There are several options here. E.g.: 1) Given that you have "original key" of the record, you can fetch the stored record key from HBase and use it to create Put with updated (or new) cells.
Currently you'll need to use distributes scan for that, there's not analogue for Get operation yet (see https://github.com/sematext/HBaseWD/issues/1). Note: you need to first find out the real key of stored record by fetching data from HBase in case you use included in current lib RowKeyDistributorByOneBytePrefix. Alternatively, see next option: 2) You can create your own RowKeyDistributor implementation which will create "distributed key" based on original key value so that later when you have original key and want to update the record you can calculate distributed key without roundtrip to HBase. E.g. your RowKeyDistributor implementation you can calculate 1-byte hash of original key (https://github.com/sematext/HBaseWD/issues/2). In either way you don't need to delete record to update some cells of it or add new cells. Please let me know if you have more Qs! Alex Baranau ---- Sematext :: http://sematext.com/ :: Solr - Lucene - Nutch - Hadoop - HBase On Wed, May 18, 2011 at 1:19 AM, Weishung Chung <weish...@gmail.com> wrote: > I have another question. For overwriting, do I need to delete the existing > one before re-writing it? > > On Sat, May 14, 2011 at 10:17 AM, Weishung Chung <weish...@gmail.com> > wrote: > > > Yes, it's simple yet useful. I am integrating it. Thanks alot :) > > > > > > On Fri, May 13, 2011 at 3:12 PM, Alex Baranau <alex.barano...@gmail.com > >wrote: > > > >> Thanks for the interest! > >> > >> We are using it in production. It is simple and hence quite stable. > Though > >> some minor pieces are missing (like > >> https://github.com/sematext/HBaseWD/issues/1) this doesn't affect > >> stability > >> and/or major functionality. > >> > >> Alex Baranau > >> ---- > >> Sematext :: http://sematext.com/ :: Solr - Lucene - Nutch - Hadoop - > >> HBase > >> > >> On Fri, May 13, 2011 at 10:45 AM, Weishung Chung <weish...@gmail.com> > >> wrote: > >> > >> > What's the status on this package? Is it mature enough? > >> > I am using it in my project, tried out the write method yesterday and > >> > going > >> > to incorporate into read method tomorrow. > >> > > >> > On Wed, May 11, 2011 at 3:41 PM, Alex Baranau < > alex.barano...@gmail.com > >> > >wrote: > >> > > >> > > > The start/end rows may be written twice. > >> > > > >> > > Yeah, I know. I meant that size of startRow+stopRow data is > "bearable" > >> in > >> > > attribute value no matter how long are they (keys), since we already > >> OK > >> > > with > >> > > transferring them initially (i.e. we should be OK with transferring > 2x > >> > > times > >> > > more). > >> > > > >> > > So, what about the suggestion of sourceScan attribute value I > >> mentioned? > >> > If > >> > > you can tell why it isn't sufficient in your case, I'd have more > info > >> to > >> > > think about better suggestion ;) > >> > > > >> > > > It is Okay to keep all versions of your patch in the JIRA. > >> > > > Maybe the second should be named HBASE-3811-v2.patch< > >> > > > >> > > >> > https://issues.apache.org/jira/secure/attachment/12478694/HBASE-3811.patch > >> > > >? > >> > > > >> > > np. Can do that. Just thought that they (patches) can be sorted by > >> date > >> > to > >> > > find out the final one (aka "convention over naming-rules"). > >> > > > >> > > Alex. > >> > > > >> > > On Wed, May 11, 2011 at 11:13 PM, Ted Yu <yuzhih...