As a developer coming to Apache Hadoop it is important to understand how testing is organized in the project. For the most part it is simple — it’s really just a lot of JUnit tests — but there are some aspects that are not so well known.
Running Hadoop Unit Tests
Let’s have a look at some of the tests in Hadoop Core, and see how to run them. First check out the Hadoop Core source,
(Added 6/4/2013) Please note the instructions below are deprecated. Please refer to the CDH4 Security Guide for up-to-date procedures.
A few weeks ago we ran an Apache Hadoop hackathon. ApacheCon participants were invited to use our 10-node Hadoop cluster to explore Hadoop and play with some datasets that we had loaded on in advance. One challenge we had to face was, how do we do this in a secure way?
(guest blog post by Matei Zaharia)
When Apache Hadoop started out, it was designed mainly for running large batch jobs such as web indexing and log mining. Users submitted jobs to a queue, and the cluster ran them in order. However, as organizations placed more data in their Hadoop clusters and developed more computations they wanted to run, another use case became attractive: sharing a MapReduce cluster between multiple users.
As promised in my post about installing Scribe for log collection, I’m going to cover how to configure and use Scribe for the purpose of collecting Hadoop logs. In this post I’ll describe how to create the Scribe Thrift client for use in Java, add a new log4j Appender to Hadoop, configure Scribe, and collect logs from each node in a Hadoop cluster. At the end of the post, I will link to all source and configuration files mentioned in this guide.
Apache Hadoop exists within a rich ecosystem of tools for processing and analyzing large data sets. At Facebook, my previous employer, we contributed a few projects of note to this ecosystem, all under the Apache 2.0 license:
- Thrift: A cross-language RPC framework that powers many of Facebook’s services, include search, ads, and chat. Among other things, Thrift defines a compact binary serialization format that is often used to persist data structures for later analysis.