The benchmark testing results detailed below can help you make an informed decision about AWS storage options for Impala.
In a recent post, you learned how Impala 2.6 on S3 delivers cloud-native features unmatched by other analytic databases in the cloud. With support to read/write data from Amazon S3, Impala provides cloud capabilities such as direct querying of data from S3, elastic scaling of compute, and seamless data portability and flexibility not found on other cloud-based analytic databases, such as Amazon Redshift.
This FAQ contains answers to the most frequently asked questions about the architecture and configuration choices involved.
In December 2013, Cloudera and Amazon Web Services (AWS) announced a partnership to support Cloudera Enterprise on AWS infrastructure. Along with this announcement, we released a Deployment Reference Architecture Whitepaper. In this post, you’ll get answers to the most frequently asked questions about the architecture and the configuration choices that have been highlighted in that whitepaper.
Editor’s Note (added Feb. 25, 2015): For releases beyond 4.5, Cloudera recommends the use of Cloudera Director for deploying CDH in cloud environments.
Cloudera Manager includes a new express installation wizard for Amazon Web Services (AWS) EC2. Its goal is to enable Cloudera Manager users to provision CDH clusters and Cloudera Impala (the open source distributed query engine for Apache Hadoop) on EC2 as easily as possible (for testing and development purposes only,
This was post was originally published by U.C. Berkeley AMPLab developer (and former Clouderan) Matt Massie, on his personal blog. Matt has graciously permitted us to re-publish here for your convenience.
Note: The post below is valid for Impala version 0.6 only and is not being maintained for subsequent releases. To deploy Impala 0.7 and later using a much easier (and also free) method, use this how-to.
(guest blog post by Pete Skomoroch)
In a previous post, I outlined how to build a basic trend tracking site called trendingtopics.org with Cloudera’s Distribution for Hadoop and Hive. TrendingTopics uses Hadoop to identify the top articles trending on Wikipedia and displays related news stories and charts. The data powering the site was pulled from an Amazon EBS Wikipedia Public Dataset containing 8 months of hourly pageview logfiles.