spark连接mysql数据库

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

pyspark --jars /usr/local/spark/jars/mysql-connector-java-8.0.25.jar --driver-class-path /usr/local/spark/jars/mysql-connector-java-8.0.25.jar

 

 

 

 

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

createdatabase spark; use spark; createtable student (idint(4), namechar(20), gender char(4), age int(4)); altertable student changeididint auto_increment primary key; insertinto student values(1,‘Xueqian‘,‘F‘,23); insertinto student values(2,‘Weiliang‘,‘M‘,24); 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()

jdbcDF = 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", "123456").load() jdbcDF.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 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.jdbc.Driver" studentDF.write.jdbc("jdbc:mysql://localhost:3306/spark",‘student‘,‘append‘, prop)

 

select * from student;