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).
  - 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.

Direct Access NFS

Describes the MapR direct access file system.

The MapR direct access file system enables real-time read/write data ﬂows using the Network File System (NFS) protocol. Standard applications and tools can directly access the MapR File System storage layer using NFS. Legacy systems can access data, and traditional file I/O operations work as expected on a conventional UNIX file system. A remote client can easily mount a MapR cluster over NFS to move data to and from the cluster. Application servers can write log ﬁles and other data directly to the MapR cluster’s storage layer instead of caching the data on an external direct or network-attached storage.

You can mount a MapR cluster directly through a network file system (NFS) from a Linux or a Mac client. When you mount a MapR cluster, applications can read and write data directly into the cluster with standard tools, applications, and scripts. MapR enables direct file modification and multiple concurrent reads and writes with POSIX semantics. For example, you can run a MapReduce application that outputs to a CSV file, and then import the CSV file directly into SQL through NFS.

MapR exports each cluster as the directory /mapr/<cluster name>. If you create a mount point with the local path /mapr, Hadoop FS paths and NFS paths to the cluster will be the same. This makes it easy to work on the same files through NFS and Hadoop. In a multi-cluster setting, the clusters share a single namespace. You can see them all by mounting the top-level /mapr directory.