日韩精品一区二区三区高清_久久国产热这里只有精品8_天天做爽夜夜做爽_一本岛在免费一二三区

合肥生活安徽新聞合肥交通合肥房產生活服務合肥教育合肥招聘合肥旅游文化藝術合肥美食合肥地圖合肥社保合肥醫院企業服務合肥法律

代寫EMS5730、代做Python設計程序

時間:2024-02-14  來源:合肥網hfw.cc  作者:hfw.cc 我要糾錯



EMS5**0 Spring 2024 Homework #0
Release date: Jan 10, 2024
Due date: Jan 21, 2024 (Sunday) 23:59 pm
(Note: The course add-drop period ends at 5:30 pm on Jan 22.)
No late homework will be accepted!
Every Student MUST include the following statement, together with his/her signature in the
submitted homework.
I declare that the assignment submitted on the Elearning system is
original except for source material explicitly acknowledged, and that the
same or related material has not been previously submitted for another
course. I also acknowledge that I am aware of University policy and
regulations on honesty in academic work, and of the disciplinary
guidelines and procedures applicable to breaches of such policy and
regulations, as contained in the website
Submission notice:
● Submit your homework via the elearning system
General homework policies:
A student may discuss the problems with others. However, the work a student turns in must
be created COMPLETELY by oneself ALONE. A student may not share ANY written work or
pictures, nor may one copy answers from any source other than one’s own brain.
Each student MUST LIST on the homework paper the name of every person he/she has
discussed or worked with. If the answer includes content from any other source, the
student MUST STATE THE SOURCE. Failure to do so is cheating and will result in
sanctions. Copying answers from someone else is cheating even if one lists their name(s) on
the homework.
If there is information you need to solve a problem but the information is not stated in the
problem, try to find the data somewhere. If you cannot find it, state what data you need,
make a reasonable estimate of its value and justify any assumptions you make. You will be
graded not only on whether your answer is correct, but also on whether you have done an
intelligent analysis.
Q0 [10 marks]: Secure Virtual Machines Setup on the Cloud
In this task, you are required to set up virtual machines (VMs) on a cloud computing
platform. While you are free to choose any cloud platform, Google Cloud is recommended.
References [1] and [2] provide the tutorial for Google Cloud and Amazon AWS, respectively.
The default network settings in each cloud platform are insecure. Your VM can be hacked
by external users, resulting in resource overuse which may charge your credit card a
big bill of up to $5,000 USD. To protect your VMs from being hacked and prevent any
financial losses, you should set up secure network configurations for all your VMs.
In this part, you need to set up a whitelist for your VMs. You can choose one of the options
from the following choices to set up your whitelist: 1. only the IP corresponding to your
current device can access your VMs via SSH. Traffic from other sources should be blocked.
2. only users in the CUHK network can access your VMs via SSH. Traffic outside CUHK
should be blocked. You can connect to CUHK VPN to ensure you are in the CUHK network
(IP Range: 137.189.0.0/16). Reference [3] provides the CUHK VPN setup information from
ITSC.
a. [10 marks] Secure Virtual Machine Setup
Reference [4] and [5] are the user guides for the network security configuration of
AWS and Google Cloud, respectively. You can go through the document with respect
to the cloud platform you use. Then follow the listed steps to configure your VM’s
network:
i. locate or create the security group/ firewall of your VM;
ii. remove all rules of inbound/ ingress and outbound/ egress, except for the
default rule(s) responsible for internal access within the cloud platform;
iii. add a new rule to the inbound/ ingress, with the SSH port(s) of VMs (default:
22) and source specified, e.g., ‘137.189.0.0/16’ for CUHK users only;
iv. (Optional) more ports may be further permitted based on your needs (e.g.,
when completing Q1 below).
Q1 [** marks + 20 bonus marks]: Hadoop Cluster Setup
Hadoop is an open-source software framework for distributed storage and processing. In this
problem, you are required to set up a Hadoop cluster using the VMs you instantiated in Q0.
In order to set up a Hadoop cluster with multiple virtual machines (VM), you can set up a
single-node Hadoop cluster for each VM first [6]. Then modify the configuration file in each
node to set up a Hadoop cluster with multiple nodes. References [7], [9], [10], [11] provide
the setup instructions for a Hadoop cluster. Some important notes/ tips on instantiating VMs
are given at the end of this section.
a. [20 marks] Single-node Hadoop Setup
In this part, you need to set up a single-node Hadoop cluster in a pseudo-distributed
mode and run the Terasort example on your Hadoop cluster.
i. Set up a single-node Hadoop cluster (recommended Hadoop version: 2.9.x,
all versions available in [16]). Attach the screenshot of http://localhost:50070
(or http://:50070 if opened in the browser of your local machine) to
verify that your installation is successful.
ii. After installing a single-node Hadoop cluster, you need to run the Terasort
example [8] on it. You need to record all your key steps, including your
commands and output. The following commands may be useful:
$ ./bin/hadoop jar \
./share/hadoop/mapreduce/hadoop-mapreduce-examples-2.9.2.jar \
teragen 120000 terasort/input
//generate the data for sorting
$ ./bin/hadoop jar \
./share/hadoop/mapreduce/hadoop-mapreduce-examples-2.9.2.jar \
terasort terasort/input terasort/output
//terasort the generated data
$ ./bin/hadoop jar \
./share/hadoop/mapreduce/hadoop-mapreduce-examples-2.9.2.jar \
