auto

project1/DDL.sql

+drop table if exists prereq;
+drop table if exists time_slot;
+drop table if exists advisor;
+drop table if exists takes;
+drop table if exists student;
+drop table if exists teaches;
+drop table if exists section;
+drop table if exists instructor;
+drop table if exists course;
+drop table if exists department;
+drop table if exists classroom;
+
+create table classroom
+	(building		varchar(15),
+	 room_number		varchar(7),
+	 capacity		numeric(4,0),
+	 primary key (building, room_number)
+	);
+
+create table department
+	(dept_name		varchar(20), 
+	 building		varchar(15), 
+	 budget		        numeric(12,2) check (budget > 0),
+	 primary key (dept_name)
+	);
+
+create table course
+	(course_id		varchar(8), 
+	 title			varchar(50), 
+	 dept_name		varchar(20),
+	 credits		numeric(2,0) check (credits > 0),
+	 primary key (course_id),
+	 foreign key (dept_name) references department
+		on delete set null
+	);
+
+create table instructor
+	(ID			varchar(5), 
+	 name			varchar(20) not null, 
+	 dept_name		varchar(20), 
+	 salary			numeric(8,2) check (salary > 29000),
+	 primary key (ID),
+	 foreign key (dept_name) references department
+		on delete set null
+	);
+
+create table section
+	(course_id		varchar(8), 
+         sec_id			varchar(8),
+	 semester		varchar(6)
+		check (semester in ('Fall', 'Winter', 'Spring', 'Summer')), 
+	 year			numeric(4,0) check (year > 1701 and year < 2100), 
+	 building		varchar(15),
+	 room_number		varchar(7),
+	 time_slot_id		varchar(4),
+	 primary key (course_id, sec_id, semester, year),
+	 foreign key (course_id) references course
+		on delete cascade,
+	 foreign key (building, room_number) references classroom
+		on delete set null
+	);
+
+create table teaches
+	(ID			varchar(5), 
+	 course_id		varchar(8),
+	 sec_id			varchar(8), 
+	 semester		varchar(6),
+	 year			numeric(4,0),
+	 primary key (ID, course_id, sec_id, semester, year),
+	 foreign key (course_id,sec_id, semester, year) references section
+		on delete cascade,
+	 foreign key (ID) references instructor
+		on delete cascade
+	);
+
+create table student
+	(ID			varchar(5), 
+	 name			varchar(20) not null, 
+	 dept_name		varchar(20), 
+	 tot_cred		numeric(3,0) check (tot_cred >= 0),
+	 primary key (ID),
+	 foreign key (dept_name) references department
+		on delete set null
+	);
+
+create table takes
+	(ID			varchar(5), 
+	 course_id		varchar(8),
+	 sec_id			varchar(8), 
+	 semester		varchar(6),
+	 year			numeric(4,0),
+	 grade		        varchar(2),
+	 primary key (ID, course_id, sec_id, semester, year),
+	 foreign key (course_id,sec_id, semester, year) references section
+		on delete cascade,
+	 foreign key (ID) references student
+		on delete cascade
+	);
+
+create table advisor
+	(s_ID			varchar(5),
+	 i_ID			varchar(5),
+	 primary key (s_ID),
+	 foreign key (i_ID) references instructor (ID)
+		on delete set null,
+	 foreign key (s_ID) references student (ID)
+		on delete cascade
+	);
+
+create table time_slot
+	(time_slot_id		varchar(4),
+	 day			varchar(1),
+	 start_hr		numeric(2) check (start_hr >= 0 and start_hr < 24),
+	 start_min		numeric(2) check (start_min >= 0 and start_min < 60),
+	 end_hr			numeric(2) check (end_hr >= 0 and end_hr < 24),
+	 end_min		numeric(2) check (end_min >= 0 and end_min < 60),
+	 primary key (time_slot_id, day, start_hr, start_min)
+	);
+
+create table prereq
+	(course_id		varchar(8), 
+	 prereq_id		varchar(8),
+	 primary key (course_id, prereq_id),
+	 foreign key (course_id) references course
+		on delete cascade,
+	 foreign key (prereq_id) references course
+	);
+

