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HPE Data Fabric 8.0.0 Software Documentation
  • About Release 8.0.0

    This site contains documentation for HPE Data Fabric release 8.0.0, including installation, configuration, administration, and reference content, as well as content for the associated ecosystem components and drivers.

  • 8.0.0 Installation

    This section contains information about installing HPE 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.

  • 8.0.0 Upgrade

    This section describes how to upgrade HPE Data Fabric software.

  • 8.0.0 Data Fabric

    HPE Data Fabric is the industry-leading data platform for AI and analytics that solves enterprise business needs.

  • 8.0.0 Administration

    This section describes how to manage the nodes and services that make up a cluster.

  • 8.0.0 Development

    This section contains information related to application development for Ezmeral ecosystem components and HPE 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 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 Data Fabric Database and Apps

      This section contains information about developing client applications for JSON and key-value tables.

    • Apache Kafka Wire Protocol Service

      HPE Data Fabric Streams supports Apache Kafka Wire Protocol Service. Apache Kafka Wire Protocol Service is a TCP/IP service that emulates a Kafka cluster backed by HPE Data Fabric Streams. The service makes it possible for Apache Kafka clients written in any programming language to access topics in HPE Data Fabric Streams.

    • Model Context Protocol (MCP)
    • HPE Data Fabric Streams and Apps

      HPE Data Fabric Streams brings integrated publish and subscribe messaging to HPE 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 Data Fabric.

      • Ecosystem Packs

      • Apache Airflow

        This topic provides an overview of Apache Airflow on HPE Data Fabric.

      • AsyncHBase

      • Cascading

      • Apache Drill
      • Apache Flink
      • Hadoop
      • HBase

      • HBase Client and HPE Data Fabric Database Binary Tables

      • HCatalog
      • Hive
      • HttpFS
      • Hue
      • Livy

        Apache Livy is primarily used to provide integration between Hue and Spark.

      • HPE Data Fabric Streams Clients and Tools

        Describes the supported HPE Data Fabric Streams tools and clients.

        • KSQL

          KSQL is an open-source streaming SQL engine that implements continuous, interactive queries.

        • Kafka Streams

          Kafka Streams is a programming library used for creating Java or Scala streaming applications and, specifically, building streaming applications that transform input topics into output topics.

        • Kafka REST Proxy

          The Kafka REST Proxy provides a RESTful interface to HPE Data Fabric Streams clusters to consume and produce messages and to perform administrative operations.

        • Kafka Connect

          Kafka Connect is a utility for streaming data between HPE Data Fabric Streams and other storage systems.

        • Kafka Schema Registry

          Kafka Schema Registry provides a RESTful interface for storing and retrieving schemas.

        • Structured Streaming in Spark

          Starting in EEP 5.0.0, structured streaming is supported in Spark.

          • Prerequisites for Using Structured Streaming in Spark

            To deploy a structured streaming application in Spark, you must create a Data Fabric Streams topic and install a Kafka client on all nodes in your cluster.

          • Using Structured Streaming to Create a Word Count Application

            The example in this section creates a dataset representing a stream of input lines from Kafka and prints out a running word count of the input lines to the console.

          • Writing a Structured Spark Stream to HPE Data Fabric Database JSON Table

            The example in this section writes a structured stream in Spark to HPE Data Fabric Database JSON table.

          • Writing a Spark Stream Word Count Application to HPE Data Fabric Database

            The example in this section writes a Spark stream word count application to HPE Data Fabric Database.

      • NiFi

        This topic provides an overview of Apache NiFi on HPE Data Fabric.

      • OTel

        This topic provides an overview of OpenTelemetry on HPE Data Fabric.

      • Apache Polaris
      • Ranger
      • Apache Spark
      • YARN
      • Zeppelin

    • Maven and the HPE Data Fabric

      This section discusses topics associated with Maven and the HPE Data Fabric.

    • Developer's Reference

      This section contains in-depth information for the developer.

    • API Documentation

      HPE Data Fabric supports public APIs for file system, HPE Data Fabric Database, and HPE 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.

Structured Streaming in Spark

Starting in EEP 5.0.0, structured streaming is supported in Spark.

Related Links

Spark streaming is integrated with HPE Data Fabric Streams for Apache Kafka.

  • Data Fabric Event Store For Apache Kafka Clients and Tools
  • Prerequisites for Using Structured Streaming in Spark
    To deploy a structured streaming application in Spark, you must create a Data Fabric Streams topic and install a Kafka client on all nodes in your cluster.
  • Using Structured Streaming to Create a Word Count Application
    The example in this section creates a dataset representing a stream of input lines from Kafka and prints out a running word count of the input lines to the console.
  • Writing a Structured Spark Stream to HPE Data Fabric Database JSON Table
    The example in this section writes a structured stream in Spark to HPE Data Fabric Database JSON table.
  • Writing a Spark Stream Word Count Application to HPE Data Fabric Database
    The example in this section writes a Spark stream word count application to HPE Data Fabric Database.
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HPE Data Fabric 8.0.0 Software Documentation
Abstract This site contains documentation for HPE Data Fabric Software version 8.0.0 including installation, configuration, administration, and reference content, as well as content for the associated bundled ecosystem components and drivers.
Published October 2025
Edition 8.0.0
Topic last updated2024-07-05
EZDF 8.0.x
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