepner <kepner@ll.mit.edu> wrote:

> Why do you think 500K/sec is slow?
>
> On Wed, Aug 29, 2018 at 04:39:32PM +0300, guy sharon wrote:
> > Well, in one experiment I used a machine with 48 cores and 192GB and the
> > results actually came out worse. And in another I had 7 tservers on
> servers
> > with 4 cores. I think I'm not configuring things correctly because I'd
> > expect the improved hardware to improve performance and that doesn't seem
> > to be the case.
> >
> > On Wed, Aug 29, 2018 at 4:00 PM Jeremy Kepner <kepner@ll.mit.edu> wrote:
> >
> > > Your node is fairly underpowered (2 cores and 8 GB RAM) and is less
> than
> > > most laptops.  That said
> > >
> > > 6M / 12sec = 500K/sec
> > >
> > > is good for a single node Accumulo instance on this hardware.
> > >
> > > Spitting might not help since you only have 2 cores so added parallism
> > > can't
> > > be exploited.
> > >
> > > Why do you think 500K/sec is slow?
> > >
> > > To determine slowness one would have to compare with other database
> > > technology on the same platform.
> > >
> > >
> > > On Wed, Aug 29, 2018 at 03:04:51PM +0300, guy sharon wrote:
> > > > hi,
> > > >
> > > > Continuing my performance benchmarks, I'm still trying to figure out
> if
> > > the
> > > > results I'm getting are reasonable and why throwing more hardware at
> the
> > > > problem doesn't help. What I'm doing is a full table scan on a table
> with
> > > > 6M entries. This is Accumulo 1.7.4 with Zookeeper 3.4.12 and Hadoop
> > > 2.8.4.
> > > > The table is populated by
> > > > org.apache.accumulo.examples.simple.helloworld.InsertWithBatchWriter
> > > > modified to write 6M entries instead of 50k. Reads are performed by
> > > > "bin/accumulo org.apache.accumulo.examples.simple.helloworld.ReadData
> -i
> > > > muchos -z localhost:2181 -u root -t hellotable -p secret". Here are
> the
> > > > results I got:
> > > >
> > > > 1. 5 tserver cluster as configured by Muchos (
> > > > https://github.com/apache/fluo-muchos), running on m5d.large AWS
> > > machines
> > > > (2vCPU, 8GB RAM) running CentOS 7. Master is on a separate server.
> Scan
> > > > took 12 seconds.
> > > > 2. As above except with m5d.xlarge (4vCPU, 16GB RAM). Same results.
> > > > 3. Splitting the table to 4 tablets causes the runtime to increase
> to 16
> > > > seconds.
> > > > 4. 7 tserver cluster running m5d.xlarge servers. 12 seconds.
> > > > 5. Single node cluster on m5d.12xlarge (48 cores, 192GB RAM), running
> > > > Amazon Linux. Configuration as provided by Uno (
> > > > https://github.com/apache/fluo-uno). Total time was 26 seconds.
> > > >
> > > > Offhand I would say this is very slow. I'm guessing I'm making some
> sort
> > > of
> > > > newbie (possibly configuration) mistake but I can't figure out what
> it
> > > is.
> > > > Can anyone point me to something that might help me find out what it
> is?
> > > >
> > > > thanks,
> > > > Guy.
> > >
>

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