SGG-2024年新版spark教程(Java语言)

墨离尘 · 发表于 2024-8-2 13:43

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[color=rgba(0, 0, 0, 0.55)]目录

[color=rgba(0, 0, 0, 0.55)]001.Spark-教程简介

[color=rgba(0, 0, 0, 0.55)]002.Spark-文件结构-介绍

[color=rgba(0, 0, 0, 0.55)]003.Spark-基础概念-介绍-分布式

[color=rgba(0, 0, 0, 0.55)]004.Spark-基础概念-介绍-计算

[color=rgba(0, 0, 0, 0.55)]005.Spark-基础概念-介绍-分布式基础架构

[color=rgba(0, 0, 0, 0.55)]006.Spark-基础概念-介绍-框架

[color=rgba(0, 0, 0, 0.55)]007.Spark-基础概念-介绍-Spark和MR的关系

[color=rgba(0, 0, 0, 0.55)]008.Spark-介绍

[color=rgba(0, 0, 0, 0.55)]009.Spark-部署方式-介绍

[color=rgba(0, 0, 0, 0.55)]010.Spark-解压后的文件结构

[color=rgba(0, 0, 0, 0.55)]011.Spark-部署环境-Local

[color=rgba(0, 0, 0, 0.55)]012.Spark-部署环境-Local-演示

[color=rgba(0, 0, 0, 0.55)]013.Spark-部署环境-Yarn-演示

[color=rgba(0, 0, 0, 0.55)]014.Spark-部署环境-Yarn-历史服务

[color=rgba(0, 0, 0, 0.55)]015.Spark-部署环境-Yarn-两种执行方式Cluster和Client

[color=rgba(0, 0, 0, 0.55)]016.Spark-部署环境-几种模式的对比

[color=rgba(0, 0, 0, 0.55)]017.Spark-数据结构-说明

[color=rgba(0, 0, 0, 0.55)]018.Spark-RDD-介绍

[color=rgba(0, 0, 0, 0.55)]019.Spark-RDD-数据处理流程简介

[color=rgba(0, 0, 0, 0.55)]020.Spark-RDD-计算原理

[color=rgba(0, 0, 0, 0.55)]021.Spark-RDD-计算原理-补充

[color=rgba(0, 0, 0, 0.55)]022.Spark-RDD-代码-环境的准备

[color=rgba(0, 0, 0, 0.55)]023.Spark-RDD-代码-对接内存数据源构建RDD对象

[color=rgba(0, 0, 0, 0.55)]024.Spark-RDD-代码-对接磁盘数据源构建RDD对象

[color=rgba(0, 0, 0, 0.55)]025.Spark-RDD-代码-RDD的理解

[color=rgba(0, 0, 0, 0.55)]026.Spark-RDD-代码-RDD的分区

[color=rgba(0, 0, 0, 0.55)]027.Spark-RDD-代码-内存数据源-分区数量的设定

[color=rgba(0, 0, 0, 0.55)]028.Spark-RDD-代码-磁盘文件数据源-分区数量的设定

[color=rgba(0, 0, 0, 0.55)]029.Spark-RDD-代码-内存数据源-分区数据的分配

[color=rgba(0, 0, 0, 0.55)]030.Spark-RDD-代码-磁盘文件数据源-分区数据的分配

[color=rgba(0, 0, 0, 0.55)]031.Spark-RDD-代码-磁盘文件数据源-分区数据的分配-演示

[color=rgba(0, 0, 0, 0.55)]032 .Spark-RDD-课件梳理

[color=rgba(0, 0, 0, 0.55)]033.Spark-RDD-方法-介绍

[color=rgba(0, 0, 0, 0.55)]034.Spark-RDD-方法-方法的两大类-转换和行动

[color=rgba(0, 0, 0, 0.55)]035.Spark-RDD-方法-数据处理的两大类-单值和键值

[color=rgba(0, 0, 0, 0.55)]036.Spark-RDD-方法-转换-map

[color=rgba(0, 0, 0, 0.55)]037.Spark-RDD-方法-转换-map-1

[color=rgba(0, 0, 0, 0.55)]038.Spark-RDD-方法-转换-map-2

