Topic: mapreduce

MapR introduces publish/subscribe streaming for Hadoop

While many in the Big Data space are talking about stream processing, MapR today announced the availability of Streams, a new product in its Hadoop stack that can be used to stream events across clusters distributed around the world. The new product offers a publish-and-subscribe model for event-driven data access and decision-making. While MapR Streams … continue reading

Heroku Enterprise, MapReduce for C, and Microsoft to optimize asm.js—SD Times news digest: Feb. 19, 2015

Salesforce has announced Heroku Enterprise, a new edition of the Heroku cloud application development platform featuring new team collaboration tooling, enhanced access controls and enterprise-grade support. Heroku Enterprise, built for enterprise-scale development, contains several new collaboration and control features for app development in large distributed teams: Shared Application Projects: Enable developer teams, partners and contractors … continue reading

Inside the Apache Software Foundation’s Flink

The Apache Software Foundation has announced Apache Flink as a Top-Level Project (TLP). Flink is an open-source Big Data system that fuses processing and analysis of both batch and streaming data. The data-processing engine, which offers APIs in Java and Scala as well as specialized APIs for graph processing, is presented as an alternative to … continue reading

New versions of Splunk Enterprise and Hunk now generally available

SAN FRANCISCO — Splunk Inc., provider of the leading software platform for real-time Operational Intelligence, today announced the general availability (GA) of Splunk Enterprise 6.2, the latest version of the award-winning platform for machine data, and version 6.2 of Hunk: Splunk Analytics for Hadoop and NoSQL Data Stores. Splunk Enterprise 6.2 delivers simplified analysis and … continue reading

MapR Announces Initiative for Integration between Apache Drill and Apache Spark

MapR Technologies, Inc., provider of the top-ranked distribution for Apache Hadoop, today announced an initiative to integrate Apache Drill, which provides instant, self-service data exploration across multiple data sources, with Apache Spark, the in-memory processing framework that provides speed, programming ease and real-time processing advantages. “The MapR initiative to integrate Apache Drill with Apache Spark’s … continue reading

Zeichick’s Take: Five phrases you need to know about Big Data

These terms will familiarize anyone who wants to work with it (and we need people who want to work with it) … continue reading

Hadoop is now a general-purpose platform

Skepticism is giving way once developers see what the latest version of Hadoop can do … continue reading

Code Watch: What would Map do?

The limitations of Map/Reduce drive some introspection on object-oriented programming … continue reading

Code Watch: Map/Reduce, turn by turn

There’s a best way to do Map/Reduce; here’s a quick primer and suggested reading … continue reading

Hadoop 2.0: More than MapReduce

Next version, shown at Summit, refocuses project as general data processing platform … continue reading

Diving into the Big Data pool

Hadoop is at the center of the big-data universe, but a handful of companies are providing alternatives … continue reading

The ins and outs of MapReduce

Newcomers to Hadoop should read this walkthrough of what MapReduce does to handle Big Data … continue reading Protection Status