数据库代写 | COMP5338: Advanced Data Models Sem

本次数据库代写是使用MongoDB创建数据库并进行对应的操作
COMP5338: Advanced Data Models Sem. 2/2020
MongoDB Assignment

1 Introduction
In this assignment, you will demonstrate that you are able to work with MongoDB by
writing practical queries to explore real world data and their relations.
The data set you will work with consists of tweet objects downloaded from Twitter
using Twitter API. You are asked to implement a set of target queries to explore different
features of the data.
2 Data set
The practice data set contains a single JSON file downloaded using keyword search of
twitter’s standard search API. The JSON file contains around 10K tweet objects. A tweet
object may refer to a general tweet, a retweet or a reply to a tweet. A general tweet is “a
message posted to Twitter containing text, photos, a GIF, and/or video”1
. A reply is a
response to another person’s tweet2
. “A Retweet is a re-posting of a Tweet.”3 Note that
reply or retweet could happen not only on general tweet, but also on other reply and/or
retweet. In other words, there could be reply to a retweet or a reply; and retweet of a
reply. In this assignment, we may refer to tweet that receives a reply or retweet as parent
tweet. This is not a standard terminologies used by Twitter or general public, rather a
borrowed term from tree data structure.
Below is an example tweet object representing a retweet:
1About different types of Tweets General Tweets
2About different types of Tweets General Tweets
3Retweet FAQs
1
1 {
2 “id”: 1300296290924929024,
3 “created_at”: “2020-08-31 04:56:08”,
4 “text”: “RT @LewisForMN: Before Biden changed his story and said he
DIDN’T take a cognitive test, he said he DID take a cognitive
test. \n\nIf he didn’t”,
5 “user_id”: 1104621094122737664,
6 “retweet_count”: 20,
7 “favorite_count”: 0,
8 “retweet_id”: 1300264093270540288,
9 “retweet_user_id”: 20934272,
10 “user_mentions”: [
11 {
12 “id”: 20934272,
13 “indices”: [3,14]
14 }
15 ]
16 }
The common fields in all tweet objects are:
• id: the unique id of the tweet.
• created_at: the date and time the tweet is created.
• text: the textual content of the tweet
• user_id: the id of the user who created the tweet.
• retweet_count: retweet count of the tweet or its parent tweet if the tweet is a
retweet
• favorite_count: favorite count of the tweet
The optional fields in a tweet object are:
• retweet_id: if the tweet is a retweet of another tweet, this field contains the parent
tweet’s id
• retweet_user_id: if the tweet is a retweet of another tweet, this field contains the
parent tweet’s user_id
• replyto_id: if the tweet is a reply to another tweet, this field contains the parent
tweet’s id
2
• replyto_userid: if the tweet is a reply to another tweet, this field contains the
parent tweet’s user id.
• user_mentions: an array of {id, indices} showing the id of the users mentioned in
the tweet text, as well as the location this user is mentioned.
• hash_tags: an array of {tag, indices} showing the hash tag appearing in the tweet
text and the location it appears
Note that in releasing the twitter data for assignment use, we follow the content and
size limitation imposed by content redistribution policy as part of the Twitter API developer
agreement and policy. It is important that you do not redistribute the data set used in the
assignment to any party outside this course.
3 Query workload
• [Q1] Find out the number of general tweets, replies and retweets in the data set. A
general tweet is a tweet with no replyto_id, nor retweet_id field; a reply is a tweet
with the replyto_id field; a retweet is a tweet with the retweet_id field.
Below are sample answers for the practice data set :
General Tweet Reply Retweet
1035 1148 7817
• [Q2] Find out the top 5 hashtags sorted by their occurrence in general or reply tweets.
We do not count retweet, which has the same textual content as the parent tweet.
The sample answers for the practice data set are:
Yosemite yosemite YoSemite NationalPark California
47 47 16 10 9
Note that the order does not matter if a few hashtags have the same occurrence
number. The 5
th tag in the sample result could be ‘nature’,which also occurs 9 times.
• [Q3] Find out the tweet taking the longest time to receive a reply; print out the id
and the duration between the tweet’s creation time and the creation time of its first
reply in second.
The sample answers for the practice data set are:
id: 1298008149551587328; first response in: 75952s
3
• [Q4] Find out the number of general and reply tweets that do not have all their
retweets included in the data set. Note that the total number of retweets a tweet is
stored in the field retweet_count.
Sample answer for the practice data set is: 139
• [Q5] Find out the number of tweets that do not have its parent tweet object in the
data set.
The sample answer for the practice data set is: 6924
• [Q6] Find out the number of general tweets that do not have a reply nor a retweet in
the data set.
The sample answer for the practice data set is: 824
4 Implementation Requirements
The given json file should be initially imported to a collection called tweets, belonging to
a database called a1. This collection should not be updated in any subsequent queries.
The recommended practice is to make a copy of the tweets collection using a name of
your own choice. You can make necessary updates, such as type change when duplicating
tweets collection. You can create other auxiliary collections if necessary. All subsequent
read and write queries should happen in the newly created collection(s).
Implementation of all target queries should be packaged as a single mongo shell script,
which is a JavaScript file. The script should be executed by mongo shell in the form of
mongo script.js. A sample script a1sample.js is released along with the assignment
instruction. This script assumes the practice data has been imported to a collection called
tweets in a database called a1. Your script should make the same assumption and can
reuse the first few statements in the sample to connect to the database server and to
specify the database.
Implement all target queries as MongoDB query or aggregation commands. Ideally, you
should implement each target query as a single command. You can modify the document
structure by adding fields that will help implementing the target queries. All such modifications, including computations should be carried out as MongoDB query or aggregation
command as well. You can also create index to improve the performance.
At the end of the script, include command(s) to remove all collections you have created and leave the database back to the initial clean state with only a tweets collection.
An example can be seen from the last line in a1sample.js, which drops the collection
tweets_v2 created at the beginning of the script.
Running your script should produce the result of each query in correct order with results for different queries clearly labelled and delimited. Below is a sample output:
4
Q1=======
{
“general” : 1035,
“reply” : 1148,
“retweet” : 7817,
}
Q2======
{
“Yosemite” : 47,
“yosemite” : 47,
“YoSemite” : 16),
“NationalPark” : 10),
“California” : 9)
}
Q3=======
{
“id” : 1298008149551587328,
“duration” : 75952
}
Q4=======
139
Q5=======
6924
Q6=======
824


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