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.
      - Architecture of Kafka Connect
        Kafka Connect for MapR Event Store For Apache Kafka has the following major models in its design: connector, worker, and data.
      - Connectors, Tasks, and Workers
        Describes how Kafka Connect for MapR Event Store For Apache Kafka works and how connectors, tasks, offsets, and workers are associated.
      - Connector Configuration
        This section describes how and where connectors are configured.
      - Worker Configuration
        This section describes how and where to configure workers.
      - JDBC Connector
        The topics describes the JDBC connector, drivers, and configuration parameters.
      - Managing Kafka Connect Services
        Lists the commands you use to start, stop, or restart Kafka Connect Services
      - HDFS Connector
        These topics describe the Kafka Connect for MapR Event Store For Apache Kafka HDFS connector, driver, and configuration parameters.
      - REST API
        The Kafka Connect REST API for MapR Event Store For Apache Kafka manages connectors.
        GET /connectors
        Gets a list of active connectors.
        POST /connectors
        Creates a new connector, returning the current connector information if successful.
        GET /connector/(string:name)
        Gets information about a specific connector.
        GET /connectors/(string:name)/config
        Gets the configuration for the connector.
        PUT /connectors/(string:name)/config
        Creates a new connector using the given configuration or updates the configuration for an existing connector. Returns information about the connector after the change has been made.
        GET /connectors/(string:name)/tasks
        Gets a list of tasks currently running for the connector.
        DELETE /connectors/(string:name)/
        Deletes a connector by halting all tasks and deleting its configuration.
        GET /connector-plugins
        Lists the connector plugins available on this worker.
        POST /connectors/(string:name)/restart
        Restarts a connector and its tasks.
        GET /connectors/(string:name)/tasks/(int:taskId)/status
        Gets the status for a task.
        POST /connectors/(string:name)/tasks/(int:number of tasks)/restart
        Restarts an individual task.
        PUT /connectors/(string:name)/pause
        Pauses the connector and its tasks, which stops message processing until the connector is resumed.
        PUT /connectors/(string:name)/resume
        Resumes a paused connector or do nothing if the connector is not paused.
        GET /connectors/(string:name)/status
        Gets current status of the connector, including whether it is running, failed or paused, which worker it is assigned to, error information if it has failed, and the state of all its tasks.
      - Saving Kafka Connect Configurations
        Describes how Kafka Connect configurations are saved during an upgrade.
    - Kafka Schema Registry
      Kafka Schema Registry provides a RESTful interface for storing and retrieving 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.

GET /connectors/(string:name)/tasks

Gets a list of tasks currently running for the connector.

Description

Table 1. Parameters
Parameters	Description
tasks (array)	List of active task configurations created by the connector.
tasks[i].id (string)	ID of the task.
tasks[i].id.connector (string)	Name of the connector that the task belongs to.
tasks[i].id.task (int)	Task ID within the connector.
tasks[i].config (map)	Configuration parameters for the task.

Syntax

http://<host>:8083/connectors/<connector_name>/tasks

Request Example

GET /connectors/hdfs-sink-connector/tasks HTTP/1.1 Host: connect.example.com

Response Example

HTTP/1.1 200 OK  
[     {         
          "task.class": "io.confluent.connect.hdfs.HdfsSinkTask",         
          "topics": "test-topic",         
          "hdfs.url": "hdfs://fakehost:9000",         
          "hadoop.conf.dir": "/opt/hadoop/conf",         
          "hadoop.home": "/opt/hadoop",         
          "flush.size": "100",         
          "rotate.interval.ms": "1000"     },     
       {         
          "task.class": "io.confluent.connect.hdfs.HdfsSinkTask",         
          "topics": "test-topic",         
          "hdfs.url": "hdfs://fakehost:9000",         
          "hadoop.conf.dir": "/opt/hadoop/conf",         
          "hadoop.home": "/opt/hadoop",         
          "flush.size": "100",         
          "rotate.interval.ms": "1000"     } 
]