Yeah, I meant true... On Sat, Feb 9, 2013 at 12:17 AM, lars hofhansl <[email protected]> wrote:
> Should be set to true. If tcpnodelay is set to true, Nagle's is disabled. > > -- Lars > > > > ________________________________ > From: Varun Sharma <[email protected]> > To: [email protected]; lars hofhansl <[email protected]> > Sent: Saturday, February 9, 2013 12:11 AM > Subject: Re: Get on a row with multiple columns > > > Okay I did my research - these need to be set to false. I agree. > > > On Sat, Feb 9, 2013 at 12:05 AM, Varun Sharma <[email protected]> wrote: > > I have ipc.client.tcpnodelay, ipc.server.tcpnodelay set to false and the > hbase one - [hbase].ipc.client.tcpnodelay set to true. Do these induce > network latency ? > > > > > >On Fri, Feb 8, 2013 at 11:57 PM, lars hofhansl <[email protected]> wrote: > > > >Sorry.. I meant set these two config parameters to true (not false as I > state below). > >> > >> > >> > >> > >>----- Original Message ----- > >>From: lars hofhansl <[email protected]> > >>To: "[email protected]" <[email protected]> > >>Cc: > >>Sent: Friday, February 8, 2013 11:41 PM > >>Subject: Re: Get on a row with multiple columns > >> > >>Only somewhat related. Seeing the magic 40ms random read time there. Did > you disable Nagle's? > >>(set hbase.ipc.client.tcpnodelay and ipc.server.tcpnodelay to false in > hbase-site.xml). > >> > >>________________________________ > >>From: Varun Sharma <[email protected]> > >>To: [email protected]; lars hofhansl <[email protected]> > >>Sent: Friday, February 8, 2013 10:45 PM > >>Subject: Re: Get on a row with multiple columns > >> > >>The use case is like your twitter feed. Tweets from people u follow. When > >>someone unfollows, you need to delete a bunch of his tweets from the > >>following feed. So, its frequent, and we are essentially running into > some > >>extreme corner cases like the one above. We need high write throughput > for > >>this, since when someone tweets, we need to fanout the tweet to all the > >>followers. We need the ability to do fast deletes (unfollow) and fast > adds > >>(follow) and also be able to do fast random gets - when a real user loads > >>the feed. I doubt we will able to play much with the schema here since we > >>need to support a bunch of use cases. > >> > >>@lars: It does not take 30 seconds to place 300 delete markers. It takes > 30 > >>seconds to first find which of those 300 pins are in the set of columns > >>present - this invokes 300 gets and then place the appropriate delete > >>markers. Note that we can have tens of thousands of columns in a single > row > >>so a single get is not cheap. > >> > >>If we were to just place delete markers, that is very fast. But when > >>started doing that, our random read performance suffered because of too > >>many delete markers. The 90th percentile on random reads shot up from 40 > >>milliseconds to 150 milliseconds, which is not acceptable for our > usecase. > >> > >>Thanks > >>Varun > >> > >>On Fri, Feb 8, 2013 at 10:33 PM, lars hofhansl <[email protected]> wrote: > >> > >>> Can you organize your columns and then delete by column family? > >>> > >>> deleteColumn without specifying a TS is expensive, since HBase first > has > >>> to figure out what the latest TS is. > >>> > >>> Should be better in 0.94.1 or later since deletes are batched like Puts > >>> (still need to retrieve the latest version, though). > >>> > >>> In 0.94.3 or later you can also the BulkDeleteEndPoint, which basically > >>> let's specify a scan condition and then place specific delete marker > for > >>> all KVs encountered. > >>> > >>> > >>> If you wanted to get really > >>> fancy, you could hook up a coprocessor to the compaction process and > >>> simply filter all KVs you no longer want (without ever placing any > >>> delete markers). > >>> > >>> > >>> Are you saying it takes 15 seconds to place 300 version delete > markers?! > >>> > >>> > >>> -- Lars > >>> > >>> > >>> > >>> ________________________________ > >>> From: Varun Sharma <[email protected]> > >>> To: [email protected] > >>> Sent: Friday, February 8, 2013 10:05 PM > >>> Subject: Re: Get on a row with multiple columns > >>> > >>> We are given a set of 300 columns to delete. I tested two cases: > >>> > >>> 1) deleteColumns() - with the 's' > >>> > >>> This function simply adds delete markers for 300 columns, in our case, > >>> typically only a fraction of these columns are actually present - 10. > After > >>> starting to use deleteColumns, we starting seeing a drop in cluster > wide > >>> random read performance - 90th percentile latency worsened, so did 99th > >>> probably because of having to traverse delete markers. I attribute > this to > >>> profusion of delete markers in the cluster. Major compactions slowed > down > >>> by almost 50 percent probably because of having to clean out > significantly > >>> more delete markers. > >>> > >>> 2) deleteColumn() > >>> > >>> Ended up with untolerable 15 second calls, which clogged all the > handlers. > >>> Making the cluster pretty much unresponsive. > >>> > >>> On Fri, Feb 8, 2013 at 9:55 PM, Ted Yu <[email protected]> wrote: > >>> > >>> > For