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. >>> > >>> > >>> >>
