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.
- Administering Users and Clusters
  Lists topics that help manage a MapR cluster.
- Administering Nodes
  Provides a synopsis of managing nodes in a cluster.
- Administering Volumes
  This section provide information about how to organize and manage data using volumes, a unique feature of MapR clusters.
- Administering Files and Directories
- Administering Tables
  Administration of the MapR Database is done primarily via the command line (maprcli) or with the Managed Control System (MCS). Regardless of whether the MapR Database table is used for binary files or JSON documents, the same types of commands are used with slightly different parameter options. MapR Database administration is associated with tables, columns and column families, and table regions.
- Administering Streams
- Administering MapR Gateways
  A MapR gateway mediates one-way communication between a source MapR cluster and a destination cluster. You can replicate MapR Database tables (binary and JSON) and MapR Event Store For Apache Kafka streams. MapR gateways also apply updates from JSON tables to their secondary indexes and propagate Change Data Capture (CDC) logs.
- Administering Services
- Monitoring the Cluster
  This section describes how to monitor the health and performance of a MapR cluster.
  - Monitoring Using the Control System and the CLI
    Describes the Overview page in the Control System, which displays information about the cluster.
  - Using MapR Data Platform Monitoring (Spyglass Initiative)
    MapR Data Platform Monitoring (part of the Spyglass initiative) provides the ability to collect, store, and view metrics and logs for nodes, services, and jobs/applications.
    - MapR Monitoring Architecture
      MapR Monitoring integrates with open-source components to collect, aggregate, store, and visualize metrics and logs.
    - Metric Collection
      Metrics are collected from each node in the cluster so that administrators can use the data to monitor the cluster. In general, the collectd service collects metrics every 10 seconds. The exception is volume metrics which are collected every 10 minutes.
    - Configure the OpenTSDB Service Heap Size
      By default, the OpenTSDB service is configured to use a default heap size of 6 gigabytes. The default heap size can be adjusted by modifying certain configuration files.
    - Metric Visualization
      Use dashboards to visualize metrics across multiple nodes and clusters.
    - Log Collection
      Fluentd collects log events from each node in the cluster and stores them in a centralized location so that administrators can search the logs when troubleshooting issues in the cluster. The process that fluentd uses to parse and send log events to Elasticsearch differs based on the formatting of log events in each log file.
    - Log Aggregation and Storage
      Fluentd uses a round-robin approach when writing logs to Elasticsearch nodes. If an Elasticsearch node in unavailable, Fluentd can fail over log storage to another Elasticsearch node.
      - Configure Log Retention
        By default, Elasticsearch indexes 2 days of logs. Based on your requirements, you can configure a different retention period for Elasticsearch.
      - Configure Log Rotation Policies for MapR Monitoring Services
        New log files are created based on the log rotation policy. By default, each MapR Monitoring service has a log rotation policy. In most cases, you can change the policy based on your requirements.
      - Configure the Elasticsearch Service Heap Size
        The Elasticsearch service is memory-intensive. By default, the Elasticsearch service is configured to use a minimum and maximum heap size of 2 GB. You can override these default values by making changes in the Elasticsearch Warden configuration file and the jvm.options file. Restart Elasticsearch after you modify the settings.
      - Configure Fluentd Services to Write to Elasticsearch Nodes on the Same Rack
        On clusters with high-density racks, ensure you have at least one Elasticsearch server per rack and configure each Fluentd service to write to Elasticsearch nodes that run on the same rack as the Fluentd service. This configuration minimizes the impact of log aggregation on other processes that run on the cluster and in particular, minimizes the amount of backbone bandwidth used by the log aggregation.
      - 60-mapr_elasticsearch.conf
      - 60-mapr_fluentd.conf
    - Log Visualization
      Use dashboards to visualize the logs across multiple nodes and clusters.
    - MapR Monitoring Tips and Troubleshooting
      Lists the nuances of monitoring clusters.
    - Reconfiguring MapR Monitoring
      Changes to an existing cluster, such as the addition of services, may require additional steps to enable the collection of metrics and logs.
- Configuring Security
  Describes how to configure security and manage secure clusters.
- Managing Secure Clusters
  Provides procedures that will enable you to use MapR clusters securely.
- Administering the MapR Data Access Gateway
  The MapR Data Access Gateway is a service that acts as a proxy and gateway for translating requests between lightweight client applications and the MapR cluster. This section describes considerations when upgrading the service, how to modify configuration settings, and how to administer and manage the service.
- Planning for High Availability
- Administrator's Reference
  This section contains in-depth reference information for the administrator.
- Troubleshooting Cluster Administration
  Lists the common errors and their solutions.
- Best Practices for Backing Up MapR Information
  Lists the best practices and performance considerations to follow when backing up MapR information.
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.
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.

60-mapr_elasticsearch.conf

The /etc/sysctl.d/60-mapr_elasticsearch.conf file is created when you install Elasticsearch. This file specifies a Docker host setting for Elasticsearch.

The vm.max_map_count setting is a tuning parameter that limits the number of discrete mapped memory areas for the Linux VM:

Example

vm.max_map_count=262144

For more information about the max_map_count parameter, see the Linux Kernel documentation.