Interesting, in the client we're doing a group by location the multiget. So we could have the filter as HBase core code, and then we could use it in the client for the multiget: compared to my initial proposal, we don't have to change anything in the server code and we reuse the filtering framework. The filter can be also be used independently.
Is there any issue with this? The reseek seems to be quite smart in the way it handles the bloom filters, I don't know if it behaves differently in this case vs. a simple get. On Tue, Feb 19, 2013 at 7:27 PM, lars hofhansl <la...@apache.org> wrote: > I was thinking along the same lines. Doing a skip scan via filter hinting. > The problem is as you say that the Filter is instantiated everywhere and it > might be of significant size (have to maintain all row keys you are looking > for). > > > RegionScanner now a reseek method, it is possible to do this via a > coprocessor. They are also loaded per region (but at least not for each > store), and one can use the shared coproc state I added to alleviate the > memory concern. > > Thinking about this in terms of multiple scan is interesting. One could > identify clusters of close row keys in the Gets and issue a Scan for each > cluster. > > > -- Lars > > > > ________________________________ > From: Nicolas Liochon <nkey...@gmail.com> > To: user <user@hbase.apache.org> > Sent: Tuesday, February 19, 2013 9:28 AM > Subject: Re: Optimizing Multi Gets in hbase > > Imho, the easiest thing to do would be to write a filter. > You need to order the rows, then you can use hints to navigate to the next > row (SEEK_NEXT_USING_HINT). > The main drawback I see is that the filter will be invoked on all regions > servers, including the ones that don't need it. But this would also means > you have a very specific query pattern (which could be the case, I just > don't know), and you can still use the startRow / stopRow of the scan, and > create multiple scan if necessary. I'm also interested in Lars' opinion on > this. > > Nicolas > > > > On Tue, Feb 19, 2013 at 4:52 PM, Varun Sharma <va...@pinterest.com> wrote: > > > I have another question, if I am running a scan wrapped around multiple > > rows in the same region, in the following way: > > > > Scan scan = new scan(getWithMultipleRowsInSameRegion); > > > > Now, how does execution occur. Is it just a sequential scan across the > > entire region or does it seek to hfile blocks containing the actual > values. > > What I truly mean is, lets say the multi get is on following rows: > > > > Row1 : HFileBlock1 > > Row2 : HFileBlock20 > > Row3 : Does not exist > > Row4 : HFileBlock25 > > Row5 : HFileBlock100 > > > > The efficient way to do this would be to determine the correct blocks > using > > the index and then searching within the blocks for, say Row1. Then, seek > to > > HFileBlock20 and then look for Row2. Elimininate Row3 and then keep on > > seeking to + searching within HFileBlocks as needed. > > > > I am wondering if a scan wrapped around a Get with multiple rows would do > > the same ? > > > > Thanks > > Varun > > > > On Tue, Feb 19, 2013 at 12:37 AM, Nicolas Liochon <nkey...@gmail.com> > > wrote: > > > > > Looking at the code, it seems possible to do this server side within > the > > > multi invocation: we could group the get by region, and do a single > scan. > > > We could also add some heuristics if necessary... > > > > > > > > > > > > On Tue, Feb 19, 2013 at 9:02 AM, lars hofhansl <la...@apache.org> > wrote: > > > > > > > I should qualify that statement, actually. > > > > > > > > I was comparing scanning 1m KVs to getting 1m KVs when all KVs are > > > > returned. > > > > > > > > As James Taylor pointed out to me privately: A fairer comparison > would > > > > have been to run a scan with a filter that lets x% of the rows pass > > (i.e. > > > > the selectivity of the scan would be x%) and compare that to a multi > > Get > > > of > > > > the same x% of the row. > > > > > > > > There we found that a Scan+Filter is more efficient that issuing > multi > > > > Gets if x is >= 1-2%. > > > > > > > > > > > > Or in other words, translating many Gets into a Scan+Filter is > > beneficial > > > > if the Scan would return at least 1-2% of the rows to the client. > > > > For example: > > > > if you are looking for less than 10-20k rows in 1m rows, using muli > > Gets > > > > is likely more efficient. > > > > if you are looking for more than 10-20k rows in 1m rows, using a > > > > Scan+Filter is likely more efficient. > > > > > > > > > > > > Of course this is predicated on whether you have an efficient way to > > > > represent the rows you are looking for in a filter, so that would > > > probably > > > > shift this slightly more towards Gets (just imaging a Filter that to > > > encode > > > > 100k random row keys to be matched; since Filters are instantiated > > store > > > > there is another natural limit there). > > > > > > > > > > > > As I said below, the crux of the matter is having some histograms of > > your > > > > data, so that such a decision could be made automatically. > > > > > > > > > > > > -- Lars > > > > > > > > > > > > > > > > ________________________________ > > > > From: lars hofhansl <la...@apache.org> > > > > To: "user@hbase.apache.org" <user@hbase.apache.org> > > > > Sent: Monday, February 18, 2013 5:48 PM > > > > Subject: Re: Optimizing Multi Gets in hbase > > > > > > > > As it happens we did some tests around last week. > > > > Turns out doing Gets in batches instead of a scan still gives you 1/3 > > of > > > > the performance. > > > > > > > > I.e. when you have a table with, say, 10m rows and scanning take N > > > > seconds, then calling 10m Gets in batches of 1000 take ~3N, which is > > > pretty > > > > impressive. > > > > > > > > Now, this is with all data in the cache! > > > > When the data is not in the cache and the Gets are random it is many > > > > orders of magnitude slower, as the Gets are sprayed all over the > disk. > > In > > > > that case sorting the Gets and issuing scans would indeed be much > more > > > > efficient. > > > > > > > > > > > > The Gets in a batch are already sorted on the client, but as N. says > it > > > is > > > > hard to determine when to turn many Gets into a Scan with filters > > > > automatically. Without statistics/histograms I'd even wager a guess > > that > > > > would be impossible to do. > > > > Imagine you issue 10000 random Gets, but your table has 10bn rows, in > > > that > > > > case it is almost certain that the Gets are faster than a scan. > > > > Now image the Gets only cover a small key range. With statistics we > > could > > > > tell whether it would beneficial to turn this into a scan. > > > > > > > > It's not that hard to add statistics to HBase. Would do it as part of > > the > > > > compactions, and record the histograms in some table. > > > > > > > > > > > > You can always do that yourself. If you suspect you are touching most > > > rows > > > > in a table/region, just issue a scan with a appropriate filter (may > > have > > > to > > > > implement your own filter, though). Maybe we could a version of > > RowFilter > > > > that match against multiple keys. > > > > > > > > > > > > -- Lars > > > > > > > > > > > > > > > > ________________________________ > > > > From: Varun Sharma <va...@pinterest.com> > > > > To: user@hbase.apache.org > > > > Sent: Monday, February 18, 2013 1:57 AM > > > > Subject: Optimizing Multi Gets in hbase > > > > > > > > Hi, > > > > > > > > I am trying to batched get(s) on a cluster. Here is the code: > > > > > > > > List<Get> gets = ... > > > > // Prepare my gets with the rows i need > > > > myHTable.get(gets); > > > > > > > > I have two questions about the above scenario: > > > > i) Is this the most optimal way to do this ? > > > > ii) I have a feeling that if there are multiple gets in this case, on > > the > > > > same region, then each one of those shall instantiate separate > scan(s) > > > over > > > > the region even though a single scan is sufficient. Am I mistaken > here > > ? > > > > > > > > Thanks > > > > Varun > > > > > > > > > >
