Cloudera Developer Blog · General Posts

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 Giraph Jobs on 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. 

Migrating to MapReduce 2 on YARN (For Operators)

Cloudera Manager lets you add a YARN service in the same way you would add any other Cloudera Manager-managed service.

In Apache Hadoop 2, YARN and MapReduce 2 (MR2) are long-needed upgrades for scheduling, resource management, and execution in Hadoop. At their core, the improvements separate cluster resource management capabilities from MapReduce-specific logic. They enable Hadoop to share resources dynamically between MapReduce and other parallel processing frameworks, such as Cloudera Impala; allow more sensible and finer-grained resource configuration for better cluster utilization; and permit Hadoop to scale to accommodate more and larger jobs.

Migrating to MapReduce 2 on YARN (For Users)

In Apache Hadoop 2, YARN and MapReduce 2 (MR2) are long-needed upgrades for scheduling, resource management, and execution in Hadoop. At their core, the improvements separate cluster resource management capabilities from MapReduce-specific logic. They enable Hadoop to share resources dynamically between MapReduce and other parallel processing frameworks, such as Cloudera Impala; allow more sensible and finer-grained resource configuration for better cluster utilization; and permit Hadoop to scale to accommodate more and larger jobs.

In this post, users of CDH (Cloudera’s distribution of Hadoop and related projects) who program MapReduce jobs will get a guide to the architectural and user-facing differences between MapReduce 1 (MR1) and MR2. (MR2 is the default processing framework in CDH 5, although MR1 will continue to be supported.) Operators/administrators can read a similar post designed for them here.

Terminology and Architecture

Cloudera Enterprise 5 Beta is Now Available for Download

We are pleased to announce the beta release of Cloudera Enterprise 5 (CDH 5 and Cloudera Manager 5). This release has both Cloudera Impala and Cloudera Search integrated into CDH. It also includes many new features and updated component versions including the ones below:

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