Riak is a straight key/value data store and all objects are stored on disk as binaries. It is content agnostic – meaning you can store any type of data as the value in Riak. To improve the usability and functionality of Riak, we offer multiple querying options including Riak Search, Secondary Indexing, and MapReduce. Riak Search is a full-text search that allows Riak developers to index the contents of stored values. While Riak Search offers much needed functionality, it had its flaws.
In Riak 2.0, Riak Search received a complete overhaul. Riak Search 2.0 leverages the Apache Solr full-text document indexing engine directly. Riak users now get the power of Solr, with the availability and scalability of Riak. This upgrade also supports the Solr client-queries API, which enables integration with existing software solutions.
Eric Redmond is one of the Basho engineers who works on Riak Search. At RICON, he presented “Riak Search 2.0,” which walks through what’s new with Riak Search and why you’d want to use it. He also provides some impressive demos that show off the power of Solr and Riak. His full talk is below.
For more information on Riak Search 2.0, check out these resources on Github.
Today I’m happy to announce the 3rd pre-release of Yokozuna. It’s light on new features but has some good performance improvements and added robustness. Here are the highlights:
Allow store/retrieval of schemas via HTTP.
Upgrade to Solr 4.1.0 and the latest Riak.
Improve write/index throughput by disabling Solr’s “realtime get” and switching from XML update to JSON.
Added robustness around AAE and default index creation.
Listen on ‘solr//select’ to more easily work with existing clients out of the box.
To see all changes read the full release notes. Like the last two releases, an AMI has been made, see the EC2 doc for more info.
New for this release is the addition of a source package. I hope this might encourage those who are scared off by the process of building from git to give Riak/Yokozuna a try. These four steps below will produce a ready-to-run node under ‘rel/riak’.
tar zxvf riak-yokozuna-0.3.0-src.tar.gz
Happy Holidays from all of us here at Basho. We’ve got some new code to help you ring in the new year. Ryan Zezeski and others have been hard at work on Yokozuna, the next generation of Riak Search that marries Riak with Apache Solr.
The latest pre-release, 0.2.0, was just tagged, and there’s plenty to be excited about for those of you who are interested in test-driving the code. In addition to various bug fixes, some of the new features include:
Active Anti Entropy Support – Automatic background processing that seeks out and rectifies divergences between data stored in Riak and indexes stored in Yokozuna.
Benchmark Scripts – A pre-built collection of benchmarking scripts for automating performance testing.
Sibling Support – When enabled, Yokozuna will now index all object versions. It will also handle index cleanup upon sibling resolution.
Commits in this release came from Ryan Zezeski, Eric Redmond, and Dan Reverri. Mark Steele also reported a few issues that were fixed in this release.
Remember that this is alpha software, and won’t be officially supported by Basho until a future release. That said, Ryan and the team are actively looking for beta testers with use cases that might be appropriate for Yokozuna. If you’re in the market for scalable, distributed full-text search, join the Riak Mailing List and start asking questions.
There’s a pre-built Yokozuna AWS AMI (ami-8b8d03e2) with the latest changes that’ll make it easy to take Yokozuna for a test drive.