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
    - Drill Tutorial
    - Drill-on-YARN
    - Configuring Drill
      Lists the MapR-specific configuration for Drill.
      - Adding a Drill Node to a Cluster
      - Configuring Drill Memory
        A system administrator can modify the amount of system memory that Warden allocates to the Drill service on each node in the warden.drill-bits.conf file. Drill users, with file permissions, can modify the amount of heap and direct memory allocated to the Drill service on each node in the drill-env.sh file.
      - Configuring the Parquet Block Size
        The default value for the store.parquet.block-size parameter is 268435456 (256 MB), the same size as MapR file system chunk sizes. In previous versions of Drill, the default value was 536870912 (512 MB).
      - Configuring Multiple Drill Clusters and Designating One Cluster as an OJAI Distributed Query Service
        As of MapR 6.0 and Drill 1.11, you can run operational queries through the OJAI Distributed Query Service, as well as analytical queries through Drill. If you want to run operational and analytical workloads in your MapR cluster, you must configure multiple Drill clusters within the MapR cluster and then configure a Drill cluster as the OJAI Distributed Query Service. Restricting each workload to its own cluster improves query performance.
        Step 1: Plan the Clusters
        Decide which nodes in the MapR cluster you want to run Drill and which nodes you want to run the OJAI Distributed Query Service.
        Step 2: Manually Install Drill on All Nodes
        Manually install Drill on all nodes, including the nodes designated to run the OJAI Distributed Query Service.
        Step 3: Define Node Topologies
        Node topologies restrict data to a designated set of nodes.
        Step 4: Create Volumes
        Volumes organize data and manage cluster performance. Create and mount a volume to each of the topologies (Drill clusters) you created.
        Step 5: Configure Multiple Drill Clusters
        Update the /opt/mapr/drill/drill-<version>/conf/drill-override.conf file on each Drill node that is part of a cluster with the cluster ID and a ZooKeeper entry to define the Drill cluster. Each Drill cluster should have a unique cluster ID and ZooKeeper entry to separate the clusters.
        Step 6: Configure Workspaces
        You must configure a workspace on one Drill node in each Drill cluster that points to the volume directory where data is stored. When you create a workspace, you must include the volume mount point.
        Step 7: Register a Drill Cluster as an OJAI Distributed Query Service
        You can select any of the configured Drill clusters to act as the OJAI Distributed Query Service provider for operational queries, by running the queryservice setconfig command.
      - Configuring a Multitenant Cluster
      - Configuring the ZooKeeper PStore Location
        By default, the ZooKeeper PStore offloads query profile data to maprfs:///apps/drill/profiles. You can override the default location in the drill-override.conf file.
      - Configuring HBase Persistent Storage Tables
        Starting in Drill 1.20.2 (EEP 9.0.0 on Core 7.1.0), you can configure Drill to persist query profile data to a table that is unaffected by the TTL duration.
      - Configuring cgroups to Control CPU Usage
        Starting in Drill 1.13, you can configure a Linux cgroup (control group) to enforce CPU limits on the Drillbit service running on a node. Linux cgroups enable you to limit system resources to defined user groups or processes. You can use the cgconfig service to configure a Drill cgroup to control CPU usage and then set the CPU limits for the Drill cgroup on each Drill node in the /etc/cgconfig.conf file.
    - Working with Drill
    - Securing Drill
      An administrator can install Drill with the default security configuration or manually configure custom security for Drill.
    - Drill Drivers
      HPE Ezmeral Data Fabric provides Drill ODBC and JDBC drivers that you can download and use to connect Drill to BI tools. The drivers are updated periodically to include support for new functionality in Drill.
    - Drill Configuration Files
      The Drill installation includes configuration files with start-up options that you can modify prior to starting Drill.
    - Monitoring Drill Metrics
    - Optimizing Queries with Indexes
      MapR Database provides a highly scalable key-value database platform on which you can run SQL queries using Drill. As of the 6.0 release of the MapR Data Platform, MapR Database natively supports indexes on secondary fields in JSON tables.
    - Drill Limitations
      Provides information about Drill limitations and solutions where applicable.
    - Vulnerability Reports
      Provides vulnerability information in relation to Drill.
  - Flume
  - HBase
  - HBase Client and MapR Database Binary Tables
  - HCatalog
  - Hive
  - 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.

Step 7: Register a Drill Cluster as an OJAI Distributed Query Service

You can select any of the configured Drill clusters to act as the OJAI Distributed Query Service provider for operational queries, by running the queryservice setconfig command.

When you register the Drill cluster as the OJAI Distributed Query Service, adjust the memory setting on each node. The default Drill memory setting of 13 GB is unnecessarily high for the OJAI Distributed Query Service, which only requires ~ 5 GB. You must restart the Drillbits after you update the memory settings.

Registering a Drill Cluster as the OJAI Distributed Query Service

To register a Drill Cluster as an OJAI Distributed Query Service, run the following command:

maprcli cluster queryservice setconfig -enabled true -clusterid <name_of_cluster> -storageplugin dfs -znode <zk_setting>

For example, drillbits2 and drill2 are the cluster ID and ZooKeeper settings used in examples in previous steps. For these configurations, the command is:

maprcli cluster queryservice setconfig -enabled true -clusterid drillbits2 -storageplugin dfs -znode drill2

See queryservice setconfig for more information about the command.

Configuring Memory for the OJAI Distributed Query Service

Modify the memory settings on each node in the OJAI Distributed Query Service cluster and then restart Drill. See Configuring Drill Memory for instructions.