join

1、dataset的join连接，通过key进行关联，一般情况下的join都是inner join，类似sql里的inner join key包括以下几种情况： a key expression a key-selector function one or more field position keys (Tuple DataSet only). Case Class Fields 2、inner join的几种情况 2.1 缺省的join，jion到一个Tuple2元组里 public static class User { public String name; public int zip; } public static class Store { public Manager mgr; public int zip; } DataSet<User> input1 = // [...] DataSet<Store> input2 = // [...] // result dataset is typed as Tuple2 DataSet<Tuple2<User, Store>> result = input1.join(input2) .where("zip") // key of the first input (users) .equalTo("zip"); //

Simple step for EMC NW & NMM (1) disable WINDOWS UAC (reboot) (2) SET windows domain user AS sysadmin (3) modify hosts (4) install software (NW , NMM) (reboot) (5) CONFIG NWDROP VIEW [partition_show] GO SET ANSI_NULLS ON GO SET QUOTED_IDENTIFIER ON GO CREATE view [partition_show] as SELECT distinct OBJECT_NAME(T2.object_id) TABLE_NAME ,T1.partition_number ,T4.name as "function_name" ,T3.name as "schema_name" ,T7.name File_group_name ,T1.rows ,CASE boundary_value_on_right WHEN 1 THEN 'less than' ELSE 'less than or equal to ' END as 'comparision' --,CONVERT(varchar(100), T5.value, 112) value ,T5

use master go --Get all logins with sysadmin role. select b.name,b.type,b.type_desc,c.name from sys.server_role_members a inner join sys.server_principals b on a.member_principal_id = b.principal_id inner join sys.server_principals c on a.role_principal_id = c.principal_id where c.name = 'sysadmin' and c.type='R' go use test go --Get database users with db_owner role select b.name,b.type,b.type_desc,c.name from sys.database_role_members a inner join sys.database_principals b on a.member_principal_id = b.principal_id inner join sys.database_principals c on a.role_principal_id = c.principal_id

不是原创必须要尊重原文作者，我是从国外作者 Ivan Mushketyk 拷贝过来学习的，大家也可以借鉴学习，原文地址： FLink优化方法 Use Flink Tuples When you use operations like groupBy, join, or keyBy, Flink provides you a number of options to select a key in your dataset. You can use a key selector function: // Join movies and ratings datasets movies . join ( ratings ) // Use movie id as a key in both cases . where ( new KeySelector < Movie , String > ( ) { @Override public String getKey ( Movie m ) throws Exception { return m . getId ( ) ; } } ) . equalTo ( new KeySelector < Rating , String > ( ) { @Override public String getKey ( Rating r ) throws

object DataSetDemo1 { def main ( args : Array [ String ] ) : Unit = { val session = SparkSession . builder ( ) . master ( "local" ) . appName ( this . getClass . getSimpleName ) . getOrCreate ( ) import session . implicits . _ val dataSet : Dataset [ String ] = session . read . textFile ( "D:\\abc\\person\\input\\person2.txt" ) val ds = dataSet . map ( line = > { val splits = line . split ( "," ) Student ( splits ( 0 ) , splits ( 1 ) . toInt , splits ( 2 ) . toInt ) } ) val rdd : RDD [ String ] = session . sparkContext . makeRDD ( Array ( "aa" , "bb" , "cc" ) ) val ds2 : Dataset [ String ] =

现在有 T1、T2、T3 三个线程，你怎样保证 T2 在 T1 执行完后执行，T3 在 T2 执行完后执 行？ 这个线程问题通常会在第一轮或电话面试阶段被问到，目的是检测你对”join”方法是否熟 悉。这个多线程问题比较简单，可以用 join 方法实现。 首先给出结论：t.join()方法只会使主线程进入等待池并等待t线程执行完毕后才会被唤醒。并不影响同一时刻处在运行状态的其他线程。 下面则是分析过程。 之前对于join()方法只是了解它能够使得t.join()中的t优先执行，当t执行完后才会执行其他线程。能够使得线程之间的并行执行变成串行执行。 public class TestJoin { public static void main(String[] args) throws InterruptedException { // TODO Auto-generated method stub ThreadTest t1=new ThreadTest("A"); ThreadTest t2=new ThreadTest("B"); t1.start(); t2.start(); } } class ThreadTest extends Thread { private String name; public ThreadTest(String name){ this.name