The MapR Sandbox provides tutorials, demo applications, and browser-based user interfaces to let developers and administrators get started quickly. It includes a fully functional Hadoop cluster running in a virtual machine. You can try our Sandbox now - it is completely free and available as a VMware or VirtualBox VM.

If you are a business intelligence analyst or a developer interested in self-service data exploration on Hadoop using SQL and BI Tools, the MapR Sandbox including Apache Drill will get you started quickly. You can download the Drill Sandbox here.

The MapR Sandbox includes Apache Hadoop (MapReduce, Hive, Pig, HBase, AsynchHBase, Mahout, Storm, HttpFS, Sqoop/Sqoop2, Flume, Oozie, ZooKeeper, Hue, and Myriad), Apache Spark (core, Spark SQL, GraphX, Spark Streaming, MLlib), MapR-DB (with support for both JSON and HBase tables), MapR Streams (with Apache Kafka 0.9 API support), and MapR-FS. See our What's Included page for more the supported project versions.

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KEY FEATURES

Tutorials and Examples

Developers/Analysts have access to Sandbox’s extensive training modules via the Hue interface. A wide variety of development work including uploading data, creating database tables, running queries, creating scripts, running jobs and designing and submitting workflows can be done in a hands-on fashion. In the process, you will quickly discover how salient components of the Hadoop ecosystem such as MapReduce, Pig, Hive and HBase interact with each other.

Testing Your Own Apps

Given that it is a fully functional MapR cluster, you can also leverage the Sandbox to ingest your own data using industry standard interfaces such as NFS, build a small-scale test application and/or run a proof of concept.

Hands-on Administration

Similarly, for the administrators, MapR Sandbox packages the MapR Control System web interface to provide hands-on experience in configuring, monitoring and managing Hadoop. Among other activities, you can play with the MapR Distribution’s volume-based management system, create snapshots, set alarms and quotas and also get a view into how scores of node and job metrics help you monitor the cluster easily.