首先,我们需要注册DataFrame为临时视图,然后使用Hive SQL语句来实现这个转换过程。 // 注册DataFrame为临时视图df.createOrReplaceTempView("my_table")// 使用Hive SQL语句提取数组并使用explode函数转为多行valresult=spark.sql("SELECT name, age, explode(hobbies) as hobby FROM my_table")result.show() 1. 2...
- `array_except`:返回第一个数组中与第二个数组不同的元素 - `array_intersect`:返回两个数组的交集 - `array_union`:返回两个数组的并集 - `array_join`:将数组中的元素连接成字符串 下面是一个使用`array_contains`函数的示例: ```markdown ```scala import org.apache.spark.sql.functions._ val co...
(3,"xi'an",600329)))res6:org.apache.spark.rdd.RDD[(Int,String,Int)]=ParallelCollectionRDD[10]at parallelize at<console>:22scala>res6.toDF("id","name","postcode")res7:org.apache.spark.sql.DataFrame=[id:int,name:string,postcode:int]scala>res7.show+---+---+---+|id|name|postcode...
创建RDDval lineRDD=sc.textFile("hdfs://node01:8020/person.txt").map(_.split(" "))//RDD[Array[String]]3.定义caseclass(相当于表的schema)caseclassPerson(id:Int,name:String,age:Int)4.将RDD和caseclass关联 val personRDD=lineRDD.map(x=>Person(x(0).toInt,x(1),x(2).toInt))//RDD[...
CustomParquetRelation(path: String)(@transient val sqlContext: SQLContext)extends BaseRelation with PrunedFilteredScan with InsertableRelation {private val df = sqlContext.read.parquet(path)override def schema: StructType = df.schemaoverride def buildScan(requiredColumns: Array[String], filters: Array...
spark.sql(“selectappopen[0]fromappopentable“) struct组合map array 结构 1.hive建表语句 droptableappopendetail;createtableifnotexistsappopendetail ( username String, appname String, opencountINT)rowformat delimited fields terminatedby'|'location'/hive/table/appopendetail';createtableifnotexistsappop...
scala> array(0) res28: org.apache.spark.sql.Row = [zhangsan,30] scala> array(0)(0) res29: Any = zhangsan scala> array(0).getAs[String]("name") res30: String = zhangsan 3、DataSet DataSet是具有强类型的数据集合,需要提供对应的类型信息。 3.1 创建DataSet 1)使用样例类序列创建DataSet ...
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(attributes...
package cn.itcast.spark.sql import org.apache.spark.sql.SparkSession object UDF { def main(args: Array[String]): Unit = { val spark = SparkSession.builder() .appName("window") .master("local[6]") .getOrCreate() import spark.implicits._ import org.apache.spark.sql.functions._ val ...
object SparkPi {// 必须是object,如果在IDEA创建文件的时候写为class,main函数是无法加载的。defmain(args: Array[String]){valspark=SparkSession .builder() .appName("SparkPi") .getOrCreate() 检查主类代码配置。 valspark=SparkSession .builder() .appName("SparkPi") .config("key1","value1") ...