[color=rgba(0, 0, 0, 0.55)]039.Spark-RDD-方法-转换-map-3

[color=rgba(0, 0, 0, 0.55)]040.Spark-RDD-方法-转换-map-4

[color=rgba(0, 0, 0, 0.55)]041.Spark-RDD-方法-转换-filter

[color=rgba(0, 0, 0, 0.55)]042.Spark-RDD-方法-转换-flatMap

[color=rgba(0, 0, 0, 0.55)]043.Spark-RDD-方法-转换-flatMap-1

[color=rgba(0, 0, 0, 0.55)]044.Spark-RDD-方法-转换-groupBy

[color=rgba(0, 0, 0, 0.55)]045.Spark-RDD-回顾-原理

[color=rgba(0, 0, 0, 0.55)]046.Spark-RDD-回顾-方法

[color=rgba(0, 0, 0, 0.55)]047.Spark-RDD-Shuffle

[color=rgba(0, 0, 0, 0.55)]048.Spark-RDD-Shuffle-原理

[color=rgba(0, 0, 0, 0.55)]049.Spark-RDD-Shuffle-原理-补充

[color=rgba(0, 0, 0, 0.55)]050.Spark-RDD-Shuffle-演示

[color=rgba(0, 0, 0, 0.55)]051.Spark-RDD-方法-distinct

[color=rgba(0, 0, 0, 0.55)]052.Spark-RDD-方法-sortBy

[color=rgba(0, 0, 0, 0.55)]053.Spark-RDD-方法-KV类型数据介绍

[color=rgba(0, 0, 0, 0.55)]054.Spark-RDD-方法-KV类型数据补充

[color=rgba(0, 0, 0, 0.55)]055.Spark-RDD-方法-KV-mapValues

[color=rgba(0, 0, 0, 0.55)]056.Spark-RDD-方法-KV-wordCount

[color=rgba(0, 0, 0, 0.55)]057.Spark-RDD-方法-KV-groupByKey

[color=rgba(0, 0, 0, 0.55)]058.Spark-RDD-方法-KV-reduceByKey

[color=rgba(0, 0, 0, 0.55)]059.Spark-RDD-方法-KV-sortByKey

[color=rgba(0, 0, 0, 0.55)]060.Spark-RDD-方法-KV-reduceByKey和groupByKey的区别

[color=rgba(0, 0, 0, 0.55)]061.Spark-RDD-WordCount程序在环境中运行

[color=rgba(0, 0, 0, 0.55)]062.Spark-RDD-转换方法的回顾

[color=rgba(0, 0, 0, 0.55)]063.Spark-RDD-行动算子-介绍

[color=rgba(0, 0, 0, 0.55)]064.Spark-RDD-行动算子-collect

[color=rgba(0, 0, 0, 0.55)]065.Spark-RDD-行动算子-collect-补充

[color=rgba(0, 0, 0, 0.55)]066.Spark-RDD-行动算子-其他方法-1

[color=rgba(0, 0, 0, 0.55)]067.Spark-RDD-行动算子-其他方法-2

[color=rgba(0, 0, 0, 0.55)]068.Spark-RDD-行动算子-其他方法-3

[color=rgba(0, 0, 0, 0.55)]069.Spark-RDD-行动算子-Driver端和Executor端数据传输

[color=rgba(0, 0, 0, 0.55)]070.Spark-RDD-序列化-1

[color=rgba(0, 0, 0, 0.55)]071.Spark-RDD-序列化-2

[color=rgba(0, 0, 0, 0.55)]072.Spark-案例-数据格式说明

[color=rgba(0, 0, 0, 0.55)]073.Spark-案例-需求介绍

[color=rgba(0, 0, 0, 0.55)]074.Spark-案例-需求分析

[color=rgba(0, 0, 0, 0.55)]075.Spark-案例-需求设计

[color=rgba(0, 0, 0, 0.55)]076.Spark-案例-开发原则

[color=rgba(0, 0, 0, 0.55)]077.Spark-案例-代码实现-1