teravalidate terasort/output terasort/check
//validate the output is sorted
Notes: To monitor the Hadoop service via Hadoop NameNode WebUI (http://ip>:50070) on your local browser, based on steps in Q0, you may further allow traffic
from CUHK network to access port 50070 of VMs.
b. [40 marks] Multi-node Hadoop Cluster Setup
After the setup of a single-node Hadoop cluster in each VM, you can modify the
configuration files in each node to set up the multi-node Hadoop cluster.
i. Install and set up a multi-node Hadoop cluster with 4 VMs (1 Master and 3
Slaves). Use the ‘jps’ command to verify all the processes are running.
ii. In this part, you need to use the ‘teragen’ command to generate 2 different
datasets to serve as the input for the Terasort program. You should use the
following two rules to determine the size of the two datasets of your own:
■ Size of dataset 1: (Your student ID % 3 + 1) GB
■ Size of dataset 2: (Your student ID % 20 + 10) GB
Then, run the Terasort code again for these two different datasets and
compare their running time.
Hints: Keep an image for your Hadoop cluster. You would need to use the Hadoop
cluster again for subsequent homework assignments.
Notes:
1. You may need to add each VM to the whitelist of your security group/ firewall
and further allow traffic towards more ports needed by Hadoop/YARN
services (reference [17] [18]).
2. For step i, the resulting cluster should consist of 1 namenode and 4
datanodes. More precisely, 1 namenode and 1 datanode would be running on
the master machine, and each slave machine runs one datanode.
3. Please ensure that after the cluster setup, the number of “Live Nodes” shown
on Hadoop NameNode WebUI (port 50070) is 4.
c. [30 marks] Running Python Code on Hadoop
Hadoop streaming is a utility that comes with the Hadoop distribution. This utility
allows you to create and run MapReduce jobs with any executable or script as the
mapper and/or the reducer. In this part, you need to run the Python wordcount script
to handle the Shakespeare dataset [12] via Hadoop streaming.
i. Reference [13] introduces the method to run a Python wordcount script via
Hadoop streaming. You can also download the script from the reference [14].
ii. Run the Python wordcount script and record the running time. The following
command may be useful:
$ ./bin/hadoop jar \
./share/hadoop/tools/lib/hadoop-streaming-2.9.2.jar \
-file mapper.py -mapper mapper.py \
-file reducer.py -reducer reducer.py \
-input input/* \
-output output
//submit a Python program via Hadoop streaming
d. [Bonus 20 marks] Compiling the Java WordCount program for MapReduce
The Hadoop framework is written in Java. You can easily compile and submit a Java
MapReduce job. In this part, you need to compile and run your own Java wordcount
program to process the Shakespeare dataset [12].
i. In order to compile the Java MapReduce program, you may need to use
“hadoop classpath” command to fetch the list of all Hadoop jars. Or you can
simply copy all dependency jars in a directory and use them for compilation.
Reference [15] introduces the method to compile and run a Java wordcount
program in the Hadoop cluster. You can also download the Java wordcount
program from reference [14].
ii. Run the Java wordcount program and compare the running time with part c.
Part (d) is a bonus question for IERG 4300 but required for ESTR 4300.
IMPORTANT NOTES:
1. Since AWS will not provide free credits anymore, we recommend you to use Google
Cloud (which offers a **-day, $300 free trial) for this homework.
2. If you use Putty for SSH client, please download from the website
https://www.putty.org/ and avoid using the default private key. Failure to do so will
subject your AWS account/ Hadoop cluster to hijacking.
3. Launching instances with Ubuntu (version >= 18.04 LTS) is recommended. Hadoop
version 2.9.x is recommended. Older versions of Hadoop may have vulnerabilities
that can be exploited by hackers to launch DoS attacks.
4. (AWS) For each VM, you are recommended to use the t2.large instance type with
100GB hard disk, which consists of 2 CPU cores and 8GB RAM.
5. (Google) For each VM, you are recommended to use the n2-standard-2 instance
type with 100GB hard disk, which consists of 2 CPU cores and 8GB RAM.
6. When following the given references, you may need to modify the commands
according to your own environment, e.g., file location, etc.
7. After installing a single-node Hadoop, you can save the system image and launch
multiple copies of the VM with that image. This can simplify your process of installing
the single-node Hadoop cluster on each VM.
8. Keep an image for your Hadoop cluster. You will need to use the Hadoop cluster
again for subsequent homework assignments.
9. Always refer to the logs for debugging single/multi-node Hadoop setup, which
contains more details than CLI outputs.
10. Please shut down (not to terminate) your VMs when you are not using them. This can
save you some credits and avoid being attacked when your VMs are idle.
Submission Requirements:
1. Include all the key steps/ commands, your cluster configuration details, source codes
of your programs, your compiling steps (if any), etc., together with screenshots, into a
SINGLE PDF report. Your report should also include the signed declaration (the first
page of this homework file).
2. Package all the source codes (as you included in step 1) into a zip file individually.
3. You should submit two individual files: your homework report (in PDF format) and a
zip file packaged all the codes of your homework.
4. Please submit your homework report and code zip file through the Blackboard
system. No email submission is allowed.
如有需要,請加QQ:99515681 或WX:codehelp

