HDFS to Kafka Sync App


This application reads lines from configured HDFS path and writes each line as a message in configured Apache Kafka topic. This document illustrates step by step guide to launch, configure, customize this application.The source code is available at: https://github.com/DataTorrent/app-templates/tree/master/hdfs-to-kafka-sync.

Please send feedback or feature requests to: feedback@datatorrent.com

Steps to launch application

  1. Click on the AppHub tab from the top navigation bar. AppHub link from top navigation bar

  2. Page listing the applications available on AppHub is displayed. Search for Kafka to see all applications related to Kafka. AppHub search for Kafka Click on import button for HDFS to Kafka Sync App

  3. Notification is displayed on the top right corner after application package is successfully imported. App import Notification

  4. Click on the link in the notification which navigates to the page for this application package. App details page Detailed information about the application package like version, last modified time, and short description is available on this page. Click on launch button for HDFS to Kafka Sync application.

  5. Launch HDFS-to-Kafka-Sync dialogue is displayed. One can configure name of this instance of the application from this dialogue. Launch dialogue

  6. Select Use saved configuration option. This displays list of pre-saved configurations. Please select sandbox-memory-conf.xml or cluster-memory-conf.xml depending on whether your environment is the DataTorrent sandbox, or other cluster. Select saved configuration

  7. Select Specify custom properties option. Click on add default properties button. Specify custom properties

  8. This a expands key-value editor pre-populated with mandatory properties for this application. Change values as needed. Properties editor For example, suppose we wish to process lines from all files in /user/appuser/input from source-cluster and send the output to kafka on kafka-server-node with topic test. Properties should be set as follows:

    name value
    dt.operator.kafkaOutput.prop.producerProperties serializer.class=kafka.serializer. DefaultEncoder,
    producer.type= async,
    metadata.broker. list=kafka-server-node:9092
    dt.operator.kafkaOutput.prop.topic test
    dt.operator.recordReader.prop.files /user/appuser/input

    Details about configuration options are available in Configuration options section.

  9. Click on Launch button on lower right corner to launch the application. Notification is displayed on the top right corner after application is launched successfully and includes the Application ID which can be used to monitor this instance and find its logs. Application launch notification

  10. Click on the Monitor tab from the top navigation bar. Monitor tab

  11. A page listing all running applications is displayed. Search for current application based on name or application id or any other relevant field. Click on the application name or id to navigate to application instance details page. Apps monitor listing

  12. Application instance details page shows key metrics for monitoring the application status. The logical tab shows application DAG, Stram events, operator status based on logical operators, stream status, and a chart with key metrics. Logical tab

  13. Click on the physical tab to look at the status of physical instances of the operator, containers etc. Physical tab

Configuration options

Mandatory properties

End user must specify the values for these properties.

Property Description Type Example
dt.operator.kafkaOutput. prop.producerProperties Properties for Kafka producer Comma separated String serializer.class=kafka.serializer.DefaultEncoder, producer.type=async,
dt.operator.kafkaOutput .prop.topic Kafka topic for output records String test
HDFS path for input file or directory String
  • /user/appuser/input/directory1
  • /user/appuser/input/file2.log
  • hdfs://node1.corp1.com/user/appuser/input

Advanced properties

There are pre-saved configurations based on the application environment. Recommended settings for datatorrent sandbox edition are in sandbox-memory-conf.xml and for a cluster environment in cluster-memory-conf.xml.

Property Description Type Cluster default Sandbox default


Minimum number of BlockReader partitions for parallel reading. int 1 1


Maximum number of BlockReader partitions for parallel reading. int 16 1


Partitoning for Kafka output operator String See (1) See (2)
  1. Cluster default: com.datatorrent.common.partitioner.StatelessPartitioner:16
  2. Sandbox default: com.datatorrent.common.partitioner.StatelessPartitioner:1

You can override default values for advanced properties by specifying custom values for these properties in the step specify custom property step mentioned in steps to launch an application.

Steps to customize the application

  1. Make sure you have following utilities installed on your machine and available on PATH in environment variables

  2. Use following command to clone the examples repository:

    git clone git@github.com:DataTorrent/app-templates.git

  3. Change directory to examples/tutorials/hdfs-to-kafka-sync:

    cd examples/tutorials/hdfs-to-kafka-sync

  4. Import this maven project in your favorite IDE (e.g. eclipse).

  5. Change the source code as per your requirements. Some tips are given as commented blocks in Application.java for this project.

  6. Make respective changes in the test case and properties.xml based on your environment.

  7. Compile this project using maven: mvn clean package

    This will generate the application package with the .apa extension inside the target directory.

  8. Go to DataTorrent UI Management console on web browser. Click on the Develop tab from the top navigation bar. Develop tab

  9. Click on upload package button and upload the generated .apa file. Upload

  10. Application package page is shown with the listing of all packages. Click on the Launch button for the uploaded application package. Follow the steps for launching an application.