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 >> >>
