[jira] [Commented] (HBASE-3529) Add search to HBase

["Jason Rutherglen (JIRA)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/HBASE-3529?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13042913#comment-13042913 ] 

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

SOLR-1431 is updated to trunk. I'm tempted to start trying to plug in
Solr. I think the way to do this is to use the HTable.coprocessorExec
method (for the distributed search), where the Solr shards are of the form
'shards=start:hexstartkey,end:hexendkey'. Then HBase will take care of the
rest from an RPC perspective. Eg, forwarding the request to the individual
HRegion's running the SolrCoprocessor.

I think we'll use a single Solr schema per region, though we can add a
special delimiter in the field name to indicate that the prefix is the
column family, then the column name. Something like 'headers:subject' may
work. The main caveat is that the fields marked stored in fact
will not be stored into Lucene (because they're in HBase).

> 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
>         Attachments: HBASE-3529.patch
>
>
> 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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