RELEASE_0.82b.txt

This is a bigdata (R) snapshot release.  This release is capable of loading 1B
triples in under one hour on a 15 node cluster and has been used to load up to
13B triples on the same cluster.  JDK 1.6 is required.

See [1] for instructions on installing bigdata(R), [2] for the javadoc and [3]
and [4] for news, questions, and the latest developments.  For more information
about SYSTAP, LLC and bigdata, see [5].

Please note that we recommend checking out the code from SVN using the tag for
this release.  The code will build automatically under eclipse.  You can also
build the code using the ant script.  The cluster installer requires the use of
the ant script.  You can checkout this release from the following URL:

	https://bigdata.svn.sourceforge.net/svnroot/bigdata/tags/RELEASE_0.82b

This tag corresponds to revision 2604.

New features:

- Full transaction support in the SAIL.

- Installer for the Sesame workbench server.

- SPARQL query hints in the SAIL.

- Native execution of UNION queries. (And better overall coverage for native rule
  execution in general.)
  
- Significant performance gains in SPARQL query execution as measured against the
  LUBM and BSBM benchmarks.  Using a commodity server, the LUBM U50 queries run
  in ~6 seconds using a branching factor of 64 and the RW store and BSBM query 
  performance is ~ 2300 query mixes per hour (QMpH) for 100M triples with 4
  concurrent clients and the LIRS cache).

- A new "WORM" persistence store implementation supporting concurrent IO (DiskWORM). 
  The WORMStrategy is a binary compatible replacement for the DiskOnlyStrategy
  which the potential for concurrent IOs.  People interested in a preview may
  enable this implementation on either new or existing persistence stores by
  changing the com.bigdata.journal.BufferMode to DiskWORM.

- A new "RW" persistence store implementation with limited history retention
  supporting concurrent IO, secure checksummed data, and a storage model that
  may significantly reduce storage requirements in particular for skewed data.

The roadmap for the next release includes:

- Refactor of the dynamic sharding mechanism for higher performance;

- High availability for the journal;

- Query optimizations.

Our next milestone will include both high availability and a greatly simplified
deployment, configure, and administration process for the clustered database.
Later this year we will be introducing support for RDF spatial and analytic query
workloads.

For more information, please see the following links:

[1] http://bigdata.wiki.sourceforge.net/GettingStarted
[2] http://www.bigdata.com/bigdata/docs/api/
[3] http://sourceforge.net/projects/bigdata/
[4] http://www.bigdata.com/blog 
[5] http://www.systap.com/bigdata.htm

About bigdata: 

Bigdata® is a horizontally-scaled, general purpose storage and computing fabric
for ordered data (B+Trees), designed to operate on either a single server or a
cluster of commodity hardware. Bigdata® uses dynamically partitioned key-range
shards in order to remove any realistic scaling limits - in principle, bigdata®
may be deployed on 10s, 100s, or even thousands of machines and new capacity may
be added incrementally without requiring the full reload of all data. The bigdata®
RDF database supports RDFS and OWL Lite reasoning, high-level query (SPARQL),
and datum level provenance.