掃一掃在手機打開當前頁
  • 上一篇:代做CSCI3280、Python設計編程代寫
  • 下一篇:代寫CS 476/676 程序
  • 無相關信息
    合肥生活資訊

    合肥圖文信息
    2025年10月份更新拼多多改銷助手小象助手多多出評軟件
    2025年10月份更新拼多多改銷助手小象助手多
    有限元分析 CAE仿真分析服務-企業/產品研發/客戶要求/設計優化
    有限元分析 CAE仿真分析服務-企業/產品研發
    急尋熱仿真分析?代做熱仿真服務+熱設計優化
    急尋熱仿真分析?代做熱仿真服務+熱設計優化
    出評 開團工具
    出評 開團工具
    挖掘機濾芯提升發動機性能
    挖掘機濾芯提升發動機性能
    海信羅馬假日洗衣機亮相AWE  復古美學與現代科技完美結合
    海信羅馬假日洗衣機亮相AWE 復古美學與現代
    合肥機場巴士4號線
    合肥機場巴士4號線
    合肥機場巴士3號線
    合肥機場巴士3號線
  • 短信驗證碼 trae 豆包網頁版入口 目錄網 排行網

    關于我們 | 打賞支持 | 廣告服務 | 聯系我們 | 網站地圖 | 免責聲明 | 幫助中心 | 友情鏈接 |

    Copyright © 2025 hfw.cc Inc. All Rights Reserved. 合肥網 版權所有
    ICP備06013414號-3 公安備 42010502001045

