I've an issue that i tried searching for a solution for and couldn't reach anything and would like any *pointers i can get.
So I am trying to integrate Spark structured streaming with Apache Kudu, I am reading the stream from Kafka and doing some processing and should now write to Kudu tables,the problem is that spark structured streaming doesn't provide support for a Kudu sink (that I know of?), and I am using the foreach writer but as soon as try to create a dataframe inside the "ForeachWriter.process()" it just hangs and never move on
import org.apache.spark.sql.ForeachWriter
val foreachWriter = new ForeachWriter[Row] {
override def open(partitionId: Long,version: Long): Boolean = {
val mySchema = StructType(Array(
StructField("id", IntegerType),
StructField("value", DoubleType),
StructField("EventTimestamp", TimestampType)
))
true
}
override def process(value: Row): Unit = {
println("values\n------------------")
val spark = SparkSession.builder.appName("Spark-Kafka-Integrations").master("local").getOrCreate()
val valRDD=spark.sparkContext.parallelize(value.toSeq)
val valRDF=valRDD.map(x=>x.toString.split(",").to[List])
println(value)
val valDF=spark.createDataFrame(valRDF)
valDF.show()
println("End values\n///////////////////")
//shoud insert into kudu here
}
override def close(errorOrNull: Throwable): Unit = {
}
}
//count is a Dstream/streaming dataframe
count.writeStream.foreach(foreachWriter).outputMode("complete") .option("truncate", "false").start().awaitTermination()