Enabling Continuous Data Processing with Apache Spark and Azure Event Hubs
- databricks
- real-time
- scala
- microsoft
- bigdata
- apache-spark
- spark
- continuous
- streaming
- apache
- azure
- ingestion
- event-hubs
- stream
- eventhubs
- spark-streaming
- kafka
- connector
- structured-streaming
Scala versions:
2.11
azure-eventhubs-spark 2.3.53
Group ID:
io.github.tilumi
Artifact ID:
azure-eventhubs-spark_2.11
Version:
2.3.53
Release Date:
May 27, 2019
Licenses:
Files:
Developers:
libraryDependencies += "io.github.tilumi" %% "azure-eventhubs-spark" % "2.3.53"
ivy"io.github.tilumi::azure-eventhubs-spark:2.3.53"
//> using dep "io.github.tilumi::azure-eventhubs-spark:2.3.53"
import $ivy.`io.github.tilumi::azure-eventhubs-spark:2.3.53`
<dependency> <groupId>io.github.tilumi</groupId> <artifactId>azure-eventhubs-spark_2.11</artifactId> <version>2.3.53</version> </dependency>
compile group: 'io.github.tilumi', name: 'azure-eventhubs-spark_2.11', version: '2.3.53'
