spark基础练习2
文章目录
- 1.谁是最大买“货”？（谁购买的最多，以购买总价为准）
- 2.哪个产品是最大卖货？（哪个产品销售的最多,以产品交易总价为准）
- 3.找出购买的周分布(根据一周分组,查看每天的交易额,分析每天交易量)
- 4.找出购买力最强地域 (根据洲来划分)
- 文件获取链接: https://pan.baidu.com/s/1VjAzYjzN0X8QKdu4pKQBbg 提取码: rknf
有如下四个csv文件,列属性如下:
#上传到本地
#加载数据成临时表
#1.顾客表
val df1= spark.read.format("csv").option("header","false").option("delimiter",",").load("file:///data/customers.csv").toDF("id","fname","lname","email","password","street","city","state","zipcode")
df1.registerTempTable("customers")
#产品表
val df2= spark.read.format("csv").option("header","false").option("delimiter",",").load("file:///data/products.csv").toDF("pid","pcid","pname","pdesc","price","image")
df2.registerTempTable("product")
#订单表
val df3 = spark.read.format("csv").option("header","false").option("delimiter",",").load("file:///data/orders.csv").toDF("oid","date","cid","status")
df3.registerTempTable("orders")
#订单详细表
val df4 = spark.read.format("csv").option("header","false").option("delimiter",",").load("file:///data/order_items.csv").toDF("iid","oid","pid","num","subtotal","price")
df4.registerTempTable("order_items")
1.谁是最大买“货”？（谁购买的最多，以购买总价为准）
#订单状态需要完成 连 顾客表 订单表 订单详细表 根据 顾客id分组得到 购买总价和最大的人
spark.sqlContext.sql("select c.id ,round(sum(i.subtotal)) s from customers c join orders o join order_items i on c.id = o.cid and o.oid = i.oid where o.status = \"COMPLETE\" group by c.id order by s desc limit 1").show
2.哪个产品是最大卖货？（哪个产品销售的最多,以产品交易总价为准）
#订单状态需要完成,订单表和订单详细表 连表 根据 产品id分组 求总价和最大的
spark.sqlContext.sql(" select i.pid,sum(i.num) s from order_items i join orders o on i.oid = o.oid where o.status = \"COMPLETE\"group by i.pid order by s desc limit 1").show
3.找出购买的周分布(根据一周分组,查看每天的交易额,分析每天交易量)
spark.sqlContext.sql("select dayofweek(o.date) d ,sum(i.subtotal) from orders o join order_items i on i.oid=o.oid where o.status = \"COMPLETE\" group by d")
#如果spark版本不支持dayofweek函数
spark.sqlContext.sql("select if(pmod(datediff(o.date, '1920-01-01') - 3, 7)==0,'星期日',concat('星期',pmod(datediff(o.date, '1920-01-01') - 3, 7))) d ,round(sum(i.subtotal)) from orders o join order_items i on i.oid=o.oid where o.status = \"COMPLETE\" group by d").show
4.找出购买力最强地域 (根据洲来划分)
spark.sqlContext.sql("select c.state ,round(sum(i.subtotal)) s from customers c join orders o join order_items i on c.id = o.cid and o.oid = i.oid where o.status = \"COMPLETE\" group by c.state order by s desc limit 1").show
