SparkSQL（Spark-1.4.0)实战系列（三）——SparkSQL应用案例

本节主要内容

1. 数据准备
2. 案例实战

数据准备

将实验数据Date.txt、Stock.txt、StockDetail.txt(hadoop fs -put /data /data）上传到HDFS上，如下图所示

Date.txt格式如下：

//Date.txt文件定义了日期的分类，将每天分别赋予所属的月份、星期、季度等属性  
//日期，年月，年，月，日，周几，第几周，季度，旬、半月 
2014-12-24,201412,2014,12,24,3,52,4,36,24

Stock.txt格式如下：

//Stock.txt文件定义了订单表头  
//订单号，交易位置，交易日期  
ZYSL00014630,ZY,2009-5-7

StockDetail.txt格式如下：

//订单号，行号，货品，数量，价格，金额  
HMJSL00006421,9,QY524266010101,1,80,80

案例实战-查询所有订单中每年的销售单数、销售总额：

//定义case class用于后期创建DataFrame schema
//对应Date.txt
case class DateInfo(dateID:String,theyearmonth :String,theyear:String,themonth:String,thedate :String,theweek:String,theweeks:String,thequot :String,thetenday:String,thehalfmonth:String) 
//对应Stock.txt
case class StockInfo(ordernumber:String,locationid :String,dateID:String)
//对应StockDetail.txt
case class StockDetailInfo(ordernumber:String,rownum :Int,itemid:String,qty:Int,price:Double,amount:Double) 

//加载数据并转换成DataFrame
val DateInfoDF = sc.textFile("/data/Date.txt").map(_.split(",")).map(d => DateInfo(d(0), d(1),d(2),d(3),d(4),d(5),d(6),d(7),d(8),d(9))).toDF()
//加载数据并转换成DataFrame
val StockInfoDF= sc.textFile("/data/Stock.txt").map(_.split(",")).map(s => StockInfo(s(0), s(1),s(2))).toDF()
//加载数据并转换成DataFrame
val StockDetailInfoDF = sc.textFile("/data/StockDetail.txt").map(_.split(",")).map(s => StockDetailInfo(s(0), s(1).trim.toInt,s(2),s(3).trim.toInt,s(4).trim.toDouble,s(5).trim.toDouble)).toDF()

//注册成表
DateInfoDF.registerTempTable("tblDate")
StockInfoDF.registerTempTable("tblStock")
StockDetailInfoDF.registerTempTable("tblStockDetail")

//执行SQL
//所有订单中每年的销售单数、销售总额  
//三个表连接后以count(distinct a.ordernumber)计销售单数，sum(b.amount)计销售总额 
sqlContext.sql("select c.theyear,count(distinct a.ordernumber),sum(b.amount) from tblStock a join tblStockDetail b on a.ordernumber=b.ordernumber join tblDate c on a.dateid=c.dateid group by c.theyear order by c.theyear").collect().foreach(println)

//执行过程

//执行结果

案例实战-求所有订单每年最大金额订单的销售额：

sqlContext.sql("select c.theyear,max(d.sumofamount) from tblDate c join (select a.dateid,a.ordernumber,sum(b.amount) as sumofamount from tblStock a join tblStockDetail b on a.ordernumber=b.ordernumber group by a.dateid,a.ordernumber ) d  on c.dateid=d.dateid group by c.theyear sort by c.theyear").collect().foreach(println)  

//执行过程

//执行结果

“`

透过上述代码可以感受到SparkSQL的强大，其它更为复杂的查询可以参考mmicky_wyy的博客：http://blog.csdn.net/book_mmicky/article/details/39177041

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