package mobvista.dmp.datasource.datatory import java.net.URI import mobvista.dmp.clickhouse.tracking.AdnTrackingEntity import mobvista.dmp.common.CommonSparkJob import org.apache.commons.cli.{BasicParser, Options} import org.apache.commons.lang3.StringUtils import org.apache.hadoop.fs.{FileSystem, Path} import org.apache.spark.broadcast.Broadcast import org.apache.spark.sql.{SaveMode, SparkSession} import scala.collection.mutable /** * @package: mobvista.dmp.datasource.datatory * @author: wangjf * @date: 2019/11/25 * @time: 15:00 * @email: jinfeng.wang@mobvista.com * @phone: 152-1062-7698 */ class AdnTrackingMergeDaily extends CommonSparkJob with java.io.Serializable { def commandOptions(): Options = { val options = new Options() options.addOption("date", true, "date") options.addOption("output", true, "output") options } var eventMap: Broadcast[scala.collection.Map[String, String]] = null override protected def run(args: Array[String]): Int = { val parser = new BasicParser() val options = commandOptions() val commandLine = parser.parse(options, args) val date = commandLine.getOptionValue("date") val output = commandLine.getOptionValue("output") val spark = SparkSession .builder() .appName("AdnTrackingMergeDaily") .config("spark.rdd.compress", "true") .config("spark.shuffle.compress", "true") .config("spark.sql.orc.filterPushdown", "true") .config("spark.io.compression.codec", "lz4") .config("spark.io.compression.lz4.blockSize", "64k") .config("spark.sql.warehouse.dir", "s3://mob-emr-test/spark-warehouse") .config("spark.serializer", "org.apache.spark.serializer.KryoSerializer") .enableHiveSupport() .getOrCreate() import spark.implicits._ val sc = spark.sparkContext try { FileSystem.get(new URI(s"s3://mob-emr-test"), sc.hadoopConfiguration).delete(new Path(output), true) eventMap = sc.broadcast(spark.sql(Constant.event_sql.replace("@date", date)) .rdd.map(r => { (r.getAs("event_name").toString, r.getAs("event_type").toString) }).collectAsMap()) spark.udf.register("getEventType", getEventType _) var sql = Constant.adn_tracking_install_join_event_sql.replace("@date", date) spark.sql(sql).createOrReplaceTempView("event_join") sql = Constant.adn_tracking_merge_sql.replace("@date", date) spark.sql(sql) .dropDuplicates .rdd.map(r => { val campaign_id = r.getAs("campaign_id").asInstanceOf[mutable.WrappedArray[String]] val campaignSet: mutable.HashSet[String] = new mutable.HashSet[String]() campaign_id.foreach(c => { if (StringUtils.isNotBlank(c)) { campaignSet.add(c) } }) val event_name = r.getAs("event_name").asInstanceOf[mutable.WrappedArray[String]] val eventNameSet: mutable.HashSet[String] = new mutable.HashSet[String]() event_name.foreach(c => { if (StringUtils.isNotBlank(c)) { eventNameSet.add(c) } }) val event_type = r.getAs("event_type").asInstanceOf[mutable.WrappedArray[String]] val eventTypeSet: mutable.HashSet[String] = new mutable.HashSet[String]() event_type.foreach(c => { if (StringUtils.isNotBlank(c)) { eventTypeSet.add(c) } }) val app_id = r.getAs("app_id").asInstanceOf[mutable.WrappedArray[String]] val appSet: mutable.HashSet[String] = new mutable.HashSet[String]() app_id.foreach(c => { if (StringUtils.isNotBlank(c)) { appSet.add(c) } }) AdnTrackingEntity(r.getAs("device_id"), r.getAs("device_model"), r.getAs("os_version"), r.getAs("country"), r.getAs("city"), mutable.WrappedArray.make(campaignSet.toArray), mutable.WrappedArray.make(eventNameSet.toArray), mutable.WrappedArray.make(eventTypeSet.toArray), mutable.WrappedArray.make(appSet.toArray), r.getAs("log_type")) }).toDF .write .mode(SaveMode.Overwrite) .option("orc.compress", "snappy") .orc(output) } finally { if (spark != null) { spark.stop() } } 0 } def getEventType(eventName: String): String = { eventMap.value.getOrElse(eventName, "") } } object AdnTrackingMergeDaily { def main(args: Array[String]): Unit = { new AdnTrackingMergeDaily().run(args) } }