MapR 5.1 is at End of Life (EOL) and no longer supported. Please see the latest documentation. This documentation is not being updated.

5.1 DB & Streams
This section covers the MapR-DB, MapR-Streams, and MapR-Gateways features. Each feature may contain both administrator and developer topics.
- MapR-DB
  - Architecture of MapR-DB
    MapR-DB's architecture gives it a large of advantages over other NoSQL databases.
  - Performance Enhancements for SSD Based MapR-DB Deployments
  - MapR-DB as a Document Database
    MapR-DB supports OJAI documents as a native data store. OJAI documents are stored in a compact binary format, not as plain ASCII text.
  - MapR-DB as a Wide-Column Database
    - Logical Model of MapR-DB Binary Tables
    - Filesystem Operations on MapR-DB Tables
    - Migrating Between Apache HBase Tables and MapR-DB Binary Tables
    - Designing Row Keys for MapR-DB Binary Tables
      A row key identifies a row in a MapR-DB binary table.
    - Designing Column Families for MapR-DB Binary Tables
      Scanning an entire table for matches can be very performance-intensive. Column families enable you to group related sets of data and restrict queries to a defined subset, leading to better performance. When you design a column family, think about what kinds of queries are going to be used the most often, and group your columns accordingly.
    - Configuring Maximum Row Sizes for Binary Tables
      The default maximum row size at installation is 32MB. You can configure this maximum by changing the value of the mfs.db.max.rowsize.kb parameter with the maprcli config save command.
    - Enabling Access to MapR Tables via HBase APIs, hbase shell, and MapReduce Jobs
    - Creating MapR-DB Binary Tables
    - Displaying Table Region Information for MapR-DB Tables
    - Creating Applications That Access MapR-DB Binary Tables
    - Bulk Loading and MapR-DB Binary Tables
    - Replicating MapR-DB Binary Tables
    - Indexing MapR-DB Binary Tables with Elasticsearch
    - Impersonation via the HBase REST Gateway
- MapR Streams
  MapR Streams brings integrated publish/subscribe messaging to the MapR Converged Data Platform.
- MapR Gateways
  A MapR gateway mediates one-way communication between a source MapR cluster and a destination cluster. MapR-DB binary tables and MapR Streams streams can be replicated.

Enabling Access to MapR Tables via HBase APIs, hbase shell, and MapReduce Jobs

You can use the HBase API and the hbase shell commands to access your MapR tables. MapR has extended the HBase component to handle access to both MapR tables and Apache HBase tables. MapR tables do not support low-level HBase API calls that are used to manipulate the state of an Apache HBase cluster.

See Creating MapR-DB Applications with Java for a full list of supported HBase Java APIs.

See HBase Shell for MapR-DB for a full list of supported commands in the HBase shell.

To enable the HBase API and hbase shell access, install the mapr-hbase package on every node in the cluster. The HBase component of the MapR distribution for Hadoop is typically installed under/opt/mapr/hbase. To ensure that your existing HBase applications and workflow work properly, install the mapr-hbase package that provides the same version number of HBase as your existing Apache HBase.

See Get Started: Install MapR for information about MapR installation procedures.

NOTE: The version of HBase provided by MapR has been modified to work with MapR tables in addition to Apache HBase. Do not download and install stock Apache HBase on a MapR cluster that uses MapR tables.

NOTE: If you use fat JARs to deploy your application as a single JAR including all dependencies, be aware that the fat JAR may contain versions of HBase that override the installed MapR versions, leading to problems. Check your fat JARs for the presence of stock HBase to prevent this problem.