Enabling Continuous Data Processing with Apache Spark and Azure Event Hubs
- microsoft
- databricks
- stream
- structured-streaming
- eventhubs
- bigdata
- apache
- streaming
- kafka
- apache-spark
- ingestion
- azure
- connector
- continuous
- real-time
- scala
- spark
- event-hubs
- spark-streaming
Scala versions:
2.11
spark-streaming-eventhubs_connector 2.1.4
Group ID:
com.microsoft.azure
Artifact ID:
spark-streaming-eventhubs_connector_2.11
Version:
2.1.4
Release Date:
Sep 21, 2017
Licenses:
Files:
libraryDependencies += "com.microsoft.azure" %% "spark-streaming-eventhubs_connector" % "2.1.4"
ivy"com.microsoft.azure::spark-streaming-eventhubs_connector:2.1.4"
//> using dep "com.microsoft.azure::spark-streaming-eventhubs_connector:2.1.4"
import $ivy.`com.microsoft.azure::spark-streaming-eventhubs_connector:2.1.4`
<dependency> <groupId>com.microsoft.azure</groupId> <artifactId>spark-streaming-eventhubs_connector_2.11</artifactId> <version>2.1.4</version> </dependency>
compile group: 'com.microsoft.azure', name: 'spark-streaming-eventhubs_connector_2.11', version: '2.1.4'