Not long ago, the rules for what constituted a data warehouse were fairly well defined. The schema was fixed, you could say, and was based primarily on relational database technology designed to process structured data. My, how times have changed. ...
Spark is a compelling multi-purpose platform for use cases that span investigative, as well as operational, analytics.
Data science is a broad church. I am a data scientist — or so I’ve been told — but what I do is actually ...
Sqoop is a tool designed to transfer data between Hadoop and relational databases. You can use Sqoop to import data from a relational database management system (RDBMS) such as MySQL or Oracle into the Hadoop Distributed File System (HDFS), transform ...
Hadoop-2.3.0 is the first release for the year 2014, and brings a number of enhancements to the core platform, in particular to HDFS. There are a lot of bug fixes and small changes in this one - you can read ...
Hadoop is designed to run on large clusters of commodity servers – in many cases spanning many physical racks of servers. A physical rack is in many cases a single point of failure (for example, having typically a single switch ...
Hadoop MapReduce jobs are divided into a set of map tasks and reduce tasks that run in a distributed fashion on a cluster of computers. Each task work on a small subset of the data it has been assigned so ...
History of Hadoop
Spotlight on the early history of Hadoop
The history of Hadoop: From 4 nodes to the future of data
Big Ideas: Demystifying Hadoop
What is MapReduce?
"Cluster Computing and MapReduce Lecture" series in YouTube
What is Hadoop?
What is HDFS?
The paper covers most of ...