Cloudera Engineering Blog · General Posts

Community Meetups during Strata + Hadoop World 2014

The meetup opportunities during the conference week are more expansive than ever — spanning Impala, Spark, HBase, Kafka, and more.

Strata + Hadoop World 2014 is a kaleidoscope of experiences for attendees, and those experiences aren’t contained within the conference center’s walls. For example, the meetups that occur during the conf week (which is concurrent with NYC DataWeek) are a virtual track for developers — and with Strata + Hadoop World being bigger than ever, so is the scope of that track.

How-to: Install CDH on Mac OSX 10.9 Mavericks

This overview will cover the basic tarball setup for your Mac.

If you’re an engineer building applications on CDH and becoming familiar with all the rich features for designing the next big solution, it becomes essential to have a native Mac OSX install. Sure, you may argue that your MBP with its four-core, hyper-threaded i7, SSD, 16GB of DDR3 memory are sufficient for spinning up a VM, and in most instances — such as using a VM for a quick demo — you’re right.  However, when experimenting with a slightly heavier workload that is a bit more resource intensive, you’ll want to explore a native install.

Bayesian Machine Learning on Apache Spark

Markov Chain Monte Carlo methods are another example of useful statistical computation for Big Data that is capably enabled by Apache Spark.

During my internship at Cloudera, I have been working on integrating PyMC with Apache Spark. PyMC is an open source Python package that allows users to easily apply Bayesian machine learning methods to their data, while Spark is a new, general framework for distributed computing on Hadoop. Together, they provide a scalable framework for scalable Markov Chain Monte Carlo (MCMC) methods. In this blog post, I am going to describe my work on distributing large-scale graphical models and MCMC computation.

Markov Chain Monte Carlo Methods

Cloudera Live: The Instant Apache Hadoop Experience

Get started with Apache Hadoop and use-case examples online in just seconds.

Today, we announced Cloudera Live, a new online service for developers and analysts (currently in public beta) that makes it easy to learn, explore, and try out CDH, Cloudera’s open source software distribution containing Apache Hadoop and related projects. No downloads, no installations, no waiting — just point-and-play!

How-to: Implement Role-based Security in Impala using Apache Sentry

This quick demo illustrates how easy it is to implement role-based access and control in Impala using Sentry.

Apache Sentry (incubating) is the Apache Hadoop ecosystem tool for role-based access control (RBAC). In this how-to, I will demonstrate how to implement Sentry for RBAC in Impala. I feel this introduction is best motivated by a use case.

Apache Spark: A Delight for Developers

Sure, Spark is fast, but it also gives developers a positive experience they won’t soon forget.

Apache Spark is well known today for its performance benefits over MapReduce, as well as its versatility. However, another important benefit – the elegance of the development experience – gets less mainstream attention.

How-to: Index and Search Multilingual Documents in Hadoop

Learn how to use Cloudera Search along with RBL-JE to search and index documents in multiple languages.

Our thanks to Basis Technology for providing the how-to below!

How-to: Write and Run Apache Giraph Jobs on Apache Hadoop

Create a test environment for writing and testing Giraph jobs, or just for playing around with Giraph and small sample datasets.

Apache Giraph is a scalable, fault-tolerant implementation of graph-processing algorithms in Apache Hadoop clusters of up to thousands of computing nodes. Giraph is in use at companies like Facebook and PayPal, for example, to help represent and analyze the billions (or even trillions) of connections across massive datasets. Giraph was inspired by Google’s Pregel framework and integrates well with Apache Accumulo, Apache HBase, Apache Hive, and Cloudera Impala.

Impala Performance Update: Now Reaching DBMS-Class Speed

Impala’s speed now beats the fastest SQL-on-Hadoop alternatives. Test for yourself!

Since the initial beta release of Cloudera Impala more than one year ago (October 2012), we’ve been committed to regularly updating you about its evolution into the standard for running interactive SQL queries across data in Apache Hadoop and Hadoop-based enterprise data hubs. To briefly recap where we are today:

Doing DevOps with Cloudera Manager

More and more customers are using automation/configuration management frameworks alongside Cloudera Manager.

As Apache Hadoop clusters continue to grow in size, complexity, and business importance as the foundational infrastructure for an Enterprise Data Hub, the use cases for a robust and mature management console expand. 

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