寒假学习进度-5

spark sql的基本编程方法

连接文件

val df = spark.read.json(“file:///abc/lianxi/bigdata/src/main/data/people.json”)

显示

scala> df.show() 

去重并显示

scala> df.distinct().show() 

查找

scala> df.filter(df("age") > 30 ).show() 

排序

scala> df.sort(df("name").asc).show() 

平均值

scala> df.agg("age"->"avg") 

实现从 RDD 转换得到 DataFrame

import org.apache.spark.sql.catalyst.encoders.ExpressionEncoder
import org.apache.spark.sql.Encoder 
import spark.implicits._ object RDDtoDF 
{     def main(args: Array[String]) 
{ case class Employee(id:Long,name: String, age: Long)
 val employeeDF = spark.sparkContext.textFile("file:///usr/local/spark/employee.txt").map(_.split(",")).map(at tributes => Employee(attributes(0).trim.toInt,attributes(1), 
attributes(2).trim.toInt)).toDF() employeeDF.createOrReplaceTempView("employee") val employeeRDD = spark.sql("select id,name,age from employee") 
employeeRDD.map(t => "id:"+t(0)+","+"name:"+t(1)+","+"age:"+t(2)).show()     } } 

利用 DataFrame 读写 MySQL 的数据 

import java.util.Properties
import org.apache.spark.sql.types._ 
import org.apache.spark.sql.Row object TestMySQL 
{     def main(args: Array[String]) 
{ val employeeRDD = spark.sparkContext.parallelize(Array("3 Mary F 26","4 Tom M 23")).map(_.split(" ")) 
val schema = StructType(List(StructField("id", IntegerType, true),StructField("name", StringType, true),StructField("gender", StringType, true),StructField("age", IntegerType, true))) 
val rowRDD = employeeRDD.map(p => Row(p(0).toInt,p(1).trim, p(2).trim,p(3).toInt)) 
val employeeDF = spark.createDataFrame(rowRDD, schema) 
val prop = new Properties() prop.put("user", "root")  
prop.put("password", "hadoop")  
prop.put("driver","com.mysql.jdbc.Driver") 
employeeDF.write.mode("append").jdbc("jdbc:mysql://localhost:3306/sparktest", sparktest.employee", prop) 
val jdbcDF = spark.read.format("jdbc").option("url", "jdbc:mysql://localhost:3306/sparktest").option("driver","com.mysql.jdbc.Driver").optio n("dbtable","employee").option("user","root").option("password", "hadoop").load() jdbcDF.agg("age" -> "max", "age" -> "sum")     } }