OK, even with 1 manifest file per region (per column family?) - 60K X 4 = 240,000 new files 8000 per minute, 135 per second. That is probably NN limit.
Anyway, the root cause is the same as with reference files during region split: HDFS does not do well on file create/open/close/delete. -Vlad On Fri, Jul 10, 2015 at 5:09 PM, Matteo Bertozzi <theo.berto...@gmail.com> wrote: > @Vladimir there is no hfile link creation on snapshot. we create 1 manifest > per region > > Matteo > > > On Fri, Jul 10, 2015 at 5:06 PM, Vladimir Rodionov <vladrodio...@gmail.com > > > wrote: > > > Being not very familiar with snapshot code, I could speculate only on > where > > most time is spent ... > > > > In creating 60K x 4 x K (K is average # of store files per region) small > > HFileLInks? This can be very large # of files. > > > > -Vlad > > > > > > > > On Fri, Jul 10, 2015 at 4:57 PM, Matteo Bertozzi < > theo.berto...@gmail.com> > > wrote: > > > > > the total time taken by a snapshot should be bounded by the slowest > > > machine. > > > we send a notification to each RS and each RS execute the snapshot > > > operation for each region. > > > can you track down what is slow in your case? > > > > > > clone has to create a reference for each file, and that is a master > > > operation, and these calls may all go away if we change the layout in a > > > proper way instead of doing what is proposed in HBASE-13991. > > > Most of the time should be spent on the enableTable phase of the clone. > > > > > > > > > On Fri, Jul 10, 2015 at 4:36 PM, Jean-Marc Spaggiari < > > > jean-m...@spaggiari.org> wrote: > > > > > > > Hi Rahul, > > > > > > > > Have you identified with it takes those 30 minutes? Is the table > > balances > > > > correctly across the servers? Form the logs, are you able to identify > > > what > > > > takes that much time? > > > > > > > > JM > > > > > > > > 2015-07-10 18:46 GMT-04:00 rahul gidwani <rahul.gidw...@gmail.com>: > > > > > > > > > Hi Matteo, > > > > > > > > > > We do SKIP_FLUSH. We have 1200+ regionservers with a single table > > with > > > > 60k > > > > > regions and 4 column families. It takes around 30 minutes to > > snapshot > > > > this > > > > > table using manifests compared to just seconds doing this with > hdfs. > > > > > Cloning this table takes considerably longer. > > > > > > > > > > For cases where someone would want to run Map/Reduce over snapshots > > > this > > > > > could be much faster as we could take an hdfs snapshot and bypass > the > > > > > clone. > > > > > > > > > > rahul > > > > > > > > > > > > > > > On Thu, Jul 9, 2015 at 12:20 PM, Matteo Bertozzi < > > > > theo.berto...@gmail.com> > > > > > wrote: > > > > > > > > > > > On Thu, Jul 9, 2015 at 12:12 PM, rahul gidwani < > > > > rahul.gidw...@gmail.com> > > > > > > wrote: > > > > > > > > > > > > > Even with manifests (Snapshot V2) for our larger tables it can > > take > > > > > hours > > > > > > > to Snapshot and Clone a table. > > > > > > > > > > > > > > > > > > > on snapshot time the only thing that can take hours, is "flush". > > > > > > if you don't need that (which is what you get with hdfs > snapshots) > > > you > > > > > can > > > > > > specify SKIP_FLUSH => true > > > > > > > > > > > > > > > > > > Matteo > > > > > > > > > > > > > > > > > > On Thu, Jul 9, 2015 at 12:12 PM, rahul gidwani < > > > > rahul.gidw...@gmail.com> > > > > > > wrote: > > > > > > > > > > > > > HBase snapshots are a very useful feature. but it was > implemented > > > > back > > > > > > > before there was the ability to snapshot via HDFS. > > > > > > > > > > > > > > Newer versions of Hadoop support HDFS snapshots. I was > wondering > > > if > > > > > the > > > > > > > community would be interested in something like a Snapshot V3 > > where > > > > we > > > > > > use > > > > > > > HDFS to take these snapshots. > > > > > > > > > > > > > > Even with manifests (Snapshot V2) for our larger tables it can > > take > > > > > hours > > > > > > > to Snapshot and Clone a table. > > > > > > > > > > > > > > Would this feature be of use to anyone? > > > > > > > > > > > > > > thanks > > > > > > > rahul > > > > > > > > > > > > > > > > > > > > > > > > > > > >
