HPE Ezmeral Data Fabric 6.1.x is In Maintenance and transitions to "End of Maintenance" in June 2024. Please see the latest documentation.

About MapR 6.1
This site contains the main documentation for Version 6.1 of the MapR Converged Data Platform, including installation, configuration, administration, and reference information.
6.1 Installation
This section contains information about installing and upgrading MapR software. It also contains information about how to migrate data and applications from an Apache Hadoop cluster to a MapR cluster.
6.1 MapR Data Platform
MapR Data Platform is the industry-leading data platform for AI and analytics that solves enterprise business needs.
6.1 Administration
This section describes how to manage the nodes and services that make up a cluster.
6.1 Development
This section contains information related to application development for Ezmeral ecosystem components and MapR Data Platform products, including the file system, Database (Key-Value and JSON), and Event Streams.
- Application Development Process
  Before you start developing applications on the MapR Data Platform platform, consider how you will get the data into the platform, the storage format of the data, the type of processing or modeling that is required, and how the data will be accessed.
- MapR XD and Apps
  The following sections provide information about accessing the MapR XD with C and Java applications.
- MapR Database and Apps
  This section contains information about developing client applications for JSON and key-value tables.
- MapR Event Store For Apache Kafka and Apps
  MapR Event Store For Apache Kafka brings integrated publish and subscribe messaging to MapR Data Platform.
- MapReduce and Apps
  This section contains information associated with developing YARN applications.
  - External Applications and Classpath
    Describes how to configure the class path for external applications.
  - Classpath Construction
    This section describes how the MapReduce classpath is constructed.
  - Managing Third-Party Libraries
    Any third-party library that is required by a MapReduce program must be accessible to the data node that processes the application.
- MapR Data Science Refinery
  The MapR Data Science Refinery product is an easy-to-deploy and scalable data science toolkit with native access to all platform assets and superior out-of-the-box security.
- MapR Data Fabric for Kubernetes
  This section describes how to leverage the capabilities of the MapR Data Fabric for Kubernetes.
- Ecosystem Components
  The following sections provide information about each open-source project that is supported by the MapR Data Platform.
- Maven and MapR
  This section discusses topics associated with Maven and MapR.
- Developer's Reference
  This section contains in-depth information for the developer.
- API Documentation
  MapR Data Platform supports public APIs for MapR File System, MapR Database, and MapR Event Store For Apache Kafka. These APIs are available for application-development purposes.
Other Docs
This section contains release-independent information, including: MapR Installer documentation, Ecosystem release notes, interoperability matrices, security vulnerabilities, and links to other MapR version documentation.
Glossary
Definitions for commonly used terms in MapR Converged Data Platform environments.

Managing Third-Party Libraries

Any third-party library that is required by a MapReduce program must be accessible to the data node that processes the application.

A data node is a node in the cluster that includes the NodeManager role. You can provide the third-party libraries when you submit the program, or you can install the third-party libraries on each node that processes the application.

Include the third-party libraries with each program

Including the third-party libraries with each program is the preferred method.

Perform one the following operations to include the third-party jars when you submit the program:

Package the third-party libraries with the MapReduce jar file. The benefit of this method is that the node from which you submit the program and the node that runs the program are not required to have the libraries files.
Use the -libjars parameter to specify the third-party libraries on the command line. With this option, the library files are submitted to the data node along with the program. The benefit of this method is that the node that runs the program does not need to have the library files installed. However, the node that submits the program must have the library files installed.

Install the third-party libraries on each node that runs the program

You can also install the third-party libraries on each data node. However, this may not be preferred as there could be conflicts between library versions or library files.

To install the third-party libraries on each data node, perform one of the following operations:

Install the third-party libraries in the following directory on each Node Manager node: /opt/mapr/hadoop/hadoop-2.x/share/hadoop/common
On each node with the NodeManager role, install the required third-party libraries and then specify the location(s) of the third-party libraries with the HADOOP_CLASSPATH env variable in the env_override.sh file. The env_override.sh file is located in the following directory: /opt/mapr/conf. For more information about the file, see About env_override.sh.