一、基于物品的Jaccard相似度公式

其中，i、j表示任意两个物品，N(i)表示喜欢物品i的用户数，N(j)表示喜欢物品j的用户数。

代码：

public class ItemCFApp {public static void main(String[]args){SparkConf sparkConf = new SparkConf();sparkConf.setAppName("ItemCFApp");sparkConf.setMaster("local[*]");SparkSession sparkSession = SparkSession.builder().config(sparkConf).getOrCreate();String url = "jdbc:mysql://localhost:3306/spark-mysql?useUnicode=true&characterEncoding=utf8&autoReconnect=true&failOverReadOnly=false";String driver = "com.mysql.jdbc.Driver";String user = "root";String password = "admin";Dataset<Row> dataset = sparkSession.read().format("jdbc").option("driver", driver).option("url",url).option("dbtable","user_item").option("user",user).option("password",password).load();Dataset<Row> itemCount = dataset.groupBy("item_id").count();Dataset<Row> item2ItemCount = dataset.as("a").join(dataset.as("b"),functions.column("a.user_id").$eq$eq$eq(functions.column("b.user_id"))).where(functions.column("a.item_id").notEqual(functions.column("b.item_id"))).select(functions.column("a.item_id").as("a_item_id"),functions.column("b.item_id").as("b_item_id")).groupBy("a_item_id", "b_item_id").count();Dataset<Row> result =  item2ItemCount.as("i2i").join(itemCount.as("ic1"), functions.column("i2i.a_item_id").$eq$eq$eq(functions.column("ic1.item_id"))).join(itemCount.as("ic2"), functions.column("i2i.b_item_id").$eq$eq$eq(functions.column("ic2.item_id"))).selectExpr("i2i.a_item_id", "i2i.b_item_id", "i2i.count/(ic1.count + ic2.count - i2i.count) as count");result.show();
//        result.write()
//                .mode(SaveMode.Overwrite)
//                .format("jdbc")
//                .option("driver", driver)
//                .option("url",url)
//                .option("dbtable","item_similar")
//                .option("user",user)
//                .option("password",password)
//                .save();sparkSession.stop();}
}

 

二、基于物品的余弦相似度公式

其中，i、j表示任意两个物品，N(i)表示喜欢物品i的用户数，N(j)表示喜欢物品j的用户数。

代码：

public class ItemCF2App {public static void main(String[]args){SparkConf sparkConf = new SparkConf();sparkConf.setAppName("ItemCFApp");sparkConf.setMaster("local[*]");SparkSession sparkSession = SparkSession.builder().config(sparkConf).getOrCreate();String url = "jdbc:mysql://localhost:3306/spark-mysql?useUnicode=true&characterEncoding=utf8&autoReconnect=true&failOverReadOnly=false";String driver = "com.mysql.jdbc.Driver";String user = "root";String password = "admin";Dataset<Row> dataset = sparkSession.read().format("jdbc").option("driver", driver).option("url",url).option("dbtable","user_item").option("user",user).option("password",password).load();Dataset<Row> itemCount = dataset.groupBy("item_id").count();Dataset<Row> item2ItemCount = dataset.as("a").join(dataset.as("b"),functions.column("a.user_id").$eq$eq$eq(functions.column("b.user_id"))).where(functions.column("a.item_id").notEqual(functions.column("b.item_id"))).select(functions.column("a.item_id").as("a_item_id"),functions.column("b.item_id").as("b_item_id")).groupBy("a_item_id", "b_item_id").count();Dataset<Row> result =  item2ItemCount.as("i2i").join(itemCount.as("ic1"), functions.column("i2i.a_item_id").$eq$eq$eq(functions.column("ic1.item_id"))).join(itemCount.as("ic2"), functions.column("i2i.b_item_id").$eq$eq$eq(functions.column("ic2.item_id"))).selectExpr("i2i.a_item_id", "i2i.b_item_id", "i2i.count/pow(ic1.count * ic2.count, 0.5) as count");result.show();
//        result.write()
//                .mode(SaveMode.Overwrite)
//                .format("jdbc")
//                .option("driver", driver)
//                .option("url",url)
//                .option("dbtable","item_similar")
//                .option("user",user)
//                .option("password",password)
//                .save();sparkSession.stop();}
}