Scala入门到精通——第二十九节 Scala数据库编程

本节主要内容

1. Scala Mavenproject的创建
2. Scala JDBC方式訪问MySQL
3. Slick简单介绍
4. Slick数据库编程实战
5. SQL与Slick相互转换

本课程在多数内容是在官方教程上改动而来的，官方给的样例是H2数据库上的。经过本人改造，用在MySQL数据库上，官方教程地址：http://slick.typesafe.com/doc/2.1.0/sql-to-slick.html

1. Scala Mavenproject的创建

本节的project项目採用的是Maven Project，在POM.xml文件里加入以下两个依赖就能够使用scala进行JDBC方式及Slick框架操作MySQL数据库：

 <dependency>
        <groupId>mysql</groupId>
        <artifactId>mysql-connector-java</artifactId>
        <version>5.1.18</version>
     </dependency>
     <dependency>
    <groupId>com.typesafe.slick</groupId>
    <artifactId>slick_2.11</artifactId>
    <version>2.1.0</version>
   </dependency>

scala IDE for eclipse 中创建scala Maven项目的方式例如以下：
在Eclispe 中点击” File->new->other”。例如以下图

输入Maven能够看到Maven Project:

直接next。得到

再点击next，在filter中输入scala得到：

选中，然后next输入相应的groupId等。直接finish就可以。创建完项目将上述依赖加入到pom.xml文件其中。这样就完毕了scala maven Project的创建。

2. Scala JDBC方式訪问MySQL

以下给出的是scala採用JDBC訪问MySQL的代码演示样例

package cn.scala.xtwy.jdbc

import java.sql.{ Connection, DriverManager }
object ScalaJdbcConnectSelect extends App {
  // 訪问本地MySQLserver，通过3306端口訪问mysql数据库
  val url = "jdbc:mysql://localhost:3306/mysql"
  //驱动名称
  val driver = "com.mysql.jdbc.Driver"
  //用户名
  val username = "root"
  //密码
  val password = "123"
  //初始化数据连接
  var connection: Connection = _
  try {
   //注冊Driver
    Class.forName(driver)
    //得到连接
    connection = DriverManager.getConnection(url, username, password)
    val statement = connection.createStatement
    //运行查询语句，并返回结果
    val rs = statement.executeQuery("SELECT host, user FROM user")
    //打印返回结果
    while (rs.next) {
      val host = rs.getString("host")
      val user = rs.getString("user")
      println("host = %s, user = %s".format(host, user))
    }
  } catch {
    case e: Exception => e.printStackTrace
  }
  //关闭连接。释放资源
  connection.close
}

3. Slick简单介绍

在前一小节中我们演示了怎样通过JDBC进行数据库訪问。相同在Scala中也能够利用JAVA中的ORM框架如Hibernate、IBatis等进行数据库的操纵，但它们都是Java风格的数据库操纵方式，Scala语言中也有着自己的ORM框架。眼下比較流行的框架包括:

1、Slick （typesafe公司开发）

2、Squeryl

3、Anorm

4、ScalaActiveRecord （基于Squeryl之上）

5、circumflex-orm

6、activate-framework（Scala版的Hibernate）

本节课程要讲的便是Slick框架，它是Scala语言创建者所成立的公司TypeSafe所开发的一个Scala风格的开源数据库操纵框架，它眼下支持以下几种主流的数据：

DB2 (via slick-extensions)
Derby/JavaDB
H2
HSQLDB/HyperSQL
Microsoft Access
Microsoft SQL Server (via slick-extensions)
MySQL
Oracle (via slick-extensions)
PostgreSQL
SQLite

当然它也支持其他数据，仅仅只是功能可能还不完好。在Slick中。能够像訪问Scala自身的集合一样对数据库进行操作。它具有例如以下几个特点：

1 数据库的訪问採用Scala风格：

//以下给出的是数据查询操作
class Coffees(tag: Tag) extends Table[(String, Double)](tag, "COFFEES") {
  def name = column[String]("COF_NAME", O.PrimaryKey)
  def price = column[Double]("PRICE")
  def * = (name, price)
}
val coffees = TableQuery[Coffees]

//以下给出的数据訪问API
// Query that only returns the "name" column
coffees.map(_.name)

// Query that does a "where price < 10.0"
coffees.filter(_.price < 10.0)

从上面的代码能够看到。Slick訪问数据库就跟Scala操纵自身的集合一样.

