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.
