OK, good news at last! Performance has improved by one order of magnitude. The bad news is that I don't know why. As far as I can tell the only things I changed were table.scan.max.memory and the performance profile on Muchos. Both had no effect when I initially tested them and I doubt that there's a "settling in" period for both of these so I don't know what it is. But at least now it's clear that it's possible to get better performance. I'll try to investigate why it happened. Thanks everyone for helping!
Regarding my use case: I'm trying to use Accumulo as a graph database. Traversing a graph, or several graphs at once, means getting a row (vertex) by ID, sending it to the client, deciding if it's relevant and then retrieving the neighboring vertices. So lots of reads by ID and back and forth between client and server. A full table scan is not exactly like that but it was the simplest use case I could think of that looked somewhat similar. On Wed, Aug 29, 2018 at 10:45 PM <dlmar...@comcast.net> wrote: > This may suggest an issue with client, either getting the data to the > client or the client itself (although I think there are other performance > related changes you could make). I’m curious what the end goal is here. Is > this a real world use case? If you are using this type of benchmark to > evaluate the speed of Accumulo, then you will likely not get the same > performance when you apply your data and your real use cases. > > > > *From:* guy sharon <guy.sharon.1...@gmail.com> > *Sent:* Wednesday, August 29, 2018 3:13 PM > *To:* user@accumulo.apache.org > *Subject:* Re: Accumulo performance on various hardware configurations > > > > hi Mike, > > > > As per Mike Miller's suggestion I started using > org.apache.accumulo.examples.simple.helloworld.ReadData from Accumulo with > debugging turned off and a BatchScanner with 10 threads. I redid all the > measurements and although this was 20% faster than using the shell there > was no difference once I started playing with the hardware configurations. > > > > Guy. > > > > On Wed, Aug 29, 2018 at 10:06 PM Michael Wall <mjw...@gmail.com> wrote: > > Guy, > > > > Can you go into specifics about how you are measuring this? Are you still > using "bin/accumulo shell -u root -p secret -e "scan -t hellotable -np" | > wc -l" as you mentioned earlier in the thread? As Mike Miller suggested, > serializing that back to the display and then counting 6M entries is going > to take some time. Try using a Batch Scanner directly. > > > > Mike > > > > On Wed, Aug 29, 2018 at 2:56 PM guy sharon <guy.sharon.1...@gmail.com> > wrote: > > Yes, I tried the high performance configuration which translates to 4G > heap size, but that didn't affect performance. Neither did setting > table.scan.max.memory to 4096k (default is 512k). Even if I accept that the > read performance here is reasonable I don't understand why none of the > hardware configuration changes (except going to 48 cores, which made things > worse) made any difference. > > > > On Wed, Aug 29, 2018 at 8:33 PM Mike Walch <mwa...@apache.org> wrote: > > Muchos does not automatically change its Accumulo configuration to take > advantage of better hardware. However, it does have a performance profile > setting in its configuration (see link below) where you can select a > profile (or create your own) based on your the hardware you are using. > > > > > https://github.com/apache/fluo-muchos/blob/master/conf/muchos.props.example#L94 > > On Wed, Aug 29, 2018 at 11:35 AM Josh Elser <els...@apache.org> wrote: > > Does Muchos actually change the Accumulo configuration when you are > changing the underlying hardware? > > On 8/29/18 8:04 AM, 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. > > > > > >