2 Slick数据操纵是类型安全的

// The result of "select PRICE from COFFEES" is a Seq of Double
// because of the type safe column definitions
val coffeeNames: Seq[Double] = coffees.map(_.price).list

// Query builders are type safe:
coffees.filter(_.price < 10.0)
// Using a string in the filter would result in a compilation error

3 支持链式操作

// Create a query for coffee names with a price less than 10, sorted by name
coffees.filter(_.price < 10.0).sortBy(_.name).map(_.name)
// The generated SQL is equivalent to:
// select name from COFFEES where PRICE < 10.0 order by NAME

4. Slick 数据库编程实战

以下的代码演示了Slick怎样创建数据库表、怎样进行数据插入操作及怎样进行数据的查询操作（以MySQL为例）：

package cn.scala.xtwy

//导入MySQL相关方法
import scala.slick.driver.MySQLDriver.simple._

object UseInvoker extends App {

  // 定义一个Test表
  //表中包括两列，各自是id,name
  class Test(tag: Tag) extends Table[(Int, String)](tag, "Test") {
    def k = column[Int]("id", O.PrimaryKey)
    def v = column[String]("name")
     // Every table needs a * projection with the same type as the table's type parameter
     //每一个Table中都应该有*方法。它的类型必须与前面定义的类型參数(Int, String)一致
    def * = (k, v)
  }
  //创建TableQuery对象（这里调用的是TableQuery的apply方法
  //没有显式地调用new 
  val ts = TableQuery[Test]

  //forURL注冊MySQL驱动器，传入URL，用户名及密码
  //方法回返的是一个DatabaseDef对象，然后再调用withSession方法
  Database.forURL("jdbc:mysql://localhost:3306/slick", "root","123",
      driver = "com.mysql.jdbc.Driver") withSession { 

    //定义一个隐式值
    //implicit session: MySQLDriverbackend.Session
    //兴许方法中当做隐式參数传递
    implicit session =>

    // 创建Test表
    //create方法中带有一个隐式參数
    //def create(implicit session: JdbcBackend.SessionDef): Unit
    ts.ddl.create
    //插入数据
    //def insertAll(values: U*)(implicit session: JdbcBackend.SessionDef): MultiInsertResult
    ts.insertAll(1 -> "a", 2 -> "b", 3 -> "c", 4 -> "d", 5 -> "e")
   //数据库查询（这里返回全部数据）
   ts.foreach { x => println("k="+x._1+" v="+x._2) }

   //这里查询返回全部主鍵 <3的
   ts.filter { _.k <3 }.foreach { x => println("k="+x._1+" v="+x._2) }
  }
  //模式匹配方式
  ts.foreach { case(id,name) => println("id="+id+" name="+name) }
}

以下我们再给一个更为复杂的样例来演示Slick中是怎样进行数据的入库与查询操作的：

package cn.scala.xtwy

import scala.slick.driver.MySQLDriver.simple._

object CoffeeExample extends App {
  // Definition of the SUPPLIERS table
  //定义Suppliers表
  class Suppliers(tag: Tag) extends Table[(Int, String, String, String, String, String)](tag, "SUPPLIERS") {
    def id = column[Int]("SUP_ID", O.PrimaryKey) // This is the primary key column
    def name = column[String]("SUP_NAME")
    def street = column[String]("STREET")
    def city = column[String]("CITY")
    def state = column[String]("STATE")
    def zip = column[String]("ZIP")
    // Every table needs a * projection with the same type as the table's type parameter
    def * = (id, name, street, city, state, zip)
  }
  val suppliers = TableQuery[Suppliers]

  // Definition of the COFFEES table
   //定义Coffees表
  class Coffees(tag: Tag) extends Table[(String, Int, Double, Int, Int)](tag, "COFFEES") {
    def name = column[String]("COF_NAME", O.PrimaryKey)
    def supID = column[Int]("SUP_ID")
    def price = column[Double]("PRICE")
    def sales = column[Int]("SALES")
    def total = column[Int]("TOTAL")
    def * = (name, supID, price, sales, total)
    // A reified foreign key relation that 
    //can be navigated to create a join
    //外鍵定义，它使得supID域中的值关联到suppliers中的id
    //从而保证表中数据的正确性
    //它定义的事实上是一个n:1的关系，
    //即一个Coffees相应仅仅有一个Suppliers,
    //而一个Suppliers能够相应多个Coffees
    def supplier = foreignKey("SUP_FK", supID, suppliers)(_.id)
  }
  val coffees = TableQuery[Coffees]

  Database.forURL("jdbc:mysql://localhost:3306/slick", "root", "123",
    driver = "com.mysql.jdbc.Driver") withSession {

      implicit session =>
        // Create the tables, including primary and foreign keys
        //按顺序创建表
        (suppliers.ddl ++ coffees.ddl).create

        // Insert some suppliers
        //插入操作，集合的方式
        suppliers += (101, "Acme, Inc.", "99 Market Street", "Groundsville", "CA", "95199")
        suppliers += (49, "Superior Coffee", "1 Party Place", "Mendocino", "CA", "95460")
        suppliers += (150, "The High Ground", "100 Coffee Lane", "Meadows", "CA", "93966")

        // Insert some coffees (using JDBC's batch insert feature, if supported by the DB)
        //批量插入操作，集合方式
        coffees ++= Seq(
          ("Colombian", 101, 7.99, 0, 0),
          ("French_Roast", 49, 8.99, 0, 0),
          ("Espresso", 150, 9.99, 0, 0),
          ("Colombian_Decaf", 101, 8.99, 0, 0),
          ("French_Roast_Decaf", 49, 9.99, 0, 0))
       //返回表中全部数据，相当于SELECT * FROM COFFEES
       coffees foreach {
          case (name, supID, price, sales, total) =>
            println("  " + name + "	" + supID + "	" + price + "	" + sales + "	" + total)

