SPARK_sql加载,hive以及jdbc使用

sql加载

格式

 或者下面这种直接json加载

或者下面这种spark的text加载

以及rdd的加载

上述记得配置文件加入.mastrt("local")或者spark://master:7077

dataset的生成

 下面是dataframe

 下面是dataset

$ bin/spark-shell --master spark://master01:7077 --jars mysql-connector-java-5.1.27-bin.jar 

加载连接的两种方式

// Note: JDBC loading and saving can be achieved via either the load/save or jdbc methods

// Loading data from a JDBC source

val jdbcDF = spark.read.format("jdbc").option("url",

"jdbc:mysql://master01:3306/mysql").option("dbtable", "db").option("user",

"root").option("password", "hive").load()

val connectionProperties = new Properties()

connectionProperties.put("user", "root")

connectionProperties.put("password", "hive")

val jdbcDF2 = spark.read .jdbc("jdbc:mysql://master01:3306/mysql", "db", connectionProperties)

保存数据的两种方式

// Saving data to a JDBC source

jdbcDF.write

.format("jdbc")

.option("url", "jdbc:mysql://master01:3306/mysql")

.option("dbtable", "db")

.option("user", "root")

.option("password", "hive")

.save()

jdbcDF2.write .jdbc("jdbc:mysql://master01:3306/mysql", "db", connectionProperties)

// Specifying create table column data types on write

jdbcDF.write

.option("createTableColumnTypes", "name CHAR(64), comments VARCHAR(1024)")

.jdbc("jdbc:mysql://master01:3306/mysql", "db", connectionProperties)

原文地址：https://www.cnblogs.com/pursue339/p/10618722.html