Katta is a scalable, failure tolerant, distributed, data storage for real time access.
Katta serves large, replicated, indices as shards to serve high loads and very large data sets. These indices can be of different type. Currently implementations are available for Lucene and Hadoop mapfiles.
* Makes serving large or high load indices easy
* Serves very large Lucene or Hadoop Mapfile indices as index shards on many servers
* Replicate shards on different servers for performance and fault-tolerance
* Supports pluggable network topologies
* Master fail-over
* Fast, lightweight, easy to integrate
* Plays well with Hadoop clusters
* Apache Version 2 License
Apache's Hadoop project aims to solve these problems by providing a framework for running large data processing applications on clusters of commodity hardware. Combined with Amazon EC2 for running the application, and Amazon S3 for storing the data, we can run large jobs very economically. This paper describes how to use Amazon Web Services and Hadoop to run an ad hoc analysis on a large collection of web access logs that otherwise would have cost a prohibitive amount in either time or money.
H. chih Yang, A. Dasdan, R. Hsiao, and D. Parker. SIGMOD '07: Proceedings of the 2007 ACM SIGMOD international conference on Management of data, page 1029--1040. New York, NY, USA, ACM, (2007)
H. chih Yang, A. Dasdan, R. Hsiao, and D. Parker. SIGMOD '07: Proceedings of the 2007 ACM SIGMOD international conference on Management of data, page 1029--1040. New York, NY, USA, ACM, (2007)