A lot of confusion seems to have built around the facts: Hadoop MapReduce is being opened up into something called MapReduce 2 (MRv2). Something called YARN (Yet Another Resource Negotiator) is involved. One purpose of the whole thing is to make MapReduce not be required for Hadoop. MPI (Message Passing Interface) was mentioned as a paradigmatic example of a MapReduce alternative, yet the MPI/YARN

This post is part of a series on managing and analyzing graph data. Posts to date include: Graph data model basics (this post) Relationship analytics definition Relationship analytics applications Analysis of large graphs Interest in graph data models keeps increasing. But it’s tough to discuss them with any generality, because “graph data model” encompasses so many different things. Indeed, just

My clients at Cloudera have been around for a while, in effect positioned as “the Hadoop company.” Their business, in a nutshell, consists of: Packaging up a Cloudera distribution of Apache Hadoop. This distribution doesn’t have proprietary code; it’s just packaged by Cloudera from Apache projects (with a decent minority of the code happening to have been contributed by Cloudera engineers). Paid s

After suggesting that there’s little point to Hadoop appliances, it occurred to me to look into what kinds of hardware actually are used with Hadoop. So far as I can tell: Hadoop nodes today tend to run on fairly standard boxes. Hadoop nodes in the past have tended to run on boxes that were light with respect to RAM. The number of spindles per core on Hadoop node boxes is going up even as disks ge

A press person recently asked about: … start-ups that are building technologies to enable MySQL and other SQL databases to get over some of the problems they have in scaling past a certain size. … I’d like to get a sense as to whether or not the problems are as severe and wide spread as these companies are telling me? If so, why wouldn’t a customer just move to a new database? While that sounds as