project1/README.md

+## Project 1: SQL Assignment, CMSC424, Fall 2019
+
+*The assignment is to be done by yourself.*
+
+Start by `cd`-ing into `424f19`. Do a `git pull origin master`. You should see a `project1` directory with the following files:
+
+1. README.md: This file.
+1. small.sql: The SQL script for creating the data.
+1. queries.py: The file where to enter your answer; this is the file to be submitted
+1. answers.py: The answers to the queries on the small dataset.
+1. SQLTesting.py: File to be used for testing your submission -- see below.
+
+**Note:** The testing will be done on a different, larger dataset. 
+
+### Schema 
+The **flights** dataset contains synthetic air flight data. Specifically it contains the following tables:
+
+1. airports: airportid, city, name, total2011, total2012
+1. customers: customerid, name, birthdate, frequentflieron
+1. airlines: airlineid, name, hub
+1. flights: flightid, source, dest, airlineid, local_departing_time, local_arrival_time
+1. flewon: flightid, customerid, flightdate
+
+See the provided SQL file for the table definitions.
+
+The dataset was generated synthetically: the airport ids and the cities were chosen from the biggest airports in the US, but the rest of the data is populated randomly. The data will not make sense. For example, two different flights between the same cities may have very different flight durations. The flight times between the cities may not correspond to geographical distances that you know. Some other information about the data:
+- **The dates in the *large* database might be different than in the *small*.**
+- Each customer may at most take one flight every day.
+- The flight times were chosen between 30 minutes to 5 hours randomly.
+- All flights are daily (start and end on a single day), and none are overnight. 
+- For every flight from city A to city B, there is corresponding return flight from B to A.
+- The "flewon" table only contains the flight date -- the flight times must be extracted from the flights table.
+
+In many cases (especially for complex queries or queries involving 
+`max` or `min`), you will find it easier to create temporary tables
+using the `with` construct. This also allows you to break down the full
+query and makes it easier to debug.
+
+You don't have to use the "hints" if you don't want to; there might 
+be simpler ways to solve the questions.
+
+### Testing and submitting using SQLTesting.py
+Your answers (i.e., SQL queries) should be added to the `queries.py` file. A simple query is provided for the first answer to show you how it works.
+You are also provided with a Python file `SQLTesting.py` for testing your answers.
+
+- We recommend that you use `psql` (as in `psql flights`) to design
+  your queries, and then paste the queries to the `queries.py` file,
+  and confirm it works.  
+
+- SQLTesting takes quite a few options: use `python3 SQLTesting.py -h` to see the options.
+
+- To get started with SQLTesting, do: `python3 SQLTesting.py -v -i` -- that will run each of the queries and show you your answer and correct answer.
+
+- If you want to test your answer to Question 1, use: `python3 SQLTesting.py -q 1`. The program compares the result of running your query against the provided answer (in the `answers.py` file).
+
+- The `-v` flag will print out more information, including the correct and submitted answers etc.
+
+- If you want to test your answers to all questions (this is what we will do), use: `python3 SQLTesting.py` and look at the final total score.
+
+- `-i` flag to SQLTesting will run all the queries, one at a time (waiting for you to press Enter after each query).
+
+- **Note that**: We will basically run this same program on your submitted `queries.py` file, but with the larger dataset; your score on the assignment will 
+be score output by the program. The program tries to do partial credits (as you can see in the code). It is very unlikely that your score on the larger, hidden 
+dataset will be higher than your score on the provided dataset.  
+
+### Submission Instructions
+Submit the `queries.py` file using ELMS  [here](https://myelms.umd.edu/courses/1227917/assignments/4492249). **Due September 17.**
+      
+### Assignment Questions
+See `queries.py` file.

