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6.0 Platform
Provides a brief overview of what the MapR data platform is and how you can use it to solve enterprise business needs.
MapR-DB
MapR-DB is an enterprise-grade, high-performance, NoSQL database management system. You can use it for real-time, operational analytics capabilities.
Secondary Indexes
Beginning with MapR 6.0, MapR-DB JSON natively supports secondary indexes on fields in JSON tables. Indexes provide you with flexible, high performance access to data stored in MapR-DB.
Secondary Index Concepts
Describes secondary index concepts, including use cases, types of indexes, types of queries that benefit from indexes, and how indexes are implemented.
Data Types and Secondary Index Fields
Secondary indexes support a specific set of data types. This section describes how indexed and included fields in secondary indexes behave for different categories of data types.

MapR 6.0 Documentation

6.0 Platform
Provides a brief overview of what the MapR data platform is and how you can use it to solve enterprise business needs.
- MapR-XD
- MapR-DB
  MapR-DB is an enterprise-grade, high-performance, NoSQL database management system. You can use it for real-time, operational analytics capabilities.
  - Architecture
    MapR-DB is an enterprise-grade, high performance, NoSQL (“Not Only SQL”) database management system. You can use it to add realtime, operational analytics capabilities to big data applications. As a multi-model NoSQL database, it supports both JSON document models and wide column data models.
  - Data Models
    MapR-DB can be used as both a document database and a wide-column database. As a document database, JSON documents are stored in MapR-DB JSON table. As a wide-column database, binary files are in stored MapR-DB binary tables.
  - Secondary Indexes
    Beginning with MapR 6.0, MapR-DB JSON natively supports secondary indexes on fields in JSON tables. Indexes provide you with flexible, high performance access to data stored in MapR-DB.
    - Secondary Index Concepts
      Describes secondary index concepts, including use cases, types of indexes, types of queries that benefit from indexes, and how indexes are implemented.
      - Uses for Secondary Indexes
        Describes typical use cases that can benefit from secondary indexes.
      - Types of Secondary Indexes
        MapR-DB JSON supports several index types, including simple indexes, composite indexes, hashed indexes, and indexes with casting. This section describes the properties of these indexes and the situations where each provides value.
      - Data Types and Secondary Index Fields
        Secondary indexes support a specific set of data types. This section describes how indexed and included fields in secondary indexes behave for different categories of data types.
      - Restrictions on Secondary Indexes
        This topic lists and describes the restrictions on secondary indexes. It is important for you to understand the type, size, field definition, option, and index use restrictions when defining and using secondary indexes.
      - Queries that Benefit from Secondary Indexes
        Secondary indexes benefit queries with filter conditions, ORDER BY clause, and projections.
      - Selection and Execution of Secondary Indexes
        This section provides an overview of secondary index selection and execution in MapR-DB JSON. It describes the variations in functionality, depending on the components you are using.
      - Implementation of Secondary Indexes
        This topic describes how MapR-DB implements secondary indexes. It provides an overview of basic architectural concepts and the rationale behind design choices.
    - Understanding the Secondary Index Workflow
      Describes the overall workflow for using secondary indexes. This includes the roles of different users and the workflow steps involved.
    - Designing Secondary Indexes
      It is important that you create secondary indexes that provide the most benefit to your MapR-DB JSON queries. This topic describes a general design approach that includes identifying query patterns, using common query patterns involving filters and ordering to determine which indexes to create, weighing the benefits of indexes against their update and storage costs, and taking into consideration index limitations.
  - Change Data Capture
    The Change Data Capture (CDC) system allows you to capture changes made to data records in MapR-DB tables (JSON or binary) and propagate them to a MapR-ES topic.
  - Table Replication
    Data in one table can be replicated to another table that is in the same cluster or in a separate cluster. This type of replication is in addition to the automatic replication that occurs with table regions within a volume.
  - Gateways for Indexing MapR-DB Data in Elasticsearch
    As of with MapR 6.0, MapR-DB Elastic Search integration capability is deprecated and no longer available in the MapR-DB product.
- MapR-ES
  MapR-ES brings integrated publish and subscribe messaging to the MapR Converged Data Platform.
- Cluster Management
- Security
- YARN
- Client Connections

Data Types and Secondary Index Fields

Secondary indexes support a specific set of data types. This section describes how indexed and included fields in secondary indexes behave for different categories of data types.

Data Types of Indexed Fields

Indexed fields in a secondary index must contain scalar data. Otherwise, if the field contains an array or nested document, MapR-DB excludes the corresponding document from the index. The indexed field can be a subfield of a nested document, provided the subfield is a scalar type. The indexed field cannot be an array element, even if the array element is scalar. See the table in the Scalar Data section of JSON Document Data Types for a list of scalar types.

The following table summarizes what MapR-DB supports, depending on the characteristics of the indexed field:

Characteristics of Indexed Field	Behavior
Field contains scalar data	Supported
Field path is a nested document subfield that contains scalar data	Supported
Field contains nested document data	Missing in index
Field contains array data	Missing in index
Field is an individual array element	Not supported

Data Types of Included Fields

There are no type restrictions on the included fields in an index.

Comparisons and Sorts on Indexed Fields

Comparisons and sorts across data types differ depending on whether the types are comparable or noncomparable. This is not specific to secondary indexes. But it impacts comparisons when using secondary indexes and the order MapR-DB stores data in an index. See Using Comparable JSON Document Data Types in Comparisons and Sorts and Using Noncomparable JSON Document Data Types in Comparisons and Sorts to learn which types fall into each category and to understand their behavior.

(Topic last modified: 2018-08-27)