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Date: Fri, 25 Feb 2011 20:41:21 +0000 (UTC)
From: "ryan rawson (JIRA)" <jira@apache.org>
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Subject: [jira] Commented: (HBASE-3529) Add search to HBase
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    [ https://issues.apache.org/jira/browse/HBASE-3529?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12999546#comment-12999546 ] 

ryan rawson commented on HBASE-3529:
------------------------------------

it's going to be tricky, since with security some people may choose to run hdfs and hbase on different users. Futhermore most hadoop installs have multiple jbod-style disks, and places like /tmp won't have much room (my /tmp has < 2GB). If you can avoid local files as much as possible, I'd try to do that.

> 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

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