About Release 7.9.0
This site contains documentation for HPE Ezmeral Data Fabric release 7.9.0, including installation, configuration, administration, and reference content, as well as content for the associated ecosystem components and drivers.
7.9.0 Installation
This section contains information about installing and upgrading HPE Ezmeral Data Fabric software. It also contains information about how to migrate data and applications from an Apache Hadoop cluster to a HPE Ezmeral Data Fabric cluster.
7.9.0 Data Fabric
HPE Ezmeral Data Fabric is the industry-leading data platform for AI and analytics that solves enterprise business needs.
- HPE Ezmeral Data Fabric File Store
  HPE Ezmeral Data Fabric File Store is a distributed file system for data storage, data management, and data protection. File Store supports mounting and cluster access via NFS and FUSE-based POSIX clients (basic, platinum, or PACC) and also supports access and management via HDFS APIs.
- HPE Ezmeral Data Fabric Object Store
  The HPE Ezmeral Data Fabric Object Store is a native object storage solution that efficiently stores objects and metadata for optimized access.
- HPE Ezmeral Data Fabric Database
  HPE Ezmeral Data Fabric Database is an enterprise-grade, high-performance, NoSQL database management system that you can use for real-time, operational analytics.
  - Architecture
    HPE Ezmeral Data Fabric Database 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 key-value data models.
  - Data Models
    HPE Ezmeral Data Fabric Database can be used as both a document database and a column-oriented database. As a document database, JSON documents are stored in HPE Ezmeral Data Fabric Database JSON table. As a column-oriented database, binary files are in stored HPE Ezmeral Data Fabric Database binary tables.
  - Secondary Indexes
    Beginning with data-fabric 6.0, HPE Ezmeral Data Fabric Database JSON natively supports secondary indexes on fields in JSON tables. Indexes provide you with flexible, high performance access to data stored in HPE Ezmeral Data Fabric Database.
    - 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
        HPE Ezmeral Data Fabric Database 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 various 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 HPE Ezmeral Data Fabric Database JSON. It describes the variations in functionality, depending on the components you are using.
      - Implementation of Secondary Indexes
        This topic describes how HPE Ezmeral Data Fabric Database 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 HPE Ezmeral Data Fabric Database 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 HPE Ezmeral Data Fabric Database tables (JSON or binary) and propagate them to a HPE Ezmeral Data Fabric Streams topic.
  - Table Replication
    You can replicate data in one table 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 HPE Ezmeral Data Fabric Database Data in Elasticsearch
    As of data-fabric 6.0, HPE Ezmeral Data Fabric Database Elastic Search integration capability is deprecated and no longer available in the HPE Ezmeral Data Fabric Database product.
- HPE Ezmeral Data Fabric Streams
  HPE Ezmeral Data Fabric Streams brings integrated publish and subscribe messaging to the HPE Ezmeral Data Fabric.
- HPE Ezmeral Unified Analytics
  Describes the HPE Ezmeral Unified Analytics Software and provides a link to more information.
- Kubernetes Interfaces for Data Fabric
  This section describes the Kubernetes Interfaces for Data Fabric, which include the Container Storage Interface (CSI) driver for multiple container-orchestration systems, and the FlexVolume driver for Kubernetes.
- Cluster Management
  Provides a synopsis of the various cluster components and their management.
- Performance
  Describes how to tune system performance, manage RDMA, and optimize CLDB tables.
- Security
  Provides an overview of the Data Fabric security features.
- YARN
- Client Connections
  The following sections describe how a client connects to local and remote data-fabric clusters.
7.9.0 Administration
This section describes how to manage the nodes and services that make up a cluster.
7.9.0 Development
This section contains information related to application development for Ezmeral ecosystem components and HPE Ezmeral Data Fabric products, including the file system, Database (Key-Value and JSON), and Event Streams.
Other Docs
This section contains release-independent information, including: Installer documentation, Ecosystem release notes, interoperability matrices, security vulnerabilities, and links to other data-fabric version documentation.
Glossary
Definitions for commonly used terms in MapR Converged Data Platform environments.

Uses for Secondary Indexes

Describes typical use cases that can benefit from secondary indexes.

Operational Analytics

Operational analytics require highly scalable, highly responsive, interactive, user-facing applications.

Application developers can use OJAI API to build richer and more interactive applications. This enables users to retrieve data on a variety of columns in HPE Ezmeral Data Fabric Database JSON tables in a flexible way. In addition to processing queries, OJAI also enables them to sort on columns and paginate or restrict the results. The applications can be operational applications or operational analytical applications. For both categories, the level of user interactivity and query complexity is high. Sample applications include Customer 360, expense reporting systems, game management, product catalogs, and a variety of domain-specific analytics as service applications.

Operational BI and Dashboards

Typical analytical workloads query snapshots of read-only data. Querying against HPE Ezmeral Data Fabric Database using Drill SQL enables these applications to get insights into the latest, changing data. Moreover, operational analytical queries usually access only a subset of fields from a table, often aggregating the data on a variety of dimensions and time ranges. Secondary indexes are extremely useful in these use cases. They improve the performance of well known query patterns.

Self-service Data Exploration

Users want to use their favorite BI reporting tool to issue ad-hoc queries against HPE Ezmeral Data Fabric Database JSON tables. They can achieve a simple, high performing data exploration experience using HPE Ezmeral Data Fabric Database and Drill SQL, while leveraging the capabilities of both. Using the HPE Ezmeral Data Fabric Database document model provides end to end JSON flexibility at the data storage level. Using Drill SQL provides dynamic schema discovery.

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HPE Ezmeral Data Fabric – Customer-Managed 7.9.0 Documentation
Abstract	This site contains documentation for the customer-managed platform of the HPE Ezmeral Data Fabric version 7.9.0 including installation, configuration, administration, and reference content, as well as content for the associated bundled ecosystem components and drivers.
Published	November 2024
Edition	7.9.0