Take out the conditional and the sqlcontext and just do rdd => { rdd.foreach(println)
as a base line to see if you're reading the data you expect On Tue, Aug 9, 2016 at 3:47 PM, Diwakar Dhanuskodi <diwakar.dhanusk...@gmail.com> wrote: > Hi, > > I am reading json messages from kafka . Topics has 2 partitions. When > running streaming job using spark-submit, I could see that val dataFrame = > sqlContext.read.json(rdd.map(_._2)) executes indefinitely. Am I doing > something wrong here. Below is code .This environment is cloudera sandbox > env. Same issue in hadoop production cluster mode except that it is > restricted thats why tried to reproduce issue in Cloudera sandbox. Kafka > 0.10 and Spark 1.4. > > val kafkaParams = > Map[String,String]("bootstrap.servers"->"localhost:9093,localhost:9092", > "group.id" -> "xyz","auto.offset.reset"->"smallest") > val conf = new SparkConf().setMaster("local[3]").setAppName("topic") > val ssc = new StreamingContext(conf, Seconds(1)) > > val sqlContext = new org.apache.spark.sql.SQLContext(ssc.sparkContext) > > val topics = Set("gpp.minf") > val kafkaStream = KafkaUtils.createDirectStream[String, String, > StringDecoder,StringDecoder](ssc, kafkaParams, topics) > > kafkaStream.foreachRDD( > rdd => { > if (rdd.count > 0){ > val dataFrame = sqlContext.read.json(rdd.map(_._2)) > dataFrame.printSchema() > //dataFrame.foreach(println) > } > } --------------------------------------------------------------------- To unsubscribe e-mail: user-unsubscr...@spark.apache.org