Archive for the ‘DataFu’ Category

DataFu: The WD-40 of Big Data

Saturday, January 26th, 2013

DataFu: The WD-40 of Big Data by Sam Shah.

From the post:

If Pig is the “duct tape for big data“, then DataFu is the WD-40. Or something.

No, seriously, DataFu is a collection of Pig UDFs for data analysis on Hadoop. DataFu includes routines for common statistics tasks (e.g., median, variance), PageRank, set operations, and bag operations.

It’s helpful to understand the history of the library. Over the years, we developed several routines that were used across LinkedIn and were thrown together into an internal package we affectionately called “littlepiggy.” The unfortunate part, and this is true of many such efforts, is that the UDFs were ill-documented, ill-organized, and easily got broken when someone made a change. Along came PigUnit, which allowed UDF testing, so we spent the time to clean up these routines by adding documentation and rigorous unit tests. From this “datafoo” package, we thought this would help the community at large, and there you have DataFu.

So what can this library do for you? Let’s look at one of the classical examples that showcase the power and flexibility of Pig: sessionizing a click steam.

DataFu

The UDF bag and set operations are likely to be of particular interest.

Introducing DataFu: an open source collection of useful Apache Pig UDFs

Thursday, January 12th, 2012

Introducing DataFu: an open source collection of useful Apache Pig UDFs

From the post:

At LinkedIn, we make extensive use of Apache Pig for performing data analysis on Hadoop. Pig is a simple, high-level programming language that consists of just a few dozen operators and makes it easy to write MapReduce jobs. For more advanced tasks, Pig also supports User Defined Functions (UDFs), which let you integrate custom code in Java, Python, and JavaScript into your Pig scripts.

Over time, as we worked on data intensive products such as People You May Know and Skills, we developed a large number of UDFs at LinkedIn. Today, I’m happy to announce that we have consolidated these UDFs into a single, general-purpose library called DataFu and we are open sourcing it under the Apache 2.0 license:

Check out DataFu on GitHub!

DataFu includes UDFs for common statistics tasks, PageRank, set operations, bag operations, and a comprehensive suite of tests. Read on to learn more.

This is way cool!

Read the rest of Matthew’s post (link above) or get thee to GitHub!