Difficulty: beginner
Estimated Time: 15 minutes

The MapR Data Platform integrates Apache Hadoop, Apache Spark, and Apache Drill with real-time database capabilities, global event streaming, and scalable enterprise storage to power a new generation of Big Data applications. MapR solves the challenges of complex data environments by managing data and its ecosystem across multiple clouds and containerized infrastructures.

In this scenario you will become familiar with the MapR data platform by interacting with a single-node MapR cluster.

In this scenario you saw how MapR combines Hadoop, Spark, and Apache Drill with a distributed file system, distributed database, and distributed event streaming, all on a single cluster. This improves performance and lowers hardware costs for Big Data applications. The MapR Data Platform allows you to manage your data with any tooling on any infrastructure.

Would you like to learn more about MapR? Check out our blog, In Search of a Data Platform.

If you'd like to speak with MapR, contact us!

Introduction to MapR

Step 1 of 5

Step 1 - Login

The MapR data platform consists of the following three core components:

  1. MapR XD Distributed File and Object Store
  2. MapR Database
  3. MapR Event Store for Apache Kafka

In this tutorial you will explore each of these components on a single-node MapR cluster.

Before you begin you need to authenticate. Run the following command to login:

maprlogin password -user mapr

Use password mapr.

Verify that you've authenticated by running the following maprcli command: maprcli node list -columns ip.

MapR can also be administered using the maprcli command or with a web interface known as the MapR Control System (MCS). Click here to open MCS, and login with these credentials:

Username: mapr

Password: mapr

When you're finished exploring MCS, return to the Terminal tab and click the Continue button.