About Release 7.0
This site contains documentation for HPE Ezmeral Data Fabric release 7.0, including installation, configuration, administration, and reference content, as well as content for the associated ecosystem components and drivers.
7.0 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.
7.0 Data Fabric
HPE Ezmeral Data Fabric is the industry-leading data platform for AI and analytics that solves enterprise business needs.
7.0 Administration
This section describes how to manage the nodes and services that make up a cluster.
7.0 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.
- Application Development Process
  Before you start developing applications on the HPE Ezmeral Data Fabric platform, consider how you will get the data into the platform, the storage format of the data, the type of processing or modeling that is required, and how the data will be accessed.
- File Store and Apps
  The following sections provide information about accessing the File Store with C and Java applications.
- HPE Ezmeral Data Fabric Database and Apps
  This section contains information about developing client applications for JSON and key-value tables.
- HPE Ezmeral Data Fabric Streams and Apps
  HPE Ezmeral Data Fabric Streams brings integrated publish and subscribe messaging to HPE Ezmeral Data Fabric.
- MapReduce and Apps
  This section contains information associated with developing YARN applications.
- Kubernetes Interfaces for Data Fabric
  This section describes how to leverage the capabilities of the Kubernetes Interfaces for Data Fabric.
- Ecosystem Components
  The following sections provide information about each open-source project that is supported by the HPE Ezmeral Data Fabric.
  - Ecosystem Packs
  - Apache Airflow
    This topic provides an overview of Apache Airflow on HPE Ezmeral Data Fabric.
  - AsyncHBase
  - Cascading
  - Apache Drill
  - Flume
  - Hadoop
  - HBase
  - HBase Client and HPE Ezmeral Data Fabric Database Binary Tables
  - HCatalog
  - Hive
  - HttpFS
  - Hue
  - Livy
    Apache Livy is primarily used to provide integration between Hue and Spark.
  - HPE Ezmeral Data Fabric Streams Clients and Tools
    Describes the supported HPE Ezmeral Data Fabric Streams tools and clients.
  - S3 Gateway
    The S3 gateway is a service that provides an S3-compatible interface to expose data in HPE Ezmeral Data Fabric as objects. The S3 gateway manages all inbound S3 API requests to put data into and get data out of cloud storage.
  - Oozie
  - Pig
  - Apache Spark
  - Sqoop
  - YARN
- Maven and the HPE Ezmeral Data Fabric
  This section discusses topics associated with Maven and the HPE Ezmeral Data Fabric.
- Developer's Reference
  This section contains in-depth information for the developer.
- API Documentation
  HPE Ezmeral Data Fabric supports public APIs for file system, HPE Ezmeral Data Fabric Database, and HPE Ezmeral Data Fabric Streams. These APIs are available for application-development purposes.
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.

Use Pig

IMPORTANT This component is deprecated. Hewlett Packard Enterprise recommends using an alternate product. Deprecated components are either in maintenance or have reached the end of their maintenance lifecycle. For more information, see Discontinued Ecosystem Components.

Once Pig is installed, the executable is located in /opt/mapr/pig/pig-<version>/bin/pig.

The following topics provide information about using Pig. You can also refer to the documentation available on the Apache Pig website.