I think the first question is where is the time spent. Does your analysis show that all the time spent is on the regionservers or is a portion of the bottleneck on the client side?
Jacques On Sun, Aug 12, 2012 at 4:00 PM, Mohammad Tariq <[email protected]> wrote: > Methods getStartKey and getEndKey provided by HRegionInfo class can used > for that purpose. > Also, please make sure, any HTable instance is not left opened once you are > are done with reads. > Regards, > Mohammad Tariq > > > > On Mon, Aug 13, 2012 at 4:22 AM, Gurjeet Singh <[email protected]> wrote: > > > Hi Mohammad, > > > > This is a great idea. Is there a API call to determine the start/end > > key for each region ? > > > > Thanks, > > Gurjeet > > > > On Sun, Aug 12, 2012 at 3:49 PM, Mohammad Tariq <[email protected]> > > wrote: > > > Hello experts, > > > > > > Would it be feasible to create a separate thread for each > > region??I > > > mean we can determine start and end key of each region and issue a scan > > for > > > each region in parallel. > > > > > > Regards, > > > Mohammad Tariq > > > > > > > > > > > > On Mon, Aug 13, 2012 at 3:54 AM, lars hofhansl <[email protected]> > > wrote: > > > > > >> Do you really have to retrieve all 200.000 each time? > > >> Scan.setBatch(...) makes no difference?! (note that batching is > > different > > >> and separate from caching). > > >> > > >> Also note that the scanner contract is to return sorted KVs, so a > single > > >> scan cannot be parallelized across RegionServers (well not entirely > > true, > > >> it could be farmed off in parallel and then be presented to the client > > in > > >> the right order - but HBase is not doing that). That is why one vs 12 > > RSs > > >> makes no difference in this scenario. > > >> > > >> In the 12 node case you'll see low CPU on all but one RS, and each RS > > will > > >> get its turn. > > >> > > >> In your case this is scanning 20.000.000 KVs serially in 400s, that's > > >> 50000 KVs/s, which - depending on hardware - is not too bad for HBase > > (but > > >> not great either). > > >> > > >> If you only ever expect to run a single query like this on top your > > >> cluster (i.e. your concern is latency not throughput) you can do > > multiple > > >> RPCs in parallel for a sub portion of your key range. Together with > > >> batching can start using value before all is streamed back from the > > server. > > >> > > >> > > >> -- Lars > > >> > > >> > > >> > > >> ----- Original Message ----- > > >> From: Gurjeet Singh <[email protected]> > > >> To: [email protected] > > >> Cc: > > >> Sent: Saturday, August 11, 2012 11:04 PM > > >> Subject: Slow full-table scans > > >> > > >> Hi, > > >> > > >> I am trying to read all the data out of an HBase table using a scan > > >> and it is extremely slow. > > >> > > >> Here are some characteristics of the data: > > >> > > >> 1. The total table size is tiny (~200MB) > > >> 2. The table has ~100 rows and ~200,000 columns in a SINGLE family. > > >> Thus the size of each cell is ~10bytes and the size of each row is > > >> ~2MB > > >> 3. Currently scanning the whole table takes ~400s (both in a > > >> distributed setting with 12 nodes or so and on a single node), thus > > >> 5sec/row > > >> 4. The row keys are unique 8 byte crypto hashes of sequential numbers > > >> 5. The scanner is set to fetch a FULL row at a time (scan.setBatch) > > >> and is set to fetch 100MB of data at a time (scan.setCaching) > > >> 6. Changing the caching size seems to have no effect on the total scan > > >> time at all > > >> 7. The column family is setup to keep a single version of the cells, > > >> no compression, and no block cache. > > >> > > >> Am I missing something ? Is there a way to optimize this ? > > >> > > >> I guess a general question I have is whether HBase is good datastore > > >> for storing many medium sized (~50GB), dense datasets with lots of > > >> columns when a lot of the queries require full table scans ? > > >> > > >> Thanks! > > >> Gurjeet > > >> > > >> > > >
