import org.apache.spark.SparkContext import org.apache.spark.SparkConf import org.apache.spark.rdd.RDD import org.apache.spark.sql._ import org.apache.spark.sql.functions._ class Sale { } object Sale { case class Sale(cardId:String,productId:Int,quantity:Int,money:Double) def main(args: Array[String]): Unit = { val conf = new SparkConf().setAppName("Pharmacy Sales Analysis").setMaster("local") val sc = new SparkContext(conf) sc.setLogLevel("ERROR") val sqlContext = new SQLContext(sc) // load data val data = sc.textFile(args(0)) // parse data val salesRDD: RDD[Sale] = data.map(line => line.split(" ")).map(arr => Sale(arr(0), arr(1).toInt, arr(2).toInt, arr(3).toDouble)) import sqlContext.implicits._ val df = salesRDD.toDF() val nameMoneyDF = df.select("productId","money","quantity") nameMoneyDF.show(5) val totalSales = nameMoneyDF.groupBy("productId").sum("quantity") //totalSales.show(5) val topSales = totalSales.select(totalSales("productId"),totalSales("sum(quantity)").as("Totalquantity")) .orderBy(desc("Totalquantity")) topSales.show(5) val totalbuy = df.groupBy("cardId").sum("quantity") //totalbuy.show(5) val topbuy = totalbuy.select(totalbuy("cardId"),totalbuy("sum(quantity)").as("Totalquantity")) .orderBy(desc("Totalquantity")) topbuy.show(5) val Oneproduct:Dataset[Row]= topSales.select("productId","Totalquantity").filter(row=>row.getAs[String]("productId") == 230010) Oneproduct.show() sc.stop() }}帮我写个注释

```scala import org.apache.spark.SparkContext import org.apache.spark.SparkConf import org.apache.spark.rdd.RDD import org.apache.spark.sql._ import org.apache.spark.sql.functions._ class Sale { } object Sale { case class Sale(cardId:String,productId:Int,quantity:Int,money:Double) def main(args: Array[String]): Unit = { val conf = new SparkConf().setAppName("Pharmacy Sales Analysis").setMaster("local") val sc = new SparkContext(conf) sc.setLogLevel("ERROR") val sqlContext = new SQLContext(sc) // load data val data = sc.textFile(args(0)) // parse data val salesRDD: RDD[Sale] = data.map(line => line.split(" ")).map(arr => Sale(arr(0), arr(1).toInt, arr(2).toInt, arr(3).toDouble)) import sqlContext.implicits._ val df = salesRDD.toDF() // select columns and show top 5 rows val nameMoneyDF = df.select("productId","money","quantity") nameMoneyDF.show(5) // group by productId and sum the quantity, then show top 5 products with highest sales val totalSales = nameMoneyDF.groupBy("productId").sum("quantity") val topSales = totalSales.select(totalSales("productId"),totalSales("sum(quantity)").as("Totalquantity")).orderBy(desc("Totalquantity")) topSales.show(5) // group by cardId and sum the quantity, then show top 5 customers with highest purchase quantity val totalbuy = df.groupBy("cardId").sum("quantity") val topbuy = totalbuy.select(totalbuy("cardId"),totalbuy("sum(quantity)").as("Totalquantity")).orderBy(desc("Totalquantity")) topbuy.show(5) // select rows for one specific product (productId = 230010) and show the result val Oneproduct:Dataset[Row]= topSales.select("productId","Totalquantity").filter(row=>row.getAs[String]("productId") == 230010) Oneproduct.show() sc.stop() } } ``` 注释如下： ```scala // 导入Spark相关的库 import org.apache.spark.SparkContext import org.apache.spark.SparkConf import org.apache.spark.rdd.RDD import org.apache.spark.sql._ import org.apache.spark.sql.functions._ // 定义Sale类 class Sale { } // Sale伴生对象 object Sale { // 定义Sale类的属性 case class Sale(cardId:String,productId:Int,quantity:Int,money:Double) def main(args: Array[String]): Unit = { // 设置Spark的配置信息，并创建SparkContext val conf = new SparkConf().setAppName("Pharmacy Sales Analysis").setMaster("local") val sc = new SparkContext(conf) sc.setLogLevel("ERROR") val sqlContext = new SQLContext(sc) // 加载数据 val data = sc.textFile(args(0)) // 解析数据并创建RDD val salesRDD: RDD[Sale] = data.map(line => line.split(" ")).map(arr => Sale(arr(0), arr(1).toInt, arr(2).toInt, arr(3).toDouble)) // 将RDD转换为DataFrame import sqlContext.implicits._ val df = salesRDD.toDF() // 选择需要的列并展示前5行 val nameMoneyDF = df.select("productId","money","quantity") nameMoneyDF.show(5) // 按productId分组并计算销售量，然后展示销售量最高的5个商品 val totalSales = nameMoneyDF.groupBy("productId").sum("quantity") val topSales = totalSales.select(totalSales("productId"),totalSales("sum(quantity)").as("Totalquantity")).orderBy(desc("Totalquantity")) topSales.show(5) // 按cardId分组并计算购买量，然后展示购买量最高的5个客户 val totalbuy = df.groupBy("cardId").sum("quantity") val topbuy = totalbuy.select(totalbuy("cardId"),totalbuy("sum(quantity)").as("Totalquantity")).orderBy(desc("Totalquantity")) topbuy.show(5) // 选择productId为230010的行并展示结果 val Oneproduct:Dataset[Row]= topSales.select("productId","Totalquantity").filter(row=>row.getAs[String]("productId") == 230010) Oneproduct.show() // 停止SparkContext sc.stop() } } ```