Hive for Beginners (1): First Look at Hive
Having finished the Hadoop beginner series, we're finally getting to the real data warehouse work. Let's start by understanding what Hive is in the Hadoop ecosystem.
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Page 4 of 11ZooKeeper for Beginners (4): Inside ZooKeeper
The first three ZooKeeper tutorials left you able to use it. This post goes a step further and gives you a general idea of how ZooKeeper actually works.
ZooKeeper for Beginners (3): A Small Demo for Watching Node Changes
Last time we could already drive ZooKeeper from code and learned about registering watchers. Time to try it out: this post walks through a simple hands-on example that watches a node for changes.
ZooKeeper for Beginners (2): Programming with the ZooKeeper API
Last post got ZooKeeper installed. The command line works, but most of the time you operate ZooKeeper through API calls, so this post covers the basic beginner-level operations.
Hadoop for Beginners (14): How MapReduce Shuffle Works
The previous tutorial introduced how MapReduce executes and sketched out InputFormat. Now it's time to talk about Shuffle. The data processing that happens after the Map method and before the Reduce method is called Shuffle.
Hadoop for Beginners (13): MapReduce Input Splits and Parallelism
In the previous post we got hands-on with MapReduce by writing some code. The MapReduce workflow looks roughly like this.
Hadoop for Beginners (12): Hadoop's Writable Classes
Last session we went through using MapReduce from code, where we met Writable classes for the first time. This section covers roughly what they're for.
Hadoop for Beginners (11): Writing MapReduce in Code — a WordCount Example
Last post gave us a general idea of what MapReduce is. In this one we'll implement WordCount in code and get a feel for how MapReduce actually works.
Hadoop for Beginners (10): First Look at MapReduce Distributed Computing
Earlier posts introduced HDFS. Now let's dip into the other core Hadoop component: MapReduce.
Hadoop for Beginners (9): Setting Up a Local Hadoop Development Environment
Last post covered HDFS broadly. From this section on we'll drive Hadoop by writing code, so first we need a local Hadoop development environment. If you followed the earlier posts and got Hadoop running in a VM, setting it up locally is a walk in the park. If you haven't — or haven't read those posts — read them first.
