Sven,
Strange results. BatchScanners most definitely can be processed in
parallel by the tabletservers.
There is a dynamically resizing threadpool in the TabletServers that
respond to load on the system. As the pool remains full, it will grow.
As it remains empty, it will shrink.
A few more questions: how many TabletServers do you have and did you run
this benchmark multiple times in succession to see if the results
changed? Also, have you tried increasing the number of threads per
batchscanner to see if that makes a difference?
I might have to try to run a similar later today. I am curious :)
Sven Hodapp wrote:
Hi,
I've changed the code a little bit, so that it uses a thread pool (via the
Future):
val ranges500 = ranges.asScala.grouped(500) // this means 6 BatchScanners
will be created
for (ranges<- ranges500) {
val bscan = instance.createBatchScanner(ARTIFACTS, auths, 2)
bscan.setRanges(ranges.asJava)
Future {
time("mult-scanner") {
bscan.asScala.toList // toList forces the iteration of the iterator
}
}
}
Here are the results:
background log: info: mult-scanner time: 4807.289358 ms
background log: info: mult-scanner time: 4930.996522 ms
background log: info: mult-scanner time: 9510.010808 ms
background log: info: mult-scanner time: 11394.152391 ms
background log: info: mult-scanner time: 13297.247295 ms
background log: info: mult-scanner time: 14032.704837 ms
background log: info: single-scanner time: 15322.624393 ms
Every Future completes independent, but in return every batch scanner iterator
needs more time to complete. :(
This means the batch scanners aren't really processed in parallel on the server
side?
Should I reconfigure something? Maybe the tablet servers haven't/can't allocate
enough threads or memory? (Every of the two nodes has 8 cores and 64GB memory
and a storage with ~300MB/s...)
Regards,
Sven
