Enabling Continuous Data Processing with Apache Spark and Azure Event Hubs
- continuous
- azure
- structured-streaming
- microsoft
- spark-streaming
- scala
- apache
- real-time
- databricks
- bigdata
- stream
- eventhubs
- kafka
- streaming
- spark
- event-hubs
- connector
- ingestion
- apache-spark
Scala versions:
2.11
azure-eventhubs-spark 2.2.20
Group ID:
io.github.tilumi
Artifact ID:
azure-eventhubs-spark_2.11
Version:
2.2.20
Release Date:
Jan 16, 2019
Licenses:
Files:
libraryDependencies += "io.github.tilumi" %% "azure-eventhubs-spark" % "2.2.20"
ivy"io.github.tilumi::azure-eventhubs-spark:2.2.20"
//> using dep "io.github.tilumi::azure-eventhubs-spark:2.2.20"
import $ivy.`io.github.tilumi::azure-eventhubs-spark:2.2.20`
<dependency> <groupId>io.github.tilumi</groupId> <artifactId>azure-eventhubs-spark_2.11</artifactId> <version>2.2.20</version> </dependency>
compile group: 'io.github.tilumi', name: 'azure-eventhubs-spark_2.11', version: '2.2.20'