Apache Hadoop HA Configuration

Categories: General Guest Hadoop HDFS

Disclaimer: Cloudera no longer approves of the recommendations in this post. Please see this documentation for configuration recommendations.

One of the things we get a lot of questions about is how to make Hadoop highly available. There is still a lot of work to be done on this front, but we wanted to take a moment and share the best practices from one of our customers. Check out what Paul George has to say about how they keep thier NameNode up at ContextWeb.

Read more

The Project Split

Categories: Community General Hadoop HDFS MapReduce

Last Wednesday, we hosted a Hadoop meetup, and I gave a short talk about the new project split. How does the split change the project’s organization, and what does it mean for end users?

The mailing lists and the source code repositories have been rearranged. For those doing development against Hadoop’s “trunk” branch, compiling Hadoop and using the various components in concert has become more complicated.

My presentation slides cover which mailing lists to subscribe to,

Read more

File Appends in HDFS

Categories: General Hadoop HDFS

There is some confusion about the state of the file append operation in HDFS. It was in, now it’s out. Why was it removed, and when will it be reinstated? This post looks at some of the history behind HDFS capability for supporting file appends.

Background

Early versions of HDFS had no support for an append operation. Once a file was closed, it was immutable and could only be changed by writing a new copy with a different filename.

Read more

Hadoop Graphing with Cacti

Categories: Data Ingestion Guest Hadoop

An important part of making sure Apache Hadoop works well for all users is developing and maintaining strong relationships with the folks who run Hadoop day in and day out. Edward Capriolo keeps About.com’s Hadoop cluster happy, and we frequently chew the fat with Ed on issues ranging from administrative best practices to monitoring. Ed’s been an invaluable resource as we beta test our distribution and chase down bugs before our official releases. Today’s article looks at some of Ed’s tricks for monitoring Hadoop with Cacti through JMX.

Read more

Debugging MapReduce Programs With MRUnit

Categories: Hadoop MapReduce

The distributed nature of MapReduce programs makes debugging a challenge. Attaching a debugger to a remote process is cumbersome, and the lack of a single console makes it difficult to inspect what is occurring when several distributed copies of a mapper or reducer are running concurrently. Furthermore, operations that work on small amounts of input (e.g., saving the inputs to a reducer in an array) fail when running at scale, causing out-of-memory exceptions or other unintended effects.

Read more