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
        Additional implemented C APIs
        C API for impersonation
        Specifying MapR-DB Binary Tables When Using the C APIs
        Installing the mapr-client Package
        Building and Launching Applications
        Sample Application for Accessing MapR-DB Tables
        Sample Application for Impersonation Support
        Thread-pool Settings for Improving Application Performance
        Support for HBase Java Filters by the MapR-DB C APIs
        Examples of using hb_get_set_filter() and hb_scanner_set_filter()
        Filter Format and Arguments
        Evaluation of Filters
        Compare Operators and Comparators for Comparison Filters
        Supported Filters
      - 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.

Support for HBase Java Filters by the MapR-DB C APIs

The hb_get_set_filter() and hb_scanner_set_filter() APIs filter the results of GET and SCAN operations. Their signatures are:

int32_t hb_get_set_filter(hb_get_t get, const byte_t *filter, const int32_t filterLen);
int32_t hb_scanner_set_filter(hb_scanner_t scanner, const byte_t *filter, const int32_t filterLen);

They both take filters that are passed as strings, as well as the length of these strings. MapR-DB parses the strings to construct filters.