Database Reference
In-Depth Information
While installing Hadoop with traditional methods might be a multiday ordeal, Ambari can
accomplish this in a few hours with relative ease. Ambari graduated from Incubator status to
Top Level Project late in 2013 and should now be ready for production use.
Tutorial Links
There is a
silent video
that takes you through a cluster build with Ambari.
Here's a great
slideshow tutorial
.
Example Code
Ambari is a GUI-based tool, so there's no way we can present a code example.
HCatalog
License
Apache License, Version 2.0
Activity
High
Purpose
Data abstraction layer
Official Page
Hadoop Integration Fully Integrated
Suppose you have a set of files that you access with MapReduce, Hive, and Pig. Wouldn't it
be useful if you had a way of accessing them so that you didn't have to know details of file
format and location? You do. HCatalog provides an abstraction layer on many file types in
HDFS allowing users of Pig, Hive, and MapReduce to concentrate on reading and writing
their data without detailed consideration of what format it is using. This abstraction layer
makes the data look very much like relational data (i.e., arranged in tables with rows and
