Database Reference
In-Depth Information
WebSphere Decision Server: iLog Rules
Big Data processing often requires complex rules for data analysis, and rules
deployment has rightfully received significant enterprise focus in the last
few years. Your Big Data environments can leverage WebSphere Decision
Server (iLog Rules) to build smarter application flows. Our research teams
have shown how to use iLog Rules with Streams to analyze a data stream
based on conditions and vectors that are passed by iLog Rules (we expect to
say a lot more in this space after the topic is published—our lawyers won't
let us detail it just yet).
Rational
Job and application development lifecycle management is often overlooked
in Big Data environments, which is a costly mistake. Eclipse is a pluggable
integrated development environment (IDE) that was invented and donated
to the open source community by IBM. Eclipse is used extensively in the
open source Big Data technologies, as well as the IBM Big Data platform.
The IBM Big Data platform provides plug-ins for the development of
Streams Processing Language (SPL) flows, SQL, Java MapReduce, Hive, Pig,
Jaql, AQL-based text analytics, and more. These plug-ins are installable either
from an open source Eclipse installation or from Eclipse-based value-add
offerings such as Rational Application Developer (RAD). The IBM Big Data
platform extends the Eclipse IDE with out-of-the-box plugs-ins for Streams
and BigInsights that can leverage underlying Eclipse project artifacts. These
artifacts, in turn, can be managed by extended Rational tool sets for version
control (such as Rational ClearCase or Rational ClearQuest), collaboration
(such as Rational JAZZ), or for enterprise-class lifecycle management.
Data Repository-Level Integration
If the Big Data platform is to work effectively, data must be shared among the
various repositories within the platform. The many integration points are
described in this chapter and throughout this topic (see Chapter 5 and Chap-
ter 6). Remember, the business process doesn't start and stop within the Big
Data platform—data must be shared with other repositories and platforms.