the 300 column deletes, can you show us how the Delete(s) are > >>> > constructed ? > >>> > > >>> > Do you use this method ? > >>> > > >>> > public Delete deleteColumns(byte [] family, byte [] qualifier) { > >>> > Thanks > >>> > > >>> > On Fri, Feb 8, 2013 at 9:44 PM, Varun Sharma <[email protected]> > >>> wrote: > >>> > > >>> > > So a Get call with multiple columns on a single row should be much > >>> faster > >>> > > than independent Get(s) on each of those columns for that row. I am > >>> > > basically seeing severely poor performance (~ 15 seconds) for > certain > >>> > > deleteColumn() calls and I am seeing that there is a > >>> > > prepareDeleteTimestamps() function in HRegion.java which first > tries to > >>> > > locate the column by doing individual gets on each column you want > to > >>> > > delete (I am doing 300 column deletes). Now, I think this should > ideall > >>> > by > >>> > > 1 get call with the batch of 300 columns so that one scan can > retrieve > >>> > the > >>> > > columns and the columns that are found, are indeed deleted. > >>> > > > >>> > > Before I try this fix, I wanted to get an opinion if it will make a > >>> > > difference to batch the get() and it seems from your answer, it > should. > >>> > > > >>> > > On Fri, Feb 8, 2013 at 9:34 PM, lars hofhansl <[email protected]> > >>> wrote: > >>> > > > >>> > > > Everything is stored as a KeyValue in HBase. > >>> > > > The Key part of a KeyValue contains the row key, column family, > >>> column > >>> > > > name, and timestamp in that order. > >>> > > > Each column family has it's own store and store files. > >>> > > > > >>> > > > So in a nutshell a get is executed by starting a scan at the row > key > >>> > > > (which is a prefix of the key) in each store (CF) and then > scanning > >>> > > forward > >>> > > > in each store until the next row key is reached. (in reality it > is a > >>> > bit > >>> > > > more complicated due to multiple versions, skipping columns, etc) > >>> > > > > >>> > > > > >>> > > > -- Lars > >>> > > > ________________________________ > >>> > > > From: Varun Sharma <[email protected]> > >>> > > > To: [email protected] > >>> > > > Sent: Friday, February 8, 2013 9:22 PM > >>> > > > Subject: Re: Get on a row with multiple columns > >>> > > > > >>> > > > Sorry, I was a little unclear with my question. > >>> > > > > >>> > > > Lets say you have > >>> > > > > >>> > > > Get get = new Get(row) > >>> > > > get.addColumn("1"); > >>> > > > get.addColumn("2"); > >>> > > > . > >>> > > > . > >>> > > > . > >>> > > > > >>> > > > When internally hbase executes the batch get, it will seek to > column > >>> > "1", > >>> > > > now since data is lexicographically sorted, it does not need to > seek > >>> > from > >>> > > > the beginning to get to "2", it can continue seeking, henceforth > >>> since > >>> > > > column "2" will always be after column "1". I want to know > whether > >>> this > >>> > > is > >>> > > > how a multicolumn get on a row works or not. > >>> > > > > >>> > > > Thanks > >>> > > > Varun > >>> > > > > >>> > > > On Fri, Feb 8, 2013 at 9:08 PM, Marcos Ortiz <[email protected]> > wrote: > >>> > > > > >>> > > > > Like Ishan said, a get give an instance of the Result class. > >>> > > > > All utility methods that you can use are: > >>> > > > > byte[] getValue(byte[] family, byte[] qualifier) > >>> > > > > byte[] value() > >>> > > > > byte[] getRow() > >>> > > > > int size() > >>> > > > > boolean isEmpty() > >>> > > > > KeyValue[] raw() # Like Ishan said, all data here is sorted > >>> > > > > List<KeyValue> list() > >>> > > > > > >>> > > > > > >>> > > > > > >>> > > > > > >>> > > > > On 02/08/2013 11:29 PM, Ishan Chhabra wrote: > >>> > > > > > >>> > > > >> Based on what I read in Lars' book, a get will return a > result a > >>> > > Result, > >>> > > > >> which is internally a KeyValue[]. This KeyValue[] is sorted > by the > >>> > key > >>> > > > and > >>> > > > >> you access this array using raw or list methods on the Result > >>> > object. > >>> > > > >> > >>> > > > >> > >>> > > > >> On Fri, Feb 8, 2013 at 5:40 PM, Varun Sharma < > [email protected] > >>> > > >>> > > > wrote: > >>> > > > >> > >>> > > > >> +user > >>> > > > >>> > >>> > > > >>> On Fri, Feb 8, 2013 at 5:38 PM, Varun Sharma < > >>> [email protected]> > >>> > > > >>> wrote: > >>> > > > >>> > >>> > > > >>> Hi, > >>> > > > >>>> > >>> > > > >>>> When I do a Get on a row with multiple column qualifiers. > Do we > >>> > sort > >>> > > > the > >>> > > > >>>> column qualifers and make use of the sorted order when we > get > >>> the > >>> > > > >>>> > >>> > > > >>> results ? > >>> > > > >>> > >>> > > > >>>> Thanks > >>> > > > >>>> Varun > >>> > > > >>>> > >>> > > > >>>> > >>> > > > >> > >>> > > > >> > >>> > > > > -- > >>> > > > > Marcos Ortiz Valmaseda, > >>> > > > > Product Manager && Data Scientist at UCI > >>> > > > > Blog: http://marcosluis2186.**posterous.com< > >>> > > > http://marcosluis2186.posterous.com> > >>> > > > > Twitter: @marcosluis2186 <http://twitter.com/**marcosluis2186< > >>> > > > http://twitter.com/marcosluis2186> > >>> > > > > > > >>> > > > > > >>> > > > > >>> > > > >>> > > >>> > >> > >> > > >