@gmail.com> > wrote: > >> > > > >> > > > >> Though it might be ok, since we anyways "transfer" start/stop > >> rows > >> > > with > >> > > > Scan object. > >> > > > In write() method, we now have: > >> > > > Bytes.writeByteArray(out, this.startRow); > >> > > > Bytes.writeByteArray(out, this.stopRow); > >> > > > ... > >> > > > for (Map.Entry<String, byte[]> attr : > >> this.attributes.entrySet()) > >> > { > >> > > > WritableUtils.writeString(out, attr.getKey()); > >> > > > Bytes.writeByteArray(out, attr.getValue()); > >> > > > } > >> > > > The start/end rows may be written twice. > >> > > > > >> > > > Of course, you have full control over how to generate the unique > ID > >> for > >> > > > "sourceScan" attribute. > >> > > > > >> > > > It is Okay to keep all versions of your patch in the JIRA. Maybe > the > >> > > second > >> > > > should be named HBASE-3811-v2.patch< > >> > > > >> > > >> > https://issues.apache.org/jira/secure/attachment/12478694/HBASE-3811.patch > >> > > >? > >> > > > > >> > > > Thanks > >> > > > > >> > > > > >> > > > On Wed, May 11, 2011 at 1:01 PM, Alex Baranau < > >> > alex.barano...@gmail.com > >> > > >wrote: > >> > > > > >> > > >> > Can you remove the first version ? > >> > > >> Isn't it ok to keep it in JIRA issue? > >> > > >> > >> > > >> > >> > > >> > In HBaseWD, can you use reflection to detect whether Scan > >> supports > >> > > >> setAttribute() ? > >> > > >> > If it does, can you encode start row and end row as > "sourceScan" > >> > > >> attribute ? > >> > > >> > >> > > >> Yeah, smth like this is going to be implemented. Though I'd still > >> want > >> > > to > >> > > >> hear from the devs the story about Scan version. > >> > > >> > >> > > >> > >> > > >> > One consideration is that start row or end row may be quite > long. > >> > > >> > >> > > >> Yeah, that is was my though too at first. Though it might be ok, > >> since > >> > > we > >> > > >> anyways "transfer" start/stop rows with Scan object. > >> > > >> > >> > > >> > What do you think ? > >> > > >> > >> > > >> I'd love to hear from you is this variant I mentioned is what we > >> are > >> > > >> looking at here: > >> > > >> > >> > > >> > >> > > >> > From what I understand, you want to distinguish scans fired by > >> the > >> > > same > >> > > >> distributed scan. > >> > > >> > I.e. group scans which were fired by single distributed scan. > If > >> > > that's > >> > > >> what you want, distributed > >> > > >> > scan can generate unique ID and set, say "sourceScan" attribute > >> to > >> > its > >> > > >> value. This way we'll > >> > > >> > have <# of distinct "sourceScan" attribute values> = <number of > >> > > >> distributed scans invoked by > >> > > >> > client side> and two scans on server side will have the same > >> > > >> "sourceScan" attribute iff they > >> > > >> > "belong" to same distributed scan. > >> > > >> > >> > > >> > >> > > >> Alex Baranau > >> > > >> ---- > >> > > >> Sematext :: http://sematext.com/ :: Solr - Lucene - Nutch - > Hadoop > >> - > >> > > >> HBase > >> > > >> > >> > > >> On Wed, May 11, 2011 at 5:15 PM, Ted Yu <yuzhih...@gmail.com> > >> wrote: > >> > > >> > >> > > >>> Alex: > >> > > >>> Your second patch looks good. > >> > > >>> Can you remove the first version ? > >> > > >>> > >> > > >>> In HBaseWD, can you use reflection to detect whether Scan > supports > >> > > >>> setAttribute() ? > >> > > >>> If it does, can you encode start row and end row as "sourceScan" > >> > > >>> attribute ? > >> > > >>> > >> > > >>> One consideration is that start row or end row may be quite > long. > >> > > >>> Ideally we should store hash code of source Scan object as > >> > "sourceScan" > >> > > >>> attribute. But Scan doesn't implement hashCode(). We can add it, > >> that > >> > > would > >> > > >>> require running all Scan related tests. > >> > > >>> > >> > > >>> What do you think ? > >> > > >>> > >> > > >>> Thanks > >> > > >>> > >> > > >>> > >> > > >>> On Tue, May 10, 2011 at 5:46 AM, Alex Baranau < > >> > > alex.barano...