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
      - Mapping Table Namespace Between Apache HBase Tables and MapR-DB Binary Tables
      - Behavior of the MapR dbclient When Connecting to MapR-DB
        Requests from client applications to connect to MapR-DB are handled by the MapR dbclient. This dbclient has the following behaviors when establishing the first connection and when re-establishing connections after the CLDB goes offline.
      - Creating C Applications That Access MapR-DB Binary Tables
      - Creating Java Applications That Access MapR-DB Binary Tables
      - Tuning Parameters for Client Applications That Access MapR-DB Binary Tables
        Though tuning client applications is generally not necessary, MapR does offer tuning parameters to change the behavior of client-side caching.
      - Building and Running MapReduce 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.

Building and Running MapReduce Applications That Access MapR-DB Binary Tables

The steps for building and running custom MapReduce applications that run against MapR-DB are the same as the steps for building and running custom MapReduce applications that run against Apache HBase. The steps are documented in the Apache HBase Reference Guide at http://hbase.apache.org/book.html#mapreduce.

However, you must use an HBase JAR file from MapR's Maven repository at http://repository.mapr.com/nexus/content/groups/mapr-public/org/apache/hbase/hbase-server/. The name of the JAR file that you use must contain the version of HBase and the version of MapR that you are using.

For example, if you are using HBase 0.98.9 and MapR version 4.1, you would use the file hbase-server-0.98.9-mapr-1503-m7-4.1.0.jar.