Cloud Computing Blog Posts

Posted on October 18, 2016 by James Sun

If you’ve been keeping tabs on all the great product enhancements that have been coming out of MapR, you will know that the 5.2 version of the MapR Converged Data Platform went GA this summer. It takes a few cycles to make the platform available on the AWS marketplace, largely due to the testing efforts required.

Posted on November 10, 2015 by Nick Amato

This blog describes how to get an instance of the MapR-DB Document Database Developer Preview image running on Amazon AWS using one of the pre-configured AMI images supplied by MapR. With this AMI, you can start writing JSON-based applications on MapR-DB using the open source Open JSON Application Interface, or OJAI.

Posted on July 22, 2015 by Abizer Adenwala

As a follow-up to my previous post on MapR-DB, I want to describe how to index MapR-DB table data in near real-time into Elasticsearch on Amazon Web Services (AWS) Elastic Compute Cloud (EC2).

Posted on December 16, 2014 by Na Yang

Nearly one year ago the Hadoop community began to embrace Apache Spark as a powerful batch processing engine. Today, many organizations and projects are augmenting their Hadoop capabilities with Spark. As part of this trend, the Apache Hive community is working to add Spark as an execution engine for Hive. The Hive-on-Spark work is being tracked by HIVE-7292 which is one of the most popular JIRAs in the Hadoop ecosystem. Furthermore, three weeks ago, the Hive-on-Spark team offered the first demo of Hive on Spark.

Posted on December 5, 2014 by Will Ochandarena

I often get asked, “What is the easiest way to get hands-on experience with MapR?” The best way is to try the MapR Sandbox, a single-node MapR cluster that you can run on your laptop. However, Hadoop clusters are never built with just one server, and some MapR features require multiple nodes, or even multiple clusters. To get hands-on with a MapR installation that more closely resembles what you might deploy on hardware, I suggest you deploy a MapR cluster in the Amazon cloud, using the MapR Installer. This blog post will walk you through that process.

Posted on April 4, 2014 by Karen Whipple
Amazon Elastic MapReduce (Amazon EMR) makes it easy to provision and manage Hadoop in the AWS Cloud. The latest webinar from the Amazon Web Services Partner webinar series, titled “Hadoop in the Cloud: Unlocking the Potential of Big Data on AWS,” showed examples of how to use Amazon EMR with the MapR Distribution for Apache Hadoop, and outlined the advantages of using the cloud to increase flexibility and accelerate projects while lowering costs.

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