[
https://issues.apache.org/jira/browse/HBASE-3529?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13032015#comment-13032015
]
Jason Rutherglen commented on HBASE-3529:
-----------------------------------------
I think the next round of benchmarking could involve showing that we need to
directly access the underlying block file in order to not lose performance when
running Lucene on HDFS. This is somewhat as per the comment on HDFS-347:
https://issues.apache.org/jira/browse/HDFS-347?focusedCommentId=13013719&page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel#comment-13013719
{quote}The next thing we wanted to look at was random I/O. There is a lot
more overhead on the datanode for this particular use case so this
could be a place where direct access could really excel{quote}
We can test using HDFS-941 vs. direct block file access using MMap (by
obtaining the local file path and the unix domain sockets). I think then we'll
show that for the Lucene case, we're on the right track by using direct file
access.
> 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
--
This message is automatically generated by JIRA.
For more information on JIRA, see: http://www.atlassian.com/software/jira
