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.
- MapR XD Distributed File and Object Store
  MapR XD Distributed File and Object Store is a distributed file system for data storage, data management, and data protection. MapR XD supports mounting and cluster access via NFS and FUSE-based POSIX clients (basic, platinum, or PACC) and also supports access and management via HDFS APIs.
  - File System
    Discusses the features of the MapR distributed file system and compares it to the Hadoop Distributed File System (HDFS).
    - Storage Pools
      Describes what storage pools are.
    - Containers and the CLDB
      Describes what containers are, and the role of the Container Location Database (CLDB) in managing them.
    - Volumes, Snapshots, and Mirrors
      Describes what Snapshots and Mirrors are, and the advantages of using them for replication.
      - Types of Volumes
        Lists the various types of volumes.
      - Volume Topology
        Describes what volume topology is, and the topology of replicas and mirrors.
      - Authorization with Volumes: Intelligent Policy Management
        Describes methods to manage volume permissions.
      - Mirror Volumes
        Provides a synopsis of what mirror volumes are and the mirroring process.
        Mirror Types
        Explains the available mirror types.
        Local Mirroring
        Describes the use of local mirror volumes. The local mirror volume and its source are present on the same cluster,
        Remote Mirroring
        Describes the concept and purpose of remote mirror volumes.
        Mirror Cascades
        Describes what mirror cascades are, and their advantages.
        Promotable Mirrors
        Explains the use of promotable mirrors for enhanced performance, data recovery, and business continuity.
        Incorporating Mirror Volumes into a Disaster Recovery Plan
        Lists the points to note when incorporating mirror volumes into a disaster recovery plan.
        Factors that Affect RTO
        Lists the factors that affect the Recovery Time Objective (RTO).
      - Data Tiering
        Provides an overview of what tiering is, its various types, and its working.
    - Multitenancy on File System
      Describes what multitenancy is and how tenant data is kept private for each tenant.
  - Direct Access NFS
    Describes the MapR direct access file system.
  - POSIX Clients
    Describes the usage of MapR POSIX clients.
  - Copying Data from Apache Hadoop to a MapR Cluster
    Describes the procedure to copy data from an Apache Hadoop to a MapR cluster.
  - HPE Ezmeral Data Fabric PACC
    This container gives you seamless access to MapR Data Platform cluster services.
  - MapR Control System
    Provides a brief description of the MapR Control System.
  - 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 Database
  MapR Database is an enterprise-grade, high-performance, NoSQL database management system that you can use for real-time, operational analytics.
- MapR Event Store For Apache Kafka
  MapR Event Store For Apache Kafka brings integrated publish and subscribe messaging to the MapR Converged Data Platform.
- MapR Data Fabric for Kubernetes
  This section describes the MapR Data Fabric for Kubernetes, which include the Container Storage Interface (CSI) driver for multiple container-orchestration systems, and the FlexVolume driver for Kubernetes.
- Cluster Management
  Provides a synopsis of the various cluster components and their management.
- Security
  Provides an overview of the MapR security features.
- YARN
- Client Connections
  The following sections describe how a client connects to local and remote MapR clusters.
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.
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.

Incorporating Mirror Volumes into a Disaster Recovery Plan

Lists the points to note when incorporating mirror volumes into a disaster recovery plan.

Mirroring critical data to a remote data center (with the ability to make mirror volumes into read-write volumes) addresses the following objectives:

Recovery Point Objective (RPO) - the age of the files you need to recover (and how much data you can afford to lose)
Recovery Time Objective (RTO) - how soon you need to have a working data center in order to maintain business continuity

In a typical scenario that employs remote mirrors, the contents of a source volume are mirrored to a mirror volume in a remote cluster at a frequency specified by the mirror schedule. At the start of each mirror operation, a snapshot is taken of the source volume's contents. The mirror operation takes some time to complete, and while the data is being copied from the snapshot to the mirror volume, more data is written to the source volume. This data will be captured during the next mirror operation. When each mirror operation completes, the contents of the mirror volume are identical to the contents of the source volume at the time of the snapshot. For subsequent mirror operations, only the incremental changes (additions and deletions) are copied to the mirror volume, which synchronizes its contents with the contents of the source volume at the time of the snapshot.

If the source cluster goes down, any data written to the source volume since the last successful mirror operation cannot be copied to the mirror. The amount of data lost depends on the number of write operations in the interval from the last successful mirror to the time the cluster goes down.