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
azure-eventhubs-spark-parent 2.2.32
Group ID:
io.github.tilumi
Artifact ID:
azure-eventhubs-spark-parent_2.11
Version:
2.2.32
Release Date:
Feb 18, 2019
Licenses:
Files:
libraryDependencies += "io.github.tilumi" %% "azure-eventhubs-spark-parent" % "2.2.32"
ivy"io.github.tilumi::azure-eventhubs-spark-parent:2.2.32"
//> using dep "io.github.tilumi::azure-eventhubs-spark-parent:2.2.32"
import $ivy.`io.github.tilumi::azure-eventhubs-spark-parent:2.2.32`
<dependency> <groupId>io.github.tilumi</groupId> <artifactId>azure-eventhubs-spark-parent_2.11</artifactId> <version>2.2.32</version> </dependency>
compile group: 'io.github.tilumi', name: 'azure-eventhubs-spark-parent_2.11', version: '2.2.32'