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
      - Modes of replication
      - Supported replication topologies
      - Order of writes at replicas
      - Conflict resolution
      - Security
      - Licensing
      - Configuring MapR Clusters for Table Replication
        Configuring clusters for participation in replication topologies involves configuring two or more gateways on destination clusters and, if the clusters are secure, setting up secure communications between the clusters.
      - Setting Up Basic Master-Slave Replication
        In this topology, you replicate one way from source tables to replicas. The replicas can be in a remote cluster or in the cluster where the source tables are located.
      - Setting Up Variations of Master-Slave Replication
        These replication topologies are variations of master-slave replication.
      - Setting Up Replication Loops
        This replication topology is a variation of master-slave replication in which three or more clusters participate. Any one of the clusters can initiate the replication of an operation to each of the other clusters in succession.
      - Setting Up Multi-Master Replication
    - 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.

Replicating MapR-DB Binary Tables

You can replicate changes (puts and deletes) to the data in one table to another table that is in a separate cluster or within the same cluster. Replicate entire tables, specific column families, and specific columns.

Tables that data is replicated from are called source tables, while tables that data is replicated to are called replicas.

The maximum number of replicas that a source table can replicate to is 64.

The maximum number of source tables that a replica can accept updates from is 64.

Clusters that data is replicated from are called source clusters. Clusters that data is replicated to are called destination clusters. A single cluster can be both a source cluster and a destination cluster, depending on the replication configuration in which the cluster participates.

Replication takes place between source and destination clusters. However, source clusters do not send data to nodes in the destination cluster directly. The replication stream (the data being pushed to the replicas) is consumed by one or more MapR gateways in the destination cluster. The gateways receive the updates from the source cluster, batch them, and apply them to the replica tables. Multiple gateways serve the purpose of both load balancing and failover.

For more about gateways, see the topic “MapR gateways”.