Spark SQL 编程初级实践

scala> import org.apache.spark.sql.types._
import org.apache.spark.sql.types._

scala> import org.apache.spark.sql.Row
import org.apache.spark.sql.Row

scala> val peopleRDD = spark.sparkContext.textFile("file:///home/xhj/employee.txt")
peopleRDD: org.apache.spark.rdd.RDD[String] = file:///home/xhj/employee.txt MapPartitionsRDD[1] at textFile at <console>:27

scala> val schemaString = "id name age"
schemaString: String = id name age

scala> val fields = schemaString.split(" ").map(fieldName => StructField(fieldName, StringType, nullable = true))
fields: Array[org.apache.spark.sql.types.StructField] = Array(StructField(id,StringType,true), StructField(name,StringType,true), StructField(age,StringType,true))

scala> val schema = StructType(fields)
schema: org.apache.spark.sql.types.StructType = StructType(StructField(id,StringType,true), StructField(name,StringType,true), StructField(age,StringType,true))

scala> val rowRDD = peopleRDD.map(_.split(",")).map(attributes => Row(attributes(0), attributes(1).trim, attributes(2).trim))
rowRDD: org.apache.spark.rdd.RDD[org.apache.spark.sql.Row] = MapPartitionsRDD[3] at map at <console>:29

scala> val peopleDF = spark.createDataFrame(rowRDD, schema)
peopleDF: org.apache.spark.sql.DataFrame = [id: string, name: string ... 1 more field]

scala> peopleDF.createOrReplaceTempView("people")

scala> val results = spark.sql("SELECT id,name,age FROM people")
results: org.apache.spark.sql.DataFrame = [id: string, name: string ... 1 more field]

scala> results.map(attributes => "id: " + attributes(0)+","+"name:"+attributes(1)+","+"age:"+attributes(2)).show()
+--------------------+                                                          
|               value|
+--------------------+
|id: 1,name:Ella,a...|
|id: 2,name:Bob,ag...|
|id: 3,name:Jack,a...|
+--------------------+

import java.util.Properties

import com.sun.org.apache.xalan.internal.xsltc.compiler.util.IntType
import org.apache.spark.sql.types._
import org.apache.spark.sql.{Row, SparkSession}


object exercise03 {
  val spark: SparkSession = SparkSession.builder().getOrCreate()
  def main(args: Array[String]): Unit = {

    val jdbcDF = spark.read.format("jdbc").option("url", "jdbc:mysql://localhost:3306/sparktest?serverTimezone=UTC")
      .option("driver", "com.mysql.cj.jdbc.Driver").option("dbtable", "employee")
      .option("user", "root").option("password", "root").load()
    jdbcDF.show()

    val studentRDD=spark.sparkContext.parallelize(Array("3 Mary F 26","4 Tom M 23"))
      .map(x=>x.split(" "))
    val ROWRDD=studentRDD.map(x=>Row(x(0).toInt,x(1).trim,x(2).trim,x(3).toInt))
    ROWRDD.foreach(print)
    //设置模式信息
    val schema=StructType(List(StructField("id",IntegerType,true),StructField("name",StringType,true),StructField("gender",StringType,true),StructField("age", IntegerType, true)))

    val studentDF=spark.createDataFrame(ROWRDD,schema)

    val parameter=new Properties()
    parameter.put("user","root")
    parameter.put("password","root")
    parameter.put("driver","com.mysql.cj.jdbc.Driver")
    studentDF.write.mode("append").jdbc("jdbc:mysql://localhost:3306/sparktest?serverTimezone=UTC","employee",parameter)
    jdbcDF.show()
  }
}