将kafka中的数据消费到mysql的两种方式

方式一

package demo01
import java.sql.{Connection, DriverManager, PreparedStatement}
import java.text.SimpleDateFormat

import org.apache.kafka.clients.consumer.{ConsumerConfig, ConsumerRecord}
import org.apache.kafka.common.serialization.StringDeserializer
import org.apache.spark.rdd.RDD
import org.apache.spark.streaming.dstream.{DStream, InputDStream}
import org.apache.spark.streaming.kafka010.{ConsumerStrategies, KafkaUtils, LocationStrategies}
import org.apache.spark.streaming.{Seconds, StreamingContext}
import org.apache.spark.{SparkConf, SparkContext}
object demo02 {

  val driver = "com.mysql.jdbc.Driver"
  val url = "jdbc:mysql://192.168.100.201/rng_comment"
  val username = "root"
  val password = "123456"
  /**
   * 1.5.1、查询出微博会员等级为5的用户，并把这些数据写入到mysql数据库中的vip_rank表中
   * 1.5.2、查询出评论赞的个数在10个以上的数据，并写入到mysql数据库中的like_status表中
   * 1.5.3、分别计算出2018/10/20 ，2018/10/21，2018/10/22，2018/10/23这四天每一天的评论数是多少，并写入到mysql数据库中的count_conmment表中
   */
  def main(args: Array[String]): Unit = {

    val sparkConf: SparkConf = new SparkConf().setMaster("local[*]").setAppName("hw3")
    val ssc = new StreamingContext(sparkConf, Seconds(3))
    ssc.sparkContext.setLogLevel("WARN")

    // 3.设置Kafka参数
    val kafkaParams: Map[String, Object] = Map[String, Object](
      ConsumerConfig.BOOTSTRAP_SERVERS_CONFIG -> "node01:9092,node02:9092,node03:9092",
      ConsumerConfig.KEY_DESERIALIZER_CLASS_CONFIG -> classOf[StringDeserializer],
      ConsumerConfig.VALUE_DESERIALIZER_CLASS_CONFIG -> classOf[StringDeserializer],
      ConsumerConfig.GROUP_ID_CONFIG -> "SparkKafka77777",
    ConsumerConfig.AUTO_OFFSET_RESET_CONFIG -> "earliest",
    //false表示关闭自动提交.由spark帮你提交到Checkpoint或程序员手动维护
    ConsumerConfig.ENABLE_AUTO_COMMIT_CONFIG -> (false: java.lang.Boolean)
    )

    // 4.设置Topic
    var topics = Array("rng_comment")
    val recordDStream: InputDStream[ConsumerRecord[String, String]] = KafkaUtils.createDirectStream[String, String](ssc,