Cloudera Developer Blog · Hive Posts
The ecosystem is evolving at a rapid pace – so rapidly, that important developments are often passing through the public attention zone too quickly. Thus, we think it might be helpful to bring you a digest (by no means complete!) of our favorite highlights on a regular basis. (This effort, by the way, has different goals than the fine Hadoop Weekly newsletter, which has a more expansive view – and which you should subscribe to immediately, as far as we’re concerned.)
Find the first installment below. Although the time period reflected here is obviously more than a month long, we have some catching up to do before we can move to a truly monthly cadence.
Every day, more data, users, and applications are accessing ever-larger Apache Hadoop clusters. Although this is good news for data driven organizations overall, for security administrators and compliance officers, there are still lingering questions about how to enable end-users under existing Hadoop infrastructure without compromising security or compliance requirements.
While Hadoop has strong security at the filesystem level, it lacks the granular support needed to adequately secure access to data by users and BI applications. Today, this problem forces organizations in industries for which security is paramount (such as financial services, healthcare, and government) to make a choice: either leave data unprotected or lock out users entirely. Most of the time, the preferred choice is the latter, severely inhibiting access to data in Hadoop.
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.
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.
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.
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
A World-Class EDW Requires a World-Class Hadoop Team
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In this installment, meet Cloudera Software Engineer/Apache Bigtop Committer Mark Grover (@mark_grover).
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.
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.