[color=rgba(0, 0, 0, 0.55)]078.Spark-案例-代码实现-2

[color=rgba(0, 0, 0, 0.55)]079.Spark-案例-代码实现-3

[color=rgba(0, 0, 0, 0.55)]080.Spark-案例-代码实现-4

[color=rgba(0, 0, 0, 0.55)]081.Spark-RDD-KRYO序列化框架

[color=rgba(0, 0, 0, 0.55)]082.Spark-RDD-依赖关系-介绍

[color=rgba(0, 0, 0, 0.55)]083.Spark-RDD-依赖关系-原理

[color=rgba(0, 0, 0, 0.55)]084.Spark-RDD-依赖关系-血缘关系

[color=rgba(0, 0, 0, 0.55)]085.Spark-RDD-依赖关系-依赖关系

[color=rgba(0, 0, 0, 0.55)]086.Spark-RDD-依赖关系-宽窄依赖关系

[color=rgba(0, 0, 0, 0.55)]087.Spark-RDD-依赖关系-作业，阶段和任务的关系

[color=rgba(0, 0, 0, 0.55)]088.Spark-RDD-依赖关系-任务的数量

[color=rgba(0, 0, 0, 0.55)]089.Spark-RDD-依赖关系-分区的数量

[color=rgba(0, 0, 0, 0.55)]090Spark-RDD-持久化和序列化的关系

[color=rgba(0, 0, 0, 0.55)]091.Spark-RDD-持久化-cache

[color=rgba(0, 0, 0, 0.55)]092.Spark-RDD-持久化-persist

[color=rgba(0, 0, 0, 0.55)]093.Spark-RDD-持久化-checkpoint

[color=rgba(0, 0, 0, 0.55)]094.Spark-RDD-持久化-shuffle算子的持久化

[color=rgba(0, 0, 0, 0.55)]095.Spark-RDD-分区器

[color=rgba(0, 0, 0, 0.55)]096.Spark-RDD-自定义分区器

[color=rgba(0, 0, 0, 0.55)]097.Spark-两个案例

[color=rgba(0, 0, 0, 0.55)]098.Spark-第一个案例问题原因

[color=rgba(0, 0, 0, 0.55)]099.Spark-广播变量

[color=rgba(0, 0, 0, 0.55)]100.Spark-RDD的局限性

[color=rgba(0, 0, 0, 0.55)]101.SparkSQL-介绍

[color=rgba(0, 0, 0, 0.55)]102.SparkSQL-环境对象的封装

[color=rgba(0, 0, 0, 0.55)]103.SparkSQL-模型对象的封装

[color=rgba(0, 0, 0, 0.55)]104.SparkSQL-SQL的操作

[color=rgba(0, 0, 0, 0.55)]105.SparkSQL-不同场景下环境对象的转换

[color=rgba(0, 0, 0, 0.55)]106.SparkSQL-不同场景下模型数据对象的转换

[color=rgba(0, 0, 0, 0.55)]107.SparkSQL-使用SQL的方式来访问数据模型

[color=rgba(0, 0, 0, 0.55)]108.SparkSQL-使用DSL的方式来访问数据模型

[color=rgba(0, 0, 0, 0.55)]109.SparkSQL-自定义udf函数对象

[color=rgba(0, 0, 0, 0.55)]110.SparkSQL-自定义udf函数的底层实现原理

[color=rgba(0, 0, 0, 0.55)]111.SparkSQL-自定义udaf函数的底层实现原理

[color=rgba(0, 0, 0, 0.55)]112.SparkSQL-自定义udaf函数的实现步骤-1

[color=rgba(0, 0, 0, 0.55)]113.SparkSQL-自定义udaf函数的实现步骤-2

[color=rgba(0, 0, 0, 0.55)]114.SparkSQL-自定义udaf函数的实现步骤-回顾

[color=rgba(0, 0, 0, 0.55)]115.SparkSQL-数据源-CSV

[color=rgba(0, 0, 0, 0.55)]116.SparkSQL-数据源-JSON

[color=rgba(0, 0, 0, 0.55)]117.SparkSQL-数据源-Parquet

[color=rgba(0, 0, 0, 0.55)]118.SparkSQL-数据源-JDBC