    日韩精品一区二区三区高清_久久国产热这里只有精品8_天天做爽夜夜做爽_一本岛在免费一二三区

      <em id="rw4ev"></em>

        <tr id="rw4ev"></tr>

        <nav id="rw4ev"></nav>
        <strike id="rw4ev"><pre id="rw4ev"></pre></strike>
        久久在线精品| 伊人色综合久久天天| 亚洲一区二区欧美日韩| 久久久国产亚洲精品| 亚洲午夜精品视频| 亚洲欧美精品suv| 国产精品国产自产拍高清av王其| 国产亚洲成精品久久| 国产伦精品一区| 亚洲国产婷婷香蕉久久久久久99| 欧美在线不卡| 久久久久久国产精品一区| 尤物yw午夜国产精品视频明星| 午夜一区不卡| 亚洲国产日本| 尤物99国产成人精品视频| 国内偷自视频区视频综合| 免费不卡视频| 国产精品视频最多的网站| 亚洲国产一区二区三区在线播| 宅男噜噜噜66国产日韩在线观看| 久久免费高清视频| 欧美日韩精品免费观看视频完整| 欧美一区二区三区播放老司机| 蜜臀av一级做a爰片久久| 亚洲视频综合在线| 欧美伦理视频网站| 国产亚洲免费的视频看| 亚洲欧美国产精品桃花| 亚洲福利视频免费观看| 欧美成人精品h版在线观看| 亚洲主播在线播放| 亚洲综合精品| 麻豆成人91精品二区三区| 亚洲精品激情| 国产精品爽黄69| 国产色婷婷国产综合在线理论片a| 欧美一区二区免费观在线| 久久久久久日产精品| 欧美亚洲综合另类| 亚洲国产一区二区三区在线播| 欧美日韩一区二区三区在线观看免| 久久久国产精彩视频美女艺术照福利| 欧美成人伊人久久综合网| 欧美视频日韩视频| 免播放器亚洲一区| 在线观看91久久久久久| 亚洲欧美成人网| 女女同性女同一区二区三区91| 欧美激情精品久久久久久变态| 国产精品高精视频免费| 亚洲午夜高清视频| 久久综合一区二区三区| 亚洲女人小视频在线观看| 国语自产精品视频在线看8查询8| 亚洲欧洲综合| 麻豆av一区二区三区| 在线日韩视频| 亚洲国产裸拍裸体视频在线观看乱了| 国产情侣一区| 久久久国产亚洲精品| 欧美四级剧情无删版影片| 欧美日韩mv| 欧美日韩精品一二三区| 久久riav二区三区| 国产精品劲爆视频| 99re6这里只有精品| 香港久久久电影| 欧美日韩国产成人高清视频| 欧美视频在线看| 午夜视频在线观看一区二区三区| 最新国产精品拍自在线播放| 亚洲综合999| 夜夜躁日日躁狠狠久久88av| 亚洲一区二区影院| 国产精品夫妻自拍| 久久狠狠久久综合桃花| 免费观看30秒视频久久| 欧美亚洲免费高清在线观看| 99精品国产在热久久下载| 国产精品伦子伦免费视频| 一区二区三区欧美| 欧美日韩视频免费播放| 欧美日韩视频在线一区二区观看视频| 亚洲精品激情| 久久精品2019中文字幕| 欧美中文在线视频| 亚洲欧洲精品一区二区三区| 亚洲黄网站在线观看| 免费观看日韩| 有码中文亚洲精品| 欧美日韩国产小视频在线观看| 欧美一级二级三级蜜桃| 国产精品国产成人国产三级| 欧美久色视频| 欧美大片91| 黄色精品一二区| 国产精品美女一区二区| 欧美激情免费观看| 蜜桃久久精品一区二区| 国产日韩亚洲欧美精品| 久久国产精品一区二区三区| 国产精品国产三级国产aⅴ入口| 亚洲小视频在线观看| 欧美日韩免费看| 在线免费观看视频一区| 欧美一区二区精品在线| 欧美一区二区视频免费观看| 99精品黄色片免费大全| 国产精品99久久久久久久久久久久| 久久久一二三| 亚洲欧美在线观看| 亚洲人成在线观看网站高清| 欧美性猛交99久久久久99按摩| 久久久国产精彩视频美女艺术照福利| 欧美一区二区三区四区高清| 国产精品大片| 伊人一区二区三区久久精品| 亚洲一区二区三区激情| 国内精品国产成人| 欧美性色aⅴ视频一区日韩精品| 欧美韩国日本一区| 久久先锋影音av| 国产亚洲免费的视频看| 欧美成人视屏| 亚洲欧美清纯在线制服| 亚洲日本欧美在线| 一区在线观看| 欧美fxxxxxx另类| 欧美不卡一区| 午夜精品一区二区三区电影天堂| 亚洲欧美在线网| 国产精品日韩高清| 亚洲一区二区三区乱码aⅴ蜜桃女| 老巨人导航500精品| 午夜精品久久久久久久久久久久久| 在线不卡欧美| 国产九九精品视频| 亚洲一区二区三区久久| 亚洲大片精品永久免费| 欧美视频网址| 欧美三级视频在线观看| 国产欧美视频一区二区三区| 久久电影一区| 午夜免费久久久久| 亚洲视屏在线播放| 亚洲美女啪啪| 一区二区三区在线视频观看| 亚洲国产精品视频一区| 国产精品日韩| 国内一区二区在线视频观看| 亚洲免费观看高清完整版在线观看熊| 国产一区二区丝袜高跟鞋图片| 欧美欧美在线| 国产精品亚洲综合色区韩国| 国产精品日韩欧美| 亚洲精品国精品久久99热一| 亚洲欧美日产图| 女主播福利一区| 午夜精品久久久久久久久久久久| 妖精成人www高清在线观看| 国产精品久久久久久久免费软件| 欧美大片一区二区| 午夜精品成人在线|