package com.ippon.dojo.driver

import org.apache.spark.SparkConf
import org.apache.spark.SparkContext
import org.apache.spark.streaming.StreamingContext
import org.apache.spark.streaming.Seconds
import kafka.serializer.StringDecoder
import org.apache.spark.streaming._
import org.apache.spark.SparkConf
import org.apache.spark.streaming.kafka010.KafkaUtils
import org.apache.kafka.common.serialization.StringDeserializer
import org.apache.spark.streaming.kafka010._
import org.apache.spark.streaming.kafka010.LocationStrategies.PreferConsistent
import org.apache.spark.streaming.kafka010.ConsumerStrategies.Subscribe

object KafkaStreamingDriver {
  def main(args: Array[String]): Unit = {
    //configure the Streaming Context
    val sparkConf = new SparkConf().setAppName("KafkaStreamingDojoApp")
    val sparkContext = new SparkContext(sparkConf)
    val streamingContext = new StreamingContext(sparkContext, Seconds(1))

    val kafkaTopic = "dojo"
    // Create direct kafka stream with brokers and topics
    val kafkaParams = Map[String, Object](
      "bootstrap.servers" -> "ec2-54-174-179-236.compute-1.amazonaws.com:9092",
      "key.deserializer" -> classOf[StringDeserializer],
      "value.deserializer" -> classOf[StringDeserializer],
      "group.id" -> "dojo",
      "auto.offset.reset" -> "latest",
      "enable.auto.commit" -> (false: java.lang.Boolean))

    val topics = Array("dojo")
    val complaints = KafkaUtils.createDirectStream[String, String](
      streamingContext,
      PreferConsistent,
      Subscribe[String, String](topics, kafkaParams))

    //perform action on the stream
    complaints.foreachRDD((rdd, time) => {
      val count = rdd.count()
      System.out.println(count + " complaints were collected at " + time)
    })

    //start the stream
    streamingContext.start()
    streamingContext.awaitTermination()
  }
}