33ee66e23a
* [Bug fix] fix IO pipe issue that causes a blocking issue on send calls * [Bug fix] fix broken TCP connection issue that causes prolonged delay in receiving events * [Configuration] provide a configuration knob to specify whether an epoch receiver should be used. Default value is true. * [Tracing] add a Spark task ID to log messages and emit latency data for receive calls |
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| FAQ.md | ||
| LICENSE | ||
| README.md | ||
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| pom.xml | ||
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README.md
Azure Event Hubs Connector for Apache Spark
This is the source code of the Azure Event Hubs Connector for Apache Spark.
Azure Event Hubs is a highly scalable publish-subscribe service that can ingest millions of events per second and stream them into multiple applications.
Spark Streaming and Structured Streaming are scalable and fault-tolerant stream processing engines that allow users to process huge amounts of data using
complex algorithms expressed with high-level functions like map, reduce, join, and window. This data can then be pushed to
filesystems, databases, or even back to Event Hubs.
By making Event Hubs and Spark easier to use together, we hope this connector makes building scalable, fault-tolerant applications easier for our users.
Latest Releases
Spark
| Spark Version | Package Name | Package Version |
|---|---|---|
| Spark 2.4 | azure-eventhubs-spark_2.11 |  |
| Spark 2.3 | azure-eventhubs-spark_2.11 | |
| Spark 2.2 | azure-eventhubs-spark_2.11 |  |
| Spark 2.1 | azure-eventhubs-spark_2.11 | |
Databricks
| Databricks Runtime Version | Artifact Id | Package Version |
|---|---|---|
| Databricks Runtime 5.X | azure-eventhubs-spark_2.11 | |
| Databricks Runtime 4.X | azure-eventhubs-spark_2.11 | |
| Databricks Runtime 3.5 | azure-eventhubs-spark_2.11 | |
Roadmap
There is an open issue for each planned feature/enhancement.
Usage
Linking
For Scala/Java applications using SBT/Maven project definitions, link your application with the artifact below. Note: See Latest Releases to find the correct artifiact for your version of Apache Spark (or Databricks)!
groupId = com.microsoft.azure
artifactId = azure-eventhubs-spark_2.11
version = 2.3.13
Documentation
Documentation for our connector can be found here. The integration guides there contain all the information you need to use this library.
If you're new to Apache Spark and/or Event Hubs, then we highly recommend reading their documentation first. You can read Event Hubs documentation here, documentation for Spark Streaming here, and, the last but not least, Structured Streaming here.
FAQ
We maintain an FAQ - reach out to us via gitter if you think anything needs to be added or clarified!
Further Assistance
If you need additional assistance, please don't hesitate to ask! General questions and discussion should happen on our gitter chat. Please open an issue for bug reports and feature requests! Feedback, feature requests, bug reports, etc are all welcomed!
Contributing
If you'd like to help contribute (we'd love to have your help!), then go to our Contributor's Guide for more information.
Build Prerequisites
In order to use the connector, you need to have:
- Java 1.8 SDK installed
- Maven 3.x installed (or SBT version 1.x)
More details on building from source and running tests can be found in our Contributor's Guide.
Build Command
// Builds jar and runs all tests
mvn clean package
// Builds jar, runs all tests, and installs jar to your local maven repository
mvn clean install