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.
  - Installing the mapr-client Package
    The mapr-client package must be installed on each node where you will be building and running your applications. This package installs all of the MapR Libraries needed for application development regardless of programming language or type of MapR Database table (binary or JSON).
  - Passing the MapR Database Table Path
    This topic describes the methods for passing a MapR Database table name. Binary table names can be passed by either specifying the table path in the API or by setting the table path in the core-site.xml file. JSON table names are passed by specifying the table path in the API.
  - Tuning Parameters for Client Apps
    Though tuning client applications is generally not necessary, MapR does offer tuning parameters to change the behavior of client-side caching.
  - Developing Applications for Binary Tables
    MapR Database provides a C API, libMapRClient and partially supports the Apache HBase 1.1 Java APIs for performing operation on MapR Database binary tables.
    - Creating C Apps - Binary Tables
      MapR provides a library of C APIs – libMapRClient – for performing operations on MapR Database binary tables.
    - Creating Java Apps - Binary Tables
      This topics describes the supported Apache HBase Java APIs used for CRUD operations on MapR Database binary tables.
      - Compiling and Running MapR Database Binary Applications
      - HBase Java API Support
        This topic describes the methods in the Apache HBase Java API library that are supported for MapR Database tables.
        Admin Method Support
        This topic lists the methods that the MapR Database supports in the HBase interface Admin.
        BufferedMutator Method Support
        This table indicates which methods MapR Database supports in the HBase interface BufferedMutator.
        Connection Method Support
        This table indicates which methods MapR Database supports in the HBase interface Connection.
        ConnectionFactory Method Support
        This table indicates which methods MapR Database supports in the HBase class ConnectionFactory.
        RegionLocator Method Support
        This table indicates which methods MapR Database supports in the HBase interface RegionLocator.
        Table Method Support
        This table indicates which methods MapR Database supports in the HBase interface Table.
        HColumnDescriptor and HTableDescriptor Support
        This section describes the supported fields in the HColumnDescriptor and the HTableDescriptor classes.
        Support for HBase Java Filters Support
        HBase Java Comparators Support
        Unsupported HBase Java Methods
        This topic identifies the HBase Java methods that are not supported for MapR Database tables. Attempts to call any of these methods results in an UnsupportedOperationException exception.
    - Impersonation through the HBase REST Gateway
      Impersonation enables access to tables via user IDs other than the user that runs the Gateway.
    - Mapping to HBase Table Namespaces
      This section describes mapping table namespaces between Apache HBase tables and MapR Database binary tables.
    - Thread-pool Settings for Performance
    - Building MapReduce Applications
      This section provides information about building and running custom MapReduce application that access MapR Database binary tables.
  - Setting for OJAI Applications to Use MapR Client Features
    Describes how to set the classpath for OJAI applications to use MapR client features.
  - Developing Applications for JSON Tables
    As part of its support for JSON tables, MapR Database implements the OJAI API. The OJAI API provides methods for creating, reading, updating, and deleting JSON documents in MapR Database JSON tables. It is available in Java, and starting in EEP 6.0, also available in Node.js, Python, C#, and Go. MapR Database also provides a MapR Database JSON Client API for managing JSON tables and a MapR Database JSON REST API for performing basic operations using HTTP calls.
- 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.
- 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.

Unsupported HBase Java Methods

This topic identifies the HBase Java methods that are not supported for MapR Database tables. Attempts to call any of these methods results in an UnsupportedOperationException exception.

Methods for ACLs for cells:

Put.setACL(String user, org.apache.hadoop.hbase.security.access.Permission perms)
Append.setACL(Map<String,org.apache.hadoop.hbase.security.access.Permission> perms)
Delete.setACL(Map<String,org.apache.hadoop.hbase.security.access.Permission> perms)
Increment.setACL(Map<String,org.apache.hadoop.hbase.security.access.Permission> perms)

Methods for cell visibility:

Put.setCellVisibility(org.apache.hadoop.hbase.security.visibility.CellVisibility expression)
Append.setCellVisibility(org.apache.hadoop.hbase.security.visibility.CellVisibility expression)
Delete.setCellVisibility(org.apache.hadoop.hbase.security.visibility.CellVisibility expression)
Increment.setCellVisibility(org.apache.hadoop.hbase.security.visibility.CellVisibility expression)

Methods for time-to-live for cell values:

Put.setTTL(long ttl)
Append.setTTL(long ttl)
Delete.setTTL(long ttl)
Increment.setTTL(long ttl)

Other methods

Delete.deleteFamilyVersion(byte[] family, long timestamp)
Scan.setReversed(boolean reversed)
Scan.setBatch()
Scan.setCaching()
Scanner.next(int nbRows)