regarding your question on hbase support for high performance and consistency - i would say hbase is highly scalable and performant. how it does what it does can be understood by reading relevant chapters around architecture and design in the hbase book.
with regards to ranking, i see your problem. but if you split the problem into hbase specific solution and solr based solution, you can achieve the results probably. may be you do the ranking and store the rank in hbase and then use solr to get the results and then use hbase as a lookup to get the rank. or you can put the rank as part of the document schema and index the rank too for range queries and such. is my understanding of your scenario wrong? thanks On Wed, Feb 22, 2012 at 9:51 AM, Bing Li <lbl...@gmail.com> wrote: > Mr Gupta, > > Thanks so much for your reply! > > In my use cases, retrieving data by keyword is one of them. I think Solr > is a proper choice. > > However, Solr does not provide a complex enough support to rank. And, > frequent updating is also not suitable in Solr. So it is difficult to > retrieve data randomly based on the values other than keyword frequency in > text. In this case, I attempt to use HBase. > > But I don't know how HBase support high performance when it needs to keep > consistency in a large scale distributed system. > > Now both of them are used in my system. > > I will check out ElasticSearch. > > Best regards, > Bing > > > On Thu, Feb 23, 2012 at 1:35 AM, T Vinod Gupta <tvi...@readypulse.com>wrote: > >> Bing, >> Its a classic battle on whether to use solr or hbase or a combination of >> both. both systems are very different but there is some overlap in the >> utility. they also differ vastly when it compares to computation power, >> storage needs, etc. so in the end, it all boils down to your use case. you >> need to pick the technology that it best suited to your needs. >> im still not clear on your use case though. >> >> btw, if you haven't started using solr yet - then you might want to >> checkout ElasticSearch. I spent over a week researching between solr and ES >> and eventually chose ES due to its cool merits. >> >> thanks >> >> >> On Wed, Feb 22, 2012 at 9:31 AM, Ted Yu <yuzhih...@gmail.com> wrote: >> >>> There is no secondary index support in HBase at the moment. >>> >>> It's on our road map. >>> >>> FYI >>> >>> On Wed, Feb 22, 2012 at 9:28 AM, Bing Li <lbl...@gmail.com> wrote: >>> >>> > Jacques, >>> > >>> > Yes. But I still have questions about that. >>> > >>> > In my system, when users search with a keyword arbitrarily, the query >>> is >>> > forwarded to Solr. No any updating operations but appending new indexes >>> > exist in Solr managed data. >>> > >>> > When I need to retrieve data based on ranking values, HBase is used. >>> And, >>> > the ranking values need to be updated all the time. >>> > >>> > Is that correct? >>> > >>> > My question is that the performance must be low if keeping consistency >>> in a >>> > large scale distributed environment. How does HBase handle this issue? >>> > >>> > Thanks so much! >>> > >>> > Bing >>> > >>> > >>> > On Thu, Feb 23, 2012 at 1:17 AM, Jacques <whs...@gmail.com> wrote: >>> > >>> > > It is highly unlikely that you could replace Solr with HBase. >>> They're >>> > > really apples and oranges. >>> > > >>> > > >>> > > On Wed, Feb 22, 2012 at 1:09 AM, Bing Li <lbl...@gmail.com> wrote: >>> > > >>> > >> Dear all, >>> > >> >>> > >> I wonder how data in HBase is indexed? Now Solr is used in my system >>> > >> because data is managed in inverted index. Such an index is >>> suitable to >>> > >> retrieve unstructured and huge amount of data. How does HBase deal >>> with >>> > >> the >>> > >> issue? May I replaced Solr with HBase? >>> > >> >>> > >> Thanks so much! >>> > >> >>> > >> Best regards, >>> > >> Bing >>> > >> >>> > > >>> > > >>> > >>> >> >> >