project1/SQLTesting.py

+import psycopg2
+import os
+import sys
+import datetime
+from collections import Counter
+from types import *
+import argparse
+
+from queries import *
+from answers import *
+
+parser = argparse.ArgumentParser()
+parser.add_argument('-v', '--verbose', help="Print out the query results and more details", required=False, action="store_true")
+parser.add_argument('-i', '--interactive', help="Run queries one at a time, and wait for user to proceed", required=False, action="store_true")
+parser.add_argument('-q', '--query', type = int, help="Only run and check the given query number", required=False)
+parser.add_argument('-g', '--generate', help="Print out the query results and more details", required=False, action="store_true")
+args = parser.parse_args()
+
+verbose = args.verbose
+interactive = args.interactive
+generateOnly = args.generate
+
+
+# Check if x and y are almost near match
+def match(x, y):
+    if type(x) != type(y):
+        return False
+    if type(x) is int or type(x) is bool:
+        return x == y
+    if type(x) is float:
+        return (abs(x - y) < 0.01)
+    # Conver to string and compare
+    # print "Found type: {}".format(type(x))
+    return str(x).strip() == str(y).strip()
+
+def compareAnswers(ans, correct):
+    # Special case empty answer
+    if len(ans) == 0:
+        if len(correct) == 0:
+            return ("Score = 4: Both answers empty", 4)
+        else:
+            return ("Score = 0: Empty answer", 0)
+
+    if len(correct) == 0:
+        return ("Score = 0: The answer should have been empty", 0)
+
+
+    # If the number of columns is not correct, no score
+    if len(ans[0]) != len(correct[0]):
+        return ("Score = 0: Incorrect Number of Columns", 0)
+
+    # If the number of rows in the answer is the same, check for near-exact match
+    if len(ans) == len(correct):
+        c = Counter()
+        for (t1, t2) in zip(ans, correct):
+            for (t1x, t2x) in zip(t1, t2):
+                c[match(t1x, t2x)] += 1
+        if c[False] == 0:
+            return ("Score = 4: Exact or Near-exact Match", 4)
+
+    # Let's try to do an approximate match
+    flattened_ans = Counter([str(x).strip() for y in ans for x in y])
+    flattened_correct = Counter([str(x).strip() for y in correct for x in y])
+
+
+    jaccard = sum((flattened_correct & flattened_ans).values()) * 1.0/sum((flattened_correct | flattened_ans).values())
+    if verbose:
+        print("------ Creating word counts and comparing answers ---------")
+        print(flattened_correct )
+        print(flattened_ans)
+        print("Jaccard Coefficient: {}".format(jaccard) )
+
+    if jaccard > 0.9:
+        if len(ans) == len(correct):
+            return ("Score = 3: Very similar, but not an exact match (possibly wrong sort order)", 3)
+        else:
+            return ("Score = 2: Very similar, but incorrect number of rows", 2)
+    if jaccard > 0.5:
+        return ("Score = 1: Somewhat similar answers", 1)
+    return ("Score = 0: Answers too different", 0)
+
+conn = psycopg2.connect("dbname=flights user=vagrant")
+cur = conn.cursor()
+
+totalscore = 0
+
+if generateOnly:
+    print("import datetime")
+    print("correctanswers = [\"\" for i in range(0, 11)]\n")
+
+for i in range(1, 11):
+    # If a query is specified by -q option, only do that one
+    if args.query is None or args.query == i:
+        try:
+            cur.execute(queries[i])
+            ans = cur.fetchall()
+
+            if generateOnly:
+                print("correctanswers[%d] = %s\n" % (i,ans));
+
+            else:
+                print("========== Executing Query {}".format(i))
+                print(queries[i])
+                cur.execute(queries[i])
+                ans = cur.fetchall()
+
+                if verbose:
+                   print("--------- Your Query Answer ---------")
+                   for t in ans:
+                       print(t)
+                   print("--------- Correct Answer ---------")
+                   for t in correctanswers[i]:
+                       print(t)
+
+                # Compare with correctanswers[i]
+                cmp_res = compareAnswers(ans, correctanswers[i])
+                print("-----> " + cmp_res[0])
+                totalscore += cmp_res[1]
+                if interactive:
+                   input('Press enter to proceed')
+                   os.system('clear')
+        except:
+            print(sys.exc_info())
+            raise
+
+if not generateOnly:
+    print("-----------------> Total Score = {}".format(totalscore))

