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
  - 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.
    - KSQL
      KSQL is an open-source streaming SQL engine that implements continuous, interactive queries.
    - Kafka Streams
      Kafka Streams is a programming library used for creating Java or Scala streaming applications and, specifically, building streaming applications that transform input topics into output topics.
    - Kafka REST Proxy
      The Kafka REST Proxy provides a RESTful interface to MapR Event Store For Apache Kafka clusters to consume and produce messages and to perform administrative operations.
    - Kafka Connect
      Kafka Connect is a utility for streaming data between MapR Event Store For Apache Kafka and other storage systems.
    - Kafka Schema Registry
      Kafka Schema Registry provides a RESTful interface for storing and retrieving schemas.
      - Building and Deploying Kafka Schema Registry
        To build and deploy Kafka Schema Registry with Maven, you must first install development versions of Kafka common and rest-utils utilities.
      - Kafka Schema Registry Limitations
        Describes the limitations related to the Kafka Schema Registry.
      - Kafka Schema Registry Use Cases
        Describes typical use cases to register and query a schema and serialize and deserialize data.
      - Managing Kafka Schema Registry
        Describes how to manage the internal stream for Kafka Schema Registry.
      - Enabling High Availability for Kafka Schema Registry
        You can enable high availability by installing multiple instances of schema registry on the same cluster.
      - Schema Registry Demos
        Provides demonstrations for using Kafka Schema Registry to store and retrieve schemas.
    - Structured Streaming in Spark
      Starting in EEP 5.0.0, structured streaming is supported in Spark.
  - 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.

Enabling High Availability for Kafka Schema Registry

You can enable high availability by installing multiple instances of schema registry on the same cluster.

About this task

One node in the cluster acts as the primary instance. Only the primary instance can publish writes to the underlying Kafka log. The primary node can also manage read requests.

All other secondary nodes manage only read requests. These nodes serve registration requests indirectly by forwarding them to the current primary node and returning any response supplied by the primary node.

Procedure

Install schema registry on several nodes. For installation instructions, see Installing Kafka Schema Registry.
Configure high availability for the ensemble of ZooKeeper nodes. You can find the steps for this in the open source documentation, section Clustered (Multi-Server) Setup.
Modify the schema registry configuration file on each node to specify the kafkastore.connection.url property with the ZooKeeper nodes that form the HA ensemble.
Run the configure.sh -R command on each schema registry node.