Enabling Continuous Data Processing with Apache Spark and Azure Event Hubs
- continuous
- azure
- structured-streaming
- microsoft
- spark-streaming
- scala
- apache
- real-time
- databricks
- bigdata
- stream
- eventhubs
- kafka
- streaming
- spark
- event-hubs
- connector
- ingestion
- apache-spark
Scala versions:
2.11
spark-streaming-eventhubs_examples 2.0.8
Group ID:
com.microsoft.azure
Artifact ID:
spark-streaming-eventhubs_examples_2.11
Version:
2.0.8
Release Date:
Jul 31, 2017
Licenses:
Files:
libraryDependencies += "com.microsoft.azure" %% "spark-streaming-eventhubs_examples" % "2.0.8"
ivy"com.microsoft.azure::spark-streaming-eventhubs_examples:2.0.8"
//> using dep "com.microsoft.azure::spark-streaming-eventhubs_examples:2.0.8"
import $ivy.`com.microsoft.azure::spark-streaming-eventhubs_examples:2.0.8`
<dependency> <groupId>com.microsoft.azure</groupId> <artifactId>spark-streaming-eventhubs_examples_2.11</artifactId> <version>2.0.8</version> </dependency>
compile group: 'com.microsoft.azure', name: 'spark-streaming-eventhubs_examples_2.11', version: '2.0.8'