SparkStreaming:DirectStream RDD到数据帧[重复]

我正在研究spark流上下文,它从avro序列化中的kafka主题获取数据,如下所示。

val kafkaParams = Map[String, Object](
  "bootstrap.servers" -> "localhost:9092",
  "schema.registry.url" -> "http://localhost:8081",
  "key.deserializer" -> "io.confluent.kafka.serializers.KafkaAvroDeserializer",
  "value.deserializer" -> "io.confluent.kafka.serializers.KafkaAvroDeserializer",
  "group.id" -> "1"
)

使用Kafka utils,我创建了如下的直接流

val topics = Set("mysql-foobar")


val stream = KafkaUtils.createDirectStream[String, String](
  ssc,
  PreferConsistent,
  Subscribe[String,String](
    topics,
    kafkaParams)
)

我还将数据作为

stream.foreachRDD ( rdd => {
  rdd.foreachPartition(iterator => {
    while (iterator.hasNext) {
      val next = iterator.next()
      println(next.value())
    }
  })
})

this 和 this 我的输出如下

{"c1": 4, "c2": "Jarry", "create_ts": 1536758512000, "update_ts": 1537204805000}