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.
  - 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
    - Getting Started with Spark Interactive Shell
      After you have a basic understanding of Apache Spark and have it installed and running on your cluster, you can use it to load datasets, apply schemas, and query data from the Spark interactive shell.
    - Apache Spark Feature Support
      HPE Data Fabric supports most Apache Spark features. However, there are some exceptions.
    - Iceberg Support
      Describes support for Iceberg in HPE Data Fabric 7.6.x and later.
    - Spark Standalone
    - Spark on YARN
    - Spark configure.sh
      Starting in the EEP 4.0 release, run configure.sh -R to complete your Spark configuration when manually installing Spark or upgrading to a new version.
    - Spark SQL Thrift Server
      Spark SQL Thrift (Spark Thrift) was developed from Apache Hive HiveServer2 and operates like HiveSever2 Thrift server.
    - Spark History Server SSL
      Describes how to enable SSL for Spark History Server.
    - HPE Data Fabric Database Connectors for Apache Spark
      This section describes the HPE Data Fabric Database connectors that you can use with Apache Spark.
    - Integrating Spark
      This section includes the following topics about configuring Spark to work with other ecosystem components.
      - Integrate Spark-SQL (Spark 2.3.1 and later) with Avro
        You integrate Spark-SQL with Avro when you want to read and write Avro data. This information is for Spark 2.3.0 or later users.
      - Integrate Spark-SQL (Spark 1.6.1) with Avro
        You integrate Spark-SQL with Avro when you want to read and write Avro data. This information is for Spark 1.6.1 or earlier users.
      - Integrate Spark with HBase
        Integrate Spark with HBase or HPE Data Fabric Database when you want to run Spark jobs on HBase or HPE Data Fabric Database tables.
      - Integrate Spark-SQL (Spark 2.0.1 and later) with Hive
        You integrate Spark-SQL with Hive when you want to run Spark-SQL queries on Hive tables. This information is for Spark 2.0.1 or later users.
      - Integrate Spark-SQL (Spark 1.6.1) with Hive
        You integrate Spark-SQL with Hive when you want to run Spark-SQL queries on Hive tables. This information is for Spark 1.6.1 or earlier users.
      - Integrate Spark with HPE Data Fabric Streams
        Integrate Spark with MapR Streams to enable Spark to query HPE Data Fabric Streams for new messages at a given interval, process any new messages that are available, and also publish messages into HPE Data Fabric Streams.
      - Integrate Spark with R
        You integrate Spark with R when you want to run R programs as Spark jobs.
      - Integrate Spark with Kafka
        From EEP-5.0.0, Spark can be integrated with Kafka-1.0. You can configure a Spark application to produce Kafka messages.
    - Spark JDBC and ODBC Drivers
      Data Fabric provides JDBC and ODBC drivers so you can write SQL queries that access the Apache Spark data-processing engine. This section describes how to download the drivers, and install and configure them.
    - Spark API Changes
      This topic describes the public API changes that occurred for specific Spark versions.
    - Structured Streaming in Spark
      Starting in EEP 5.0.0, structured streaming is supported in Spark.
    - PAM Authentication for Spark
      Spark supports PAM authentication on secure Data Fabric clusters.
    - Read or Write LZO Compressed Data for Spark
      This topic provides details for reading or writing LZO compressed data for Spark.
    - Ports Used by Spark
      To run a Spark job from a client node, ephemeral ports should be opened in the cluster for the client from which you are running the Spark job.
    - ACL Configuration for Spark
      Starting in the EEP 6.0 release, the ACL configuration for Spark is disabled by default.
    - Helm Charts for Spark
      Starting with the EEP 9.4.0 release, Helm chart integration for Spark is supported. This topic provides detailed information about Data Fabric's Helm and Spark integration, including installation steps.
  - 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.

Integrate Spark with HBase

Integrate Spark with HBase or HPE Data Fabric Database when you want to run Spark jobs on HBase or HPE Data Fabric Database tables.

About this task

If you installed Spark with the MapR Installer, these steps are not required.

Procedure

Configure the HBase version in the /opt/mapr/spark/spark-<version>/mapr-util/compatibility.version file:
```
hbase_versions=<version>
```
The HBase version depends on the current EEP and MapR version that you are running.
If you want to create HBase tables with Spark, add the following property to hbase-site.xml:
```
<property>
hbase.table.sanity.checks</name>
<value>false</value>
</property>
```
On each Spark node, copy the hbase-site.xml to the {SPARK_HOME}/conf/ directory.

TIP
Starting in the EEP 7.0.0 release, you do not have to complete step 3. Running configure.sh copies the hbase-site.xml file to the Spark directory automatically.
Specify the hbase-site.xml file in the SPARK_HOME/conf/spark-defaults.conf file:
```
spark.yarn.dist.files SPARK_HOME/conf/hbase-site.xml
```
To verify the integration, complete the following steps:
1. Create an HBase or HPE Data Fabric Database table:
```
create '<table_name>' , '<column_family>'
```
2. Run the following command as the mapr user or as a user that mapr impersonates:
```
/opt/mapr/spark/spark-<spark_version>/bin/spark-submit --master <master> [--deploy-mode <deploy-mode>]  --class org.apache.hadoop.hbase.spark.example.rdd.HBaseBulkPutExample /opt/mapr/hbase/hbase-<hbase_versrion>/lib/hbase-spark-<hbase_version>-mapr.jar  <table_name>  <column_family>
```
  The master URL for the cluster is either spark://<host>:7077, yarn, or local (without deploy-mode). The deploy-mode is either client or cluster.
3. Check the data in the HBase or MapR-DB table:
```
hbase(main):001:0> scan '<table_name>'
```

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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	June 2026
Edition	8.0.0
Topic last updated	2020-01-13