project1/Vagrantfile

+# -*- mode: ruby -*-
+# vi: set ft=ruby :
+
+# All Vagrant configuration is done below. The "2" in Vagrant.configure
+# configures the configuration version (we support older styles for
+# backwards compatibility). Please don't change it unless you know what
+# you're doing.
+Vagrant.configure("2") do |config|
+  # The most common configuration options are documented and commented below.
+  # For a complete reference, please see the online documentation at
+  # https://docs.vagrantup.com.
+
+  # Every Vagrant development environment requires a box. You can search for
+  # boxes at https://atlas.hashicorp.com/search.
+  config.vm.box = "ubuntu/bionic64"
+
+  # Disable automatic box update checking. If you disable this, then
+  # boxes will only be checked for updates when the user runs
+  # `vagrant box outdated`. This is not recommended.
+  # config.vm.box_check_update = false
+
+  # Create a forwarded port mapping which allows access to a specific port
+  # within the machine from a port on the host machine. In the example below,
+  # accessing "localhost:8080" will access port 80 on the guest machine.
+  config.vm.network "forwarded_port", guest: 8881, host: 8881
+  config.vm.network "forwarded_port", guest: 8882, host: 8882
+  config.vm.network "forwarded_port", guest: 8883, host: 8883
+  config.vm.network "forwarded_port", guest: 8888, host: 8888
+
+  # Create a private network, which allows host-only access to the machine
+  # using a specific IP.
+  # config.vm.network "private_network", ip: "192.168.33.10"
+
+  # Create a public network, which generally matched to bridged network.
+  # Bridged networks make the machine appear as another physical device on
+  # your network.
+  # config.vm.network "public_network"
+
+  # Share an additional folder to the guest VM. The first argument is
+  # the path on the host to the actual folder. The second argument is
+  # the path on the guest to mount the folder. And the optional third
+  # argument is a set of non-required options.
+  # config.vm.synced_folder "../data", "/vagrant_data"
+
+  # Provider-specific configuration so you can fine-tune various
+  # backing providers for Vagrant. These expose provider-specific options.
+  # Example for VirtualBox:
+  #
+  # config.vm.provider "virtualbox" do |vb|
+  #   # Display the VirtualBox GUI when booting the machine
+  #   vb.gui = true
+  #
+  #   # Customize the amount of memory on the VM:
+  #   vb.memory = "1024"
+  # end
+  #
+  # View the documentation for the provider you are using for more
+  # information on available options.
+
+  # Define a Vagrant Push strategy for pushing to Atlas. Other push strategies
+  # such as FTP and Heroku are also available. See the documentation at
+  # https://docs.vagrantup.com/v2/push/atlas.html for more information.
+  # config.push.define "atlas" do |push|
+  #   push.app = "YOUR_ATLAS_USERNAME/YOUR_APPLICATION_NAME"
+  # end
+
+  # Enable provisioning with a shell script. Additional provisioners such as
+  # Puppet, Chef, Ansible, Salt, and Docker are also available. Please see the
+  # documentation for more information about their specific syntax and use.
+  config.vm.provision "shell", inline: <<-SHELL
+     apt-get update
+
+     apt-get install -y postgresql postgresql-contrib python3-pip python3-psycopg2 emacs tcsh
+     pip3 install jupyter
+     pip3 install ipython-sql
+
+     sudo -u postgres createuser -s vagrant
+     sudo -u vagrant psql -c "alter user vagrant with password 'vagrant'"
+
+     sudo -u vagrant createdb flights
+     sudo -u vagrant psql flights -f /vagrant/small.sql
+
+     sudo -u vagrant createdb university
+     sudo -u vagrant psql university -f /vagrant/DDL.sql
+     sudo -u vagrant psql university -f /vagrant/smallRelationsInsertFile.sql
+
+     pip3 install jupyter
+     pip3 install ipython-sql
+
+     cp /vagrant/.cshrc /home/vagrant/
+     cp -r /vagrant/.jupyter /home/vagrant/
+     chown -R vagrant ~vagrant/.jupyter
+     echo "PS1='424-proj0:\\w> '" >> ~vagrant/.bashrc
+
+     cp /vagrant/.cshrc /home/vagrant/
+     cp -r /vagrant/.jupyter /home/vagrant/
+     chown -R vagrant ~vagrant/.jupyter
+
+  SHELL
+end

