Home
6.0 Development
This section contains information related to application development for ecosystem components and MapR products including MapR-DB (binary and JSON), MapR-FS, and MapR Streams.
Application Development Process
Before you start developing applications on MapR’s Converged Data Platform, consider how you will get the data onto the platform, the format it will be stored in, the type of processing or modeling that is required, and how the data will be accessed.
Step 2: Write Data to MapR
Depending on your use case, move existing data onto the platform or write data directly to the platform.

MapR 6.0 Documentation

6.0 Development
This section contains information related to application development for ecosystem components and MapR products including MapR-DB (binary and JSON), MapR-FS, and MapR Streams.
- Application Development Process
  Before you start developing applications on MapR’s Converged Data Platform, consider how you will get the data onto the platform, the format it will be stored in, the type of processing or modeling that is required, and how the data will be accessed.
  - Step 1: Select a Data Storage Format
    Consider the data format options and determine how you want to use to store your data.
  - Step 2: Write Data to MapR
    Depending on your use case, move existing data onto the platform or write data directly to the platform.
  - Step 3: Explore Ways to Work With the Data
    Once the data is on the MapR platform, explore the various features and components available on the platform and determine your path. You may want to access data in its initial format or perform some data modeling or processing prior to accessing the data.
  - Step 4: Set Up the Development Environment
    Before you start building the application, figure out how your the application will connect to the cluster and what the library dependencies and installation requirements are.
  - Step 5: Build the Application
    Start building an application! This section lists a few of the sample applications available on the MapR platform.
- MapR-FS and Apps
  The following sections provide information about accessing MapR-FS with C and Java applications.
- MapR-DB and Apps
  This section contains information about developing client applications for JSON and binary tables.
- MapR-ES and Apps
  MapR-ES brings integrated publish and subscribe messaging to the MapR Converged Data Platform.
- MapReduce and Apps
  This section contains information associated with developing YARN applications.
- MapR Data Science Refinery
  The MapR Data Science Refinery 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 FlexVolume Driver
  This section describes how to use and troubleshoot the MapR Data Fabric for Kubernetes FlexVolume Driver.
- Ecosystem Components
  The following sections provide information about each open source project that MapR supports.
- 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 supports public APIs for MapR-FS, MapR-DB, and MapR-ES. These APIs are available for application development purposes.

Step 2: Write Data to MapR

Depending on your use case, move existing data onto the platform or write data directly to the platform.

You can write batch data or streaming data to the MapR Converged Data Platform. Batch data refers to data that is already in a data-store while streaming data refers to the continuous flow of real-time messages that have yet to be written to a data-store. Streaming data is generally processed as it is received while batch data is processed after a set of data is written to the datastore. There are many ways to write batch and streaming data to the platform, the following sections provide a few examples.

Write Batch Data to the Platform

You can use an NFS client, hadoop command, or ecosystem components to write batch data to MapR-FS. Basic POSIX file system operations can be used to move data to MapR-FS. For example, you can use NFS clients, POSIX clients, or applications that utilize libraries such as java.io to access the filesystem. Hadoop commands and hdfs APIs can be used to add or update files on the MapR-FS. For example, you can use the hadoop distcp command to copy data from HDFS to MapR-FS. Hadoop Ecosystem components, such as Apache Flume, can also be used to push log files to MapR-FS.

You can also write, update, or delete batch data to MapR-DB tables. Applications can use the OJAI API to write to JSON tables or the HBase API to write to binary tables.

Write Streaming Data to the Platform

Write streaming event data as messages in MapR Stream topics using Kafka API or a REST client application. C, Java, or Python applications can produce messages to one or more topics in a MapR Stream. Additionally, applications written in any language can use the REST Proxy to produce messages to one or more topics in a MapR Stream. For example, a financial service application, written in Java, could produce messages about stock market activity to a MapR Stream topic.