HPE Ezmeral Data Fabric 6.1.x is In Maintenance and transitions to "End of Maintenance" in June 2024. Please see the latest documentation.

About MapR 6.1
This site contains the main documentation for Version 6.1 of the MapR Converged Data Platform, including installation, configuration, administration, and reference information.
6.1 Installation
This section contains information about installing and upgrading MapR software. It also contains information about how to migrate data and applications from an Apache Hadoop cluster to a MapR cluster.
6.1 MapR Data Platform
MapR Data Platform is the industry-leading data platform for AI and analytics that solves enterprise business needs.
6.1 Administration
This section describes how to manage the nodes and services that make up a cluster.
6.1 Development
This section contains information related to application development for Ezmeral ecosystem components and MapR Data Platform products, including the file system, Database (Key-Value and JSON), and Event Streams.
- Application Development Process
  Before you start developing applications on the MapR Data Platform 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.
- MapR XD and Apps
  The following sections provide information about accessing the MapR XD with C and Java applications.
- MapR Database and Apps
  This section contains information about developing client applications for JSON and key-value tables.
- MapR Event Store For Apache Kafka and Apps
  MapR Event Store For Apache Kafka brings integrated publish and subscribe messaging to MapR Data Platform.
- MapReduce and Apps
  This section contains information associated with developing YARN applications.
- MapR Data Science Refinery
  The MapR Data Science Refinery product is an easy-to-deploy and scalable data science toolkit with native access to all platform assets and superior out-of-the-box security.
- MapR Data Fabric for Kubernetes
  This section describes how to leverage the capabilities of the MapR Data Fabric for Kubernetes.
- Ecosystem Components
  The following sections provide information about each open-source project that is supported by the MapR Data Platform.
  - Ezmeral Ecosystem Packs
  - AsyncHBase
  - Cascading
  - Apache Drill
  - Flume
  - HBase
  - HBase Client and MapR Database Binary Tables
  - HCatalog
  - Hive
    - Getting Started with Hive
    - Configuring Hive
    - Integrating Hive
    - Managing Hive Services
    - Connecting to Hive
    - Enabling High Availability for Hive
      This section describes how to enable High Availability for HiveServer2 and HiveMetastore.
    - Hive Features in MapR Data Platform
      Describes MapR Data Platform-specific features in Hive.
    - Hive 2.3 API Changes
      This topic describes the public API changes that occurred between Hive 2.1 EEP 5.0.0 and Hive 2.3 EEP 6.0.0.
    - Hive 2.1 API
    - Troubleshooting Hive and Tez
    - Hive Logging
      This section describes Hive logging for Hive 2.1 and later releases and includes information about log splitting.
  - HttpFS
  - Hue
  - Impala
  - Livy
    Apache Livy is primarily used to provide integration between Hue and Spark.
  - MapR Event Store For Apache Kafka Clients and Tools
    Describes the supported MapR Event Store For Apache Kafka tools and clients.
  - S3 Gateway
    The S3 gateway is a service that provides an S3-compatible interface to expose data in MapR Data Platform as objects. The S3 gateway manages all inbound S3 API requests to put data into and get data out of cloud storage.
  - Myriad
  - Oozie
  - Pig
  - Sentry
  - Apache Spark
  - Sqoop
  - YARN
  - Zeppelin
- Maven and MapR
  This section discusses topics associated with Maven and MapR.
- Developer's Reference
  This section contains in-depth information for the developer.
- API Documentation
  MapR Data Platform supports public APIs for MapR File System, MapR Database, and MapR Event Store For Apache Kafka. These APIs are available for application-development purposes.
Other Docs
This section contains release-independent information, including: MapR Installer documentation, Ecosystem release notes, interoperability matrices, security vulnerabilities, and links to other MapR version documentation.
Glossary
Definitions for commonly used terms in MapR Converged Data Platform environments.

Setting the Execution Engine

Consider the following definitions:

Runtime: execution time of job.
Session time: time from the start of Hive shell or Beeline until you exit.

You can change the execution engine during a session (session time), but not while executing job in the session (runtime). If you specify the execution engine before starting the job, it will override the hive.execution.engine property in hive-site.xml file. For example, to specify the execution engine:

hive> set hive.execution.engine=tez;
hive> *perform some query here*

If you open another session of hive shell or beeline, you will not see the setting in the session from before and you can set needed properties for every session.

MapR Technologies highly recommends configuring Tez as an execution engine instead of MR execution engine. MR execution engine is deprecated in Hive.

If you are currently using the MR execution engine for accessing Hive CLI and HS2, Hive will throw the following warning message:

Hive-on-MR is deprecated in Hive 2 and may not be available in the future versions. Consider using a different execution engine (i.e. spark, tez) or using Hive 1.X releases.

To install and configure Tez as an execution engine for Hive, see Configuring Hive and Tez.