Spark 连接 MySQL 数据库
目录
1. 安装启动检查 MySQL 服务
service mysql start
sudo netstat -tap | grep mysql
2. Spark 连接 MySQL 驱动程序
pyspark --jars /usr/local/spark/jars/mysql-connector-java-8.0.25/mysql-connector-java-8.0.25.jar --driver-class-path /usr/local/spark/jars/mysql-connector-java-8.0.25/mysql-connector-java-8.0.25.jar
3. 启动 MySQL Shell，新建数据库 spark，表 student
sudo mysql -u root -p
mysql> create database spark;
mysql> use spark;
mysql> create table student (id int(4), name char(20), gender char(4), age int(4));
mysql> alter table student change id id int auto_increment primary key;
mysql> insert into student values(1,‘Xueqian‘,‘F‘,23);
mysql> insert into student values(2,‘Weiliang‘,‘M‘,24);
mysql> select * from student;
4. Spark 读取 MySQL 数据库中的数据
>>> jdbcDF = spark.read.format("jdbc").option("url", "jdbc:mysql://localhost:3306/spark").option("driver","com.mysql.cj.jdbc.Driver").option("dbtable", "student").option("user", "root").option("password", "hadoop").load()
>>> jdbcDF.show()
5. Spark 向 MySQL 数据库写入数据
>>> from pyspark.sql.types import Row
>>> from pyspark.sql.types import StructType
>>> from pyspark.sql.types import StructField
>>> from pyspark.sql.types import StringType
>>> from pyspark.sql.types import IntegerType
>>> studentRDD = spark.sparkContext.parallelize(["3 Rongcheng M 26","4 Guanhua M 27"]).map(lambda line : line.split(" "))
# 下面要设置模式信息
>>> schema = StructType([StructField("name", StringType(), True),StructField("gender", StringType(), True),StructField("age",IntegerType(), True)])
>>> rowRDD = studentRDD.map(lambda p : Row(p[1].strip(), p[2].strip(),int(p[3])))
# 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)
>>> prop = {}
>>> prop[‘user‘] = ‘root‘
>>> prop[‘password‘] = ‘hadoop‘
>>> prop[‘driver‘] = "com.mysql.cj.jdbc.Driver"
>>> studentDF.write.jdbc("jdbc:mysql://localhost:3306/spark",‘student‘,‘append‘, prop)
mysql> select * from student;