大数据学习之sparksql-JDBC到其他数据库

jdbcDF = spark.read \ .format("jdbc") \ .option("url", "jdbc:postgresql:dbserver") \ .option("dbtable", "schema.tablename") \ .option("user", "username") \ .option("password", "password") \ .load() jdbcDF2 = spark.read \ .jdbc("jdbc:postgresql:dbserver", "schema.tablename", properties={"user": "username", "password": "password"}) # Specifying dataframe column data types on read jdbcDF3 = spark.read \ .format("jdbc") \ .option("url", "jdbc:postgresql:dbserver") \ .option("dbtable", "schema.tablename") \ .option("user", "username") \ .option("password", "password") \ .option("customSchema", "id DECIMAL(38, 0), name STRING") \ .load() # Saving data to a JDBC source jdbcDF.write \ .format("jdbc") \ .option("url", "jdbc:postgresql:dbserver") \ .option("dbtable", "schema.tablename") \ .option("user", "username") \ .option("password", "password") \ .save() jdbcDF2.write \ .jdbc("jdbc:postgresql:dbserver", "schema.tablename", properties={"user": "username", "password": "password"}) # Specifying create table column data types on write jdbcDF.write \ .option("createTableColumnTypes", "name CHAR(64), comments VARCHAR(1024)") \ .jdbc("jdbc:postgresql:dbserver", "schema.tablename", properties={"user": "username", "password": "password"})