You can have below statement for multiple topics
val dfStatus = spark.readStream.
format("kafka").
option("subscribe", "utility-status, utility-critical").
option("kafka.bootstrap.servers", "localhost:9092").
option("startingOffsets", "earliest")
.load()
On Mon, Sep 17, 2018 at 3:28 AM sivaprakash <[email protected]>
wrote:
> Hi
>
> I have integrated Spark Streaming with Kafka in which Im listening 2 topics
>
> def main(args: Array[String]): Unit = {
>
> val schema = StructType(
> List(
> StructField("gatewayId", StringType, true),
> StructField("userId", StringType, true)
> )
> )
>
> val spark = SparkSession
> .builder
> .master("local[4]")
> .appName("DeviceAutomation")
> .getOrCreate()
>
> val dfStatus = spark.readStream.
> format("kafka").
> option("subscribe", "utility-status, utility-critical").
> option("kafka.bootstrap.servers", "localhost:9092").
> option("startingOffsets", "earliest")
> .load()
>
>
> }
>
> Since I have few more topics to be listed and perform different operations
> I
> would like to move each topics into separate case class for better clarity.
> Is it possible?
>
>
>
> --
> Sent from: http://apache-spark-user-list.1001560.n3.nabble.com/
>
> ---------------------------------------------------------------------
> To unsubscribe e-mail: [email protected]
>
> --
Thanks,
Naresh
www.linkedin.com/in/naresh-dulam
http://hadoopandspark.blogspot.com/
