1.安装启动检查Mysql服务。
netstat -tunlp (3306)

2.spark 连接mysql驱动程序。

–cp /usr/local/hive/lib/mysql-connector-java-5.1.40-bin.jar /usr/local/spark/jars

3.启动 Mysql shell，新建数据库spark，表student。
select * from student;

create database spark;
use spark;
create table student (id int(4), name char(20), gender char(4), age int(4));
alter table student change id id int auto_increment primary key;
insert into student values(1,'Xueqian','F',23);
insert into student values(2,'Weiliang','M',24);
insert into student values(3,'Rongcheng','M',26);
insert into student values(4,'Guanhua','M',27);
select * from student;

4.spark读取MySQL数据库中的数据
spark.read.format("jdbc").option("url", "jdbc:mysql://localhost:3306/spark?useSSL=false") ...  .load()

spark.read.format("jdbc")\
.option("url", "jdbc:mysql://localhost:3306/spark")\
.option("driver","com.mysql.jdbc.Driver").option("dbtable", "student")\
.option("user", "root")\
.option("password", "1")\
.load()\
.show()

5.spark向MySQL数据库写入数据
studentDF.write.format(‘jdbc’).option(…).mode(‘append’).save() 

from pyspark.sql.types import Row,StructField,StringType,StructType,IntegerType

#下面设置两条数据，表示两个学生的信息
studentRDD = spark.sparkContext.parallelize(["5 zhao M 26","6 wang M 27"]).map(lambda line:line.split(" "))

#下面创建Row对象，每个Row对象都是rowRDD中的一行
rowRDD = studentRDD.map(lambda p:Row(p[1].strip(),p[2].strip(),int(p[3])))

# 下面设置模式信息
schema = StructType([StructField("name",StringType(),True),StructField("gender",StringType(),True),StructField("age",IntegerType(),True)])

#建立起Row对象和模式之间的对应关系，也就是把数据和模式对应起来
studentDF = spark.createDataFrame(rowRDD,schema)

#写入数据库
prop = {}
prop['user'] = 'root'
prop['password'] = '123456'
prop['driver'] = 'com.mysql.jdbc.Driver'
studentDF.write.jdbc("jdbc:mysql://localhost:3306/spark?useSSL=false",'student','append',prop)