AliDaily.scala

package mobvista.dmp.datasource.baichuan

import java.net.URI
import java.text.SimpleDateFormat

import mobvista.dmp.util.{DateUtil, PropertyUtil}
import mobvista.dmp.utils.clickhouse.ClickHouseConnectionFactory
import mobvista.dmp.utils.clickhouse.ClickHouseSparkExt._
import org.apache.commons.cli.{BasicParser, Options}
import org.apache.hadoop.fs.{FileSystem, Path}
import org.apache.spark.sql.{Row, SaveMode, SparkSession}
import org.apache.spark.storage.StorageLevel
import ru.yandex.clickhouse.ClickHouseDataSource

/**
  * @package: mobvista.dmp.datasource.baichuan
  * @author: wangjf
  * @date: 2019-08-28
  * @time: 17:50
  * @email: jinfeng.wang@mobvista.com
  * @phone: 152-1062-7698
  */
class AliDaily extends Serializable {
  def commandOptions(): Options = {
    val options = new Options()
    options.addOption("date", true, "date")
    options.addOption("partNum", true, "partNum")
    options.addOption("output", true, "output")
    options.addOption("host", true, "host")
    options.addOption("cluster", true, "cluster")
    options.addOption("database", true, "database")
    options.addOption("table", true, "table")
    options
  }

  protected def run(args: Array[String]) {
    val parser = new BasicParser()
    val options = commandOptions()
    val commandLine = parser.parse(options, args)
    val date = commandLine.getOptionValue("date")
    val partNum = commandLine.getOptionValue("partNum")
    val output = commandLine.getOptionValue("output")
    val cluster = commandLine.getOptionValue("cluster")
    val host = commandLine.getOptionValue("host")
    val database = commandLine.getOptionValue("database")
    val table = commandLine.getOptionValue("table")

    val spark = SparkSession
      .builder()
      .appName("BaiChuanDaily")
      .config("spark.rdd.compress", "true")
      .config("spark.io.compression.codec", "lz4")
      .config("spark.sql.warehouse.dir", "s3://mob-emr-test/spark-warehouse")
      .config("spark.serializer", "org.apache.spark.serializer.KryoSerializer")
      .config("spark.clickhouse.driver", "ru.yandex.clickhouse.ClickHouseDriver")
      .config("spark.clickhouse.url", PropertyUtil.getProperty("config.properties", "spark.clickhouse.url"))
      .config("spark.clickhouse.connection.per.executor.max", "5")
      .config("spark.clickhouse.metrics.enable", "true")
      .config("spark.clickhouse.socket.timeout.ms", "300000")
      .config("spark.clickhouse.cluster.auto-discovery", "true")
      .enableHiveSupport()
      .getOrCreate()
    try {
      val sdf1 = new SimpleDateFormat("yyyy-MM-dd")
      val sdf2 = new SimpleDateFormat("yyyyMMdd")

      val sc = spark.sparkContext
      val clusterName = "cluster_1st"
      import io.clickhouse.spark.connector._
      //  import spark.implicits._

      val dt = sdf1.format(sdf2.parse(date))
      val query = Constant.baichuan_sql.replace("@date", dt)

      val rdd = sc.clickhouseTable(query, clusterName)
        .withCustomPartitioning(Constant.buildPart(Integer.parseInt(partNum)))
        .persist(StorageLevel.MEMORY_AND_DISK_SER)
      val df = rdd.map(r => {
        ((r.getAs("device_id").toString, r.getAs("device_type").toString, r.getAs("platform").toString), r.getAs("package_name").toString)
      })

      import spark.implicits._

      val dff = df.combineByKey(
        (v: String) => Iterable(v),
        (c: Iterable[String], v: String) => c ++ Seq(v),
        (c1: Iterable[String], c2: Iterable[String]) => c1 ++ c2
      ).map(r => {
        BaiChuanEntity(r._1._1, r._1._2, r._1._3, r._2.toSet.mkString(","), "CN")
      }).toDF

      val beforeDate = DateUtil.getDay(sdf2.parse(date), "yyyyMMdd", -1)
      val install_sql = Constant.install_sql.replace("@dt", beforeDate)
      val install_df = spark.sql(install_sql)
      val new_rdd = sc.clickhouseTable(Constant.baichuan_new_sql.replace("@date", dt), clusterName)
        .withCustomPartitioning(Constant.buildPart(Integer.parseInt(partNum)))
        .map(r => {
          Row(r.getAs("device_id").toString, r.getAs("device_type").toString)
        })

      val new_df = spark.createDataFrame(new_rdd, Constant.schema)

      val old_df = spark.createDataFrame(rdd.map(r => {
        Row(r.getAs("device_id").toString, r.getAs("device_type").toString)
      }), Constant.schema)
      val daily_new_df = new_df.except(install_df.unionAll(old_df)).rdd
        .persist(StorageLevel.MEMORY_AND_DISK_SER)

      val s3_df = daily_new_df.map(r => {
        if ("idfa".equals(r.getAs("device_type").toString)) {
          BaiChuanEntity(r.getAs("device_id").toString, "idfa", "ios", "0000000000", "CN")
        } else if ("imei".equals(r.getAs("device_type").toString)) {
          BaiChuanEntity(r.getAs("device_id").toString, "imei", "android", "com.nonetaobao.nonetaobao", "CN")
        } else {
          BaiChuanEntity(r.getAs("device_id").toString, "imeimd5", "android", "com.nonetaobao.nonetaobao", "CN")
        }
      }).toDF

      FileSystem.get(new URI(s"s3://mob-emr-test"), sc.hadoopConfiguration).delete(new Path(output), true)
      s3_df.unionAll(dff).coalesce(10)
        .write
        .mode(SaveMode.Overwrite)
        .option("orc.compress", "zlib")
        .orc(output)

      implicit val clickhouseDataSource: ClickHouseDataSource = ClickHouseConnectionFactory.get(host)

      val update_date = DateUtil.getDay(sdf2.parse(date), "yyyy-MM-dd", 6)
      val ck_df = daily_new_df.map(r => {
        if ("idfa".equals(r.getAs("device_type").toString)) {
          BaiChuanCK(r.getAs("device_id"), 2, 2, 0, update_date)
          //  BaiChuanInstallEntity(r.getAs("device_id").toString, "idfa", "ios", "0")
        } else if ("imei".equals(r.getAs("device_type").toString)) {
          BaiChuanCK(r.getAs("device_id"), 2, 1, 0, update_date)
          //  BaiChuanInstallEntity(r.getAs("device_id").toString, "imei", "android", "0")
        } else {
          BaiChuanCK(r.getAs("device_id"), 2, 3, 0, update_date)
        }
      }).toDF

      //  ck_df.createClickHouseDb(database, Some(clusterName))
      //  daily_new_df.createClickHouseTable(database, table, Seq("dt"), Constant.indexColumn, Constant.orderColumn, Some(clusterName))
      ck_df.saveToClickHouse(database, table, Seq(update_date), Seq("dt"), Some(clusterName), batchSize = 1000000)
    } finally {
      if (spark != null) {
        spark.stop()
      }
    }
  }
}

object AliDaily {
  def main(args: Array[String]): Unit = {
    new AliDaily().run(args)
  }
}