@gmail.com>wrote: > >> > > >>> > >> > > >>>> Sorry for the delay in response (public holidays here). > >> > > >>>> > >> > > >>>> This depends on what info you are looking for on server side. > >> > > >>>> > >> > > >>>> From what I understand, you want to distinguish scans fired by > >> the > >> > > same > >> > > >>>> distributed scan. I.e. group scans which were fired by single > >> > > distributed > >> > > >>>> scan. If that's what you want, distributed scan can generate > >> unique > >> > ID > >> > > and > >> > > >>>> set, say "sourceScan" attribute to its value. This way we'll > have > >> <# > >> > > of > >> > > >>>> distinct "sourceScan" attribute values> = <number of > distributed > >> > scans > >> > > >>>> invoked by client side> and two scans on server side will have > >> the > >> > > same > >> > > >>>> "sourceScan" attribute iff they "belong" to same distributed > >> scan. > >> > > >>>> > >> > > >>>> Is this what are you looking for? > >> > > >>>> > >> > > >>>> Alex Baranau > >> > > >>>> > >> > > >>>> P.S. attached patch for HBASE-3811< > >> > > https://issues.apache.org/jira/browse/HBASE-3811> > >> > > >>>> . > >> > > >>>> P.S-2. should this conversation be moved to dev list? > >> > > >>>> > >> > > >>>> ---- > >> > > >>>> Sematext :: http://sematext.com/ :: Solr - Lucene - Nutch - > >> Hadoop > >> > - > >> > > >>>> HBase > >> > > >>>> > >> > > >>>> On Fri, May 6, 2011 at 12:06 AM, Ted Yu <yuzhih...@gmail.com> > >> > wrote: > >> > > >>>> > >> > > >>>>> Alex: > >> > > >>>>> What type of identification should we put in the map of the > Scan > >> > > object > >> > > >>>>> ? > >> > > >>>>> I am thinking of using the Id of RowKeyDistributor. But the > user > >> > can > >> > > >>>>> use same distributor on multiple scans. > >> > > >>>>> > >> > > >>>>> Please share your thought. > >> > > >>>>> > >> > > >>>>> > >> > > >>>>> On Thu, Apr 21, 2011 at 8:32 AM, Alex Baranau < > >> > > >>>>> alex.barano...@gmail.com> wrote: > >> > > >>>>> > >> > > >>>>>> https://issues.apache.org/jira/browse/HBASE-3811 > >> > > >>>>>> > >> > > >>>>>> Alex Baranau > >> > > >>>>>> ---- > >> > > >>>>>> Sematext :: http://sematext.com/ :: Solr - Lucene - Nutch - > >> > Hadoop > >> > > - > >> > > >>>>>> HBase > >> > > >>>>>> > >> > > >>>>>> On Thu, Apr 21, 2011 at 5:57 PM, Ted Yu <yuzhih...@gmail.com > > > >> > > wrote: > >> > > >>>>>> > >> > > >>>>>> > My plan was to make regions that have active scanners more > >> > stable > >> > > - > >> > > >>>>>> trying > >> > > >>>>>> > not to move them when balancing. > >> > > >>>>>> > I prefer second approach - adding custom attribute(s) to > Scan > >> so > >> > > >>>>>> that the > >> > > >>>>>> > Scans created by the method below can be 'grouped'. > >> > > >>>>>> > > >> > > >>>>>> > If you can file a JIRA, that would be great. > >> > > >>>>>> > > >> > > >>>>>> > On Thu, Apr 21, 2011 at 7:23 AM, Alex Baranau < > >> > > >>>>>> alex.barano...@gmail.com > >> > > >>>>>> > >wrote: > >> > > >>>>>> > > >> > > >>>>>> > > Aha, so you want to "count" it as single scan (or just > >> > > >>>>>> differently) when > >> > > >>>>>> > > determining the load? > >> > > >>>>>> > > > >> > > >>>>>> > > The current code looks like this: > >> > > >>>>>> > > > >> > > >>>>>> > > class DistributedScanner: > >> > > >>>>>> > > public static DistributedScanner create(HTable hTable, > >> Scan > >> > > >>>>>> original, > >> > > >>>>>> > > AbstractRowKeyDistributor keyDistributor) throws > >> IOException { > >> > > >>>>>> > > byte[][] startKeys = > >> > > >>>>>> > > > >> keyDistributor.getAllDistributedKeys(original.getStartRow()); > >> > > >>>>>> > > byte[][] stopKeys = > >> > > >>>>>> > > > >> keyDistributor.getAllDistributedKeys(original.getStopRow()); > >> > > >>>>>> > > Scan[] scans = new Scan[startKeys.length]; > >> > > >>>>>> > > for (byte i = 0; i < startKeys.length; i++) { > >> > > >>>>>> > > scans[i] = new Scan(original); > >> > > >>>>>> > > scans[i].setStartRow(startKeys[i]); > >> > > >>>>>> > > scans[i].setStopRow(stopKeys[i]); > >> > > >>>>>> > > } > >> > > >>>>>> > > > >> > > >>>>>> > > ResultScanner[] rss = new > >> ResultScanner[startKeys.length]; > >> > > >>>>>> > > for (byte i = 0; i < scans.length; i++) { > >> > > >>>>>> > > rss[i] = hTable.getScanner(scans[i]); > >> > > >>>>>> > > } > >> > > >>>>>> > > > >> > > >>>>>> > > return new DistributedScanner(rss); > >> > > >>>>>> > > } > >> > > >>>>>> > > > >> > > >>>>>> > > This is client code. To make these scans "identifiable" > we > >> > need > >> > > to > >> > > >>>>>> either > >> > > >>>>>> > > use some different (derived from Scan) class or add some > >> > > attribute > >> > > >>>>>> to > >> > > >>>>>> > them. > >> > > >>>>>> > > There's no API for doing the latter. But we can do the > >> former, > >> > > but > >> > > >>>>>> I > >> > > >>>>>> > don't > >> > > >>>>>> > > really like the idea of creating extra class (with no > extra > >> > > >>>>>> > functionality) > >> > > >>>>>> > > just to distinguish it from the base one. > >> > > >>>>>> > > > >> > > >>>>>> > > If you can share why/how do you want to treat them > >> differently > >> > > on > >> > > >>>>>> server > >> > > >>>>>> > > side, that would be helpful. > >> > > >>>>>> > > > >> > > >>>>>> > > Alex Baranau > >> > > >>>>>> > > ---- > >> > > >>>>>> > > Sematext :: http://sematext.com/ :: Solr - Lucene - > Nutch > >> - > >> > > >>>>>> Hadoop - > >> > > >>>>>> > HBase > >> > > >>>>>> > > > >> > > >>>>>> > > On Thu, Apr 21, 2011 at 4:58 PM, Ted Yu < > >> yuzhih...@gmail.com> > >> > > >>>>>> wrote: > >> > > >>>>>> > > > >> > > >>>>>> > > > My request would be to make the distributed scan > >> > identifiable > >> > > >>>>>> from > >> > > >>>>>> > server > >> > > >>>>>> > > > side. > >> > > >>>>>> > > > :-) > >> > > >>>>>> > > > > >> > > >>>>>> > > > On Thu, Apr 21, 2011 at 5:45 AM, Alex Baranau < > >> > > >>>>>> > alex.barano...@gmail.com > >> > > >>>>>> > > > >wrote: > >> > > >>>>>> > > > > >> > > >>>>>> > > > > > Basically bucketsCount may not equal number of > >> regions > >> > for > >> > > >>>>>> the > >> > > >>>>>> > > > underlying > >> > > >>>>>> > > > > > table. > >> > > >>>>>> > > > > > >> > > >>>>>> > > > > True: e.g. when there's only one region that holds > data > >> > for > >> > > >>>>>> the whole > >> > > >>>>>> > > > table > >> > > >>>>>> > > > > (not many records in table yet), distributed scan > will > >> > fire > >> > > N > >> > > >>>>>> scans > >> > > >>>>>> > > > against > >> > > >>>>>> > > > > the same region. > >> > > >>>>>> > > > > On the other hand, in case there are huge number of > >> > regions > >> > > >>>>>> for > >> > > >>>>>> > single > >> > > >>>>>> > > > > table, each scan can span over multiple regions. > >> > > >>>>>> > > > > > >> > > >>>>>> > > > > > I need to deal with normal scan and "distributed > >> scan" > >> > at > >> > > >>>>>> server > >> > > >>>>>> > > side. > >> > > >>>>>> > > > > > >> > > >>>>>> > > > > With current implementation "distributed" scan won't > be > >> > > >>>>>> recognized as > >> > > >>>>>> > > > > something special on the server side. It will be an > >> > ordinary > >> > > >>>>>> scan. > >> > > >>>>>> > > Though > >> > > >>>>>> > > > > the number of scan will increase, given that the > >> typical > >> > > >>>>>> situation is > >> > > >>>>>> > > > "many > >> > > >>>>>> > > > > regions for single table", the scans of the same > >> > > "distributed > >> > > >>>>>> scan" > >> > > >>>>>> > are > >> > > >>>>>> > > > > likely not to hit the same region. > >> > > >>>>>> > > > > > >> > > >>>>>> > > > > Not sure if I answered your questions here. Feel free > >> to > >> > ask > >> > > >>>>>> more ;) > >> > > >>>>>> > > > > > >> > > >>>>>> > > > > Alex Baranau > >> > > >>>>>> > > > > ---- > >> > > >>>>>> > > > > Sematext :: http://sematext.com/ :: Solr - Lucene - > >> Nutch > >> > - > >> > > >>>>>> Hadoop - > >> > > >>>>>> > > > HBase > >> > > >>>>>> > > > > > >> > > >>>>>> > > > > On Wed, Apr 20, 2011 at 2:10 PM, Ted Yu < > >> > > yuzhih...