Enabling Continuous Data Processing with Apache Spark and Azure Event Hubs
- bigdata
- azure
- eventhubs
- spark-streaming
- ingestion
- real-time
- event-hubs
- apache-spark
- microsoft
- spark
- streaming
- kafka
- stream
- scala
- databricks
- apache
- connector
- continuous
- structured-streaming
Scala versions:
2.11
spark-streaming-eventhubs 2.0.5
Group ID:
com.microsoft.azure
Artifact ID:
spark-streaming-eventhubs_2.11
Version:
2.0.5
Release Date:
Apr 20, 2017
Licenses:
Files:
libraryDependencies += "com.microsoft.azure" %% "spark-streaming-eventhubs" % "2.0.5"
ivy"com.microsoft.azure::spark-streaming-eventhubs:2.0.5"
//> using dep "com.microsoft.azure::spark-streaming-eventhubs:2.0.5"
import $ivy.`com.microsoft.azure::spark-streaming-eventhubs:2.0.5`
<dependency> <groupId>com.microsoft.azure</groupId> <artifactId>spark-streaming-eventhubs_2.11</artifactId> <version>2.0.5</version> </dependency>
compile group: 'com.microsoft.azure', name: 'spark-streaming-eventhubs_2.11', version: '2.0.5'