<?xml version="1.0" encoding="utf-8" ?><rss version="2.0"><channel><title><![CDATA[狗子的逆袭之路]]></title><description><![CDATA[JAVA小白]]></description><link>https://blog.youkuaiyun.com/u013603364</link><language>zh-cn</language><generator>https://blog.youkuaiyun.com/</generator><copyright><![CDATA[Copyright &copy; u013603364]]></copyright><item><title><![CDATA[Centos7.9离线安装Redis-5.0.4【2022年最新--保姆级部署教程-rpm安装包免费下载】]]></title><link>https://blog.youkuaiyun.com/u013603364/article/details/125180118</link><guid>https://blog.youkuaiyun.com/u013603364/article/details/125180118</guid><author>u013603364</author><pubDate>Wed, 08 Jun 2022 16:15:00 +0800</pubDate><description><![CDATA[点击如下链接下载即可【Redis-5.0.4】
Redis-5.04–免积分下载
免费分享无需积分]]></description><category></category></item><item><title><![CDATA[Centos7.9纯离线安装Nginx-1.18.0【2022年最新--保姆级部署教程-内附rpm安装包免费下载】]]></title><link>https://blog.youkuaiyun.com/u013603364/article/details/125179743</link><guid>https://blog.youkuaiyun.com/u013603364/article/details/125179743</guid><author>u013603364</author><pubDate>Wed, 08 Jun 2022 15:30:00 +0800</pubDate><description><![CDATA[注意：如需Nginx-1.20.1版本去我的资源连接下载即可
链接：nginx-1.18.0-1.el7.ngx.x86_64
免费分享无需积分]]></description><category></category></item><item><title><![CDATA[Centos7.5搭建本地Yum源【2022最新--保姆级部署】]]></title><link>https://blog.youkuaiyun.com/u013603364/article/details/125182750</link><guid>https://blog.youkuaiyun.com/u013603364/article/details/125182750</guid><author>u013603364</author><pubDate>Wed, 08 Jun 2022 13:44:59 +0800</pubDate><description><![CDATA[CentOS-7-x86_64-Everything-1804.iso]]></description><category></category></item><item><title><![CDATA[Centos7.9离线安装MySQL8.0.29【2022年最新--保姆级部署教程-rpm安装包免费下载】]]></title><link>https://blog.youkuaiyun.com/u013603364/article/details/125169541</link><guid>https://blog.youkuaiyun.com/u013603364/article/details/125169541</guid><author>u013603364</author><pubDate>Wed, 08 Jun 2022 10:26:28 +0800</pubDate><description><![CDATA[Centos7.9
mysql-8.0.29
rpm离线安装
附带本地镜像搭建]]></description><category></category></item><item><title><![CDATA[Centos7离线安装JDK1.8【超详细】]]></title><link>https://blog.youkuaiyun.com/u013603364/article/details/125032523</link><guid>https://blog.youkuaiyun.com/u013603364/article/details/125032523</guid><author>u013603364</author><pubDate>Sun, 29 May 2022 17:02:21 +0800</pubDate><description><![CDATA[Centos7离线安装JDK1.8带1.8安装包【超详细】]]></description><category></category></item><item><title><![CDATA[《将博客搬至优快云》]]></title><link>https://blog.youkuaiyun.com/u013603364/article/details/124207615</link><guid>https://blog.youkuaiyun.com/u013603364/article/details/124207615</guid><author>u013603364</author><pubDate>Thu, 14 Apr 2022 18:04:00 +0800</pubDate><description><![CDATA[《将博客搬至优快云》《将博客搬至优快云》《将博客搬至优快云》《将博客搬至优快云》《将博客搬至优快云》《将博客搬至优快云》《将博客搬至优快云》《将博客搬至优快云》《将博客搬至优快云》《将博客搬至优快云》《将博客搬至优快云》
...]]></description><category></category></item><item><title><![CDATA[大数据简介「 什么事大数据」]]></title><link>https://blog.youkuaiyun.com/u013603364/article/details/124170084</link><guid>https://blog.youkuaiyun.com/u013603364/article/details/124170084</guid><author>u013603364</author><pubDate>Thu, 14 Apr 2022 14:00:57 +0800</pubDate><description><![CDATA[什么是大数据]]></description><category></category></item><item><title><![CDATA[Spark V3.0 概述及与Hadoop对比]]></title><link>https://blog.youkuaiyun.com/u013603364/article/details/118399239</link><guid>https://blog.youkuaiyun.com/u013603364/article/details/118399239</guid><author>u013603364</author><pubDate>Thu, 01 Jul 2021 22:02:48 +0800</pubDate><description><![CDATA[]]></description><category></category></item><item><title><![CDATA[Linux防火墙关闭方法]]></title><link>https://blog.youkuaiyun.com/u013603364/article/details/95992487</link><guid>https://blog.youkuaiyun.com/u013603364/article/details/95992487</guid><author>u013603364</author><pubDate>Thu, 01 Jul 2021 21:40:38 +0800</pubDate><description><![CDATA[Linux防火墙关闭方法

