Cloudera Engineering Blog · Impala Posts

How-to: Use Parquet with Impala, Hive, Pig, and MapReduce

The CDH software stack lets you use your tool of choice with the Parquet file format – - offering the benefits of columnar storage at each phase of data processing. 

An open source project co-founded by Twitter and Cloudera, Parquet was designed from the ground up as a state-of-the-art, general-purpose, columnar file format for the Apache Hadoop ecosystem. In particular, Parquet has several features that make it highly suited to use with Cloudera Impala for data warehouse-style operations:

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.

Secrets of Cloudera Support: Inside Our Own Enterprise Data Hub

Cloudera’s own enterprise data hub is yielding great results for providing world-class customer support.

Here at Cloudera, we are constantly pushing the envelope to give our customers world-class support. One of the cornerstones of this effort is the Cloudera Support Interface (CSI), which we’ve described in prior blog posts (here and here). Through CSI, our support team is able to quickly reason about a customer’s environment, search for information related to a case currently being worked, and much more.

Apache Hadoop 2.3.0 is Released (HDFS Caching FTW!)

Hadoop 2.3.0 includes hundreds of new fixes and features, but none more important than HDFS caching.

The Apache Hadoop community has voted to release Hadoop 2.3.0, which includes (among many other things):

Native Parquet Support Comes to Apache Hive

Bringing Parquet support to Hive was a community effort that deserves congratulations!

Previously, this blog introduced Parquet, an efficient ecosystem-wide columnar storage format for Apache Hadoop. As discussed in that blog post, Parquet encodes data extremely efficiently and as described in Google’s original Dremel paper. (For more technical details on the Parquet format read Dremel made simple with Parquet, or go directly to the open and community-driven Parquet Format specification.)

How Wajam Answers Business Questions Faster With Hadoop

Thanks to Xavier Clements of Wajam for allowing us to re-publish his blog post about Wajam’s Hadoop experiences below!

Wajam is a social search engine that gives you access to the knowledge of your friends. We gather your friends’ recommendations from Facebook, Twitter, and other social platforms and serve these back to you on supported sites like Google, eBay, TripAdvisor, and Wikipedia.

How-to: Get Started Writing Impala UDFs

Cloudera provides docs and a sample build environment to help you get easily started writing your own Impala UDFs.

User-defined functions (UDFs) let you code your own application logic for processing column values during a Cloudera Impala query. For example, a UDF could perform calculations using an external math library, combine several column values into one, do geospatial calculations, or other kinds of tests and transformations that are outside the scope of the built-in SQL operators and functions.

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:

This Month (and Year) in the Ecosystem (December 2013)

Welcome to our sixth edition of “This Month in the Ecosystem,” a digest of highlights from December 2013 (never intended to be comprehensive; for completeness, see the excellent Hadoop Weekly).

With the close of 2013, we also thought it appropriate to include some high points from across the year (not listed in any particular order):

How-to: Use Impala on Amazon EMR

Developers, rejoice: Impala is now available on EMR for testing and evaluation.

Very recently, Amazon Web Services announced support for running Cloudera Impala queries on its Elastic MapReduce (EMR) service. This is very good news for EMR users — as well as for users of other platforms interested in kicking Impala’s tires in a friction-free way. It’s also yet another sign that Impala is rapidly being adopted across the ecosystem as the gold standard for interactive SQL and BI queries on Apache Hadoop.

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