Table of Contents

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  1. Preface
  2. Introduction to Data Engineering Streaming
  3. Data Engineering Streaming Administration
  4. Sources in a Streaming Mapping
  5. Targets in a Streaming Mapping
  6. Streaming Mappings
  7. Window Transformation
  8. Appendix A: Connections
  9. Appendix B: Monitoring REST API Reference
  10. Appendix C: Sample Files

Sources in a Streaming Mapping on Hadoop

Sources in a Streaming Mapping on Hadoop

A streaming mapping that runs in the Hadoop environment can include file, database, and streaming sources.
You can create physical data objects to access the different types of data. Based on the type of source you read from, you can create the following data objects:
Amazon Kinesis
A physical data object that represents data in an Amazon Kinesis Stream. Create an Amazon Kinesis data object to read from an Amazon Kinesis Stream.
Azure Event Hubs
A physical data object that represents data in Microsoft Azure Event Hubs data streaming platform and event ingestion service.
Confluent Kafka
A physical data object that can access Kafka brokers and Confluent Kafka brokers. Create a Confluent Kafka data object to read from a Kafka broker or from a Confluent Kafka broker using schema registry.
HBase
A physical data object that represents data in an HBase resource. Create an HBase data object with a read operation to perform an uncached lookup on HBase data.
JMS
A physical data object that accesses a JMS server. Create a JMS data object to read from a JMS server.
Kafka
A physical data object that accesses a Kafka broker. Create a Kafka data object to read from a Kafka broker.
MapR Streams
A physical data object that represents data in a MapR Stream. Create a MapR Streams data object to read from a MapR Stream.