package com.gmei import java.io.Serializable import com.gmei.WeafareStat.{defaultParams, parser} import org.apache.spark.sql.{SaveMode, TiContext} import org.apache.log4j.{Level, Logger} import scopt.OptionParser import com.gmei.lib.AbstractParams import com.gmei.GmeiConfig.{writeToJDBCTable,getMinusNDate} object testt { Logger.getLogger("org.apache.spark").setLevel(Level.WARN) Logger.getLogger("org.apache.eclipse.jetty.server").setLevel(Level.OFF) case class Params(env: String = "dev" ) extends AbstractParams[Params] with Serializable val defaultParams = Params() val parser = new OptionParser[Params]("Feed_EDA") { head("WeafareStat") opt[String]("env") .text(s"the databases environment you used") .action((x, c) => c.copy(env = x)) note( """ |For example, the following command runs this app on a tidb dataset: | | spark-submit --class com.gmei.WeafareStat ./target/scala-2.11/feededa-assembly-0.1.jar \ """.stripMargin + s"| --env ${defaultParams.env}" ) } def main(args: Array[String]): Unit = { parser.parse(args, defaultParams).map { param => GmeiConfig.setup(param.env) val spark_env = GmeiConfig.getSparkSession() val sc = spark_env._2 val ti = new TiContext(sc) ti.tidbMapTable(dbName = "jerry_prod", tableName = "diary_video") ti.tidbMapTable(dbName = "jerry_prod", tableName = "data_feed_click") ti.tidbMapTable(dbName = "jerry_prod", tableName = "blacklist") ti.tidbMapTable(dbName = "jerry_test", tableName = "bl_device_list") ti.tidbMapTable(dbName = "jerry_prod", tableName = "data_feed_exposure") val view_count = sc.sql( s""" |select params["business_id"] as diary_id,(params["out"]-params["in"]) as dur_time |from online.tl_hdfs_maidian_view |where action="page_view" |and params["page_name"]="diary_detail" |and (params["out"]-params["in"])<7200 |and partition_date >='20180901' """.stripMargin ) view_count.show() view_count.createOrReplaceTempView("temp") GmeiConfig.writeToJDBCTable(view_count, "avg", SaveMode.Overwrite) val result = view_count result.show() } } }