        }
       //返回表中全部数据。仅仅只是这次是直接让数据库帮我们进行转换
        val q1 = for (c <- coffees)
          yield LiteralColumn("  ") ++ c.name ++ "	" ++ c.supID.asColumnOf[String] ++
          "	" ++ c.price.asColumnOf[String] ++ "	" ++ c.sales.asColumnOf[String] ++
          "	" ++ c.total.asColumnOf[String]
        // The first string constant needs to be lifted manually to a LiteralColumn
        // so that the proper ++ operator is found
        q1 foreach println

        //联合查询
        //採用===进行比較操作，而非==操作符。用于进行值比較
        //相同的还有!=值不等比較符
        //甚至其他比較操作符与scala是一致的 <, <=, >=, >
         val q2 = for {
          c <- coffees if c.price < 9.0
          s <- suppliers if s.id === c.supID
        } yield (c.name, s.name)

}

5. SQL与Slick相互转换

package cn.scala.xtwy

import scala.slick.driver.MySQLDriver.simple._
import scala.slick.jdbc.StaticQuery.interpolation
import scala.slick.jdbc.GetResult

object SQLAndSlick extends App {
  type Person = (Int, String, Int, Int)
  class People(tag: Tag) extends Table[Person](tag, "PERSON") {
    def id = column[Int]("ID", O.PrimaryKey)
    def name = column[String]("NAME")
    def age = column[Int]("AGE")
    def addressId = column[Int]("ADDRESS_ID")
    def * = (id, name, age, addressId)
    def address = foreignKey("ADDRESS", addressId, addresses)(_.id)
  }
  lazy val people = TableQuery[People]

  type Address = (Int, String, String)
  class Addresses(tag: Tag) extends Table[Address](tag, "ADDRESS") {
    def id = column[Int]("ID", O.PrimaryKey)
    def street = column[String]("STREET")
    def city = column[String]("CITY")
    def * = (id, street, city)
  }

  lazy val addresses = TableQuery[Addresses]

  val dbUrl = "jdbc:mysql://localhost:3306/slick"
  val jdbcDriver = "com.mysql.jdbc.Driver"
  val user = "root"
  val password = "123"
  val db = Database.forURL(dbUrl, user, password, driver = jdbcDriver)

  db.withSession { implicit session =>

    (people.ddl ++ addresses.ddl).create

    //插入address数据
    addresses += (23, "文一西路", "浙江省杭州市")
    addresses += (41, "紫荆花路", "浙江省杭州市")

    //插入people数据
    people += (1, "摇摆少年梦", 27, 23)
    people += (2, "john", 28, 41)
    people += (3, "stephen", 28, 23)

    //以下两条语句是等同的（获取固定几个字段）
    val query = sql"select ID, NAME, AGE from PERSON".as[(Int, String, Int)]
    query.list.foreach(x => println("id=" + x._1 + " name=" + x._2 + " age=" + x._3))

    val query2 = people.map(p => (p.id, p.name, p.age))
    query2.list.foreach(x => println("id=" + x._1 + " name=" + x._2 + " age=" + x._3))

    //以下两条语句是等同的(Where语句）
    val query3 = sql"select * from PERSON where AGE >= 18 AND NAME = '摇摆少年梦'".as[Person]
    query3.list.foreach(x => println("id=" + x._1 + " name=" + x._2 + " age=" + x._3))

    val query4 = people.filter(p => p.age >= 18 && p.name === "摇摆少年梦")
    query4.list.foreach(x => println("id=" + x._1 + " name=" + x._2 + " age=" + x._3))

    //orderBy
    sql"select * from PERSON order by AGE asc, NAME".as[Person].list
    people.sortBy(p => (p.age.asc, p.name)).list

    //max
    sql"select max(AGE) from PERSON".as[Option[Int]].first
    people.map(_.age).max

    //隐式join
    sql"""
  select P.NAME, A.CITY
  from PERSON P, ADDRESS A
  where P.ADDRESS_ID = a.id
""".as[(String, String)].list

    people.flatMap(p =>
      addresses.filter(a => p.addressId === a.id)
        .map(a => (p.name, a.city))).run

    // or equivalent for-expression:
    (for (
      p <- people;
      a <- addresses if p.addressId === a.id
    ) yield (p.name, a.city)).run

    //join操作
    sql"""select P.NAME, A.CITY from PERSON P join ADDRESS A on P.ADDRESS_ID = a.id """.as[(String, String)].list
    (people join addresses on (_.addressId === _.id))
  .map{ case (p, a) => (p.name, a.city) }.run
  }

}

上面列出的仅仅是Slick与SQL的部分转换，还有诸如:Update、Delete等操作能够參见：http://slick.typesafe.com/doc/2.1.0/sql-to-slick.html

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