Enabling Continuous Data Processing with Apache Spark and Azure Event Hubs
- event-hubs
- continuous
- microsoft
- structured-streaming
- streaming
- ingestion
- scala
- connector
- apache
- kafka
- azure
- spark-streaming
- apache-spark
- real-time
- eventhubs
- stream
- databricks
- spark
- bigdata
Scala versions:
2.11
azure-eventhubs-spark 2.2.7
Group ID:
io.github.tilumi
Artifact ID:
azure-eventhubs-spark_2.11
Version:
2.2.7
Release Date:
Jan 2, 2019
Licenses:
Files:
libraryDependencies += "io.github.tilumi" %% "azure-eventhubs-spark" % "2.2.7"
ivy"io.github.tilumi::azure-eventhubs-spark:2.2.7"
//> using dep "io.github.tilumi::azure-eventhubs-spark:2.2.7"
import $ivy.`io.github.tilumi::azure-eventhubs-spark:2.2.7`
<dependency> <groupId>io.github.tilumi</groupId> <artifactId>azure-eventhubs-spark_2.11</artifactId> <version>2.2.7</version> </dependency>
compile group: 'io.github.tilumi', name: 'azure-eventhubs-spark_2.11', version: '2.2.7'