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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
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.
JSON Tables
Documents are stored in JSON tables, which are tables in which every row is an OJAI document.

MapR 5.1 Documentation

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.
    - OJAI Documents
      An OJAI document is a tree of fields. Each field has a type and a value, and also has either a name or an array index. Field names are strings. The root of each document is a map.
    - JSON Tables
      Documents are stored in JSON tables, which are tables in which every row is an OJAI document.
      - Table Paths
        Tables are stored in the MapR file system. When providing the path to a table in the Java API, maprcli commands, or mapr dbshell, use these conventions.
      - Designing Row Keys for JSON Tables
        A row key identifies a row in a MapR-DB JSON table. You specify row keys in the _id field in JSON documents.
      - Configuring Maximum Row Sizes for JSON 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.
      - Tools for Working with JSON Tables
        There are four tools that you can use for creating and administering JSON tables in MapR-DB.
    - Creating, Reading, Updating, and Deleting Documents and Tables with the MapR-DB JSON Java API Library
      The basic tasks that you can perform with the API library involve the Admin, Document, DocumentMutation, QueryCondition, Table, and TableDescriptor interfaces.
    - Listing Tables with the MapR-DB JSON Java API Library
      List the JSON tables that are in a folder by calling an Admin object's listTables() method, passing as an argument the path of the folder.
    - Altering JSON Tables with the MapR-DB OJAI Java API Library
      Change the values of table attributes by using a TableDescriptor object and then passing that object to the Admin interface's altertable() method.
    - Deleting JSON Tables with the MapR-DB OJAI Java API Library
      Delete a JSON table by calling an Admin object's deleteTable() method, passing as an argument the path of the table to delete.
    - Compiling and Running Applications that Access JSON Tables and Documents
      You can compile applications that use the MapR-DB JSON API by using the required JAR file from the MapR Maven repository or from the MapR installation. Run applications with the mapr command.
    - Tuning Parameters for Client Applications That Access MapR-DB JSON Tables
      Though tuning client applications is generally not necessary, MapR does offer tuning parameters to change the behavior of client-side caching.
    - Loading Documents into JSON Tables
      There are three command-line utilities for loading documents into JSON tables: mapr copytable, mapr importtable (which works in conjunction with the mapr exporttable utility), and mapr importJSON
    - MapR-DB JSON MapReduce API Library
      This API library extends the Apache Hadoop MapReduce framework, so that you can write your own MapReduce applications to write data from one JSON table to another.
    - Column Families in JSON Tables
      JSON tables store data in column families, which are collections of fields that are stored together on disk.
    - Granting or Denying Access to Fields with Access-Control Expressions
      By using access-control expressions (ACEs), you can grant or deny access to fields and column families that are in JSON tables.
    - Getting Started with MapR-DB JSON and OJAI
  - MapR-DB as a Wide-Column Database
- 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.

JSON Tables

Documents are stored in JSON tables, which are tables in which every row is an OJAI document.

Each row is part of one column family (although you can create more, as described in Column Families). The value in the row is an OJAI document that is stored in a binary format. This format makes a number of optimizations to the document’s layout to make data access fast and efficient.

The OJAI documents that are in a table do not all have to have identical structures. It is possible to include in a single table any number of OJAI documents that have no common fields or that share a subset of fields.

For example, an online retailer might have documents such as these three documents in a single JSON table:

{
    "_id" : "4GGC859",
    "product_ID" : "4GGC859",
    "name" : "Thresher 1000",
    "brand" : "Careen",
    "category" : "Bicycle",
    "type" : "Road bicycle",
    "price" : 2949.99,

    "specifications" : {
        "size" : "55cm",
        "wheel_size" : "700c",
        "frameset" : {
            "frame" : "Carbon Enduro",
            "fork" : "Gabel 2"
         },
        "groupset" : {
            "chainset" : "Kette 230",
            "brake" : "Bremse FullStop"
	    },
        "wheelset" : {
	        "wheels" : "Rad Schnell 10",
	        "tyres" : "Reifen Pro"
        }
    }
}

{
    "_id" : "2DT3201",
    "product_ID" : "2DT3201",
    "name" : " Allegro SPD-SL 6800",
    "brand" : "Careen",
    "category" : "Pedals",
    "type" : "Components,
    "price" : 112.99,

    "features" : [
        "Low-profile design",
        "Floating SH11 cleats included"
    ],

    "specifications" : {
        "weight_per_pair" : "260g",
        "color" : "black"
    }
}

{
    "_id" : "3ML6758",
    "product_ID" : "3ML6758",
    "name" : "Trikot 24-LK",
    "brand" : "Careen",
    "category" : "Jersey",
    "type" : "Clothing",
    "price" : 76.99,

    "features" : [
        "Wicks away moisture.",
        "SPF-30",
        "Reflects light at night."
    ],

    "specifications" : {
        "sizes" : ["S","M","L","XL","XXL"],
        "colors" : [
            "white",
            "navy",
            "green"
        ]
     }
}

Only a subset of fields is common to all three documents. Each document has a different nested document in a field named specifications. Only two of the documents have arrays in the field features.