关闭防火墙：

1、查看状态：systemctl status firewalld





2、关闭： systemctl stop firewalld（只执行这个，重启后不行，还必须执行systemclt disable firewalld）





1.1、查看selinux状态：getenforce





2.2、关闭：编辑文件 /etc/selinux...]]></description><category></category></item><item><title><![CDATA[HDFS入门]]></title><link>https://blog.youkuaiyun.com/u013603364/article/details/96598350</link><guid>https://blog.youkuaiyun.com/u013603364/article/details/96598350</guid><author>u013603364</author><pubDate>Wed, 12 May 2021 15:45:31 +0800</pubDate><description><![CDATA[HDFS入门

1.HDFS基本概念：


HDFS是Hadoop Distribute File System 的简称，意为：Hadoop分布式文件系统。是Hadoop核心组件之一，作为最底层的分布式存储服务而存在。
分布式文件系统解决的问题就是大数据存储。

2． HDFS重要特性


A:是一个文件系统 用于存储文件的  提供统一命名空间的目录树结构 便于用户操作文件系统
B:是一个分布式文...]]></description><category></category></item><item><title><![CDATA[Kafuka面试（整合Kafka两种模式区别）]]></title><link>https://blog.youkuaiyun.com/u013603364/article/details/124207715</link><guid>https://blog.youkuaiyun.com/u013603364/article/details/124207715</guid><author>u013603364</author><pubDate>Sat, 14 Sep 2019 21:08:00 +0800</pubDate><description><![CDATA[整合Kafka两种模式说明
★面试题：Receiver &amp; Direct

开发中我们经常会利用SparkStreaming实时地读取kafka中的数据然后进行处理，在spark1.3版本后，kafkaUtils里面提供了两种创建DStream的方法:
1.Receiver接收方式：
KafkaUtils.createDstream(开发中不用，了解即可，但是面试可能会问)
Receiv...]]></description><category></category></item><item><title><![CDATA[secondary namenode 检查点]]></title><link>https://blog.youkuaiyun.com/u013603364/article/details/124207717</link><guid>https://blog.youkuaiyun.com/u013603364/article/details/124207717</guid><author>u013603364</author><pubDate>Sat, 14 Sep 2019 21:07:00 +0800</pubDate><description><![CDATA[secondary namenode


NameNode职责是管理元数据信息，DataNode的职责是负责数据具体存储，那么SecondaryNameNode的作用是什么？对很多初学者来说是非常迷惑的。它为什么会出现在HDFS中。从它的名字上看，它给人的感觉就像是NameNode的备份。但它实际上却不是。
大家猜想一下，当HDFS集群运行一段事件后，就会出现下面一些问题：
ledit logs...]]></description><category></category></item><item><title><![CDATA[MapReduce总结]]></title><link>https://blog.youkuaiyun.com/u013603364/article/details/124207716</link><guid>https://blog.youkuaiyun.com/u013603364/article/details/124207716</guid><author>u013603364</author><pubDate>Sat, 14 Sep 2019 21:06:00 +0800</pubDate><description><![CDATA[MapReduce思想：
  核心：
  分而治之，先分在和
  应用场景：
  复杂任务，没有依赖，以并行提供处理效率
  脉络体现：