project1/queries.py

+queries = ["" for i in range(0, 12)]
+
+### 0. List all airport codes and their cities. Order by the city name in the increasing order. 
+### Output column order: airportid, city
+
+queries[0] = """
+select airportid, city 
+from airports
+order by city;
+"""
+
+### 1. Write a query to find the names of the customers whose names are at least 15 characters long, and the second letter in the  name is "l".
+### Order by name.
+queries[1] = """
+select 0;
+"""
+
+
+### 2. Write a query to find any customers who flew on their birthday.  Hint: Use "extract" function that operates on the dates. 
+### Order output by Customer Name.
+### Output columns: all columns from customers
+queries[2] = """
+select 0;
+"""
+
+### 3. Write a query to generate a list: (source_city, source_airport_code, dest_city, dest_airport_code, number_of_flights) for all source-dest pairs with at least 3 flights. 
+### Order first by number_of_flights in decreasing order, then source_city in the increasing order, and then dest_city in the increasing order.
+### Note: You must generate the source and destination cities along with the airport codes.
+queries[3] = """
+select 0;
+"""
+
+### 4. Find the name of the airline with the maximum number of customers registered as frequent fliers.
+### Output only the name of the airline. If multiple answers, order by name.
+queries[4] = """
+select 0;
+"""
+
+### 5. For all flights from OAK to IAD, list the flight id, airline name, and the 
+### duration in hours and minutes. So the output will have 4 fields: flightid, airline name,
+### hours, minutes. Order by flightid.
+queries[5] = """
+select 0;
+"""
+
+### 6. Write a query to find empty flights (flight, flight date) on any date
+###	which someone flew. Assume that if anyone flew on a given date, all
+###	flights took off as scheduled, with or without passengers. Order by flight
+###	id in increasing order, and then by date in increasing order. 
+queries[6] = """
+select 0;
+"""
+
+### 7. Write a query to generate a list of customers who don't list Southwest as their frequent flier airline, but
+### actually flew the most (by number of flights) on that airline.
+### Output columns: customerid, customer_name
+### Order by: customerid
+queries[7] = """
+select 0;
+"""
+
+### 8. Write a query to generate a list of customers where the interval between first and last flight is 5 days.
+### Order by the customer name. 
+### Output columns: name
+### Order by: name
+queries[8] = """
+select 0;
+"""
+
+
+### 9. For each customer, find the airlines on which they have never
+### flown. One output row per customer/airline-name pair.
+### Output columns: customerid, airlinename
+### Order by: customerid, airlinename
+queries[9] = """
+select 0;
+"""
+
+
+### 10. For each customer who flew on his/her own birthday, generate a
+### "coupon code" string consisting of the first three characters of
+### their name concatenated with the day-of-the-month of their birthday.  
+### Output columns: name,coupon
+### Order by: name,coupon
+queries[10] = """
+select 0;
+"""
+
+

