DataStax Enterprise Analytic nodes are powered by Apache Hadoop running on top of Apache Cassandra. Both Hadoop and Cassandra come with their own sets of library dependencies. Additionally, Hadoop relies on running user-code, which may often want to load its own set of dependencies. As long as each module uses a distinct set of dependencies, there are no problems. However, when two modules running within the same JVM need to use different versions of the same library, a library conflict arises. In this blog post I shortly describe how DSE internally manages library dependencies, and our current approach to resolving library conflicts. I'll also uncover some little bits of internal DSE classloader architecture.
Cassandra File System (CFS) is a HDFS-compatible file system implemented on top of Cassandra.
In this blog post, we present some helpful hints on what to do when things go wrong.
DSE Search provides full text search feature for Cassandra. In principle, columns stored in the database can be indexed by Solr, which is plugged into Cassandra using the secondary index API.
DataStax Enterprise 2.1 introduces a new compaction strategy optimized for Cassandra File System keyspace, the core component behind DSE Hadoop integration. The new compaction strategy not only makes your Hadoop jobs run faster, but also significantly lowers storage space requirements for your data, by allowing for much faster physical file deletion. Read More...
The Cassandra File System (CFS) is a distributed filesystem that allows for easy integration of DataStax Enterprise platform with Hadoop.