    先map后reduce
        map：把复杂的任务拆分成任务，局部进行计算，得出局部结果
        reduce：把map的局部结果进行全局汇总，得到最终结果...]]></description><category></category></item><item><title><![CDATA[Map、Reduce和Job方法总结]]></title><link>https://blog.youkuaiyun.com/u013603364/article/details/124207721</link><guid>https://blog.youkuaiyun.com/u013603364/article/details/124207721</guid><author>u013603364</author><pubDate>Sat, 14 Sep 2019 21:05:00 +0800</pubDate><description><![CDATA[map方法：

map的方法

public void map(Object key, Text value, Context context) throws IOException, InterruptedException {…}

key:偏移量，一般为0，用不到
value：每行的值
context：可以记录输入的key和value

例如：context.write(new Text(...]]></description><category></category></item><item><title><![CDATA[Reduce端join弊端&方法key探讨]]></title><link>https://blog.youkuaiyun.com/u013603364/article/details/124207722</link><guid>https://blog.youkuaiyun.com/u013603364/article/details/124207722</guid><author>u013603364</author><pubDate>Sat, 14 Sep 2019 21:04:00 +0800</pubDate><description><![CDATA[]]></description><category></category></item><item><title><![CDATA[Hadoop 两种环境下的checkpoint机制]]></title><link>https://blog.youkuaiyun.com/u013603364/article/details/124207719</link><guid>https://blog.youkuaiyun.com/u013603364/article/details/124207719</guid><author>u013603364</author><pubDate>Sat, 14 Sep 2019 21:04:00 +0800</pubDate><description><![CDATA[伪分布式环境：



HA环境checkpoint机制
配置了HA的HDFS中，有active和standby namenode两个namenode节点。他们的内存中保存了一样的集群元数据信息，因为standby namenode已经将集群状态存储在内存中了，所以创建检查点checkpoint的过程只需要从内存中生成新的fsimage。
详细过程如下： (standby namenode=SbN...]]></description><category></category></item><item><title><![CDATA[MapReduce的Partitioner案例]]></title><link>https://blog.youkuaiyun.com/u013603364/article/details/124207718</link><guid>https://blog.youkuaiyun.com/u013603364/article/details/124207718</guid><author>u013603364</author><pubDate>Sat, 14 Sep 2019 21:03:00 +0800</pubDate><description><![CDATA[项目简介

这里给出一个经典的词频统计的案例：统计如下样本数据中每个单词出现的次数。


SparkHBase
HiveFlinkStormHadoopHBaseSpark
Flink
HBaseStorm
HBaseHadoopHiveFlink
HBaseFlinkHiveStorm
HiveFlinkHadoop
HBaseHive
HadoopSparkHBaseStorm
HB...]]></description><category></category></item><item><title><![CDATA[MapReduce的WordCount案例]]></title><link>https://blog.youkuaiyun.com/u013603364/article/details/124207723</link><guid>https://blog.youkuaiyun.com/u013603364/article/details/124207723</guid><author>u013603364</author><pubDate>Sat, 14 Sep 2019 21:02:00 +0800</pubDate><description><![CDATA[项目简介

这里给出一个经典的词频统计的案例：统计如下样本数据中每个单词出现的次数。


SparkHBase
HiveFlinkStormHadoopHBaseSpark
Flink
HBaseStorm
HBaseHadoopHiveFlink
HBaseFlinkHiveStorm
HiveFlinkHadoop
HBaseHive
HadoopSparkHBaseStorm
HBaseH...]]></description><category></category></item><item><title><![CDATA[MapReduce作业任务的管理]]></title><link>https://blog.youkuaiyun.com/u013603364/article/details/124207720</link><guid>https://blog.youkuaiyun.com/u013603364/article/details/124207720</guid><author>u013603364</author><pubDate>Sat, 14 Sep 2019 21:02:00 +0800</pubDate><description><![CDATA[通过 web console 监控作业的运行：

通过 yarn application 命令来进行作业管理
列出帮助信息：yarn application --help
查看运行的 MapReduce 程序：yarn application --list
查看应用状态：yarn application -status &lt;application_id&gt;
强制杀死应用：yarn a...]]></description><category></category></item><item><title><![CDATA[MapReduce使用Partitioner分区案例]]></title><link>https://blog.youkuaiyun.com/u013603364/article/details/124207739</link><guid>https://blog.youkuaiyun.com/u013603364/article/details/124207739</guid><author>u013603364</author><pubDate>Sat, 14 Sep 2019 21:01:00 +0800</pubDate><description><![CDATA[Mapper：

import java.io.IOException;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.NullWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Mapper;
i...]]></description><category></category></item></channel></rss>