@gmail.com> > >> > > >>>>>> wrote: > >> > > >>>>>> > > > > > >> > > >>>>>> > > > > > Alex: > >> > > >>>>>> > > > > > If you read this, you would know why I asked: > >> > > >>>>>> > > > > > https://issues.apache.org/jira/browse/HBASE-3679 > >> > > >>>>>> > > > > > > >> > > >>>>>> > > > > > I need to deal with normal scan and "distributed > >> scan" > >> > at > >> > > >>>>>> server > >> > > >>>>>> > > side. > >> > > >>>>>> > > > > > Basically bucketsCount may not equal number of > >> regions > >> > for > >> > > >>>>>> the > >> > > >>>>>> > > > underlying > >> > > >>>>>> > > > > > table. > >> > > >>>>>> > > > > > > >> > > >>>>>> > > > > > Cheers > >> > > >>>>>> > > > > > > >> > > >>>>>> > > > > > On Tue, Apr 19, 2011 at 11:11 PM, Alex Baranau < > >> > > >>>>>> > > > alex.barano...@gmail.com > >> > > >>>>>> > > > > > >wrote: > >> > > >>>>>> > > > > > > >> > > >>>>>> > > > > > > Hi Ted, > >> > > >>>>>> > > > > > > > >> > > >>>>>> > > > > > > We currently use this tool in the scenario where > >> data > >> > is > >> > > >>>>>> consumed > >> > > >>>>>> > > by > >> > > >>>>>> > > > > > > MapReduce jobs, so we haven't tested the > >> performance > >> > of > >> > > >>>>>> pure > >> > > >>>>>> > > > > "distributed > >> > > >>>>>> > > > > > > scan" (i.e. N scans instead of 1) a lot. I expect > >> it > >> > to > >> > > be > >> > > >>>>>> close > >> > > >>>>>> > to > >> > > >>>>>> > > > > > simple > >> > > >>>>>> > > > > > > scan performance, or may be sometimes even faster > >> > > >>>>>> depending on > >> > > >>>>>> > your > >> > > >>>>>> > > > > data > >> > > >>>>>> > > > > > > access patterns. E.g. in case you write > timeseries > >> > data > >> > > >>>>>> > > (sequential) > >> > > >>>>>> > > > > > which > >> > > >>>>>> > > > > > > is written into the single region at a time, then > >> e.g. > >> > > if > >> > > >>>>>> you > >> > > >>>>>> > > access > >> > > >>>>>> > > > > > delta > >> > > >>>>>> > > > > > > for further processing/analysis (esp. if from not > >> > single > >> > > >>>>>> client) > >> > > >>>>>> > > > these > >> > > >>>>>> > > > > > > scans > >> > > >>>>>> > > > > > > are likely to hit the same region or couple of > >> regions > >> > > at > >> > > >>>>>> a time, > >> > > >>>>>> > > > which > >> > > >>>>>> > > > > > may > >> > > >>>>>> > > > > > > perform worse comparing to many scans hitting > data > >> > that > >> > > is > >> > > >>>>>> much > >> > > >>>>>> > > > better > >> > > >>>>>> > > > > > > spread over region servers. > >> > > >>>>>> > > > > > > > >> > > >>>>>> > > > > > > As for map-reduce job the approach should not > >> affect > >> > > >>>>>> reading > >> > > >>>>>> > > > > performance > >> > > >>>>>> > > > > > at > >> > > >>>>>> > > > > > > all: it's just that there are bucketsCount times > >> more > >> > > >>>>>> splits and > >> > > >>>>>> > > > hence > >> > > >>>>>> > > > > > > bucketsCount times more Map tasks. In many cases > >> this > >> > > even > >> > > >>>>>> > improves > >> > > >>>>>> > > > > > overall > >> > > >>>>>> > > > > > > performance of the MR job since work is better > >> > > distributed > >> > > >>>>>> over > >> > > >>>>>> > > > cluster > >> > > >>>>>> > > > > > > (esp. in situation when the aim is to constantly > >> > process > >> > > >>>>>> the > >> > > >>>>>> > coming > >> > > >>>>>> > > > > delta > >> > > >>>>>> > > > > > > which usually resides in one or just couple of > >> regions > >> > > >>>>>> depending > >> > > >>>>>> > on > >> > > >>>>>> > > > > > > processing