Cloudera Engineering Blog · Hive Posts

Breaking News: Cloudera Impala is Fast. Really Fast.

Editor’s note (added Feb. 2, 2014): You can review the latest (and exciting) Impala performance benchmark results by Cloudera here.

In the presentation below, Scott Leberknight of Near Infinity has done such a good and thorough job of dissecting Cloudera Impala, we want to share it with you here.

How HiveServer2 Brings Security and Concurrency to Apache Hive

Apache Hive was one of the first projects to bring higher-level languages to Apache Hadoop. Specifically, Hive enables the legions of trained SQL users to use industry-standard SQL to process their Hadoop data.

However, as you probably have gathered from all the recent community activity in the SQL-over-Hadoop area, Hive has a few limitations for users in the enterprise space. Until recently, two in particular – concurrency and security – were largely unaddressed.

Make Hadoop Your Best Business Tool

Data analysts and business intelligence specialists have been at the heart of new trends driving business growth over the past decade, including log file and social media analytics. However, Big Data heretofore has been beyond the reach of analysts because traditional tools like relational databases don’t scale, and scalable systems like Apache Hadoop have historically required Java expertise. 

Demo: Analyzing Data with Hue and Hive

In the first installment of the demo series about Hue — the open source Web UI that makes Apache Hadoop easier to use — you learned how file operations are simplified via the File Browser application. In this installment, we’ll focus on analyzing data with Hue, using Apache Hive via Hue’s Beeswax and Catalog applications (based on Hue 2.3 and later).

The Yelp Dataset Challenge provides a good use case. This post explains, through a video and tutorial, how you can get started doing some analysis and exploration of Yelp data with Hue. The goal is to find the coolest restaurants in Phoenix!

Dataset Challenge with Hue

How Persado Supports Persuasion Marketing Technology with Data Analyst Training

This guest post comes from Alex Giamas, Senior Software Engineer on the data warehouse team at Persado, an ultra-hot persuasion marketing technology company with operations in Athens, Greece.

A World-Class EDW Requires a World-Class Hadoop Team

Persado is the global leader in persuasion marketing technology, a new category in digital marketing. Our revolutionary technology maps the genome of marketing language and generates the messages that work best for any customer and any product at any time. To assure the highest quality experience for both our clients and end-users, our engineering team collaborates with Ph.D. statisticians and data analysts to develop new ways to segment audiences, discover content, and deliver the most relevant and effective marketing messages in real time.

Meet the Engineer: Mark Grover

Mark Grover

In this installment, meet Cloudera Software Engineer/Apache Bigtop Committer Mark Grover (@mark_grover).

How-to: Analyze Twitter Data with Hue

Hue 2.2 , the open source web-based interface that makes Apache Hadoop easier to use, lets you interact with Hadoop services from within your browser without having to go to a command-line interface. It features different applications like an Apache Hive editor and Apache Oozie dashboard and workflow builder.

This post is based on our “Analyzing Twitter Data with Hadoop” sample app and details how the same results can be achieved through Hue in a simpler way. Moreover, all the code and examples of the previous series have been updated to the recent CDH4.2 release.

Collecting Data

One User’s Impala Experience at Data Hacking Day

The following guest post comes to you from Alan Gardner of remote database services and consulting company Pythian, who participated in Data Hacking Day (and was on the winning team!) at Cloudera’s offices in February.

Last Feb. 25, just prior to attending Strata, Alex Gorbachev (our CTO) and I had the chance to visit Cloudera’s Palo Alto offices for Data Hacking Day. The goal of the event was to produce something cool that leverages Cloudera Impala – the new open source, low-latency platform for querying data in Apache Hadoop.

Apache Hadoop Developer Training Helps Query Massive Telecom Data

This guest post is provided by Rohit Menon, Product Support and Development Specialist at Subex.

I am a software developer in Denver and have been working with C#, Java, and Ruby on Rails for the past six years. Writing code is a big part of my life, so I constantly keep an eye out for new advances, developments, and opportunities in the field, particularly those that promise to have a significant impact on software engineering and the industries that rely on it. 

In my current role working on revenue assurance products in the telecom space for Subex, I have regularly heard from customers that their data is growing at tremendous rates and becoming increasingly difficulty to process, often forcing them to portion out data into small, more manageable subsets. The more I heard about this problem, the more I realized that the current approach is not a solution, but an opportunity, since companies could clearly benefit from more affordable and flexible ways to store data. Better query capability on larger data sets at any given time also seemed key to derive the rich, valuable information that helps drive business. Ultimately, I was hoping to find a platform on which my customers could process all their data whenever they needed to. As I delved into this Big Data problem of managing and analyzing at mega-scale, it did not take long before I discovered Apache Hadoop.

Mission: Hands-On Hadoop

How-to: Set Up Cloudera Manager 4.5 for Apache Hive

Last week Cloudera released the 4.5 release of Cloudera Manager, the leading framework for end-to-end management of Apache Hadoop clusters. (Download Cloudera Manager here, and see install instructions here.) Among many other features, Cloudera Manager 4.5 adds support for Apache Hive. In this post, I’ll explain how to set up a Hive server for use with Cloudera Manager 4.5 (and later).

For details about other new features in this release, please see the full release notes:

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