[color=rgba(0, 0, 0, 0.55)]119.SparkSQL-数据源-Hive

[color=rgba(0, 0, 0, 0.55)]120.SparkSQL-案例-数据准备

[color=rgba(0, 0, 0, 0.55)]121.SparkSQL-案例-数据准备-补充

[color=rgba(0, 0, 0, 0.55)]122.SparkSQL-案例-需求分析

[color=rgba(0, 0, 0, 0.55)]123.SparkSQL-案例-需求设计

[color=rgba(0, 0, 0, 0.55)]124.SparkSQL-案例-SQL实现-1

[color=rgba(0, 0, 0, 0.55)]125.SparkSQL-案例-SQL实现-2

[color=rgba(0, 0, 0, 0.55)]126.SparkSQL-案例-SQL实现-3

[color=rgba(0, 0, 0, 0.55)]127.SparkSQL-案例-SQL实现-4

[color=rgba(0, 0, 0, 0.55)]128.SparkSQL-案例-SQL实现-5

[color=rgba(0, 0, 0, 0.55)]129.SparkSQL-案例-SQL实现-6

[color=rgba(0, 0, 0, 0.55)]130.SparkSQL-案例-SQL实现-7

[color=rgba(0, 0, 0, 0.55)]131.SparkSQL-案例-SQL实现-8

[color=rgba(0, 0, 0, 0.55)]132.SparkSQL-案例-SQL实现-9

[color=rgba(0, 0, 0, 0.55)]133.SparkStreaming-介绍

[color=rgba(0, 0, 0, 0.55)]134.SparkStreaming-原理

[color=rgba(0, 0, 0, 0.55)]135.SparkStreaming-原理-补充

[color=rgba(0, 0, 0, 0.55)]136.SparkStreaming-课件梳理

[color=rgba(0, 0, 0, 0.55)]137.SparkStreaming-环境准备

[color=rgba(0, 0, 0, 0.55)]138.SparkStreaming-网络（Socket）数据流处理演示

[color=rgba(0, 0, 0, 0.55)]139.SparkStreaming-Kafka数据流处理演示

[color=rgba(0, 0, 0, 0.55)]140.SparkStreaming-DStream方法介绍

[color=rgba(0, 0, 0, 0.55)]141.SparkStreaming-DStream输出方法介绍

[color=rgba(0, 0, 0, 0.55)]142.SparkStreaming-窗口操作

[color=rgba(0, 0, 0, 0.55)]143.SparkStreaming-回顾-1

[color=rgba(0, 0, 0, 0.55)]144.SparkStreaming-回顾-2

[color=rgba(0, 0, 0, 0.55)]145.SparkStreaming-关闭-1

[color=rgba(0, 0, 0, 0.55)]146.SparkStreaming-关闭-2

[color=rgba(0, 0, 0, 0.55)]147.SparkStreaming-关闭-3

[color=rgba(0, 0, 0, 0.55)]148.Spark-内核-运行流程-1

[color=rgba(0, 0, 0, 0.55)]149.Spark-内核-运行流程-2

[color=rgba(0, 0, 0, 0.55)]150.Spark-内核-运行流程-3

[color=rgba(0, 0, 0, 0.55)]151.Spark-内核-核心对象

[color=rgba(0, 0, 0, 0.55)]152.Spark-内核-核心对象通信流程-Netty

[color=rgba(0, 0, 0, 0.55)]153.Spark-内核-Task任务的调度执行

[color=rgba(0, 0, 0, 0.55)]154.Spark-内核-Shuffle底层的实现原理-1

[color=rgba(0, 0, 0, 0.55)]155.Spark-内核-Shuffle底层的实现原理-2

[color=rgba(0, 0, 0, 0.55)]156.Spark-内核-内存管理

[color=rgba(0, 0, 0, 0.55)]157.Spark-内核-内存管理-补充

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