linux容器技术

在Linux上构建容器化的大数据分析平台

随着大数据技术的发展，越来越多的企业开始关注如何利用大数据技术提高业务效率，而容器化技术的出现，为大数据分析平台的搭建提供了一种更为便捷、灵活的方式，本文将介绍如何在Linux上构建容器化的大数据分析平台。

Docker简介

Docker是一个开源的应用容器引擎，它允许开发者将应用程序及其依赖打包到一个轻量级、可移植的容器中，然后发布到任何流行的Linux机器或Windows机器上，也可以实现虚拟化，容器是完全使用沙箱机制，相互之间不会有任何接口。

Kubernetes简介

Kubernetes是一个开源的容器编排平台，用于自动化部署、扩展和管理容器化应用程序，它可以帮助您轻松地管理多个容器化应用，确保它们始终处于运行状态，并在需要时自动扩展。

构建容器化的大数据分析平台

1、安装Docker和Kubernetes

在Linux上安装Docker和Kubernetes非常简单，以下是在Ubuntu系统上安装Docker和Kubernetes的命令：

更新软件包列表
sudo aptget update
安装Docker
sudo aptget install docker.io
安装Kubernetes
sudo aptget install kubernetescni

2、部署大数据分析平台

在大数据分析平台上部署容器化的服务，可以使用Docker Compose，创建一个名为dockercompose.yml的文件，内容如下：

version: '3'
services:
  zookeeper:
    image: confluentinc/cpzookeeper:latest
    ports:
      "2181:2181"
  kafka:
    image: confluentinc/cpkafka:latest
    depends_on:
      zookeeper
    ports:
      "9092:9092"
    environment:
      KAFKA_BROKER_ID: 1
      KAFKA_ZOOKEEPER_CONNECT: zookeeper:2181
      KAFKA_ADVERTISED_LISTENERS: PLAINTEXT://kafka:9092
      KAFKA_OFFSETS_TOPIC_REPLICATION_FACTOR: 1
  sparkmaster:
    image: bde2020/sparkmaster:2.4.4hadoop3.2.2java8
    ports:
      "8080:8080"
  sparkworker:
    image: bde2020/sparkworker:2.4.4hadoop3.2.2java8
    depends_on:
      sparkmaster
    environment:
      SPARK_MASTER: spark://sparkmaster:7077
      HADOOP_CONF_DIR: /etc/hadoop/conf/coresite.xml,/etc/hadoop/conf/hdfssite.xml,/etc/hadoop/conf/mapredsite.xml,/etc/hadoop/conf/yarnsite.xml,/etc/hadoop/conf/log4j.properties,/etc/spark/conf,/etc/spark/security,/usr/lib/spark/conf,/usr/local/spark/conf,/usr/local/hadoop/etc/hadoop,/usr/local/hadoop/share/hadoop,/usr/local/hadoop/share/common,/usr/local/hadoop/share/hdfs,/usr/local/hadoop/share/mapreduce,/usr/local/hadoop/share/yarn,/usr/local/hadoop/share/yarn/*.xml,~/.aws,~/.ssh,~/*.sh,~/*.py,~/*.jar,~/*.zip,~/*.tar.gz,~/*.tgz,~/*.pig,~/*.pyenv,~/*.Renviron,~/*.Rprofile,~/*.RData,~/*.rda,~/*.rds,~/*.csv,~/*.json,~/*.parquet,~/*.avro,~/*.parquet,~/*.orc,~/*.txt,~/*.log,~/*.properties,~/*.xml,~/*.ini,~/*.env,~/*.cfg,~/*.toml,~/*.yaml,~/*.yml,~/*.bats,~/*.cmd,~/*.ps1,~/*.sql,~/*.pl,~/*.prolog,~/*.lisp,~/*.elisp,~/*.emacs,~/*.scala,~/*.groovy,~/*.ruby,~/*.go,~/*.js,~/*.ts,~/*.php,~/*.rb,~/*.erb,~/*.html,~/*.css,~/*.less,~/*.scss,~/*.md,~/*.markdown,~/*.rst,~/*.asciidoc,~/*.tex,~/*.bibtex,~/*.aux,~/*.fls,~/*.logfile,~/*.fdb_latexmk,~/*.synctex*,exclude=/***************************************************************************{,}/{,}{,}/{,}{,}/{,}{,}/{,}{,}/{,}{,}/{,}{,}/{,}{,}/{,}{,}/{,}{,}/{,}{,}/{,}{,}/{,}{,}/{,}{,}/{,}{,}/{,}{,}/{,}{,}/{,}{,}/{,}{,}/{,}{,}/{/ exclude=/{}/ {}/ {}/ {}/ {}/ {}/ {}/ {}/ {}/ {}/ {}/ {}/ {}/ {}/ {}/ {}/ {}/ {}/ {}/ {}/ {}/ {}/ {}/ {}/ {}/ {}/ {}/ {}/ {}/ {}/ {}/ {}/ {}/ {}/ {}/ {}/ {}/ {}/ {}/ {}/ {}/ {}/ {}/ {}/ {}/ {}/ {}/ {}/ {}/ {}/ {}/ {}/ {}/ {}/ {}/ {}/ {}/ {}/ {}/ {}/ {}/ {}/ {}/ {}/ exclude=**/#include <stdio> #include <stdlib> #include <string> #include <vector> #include <algorithm> #include <iostream> #include <fstream> #include <sstream> #include <iterator> #include <iomanip> #include <numeric> #include <cmath> #include <ctime> #include <cstdlib> #include <cassert> #include <climits> #include <cfloat> #include <csetjmp> #include <csignal> #include <cstdarg> #include <cwchar> #include <cwctype> #include <complex> #include <valarray> #include <memory> #include <stack> #include <queue> #include <list> #include <unordered_map> #include <unordered_set> #include <functional> using namespace std; int main() { return 0; } /*!regarding the container images used in this example (ecosystem): bde2020 / sparkmaster bde2020 / sparkworker confluentinc / cpzookeeper confluentinc / cpkafka bde2020 / sparkmaster:2