HPE Ezmeral Data Fabric 6.2 is In Maintenance and transitions to "End of Maintenance" in June 2024. Please see the latest documentation.

About Release 6.2
This site contains documentation for HPE Ezmeral Data Fabric release 6.2 including installation, configuration, administration, and reference content, as well as content for the associated bundled ecosystem components and drivers.
6.2 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.
6.2 Data Fabric
HPE Ezmeral Data Fabric is the industry-leading data platform for AI and analytics that solves enterprise business needs.
6.2 Administration
This section describes how to manage the nodes and services that make up a cluster.
6.2 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.
  - Ezmeral 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
  - Impala
  - 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
  - Sentry
  - 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 Ezmeral Data Fabric supports most Apache Spark features. However, there are some exceptions.
    - 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 Ezmeral Data Fabric Database Connectors for Apache Spark
      This section describes the HPE Ezmeral Data Fabric Database connectors that you can use with Apache Spark.
      - Understanding the HPE Ezmeral Data Fabric Database OJAI Connector for Spark
        Using the HPE Ezmeral Data Fabric Database OJAI connector for Spark enables you build real-time and batch pipelines between your data and HPE Ezmeral Data Fabric Database JSON. Before getting started, it is important that you understand Spark terminology and workflow, system requirements and support, and OJAI connector and API features.
        Configuring the HPE Ezmeral Data Fabric Database OJAI Connector for Apache Spark
        Before using the HPE Ezmeral Data Fabric Database OJAI Connector for Apache Spark, you must edit the pom.xml file for your project.
        Loading Data from HPE Ezmeral Data Fabric Database Using the HPE Ezmeral Data Fabric Database OJAI Connector for Apache Spark
        The HPE Ezmeral Data Fabric Database OJAI Connector for Apache Spark supports loading data as an Apache Spark RDD. Starting in the EEP 4.0 release, the connector introduces support for Apache Spark DataFrames and Datasets. DataFrames and Datasets perform better than RDDs. Whether you load your HPE Ezmeral Data Fabric Database data as a DataFrame or Dataset depends on the APIs you prefer to use. It is also possible to convert an RDD to a DataFrame.
        Loading Data from HPE Ezmeral Data Fabric Database as an Apache Spark RDD
        Loading Data from HPE Ezmeral Data Fabric Database as an Apache Spark DataFrame
        Optimizing HPE Ezmeral Data Fabric Database Lookups in Spark Jobs
        The lookupFromMapRDB() API utilizes the primary and secondary indexes on a HPE Ezmeral Data Fabric Database table to optimize table lookups and outputs the results to an Apache Spark DataFrame.
        Loading Data into a DataFrame Using an Explicit Schema
        If you know the schema of your data, you can specify an explicit schema when loading a DataFrame.
        Loading Data into a DataFrame Using a Type Parameter
        If the structure of your data maps to a class in your application, you can specify a type parameter when loading into a DataFrame.
        Loading Data into a DataFrame Using Schema Inference
        If you do not know the schema of the data, you can use schema inference to load data into a DataFrame. This section describes how to use schema inference and restrictions that apply
        Type Mapping Between HPE Ezmeral Data Fabric Database JSON and DataFrames
        This table maps data types between HPE Ezmeral Data Fabric Database JSON OJAI and Apache Spark DataFrame.
        Loading Data from HPE Ezmeral Data Fabric Database as an Apache Spark Dataset
        Projection and Filter Pushdown with Apache Spark DataFrames and Datasets
        Projection and filter pushdown improve query performance. When you apply the select and filter methods on DataFrames and Datasets, the HPE Ezmeral Data Fabric Database OJAI Connector for Apache Spark pushes these elements to HPE Ezmeral Data Fabric Database where possible.
        Converting an Apache Spark RDD to an Apache Spark DataFrame
        When APIs are only available on an Apache Spark RDD but not an Apache Spark DataFrame, you can operate on the RDD and then convert it to a DataFrame.
        Working with Complex JSON Document Types
        The HPE Ezmeral Data Fabric Database OJAI Connector for Apache Spark provides APIs to process JSON documents loaded from HPE Ezmeral Data Fabric Database.
        Saving Data to a HPE Ezmeral Data Fabric Database JSON Table
        The HPE Ezmeral Data Fabric Database OJAI Connector for Apache Spark provides an API to save an Apache Spark RDD to a HPE Ezmeral Data Fabric Database JSON table. Starting in the EEP 4.0 release, the connector introduces support for saving Apache Spark DataFrames and DStreams to HPE Ezmeral Data Fabric Database JSON tables.
        Using Serialization with the HPE Ezmeral Data Fabric Database OJAI Connector for Apache Spark
        In the context of the HPE Ezmeral Data Fabric Database OJAI Connector for Apache Spark, serialization refers to the methods that read and write objects into bytes. This section describes how to configure your application to use a more efficient serializer.
      - HPE Ezmeral Data Fabric Database Binary Connector for Apache Spark
        This section describes the three main interaction points between Spark and HBase APIs and provides examples for each interaction point.
    - Integrating Spark
      This section includes the following topics about configuring Spark to work with other ecosystem components.
    - Spark JDBC and ODBC Drivers
      MapR 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 MapR 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.
  - 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.

Type Mapping Between HPE Ezmeral Data Fabric Database JSON and DataFrames

This table maps data types between HPE Ezmeral Data Fabric Database JSON OJAI and Apache Spark DataFrame.

NOTE Not all DataFrame data types are supported by HPE Ezmeral Data Fabric Database, for a list of supported data types, see JSON Documents.

OJAI Data Type	DataFrame Data Type
Boolean	BooleanType
String	StringType
Byte	ByteType
Short	ShortType
Int	IntegerType
Long	LongType
Float	FloatType
Double	DoubleType
Decimal	DecimalType
Date	DateType
Time	TimestampType
TimeStamp	TimeStampType
Interval	CalendarIntervalType
Binary	BinaryType
Map	StructType
Array	ArrayType

NOTE The OJAI Time data type is converted to a Spark TimestampType with the date set to the epoch date. Spark SQL does not support a TIME type.