project1/smallRelationsInsertFile.sql

+delete from prereq;
+delete from time_slot;
+delete from advisor;
+delete from takes;
+delete from student;
+delete from teaches;
+delete from section;
+delete from instructor;
+delete from course;
+delete from department;
+delete from classroom;
+insert into classroom values ('Packard', '101', '500');
+insert into classroom values ('Painter', '514', '10');
+insert into classroom values ('Taylor', '3128', '70');
+insert into classroom values ('Watson', '100', '30');
+insert into classroom values ('Watson', '120', '50');
+insert into department values ('Biology', 'Watson', '90000');
+insert into department values ('Comp. Sci.', 'Taylor', '100000');
+insert into department values ('Elec. Eng.', 'Taylor', '85000');
+insert into department values ('Finance', 'Painter', '120000');
+insert into department values ('History', 'Painter', '50000');
+insert into department values ('Music', 'Packard', '80000');
+insert into department values ('Physics', 'Watson', '70000');
+insert into course values ('BIO-101', 'Intro. to Biology', 'Biology', '4');
+insert into course values ('BIO-301', 'Genetics', 'Biology', '4');
+insert into course values ('BIO-399', 'Computational Biology', 'Biology', '3');
+insert into course values ('CS-101', 'Intro. to Computer Science', 'Comp. Sci.', '4');
+insert into course values ('CS-190', 'Game Design', 'Comp. Sci.', '4');
+insert into course values ('CS-315', 'Robotics', 'Comp. Sci.', '3');
+insert into course values ('CS-319', 'Image Processing', 'Comp. Sci.', '3');
+insert into course values ('CS-347', 'Database System Concepts', 'Comp. Sci.', '3');
+insert into course values ('EE-181', 'Intro. to Digital Systems', 'Elec. Eng.', '3');
+insert into course values ('FIN-201', 'Investment Banking', 'Finance', '3');
+insert into course values ('HIS-351', 'World History', 'History', '3');
+insert into course values ('MU-199', 'Music Video Production', 'Music', '3');
+insert into course values ('PHY-101', 'Physical Principles', 'Physics', '4');
+insert into instructor values ('10101', 'Srinivasan', 'Comp. Sci.', '65000');
+insert into instructor values ('12121', 'Wu', 'Finance', '90000');
+insert into instructor values ('15151', 'Mozart', 'Music', '40000');
+insert into instructor values ('22222', 'Einstein', 'Physics', '95000');
+insert into instructor values ('32343', 'El Said', 'History', '60000');
+insert into instructor values ('33456', 'Gold', 'Physics', '87000');
+insert into instructor values ('45565', 'Katz', 'Comp. Sci.', '75000');
+insert into instructor values ('58583', 'Califieri', 'History', '62000');
+insert into instructor values ('76543', 'Singh', 'Finance', '80000');
+insert into instructor values ('76766', 'Crick', 'Biology', '72000');
+insert into instructor values ('83821', 'Brandt', 'Comp. Sci.', '92000');
+insert into instructor values ('98345', 'Kim', 'Elec. Eng.', '80000');
+insert into section values ('BIO-101', '1', 'Summer', '2009', 'Painter', '514', 'B');
+insert into section values ('BIO-301', '1', 'Summer', '2010', 'Painter', '514', 'A');
+insert into section values ('CS-101', '1', 'Fall', '2009', 'Packard', '101', 'H');
+insert into section values ('CS-101', '1', 'Spring', '2010', 'Packard', '101', 'F');
+insert into section values ('CS-190', '1', 'Spring', '2009', 'Taylor', '3128', 'E');
+insert into section values ('CS-190', '2', 'Spring', '2009', 'Taylor', '3128', 'A');
+insert into section values ('CS-315', '1', 'Spring', '2010', 'Watson', '120', 'D');
+insert into section values ('CS-319', '1', 'Spring', '2010', 'Watson', '100', 'B');
+insert into section values ('CS-319', '2', 'Spring', '2010', 'Taylor', '3128', 'C');
+insert into section values ('CS-347', '1', 'Fall', '2009', 'Taylor', '3128', 'A');
+insert into section values ('EE-181', '1', 'Spring', '2009', 'Taylor', '3128', 'C');
+insert into section values ('FIN-201', '1', 'Spring', '2010', 'Packard', '101', 'B');
+insert into section values ('HIS-351', '1', 'Spring', '2010', 'Painter', '514', 'C');
+insert into section values ('MU-199', '1', 'Spring', '2010', 'Packard', '101', 'D');
+insert into section values ('PHY-101', '1', 'Fall', '2009', 'Watson', '100', 'A');
+insert into teaches values ('10101', 'CS-101', '1', 'Fall', '2009');
+insert into teaches values ('10101', 'CS-315', '1', 'Spring', '2010');
+insert into teaches values ('10101', 'CS-347', '1', 'Fall', '2009');
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+insert into prereq values ('BIO-399', 'BIO-101');
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+insert into prereq values ('EE-181', 'PHY-101');