Mailing-List: contact issues-help@hbase.apache.org; run by ezmlm
Precedence: bulk
Date: Tue, 1 Mar 2011 04:21:37 +0000 (UTC)
From: "Jason Rutherglen (JIRA)" <jira@apache.org>
To: issues@hbase.apache.org
Message-ID: 
 <1129656036.3904.1298953297315.JavaMail.tomcat@hel.zones.apache.org>
In-Reply-To: 
 <531563484.15184.1297703757561.JavaMail.tomcat@hel.zones.apache.org>
Subject: [jira] Commented: (HBASE-3529) Add search to HBase
MIME-Version: 1.0
Content-Type: text/plain; charset=utf-8
Content-Transfer-Encoding: 7bit


    [ https://issues.apache.org/jira/browse/HBASE-3529?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13000697#comment-13000697 ] 

Jason Rutherglen commented on HBASE-3529:
-----------------------------------------

Sorry, I thought through the file access a little more.  I think we can use the block local reader as is, because Lucene reads the postings sequentially, we don't really need random file access (eg, the offset issue more or less goes away), we simply need to allow seek'ing forward, and most postings will live inside of a single (64 - 128MB block).  The issue with this system is we may need to maintain an FSInputStream per thread per file because we probably don't want to open a new FSInputStream per query given the overhead or creating and destroying them?  Will this cause issues with the max file descriptors?

> Add search to HBase
> -------------------
>
>                 Key: HBASE-3529
>                 URL: https://issues.apache.org/jira/browse/HBASE-3529
>             Project: HBase
>          Issue Type: Improvement
>    Affects Versions: 0.90.0
>            Reporter: Jason Rutherglen
>
> Using the Apache Lucene library we can add freetext search to HBase.  The advantages of this are:
> * HBase is highly scalable and distributed
> * HBase is realtime
> * Lucene is a fast inverted index and will soon be realtime (see LUCENE-2312)
> * Lucene offers many types of queries not currently available in HBase (eg, AND, OR, NOT, phrase, etc)
> * It's easier to build scalable realtime systems on top of already architecturally sound, scalable realtime data system, eg, HBase.
> * Scaling realtime search will be as simple as scaling HBase.
> Phase 1 - Indexing:
> * Integrate Lucene into HBase such that an index mirrors a given region.  This means cascading add, update, and deletes between a Lucene index and an HBase region (and vice versa).
> * Define meta-data to mark a region as indexed, and use a Solr schema to allow the user to define the fields and analyzers.
> * Integrate with the HLog to ensure that index recovery can occur properly (eg, on region server failure)
> * Mirror region splits with indexes (use Lucene's IndexSplitter?)
> * When a region is written to HDFS, also write the corresponding Lucene index to HDFS.
> * A row key will be the ID of a given Lucene document.  The Lucene docstore will explicitly not be used because the document/row data is stored in HBase.  We will need to solve what the best data structure for efficiently mapping a docid -> row key is.  It could be a docstore, field cache, column stride fields, or some other mechanism.
> * Write unit tests for the above
> Phase 2 - Queries:
> * Enable distributed Lucene queries
> * Regions that have Lucene indexes are inherently available and may be searched on, meaning there's no need for a separate search related system in Zookeeper.
> * Integrate search with HBase's RPC mechanism

-- 
This message is automatically generated by JIRA.
-
For more information on JIRA, see: http://www.atlassian.com/software/jira