frequency). > >> > > >>>>>> > > > > > > > >> > > >>>>>> > > > > > > If you can share details on your case, that will > >> help > >> > to > >> > > >>>>>> > understand > >> > > >>>>>> > > > > what > >> > > >>>>>> > > > > > > effect(s) to expect from using this approach. > >> > > >>>>>> > > > > > > > >> > > >>>>>> > > > > > > Alex Baranau > >> > > >>>>>> > > > > > > ---- > >> > > >>>>>> > > > > > > Sematext :: http://sematext.com/ :: Solr - > Lucene > >> - > >> > > Nutch > >> > > >>>>>> - > >> > > >>>>>> > Hadoop > >> > > >>>>>> > > - > >> > > >>>>>> > > > > > HBase > >> > > >>>>>> > > > > > > > >> > > >>>>>> > > > > > > On Wed, Apr 20, 2011 at 8:17 AM, Ted Yu < > >> > > >>>>>> yuzhih...@gmail.com> > >> > > >>>>>> > > wrote: > >> > > >>>>>> > > > > > > > >> > > >>>>>> > > > > > > > Interesting project, Alex. > >> > > >>>>>> > > > > > > > Since there're bucketsCount scanners compared > to > >> one > >> > > >>>>>> scanner > >> > > >>>>>> > > > > > originally, > >> > > >>>>>> > > > > > > > have you performed load testing to see the > impact > >> ? > >> > > >>>>>> > > > > > > > > >> > > >>>>>> > > > > > > > Thanks > >> > > >>>>>> > > > > > > > > >> > > >>>>>> > > > > > > > On Tue, Apr 19, 2011 at 10:25 AM, Alex Baranau > < > >> > > >>>>>> > > > > > alex.barano...@gmail.com > >> > > >>>>>> > > > > > > > >wrote: > >> > > >>>>>> > > > > > > > > >> > > >>>>>> > > > > > > > > Hello guys, > >> > > >>>>>> > > > > > > > > > >> > > >>>>>> > > > > > > > > I'd like to introduce a new small java > >> project/lib > >> > > >>>>>> around > >> > > >>>>>> > > HBase: > >> > > >>>>>> > > > > > > HBaseWD. > >> > > >>>>>> > > > > > > > > It > >> > > >>>>>> > > > > > > > > is aimed to help with distribution of the > load > >> > > (across > >> > > >>>>>> > > > > regionservers) > >> > > >>>>>> > > > > > > > when > >> > > >>>>>> > > > > > > > > writing sequential (becasue of the row key > >> nature) > >> > > >>>>>> records. > >> > > >>>>>> > It > >> > > >>>>>> > > > > > > implements > >> > > >>>>>> > > > > > > > > the solution which was discussed several > times > >> on > >> > > this > >> > > >>>>>> > mailing > >> > > >>>>>> > > > list > >> > > >>>>>> > > > > > > (e.g. > >> > > >>>>>> > > > > > > > > here: http://search-hadoop.com/m/gNRA82No5Wk > ). > >> > > >>>>>> > > > > > > > > > >> > > >>>>>> > > > > > > > > Please find the sources at > >> > > >>>>>> > > > > > https://github.com/sematext/HBaseWD(there's > >> > > >>>>>> > > > > > > > > also > >> > > >>>>>> > > > > > > > > a jar of current version for convenience). It > >> is > >> > > very > >> > > >>>>>> easy to > >> > > >>>>>> > > > make > >> > > >>>>>> > > > > > use > >> > > >>>>>> > > > > > > of > >> > > >>>>>> > > > > > > > > it: e.g. I added it to one existing project > >> with > >> > 1+2 > >> > > >>>>>> lines of > >> > > >>>>>> > > > code > >> > > >>>>>> > > > > > (one > >> > > >>>>>> > > > > > > > > where I write to HBase and 2 for configuring > >> > > MapReduce > >> > > >>>>>> job). > >> > > >>>>>> > > > > > > > > > >> > > >>>>>> > > > > > > > > Any feedback is highly appreciated! > >> > > >>>>>> > > > > > > > > > >> > > >>>>>> > > > > > > > > Please find below the short intro to the lib > >> [1]. > >> > > >>>>>> > > > > > > > > > >> > > >>>>>> > > > > > > > > Alex Baranau > >> > > >>>>>> > > > > > > > > ---- > >> > > >>>>>> > > > > > > > > Sematext :: http://sematext.com/ :: Solr - > >> Lucene > >> > - > >> > > >>>>>> Nutch - > >> > > >>>>>> > > > Hadoop > >> > > >>>>>> > > > > - > >> > > >>>>>> > > > > > > > HBase > >> > > >>>>>> > > > > > > > > > >> > > >>>>>> > > > > > > > > [1] > >> > > >>>>>> > > > > > > > > > >> > > >>>>>> > > > > > > > > Description: > >> > > >>>>>> > > > > > > > > ------------ > >> > > >>>>>> > > > > > > > > HBaseWD stands for Distributing (sequential) > >> > Writes. > >> > > >>>>>> It was > >> > > >>>>>> > > > > inspired > >> > > >>>>>> > > > > > by > >> > > >>>>>> > > > > > > > > discussions on HBase mailing lists around the > >> > > problem > >> > > >>>>>> of > >> > > >>>>>> > > choosing > >> > > >>>>>> > > > > > > > between: > >> > > >>>>>> > > > > > > > > * writing records with sequential row keys > >> (e.g. > >> > > >>>>>> time-series > >> > > >>>>>> > > data > >> > > >>>>>> > > > > > with > >> > > >>>>>> > > > > > > > row > >> > > >>>>>> > > > > > > > > key > >> > > >>>>>> > > > > > > > > built based on ts) > >> > > >>>>>> > > > > > > > > * using random unique IDs for records > >> > > >>>>>> > > > > > > > > > >> > > >>>>>> > > > > > > > > First approach makes possible to perform fast > >> > range > >> > > >>>>>> scans > >> > > >>>>>> > with > >> > > >>>>>> > > > help > >> > > >>>>>> > > > > > of > >> > > >>>>>> > > > > > > > > setting > >> > > >>>>>> > > > > > > > > start/stop keys on Scanner, but creates > single > >> > > region > >> > > >>>>>> server > >> > > >>>>>> > > > > > > hot-spotting > >> > > >>>>>> > > > > > > > > problem upon writing data (as row keys go in > >> > > sequence > >> > > >>>>>> all > >> > > >>>>>> > > records > >> > > >>>>>> > > > > end > >> > > >>>>>> > > > > > > up > >> > > >>>>>> > > > > > > > > written into a single region at a time). > >> > > >>>>>> > > > > > > > > > >> > > >>>>>> > > > > > > > > Second approach aims for fastest writing > >> > performance > >> > > >>>>>> by > >> > > >>>>>> > > > > distributing > >> > > >>>>>> > > > > > > new > >> > > >>>>>> > > > > > > > > records over random regions but makes not > >> possible > >> > > >>>>>> doing fast > >> > > >>>>>> > > > range > >> > > >>>>>> > > > > > > scans > >> > > >>>>>> > > > > > > > > against written data. > >> > > >>>>>> > > > > > > > > > >> > > >>>>>> > > > > > > > > The suggested approach stays in the middle of > >> the > >> > > two > >> > > >>>>>> above > >> > > >>>>>> > and > >> > > >>>>>> > > > > > proved > >> > > >>>>>> > > > > > > to > >> > > >>>>>> > > > > > > > > perform well by distributing records over the > >> > > cluster > >> > > >>>>>> during > >> > > >>>>>> > > > > writing > >> > > >>>>>> > > > > > > data > >> > > >>>>>> > > > > > > > > while allowing range scans over it. HBaseWD > >> > provides > >> > > >>>>>> very > >> > > >>>>>> > > simple > >> > > >>>>>> > > > > API > >> > > >>>>>> > > > > > to > >> > > >>>>>> > > > > > > > > work with which makes it perfect to use with > >> > > existing > >> > > >>>>>> code. > >> > > >>>>>> > > > > > > > > > >> > > >>>>>> > > > > > > > > Please refer to unit-tests for lib usage info > >> as > >> > > they > >> > > >>>>>> aimed > >> > > >>>>>> > to > >> > > >>>>>> > > > act > >> > > >>>>>> > > > > as > >> > > >>>>>> > > > > > > > > example. > >> > > >>>>>> > > > > > > > > > >> > > >>>>>> > > > > > > > > Brief Usage Info (Examples): > >> > > >>>>>> > > > > > > > > ---------------------------- > >> > > >>>>>> > > > > > > > > > >> > > >>>>>> > > > > > > > > Distributing records with sequential keys > which > >> > are > >> > > >>>>>> being > >> > > >>>>>> > > written > >> > > >>>>>> > > > > in > >> > > >>>>>> > > > > > up > >> > > >>>>>> > > > > > > > to > >> > > >>>>>> > > > > > > > > Byte.MAX_VALUE buckets: > >> > > >>>>>> > > > > > > > > > >> > > >>>>>> > > > > > > > > byte bucketsCount = (byte) 32; // > >> distributing > >> > > into > >> > > >>>>>> 32 > >> > > >>>>>> > > buckets > >> > > >>>>>> > > > > > > > > RowKeyDistributor keyDistributor = > >> > > >>>>>> > > > > > > > > new > >> > > >>>>>> > > > > > > > > > RowKeyDistributorByOneBytePrefix(bucketsCount); > >> > > >>>>>> > > > > > > > > for (int i = 0; i < 100; i++) { > >> > > >>>>>> > > > > > > > > Put put = new > >> > > >>>>>> > > > > > Put(keyDistributor.getDistributedKey(originalKey)); > >> > > >>>>>> > > > > > > > > ... // add values > >> > > >>>>>> > > > > > > > > hTable.put(put); > >> > > >>>>>> > > > > > > > > } > >> > > >>>>>> > > > > > > > > > >> > > >>>>>> > > > > > > > > > >> > > >>>>>> > > > > > > > > Performing a range scan over written data > >> > > (internally > >> > > >>>>>> > > > > <bucketsCount> > >> > > >>>>>> > > > > > > > > scanners > >> > > >>>>>> > > > > > > > > executed): > >> > > >>>>>> > > > > > > > > > >> > > >>>>>> > > > > > > > > Scan scan = new Scan(startKey, stopKey); > >> > > >>>>>> > > > > > > > > ResultScanner rs = > >> > > >>>>>> DistributedScanner.create(hTable, scan, > >> > > >>>>>> > > > > > > > > keyDistributor); > >> > > >>>>>> > > > > > > > > for (Result current : rs) { > >> > > >>>>>> > > > > > > > > ... > >> > > >>>>>> > > > > > > > > } > >> > > >>>>>> > > > > > > > > > >> > > >>>>>> > > > > > > > > Performing mapreduce job over written data > >> chunk > >> > > >>>>>> specified by > >> > > >>>>>> > > > Scan: > >> > > >>>>>> > > > > > > > > > >> > > >>>>>> > > > > > > > > Configuration conf = > >> > HBaseConfiguration.create(); > >> > > >>>>>> > > > > > > > > Job job = new Job(conf, > "testMapreduceJob"); > >> > > >>>>>> > > > > > > > > > >> > > >>>>>> > > > > > > > > Scan scan = new Scan(startKey, stopKey); > >> > > >>>>>> > > > > > > > > > >> > > >>>>>> > > > > > > > > > >> TableMapReduceUtil.initTableMapperJob("table", > >> > > >>>>>> scan, > >> > > >>>>>> > > > > > > > > RowCounterMapper.class, > >> > > >>>>>> ImmutableBytesWritable.class, > >> > > >>>>>> > > > > > > Result.class, > >> > > >>>>>> > > > > > > > > job); > >> > > >>>>>> > > > > > > > > > >> > > >>>>>> > > > > > > > > // Substituting standard TableInputFormat > >> which > >> > > was > >> > > >>>>>> set in > >> > > >>>>>> > > > > > > > > // > >> TableMapReduceUtil.initTableMapperJob(...) > >> > > >>>>>> > > > > > > > > > >> > > job.setInputFormatClass(WdTableInputFormat.class); > >> > > >>>>>> > > > > > > > > > >> keyDistributor.addInfo(job.getConfiguration()); > >> > > >>>>>> > > > > > > > > > >> > > >>>>>> > > > > > > > > > >> > > >>>>>> > > > > > > > > Extending Row Keys Distributing Patterns: > >> > > >>>>>> > > > > > > > > ----------------------------------------- > >> > > >>>>>> > > > > > > > > > >> > > >>>>>> > > > > > > > > HBaseWD is designed to be flexible and to > >> support > >> > > >>>>>> custom row > >> > > >>>>>> > > key > >> > > >>>>>> > > > > > > > > distribution > >> > > >>>>>> > > > > > > > > approaches. To define custom row key > >> distributing > >> > > >>>>>> logic just > >> > > >>>>>> > > > > > implement > >> > > >>>>>> > > > > > > > > AbstractRowKeyDistributor abstract class > which > >> is > >> > > >>>>>> really very > >> > > >>>>>> > > > > simple: > >> > > >>>>>> > > > > > > > > > >> > > >>>>>> > > > > > > > > public abstract class > >> AbstractRowKeyDistributor > >> > > >>>>>> implements > >> > > >>>>>> > > > > > > > > Parametrizable { > >> > > >>>>>> > > > > > > > > public abstract byte[] > >> > getDistributedKey(byte[] > >> > > >>>>>> > > > originalKey); > >> > > >>>>>> > > > > > > > > public abstract byte[] > >> getOriginalKey(byte[] > >> > > >>>>>> > adjustedKey); > >> > > >>>>>> > > > > > > > > public abstract byte[][] > >> > > >>>>>> getAllDistributedKeys(byte[] > >> > > >>>>>> > > > > > > originalKey); > >> > > >>>>>> > > > > > > > > ... // some utility methods > >> > > >>>>>> > > > > > > > > } > >> > > >>>>>> > > > > > > > > > >> > > >>>>>> > > > > > > > > >> > > >>>>>> > > > > > > > >> > > >>>>>> > > > > > > >> > > >>>>>> > > > > > >> > > >>>>>> > > > > >> > > >>>>>> > > > >> > > >>>>>> > > >> > > >>>>>> > >> > > >>>>> > >> > > >>>>> > >> > > >>>> > >> > > >>> > >> > > >> > >> > > > > >> > > > >> > > >> > > > > >
