Lab 12: SQL

Due at 11:59pm on Friday, 11/16/2018.

Starter Files

Download Inside the archive, you will find starter files for the questions in this lab, along with a copy of the Ok autograder.


By the end of this lab, you should have submitted the lab with python3 ok --submit. You may submit more than once before the deadline; only the final submission will be graded. Check that you have successfully submitted your code on

  • To receive credit for this lab, you must complete Questions 2-4 in lab12.sql, and submit through OK.
  • Questions 5-6 are also considered extra practice. They can be found in the lab12_extra.sql file. It is recommended that you complete these when you are finished with the required questions.



The simplest way to start using SQLite is to download a precompiled binary from the SQLite website. The latest version of SQLite at the time of writing is 3.24.0, but you can check for additional updates on the website.


  1. Visit the download page linked above and navigate to the section Precompiled Binaries for Windows. Click on the link sqlite-tools-win32-x86-*.zip to download the binary.
  2. Unzip the file. There should be a sqlite3.exe file in the directory after extraction.
  3. Navigate to the folder containing the sqlite3.exe file and check that the version is at least 3.8.3:

    $ cd path/to/sqlite
    $ ./sqlite3 --version
    3.12.1 2016-04-08 15:09:49 fe7d3b75fe1bde41511b323925af8ae1b910bc4d

macOS Yosemite (10.10) or newer

SQLite comes pre-installed. Check that you have a version that's greater than 3.8.3:

    $ sqlite3
    SQLite version

Mac OS X Mavericks (10.9) or older

SQLite comes pre-installed, but it is the wrong version.

  1. Visit the download page linked above and navigate to the section Precompiled Binaries for Mac OS X (x86). Click on the link sqlite-tools-osx-x86-*.zip to download the binary.
  2. Unzip the file. There should be a sqlite3 file in the directory after extraction.
  3. Navigate to the folder containing the sqlite3 file and check that the version is at least 3.8.3:

    $ cd path/to/sqlite
    $ ./sqlite3 --version
    3.12.1 2016-04-08 15:09:49 fe7d3b75fe1bde41511b323925af8ae1b910bc4d


The easiest way to use SQLite on Ubuntu is to install it straight from the native repositories (the version will be slightly behind the most recent release):

$ sudo apt install sqlite3
$ sqlite3 --version
3.8.6 2014-08-15 11:46:33 9491ba7d738528f168657adb43a198238abde19e


You can start an interactive SQLite session in your Terminal or Git Bash with the following commands:

  • Ubuntu / Mac OS X (Yosemite or newer)

  • Windows / Mac OS X (Mavericks or older)


While the interpreter is running, you can type .help to see some of the commands you can run.

To exit out of the SQLite intepreter, type .exit or .quit or press Ctrl-C. Remember that if you see ...> after pressing return, you probably forgot a ;.

You can also run all the statements in a .sql file by doing the following:

Note: If you downloaded a precompiled binary above, make sure that sqlite3.exe file is in the same directory as your .sql file. (Extract and move it out from the zip file you downloaded.)

  1. Runs your code and then exits SQLite immediately afterwards.

    • Ubuntu / Mac OS X (Yosemite or newer)

      sqlite3 < lab12.sql
    • Windows / Mac OS X (Mavericks or older)

      ./sqlite3 < lab12.sql
  2. Runs your code and then opens an interactive SQLite session, which is similar to running Python code with the interactive -i flag.

    • Ubuntu / Mac OS X (Yosemite or newer)

      sqlite3 --init lab12.sql
    • Windows / Mac OS X (Mavericks or older)

      ./sqlite3 --init lab12.sql


SQL Basics

Creating Tables

You can create SQL tables either from scratch or from existing tables.

The following statement creates a table by specifying column names and values without referencing another table. Each SELECT clause specifies the values for one row, and UNION is used to join rows together. The AS clauses give a name to each column; it need not be repeated in subsequent rows after the first.

CREATE TABLE [table_name] AS
  SELECT [val1] AS [column1], [val2] AS [column2], ... UNION
  SELECT [val3]             , [val4]             , ... UNION
  SELECT [val5]             , [val6]             , ...;

Let's say we want to make the following table called big_game which records the scores for the Big Game each year. This table has three columns: berkeley, stanford, and year.

We could do so with the following CREATE TABLE statement:

  SELECT 30 AS berkeley, 7 AS stanford, 2002 AS year UNION
  SELECT 28,             16,            2003         UNION
  SELECT 17,             38,            2014;

Selecting From Tables

More commonly, we will create new tables by selecting specific columns that we want from existing tables by using a SELECT statement as follows:

SELECT [columns] FROM [tables] WHERE [condition] ORDER BY [columns] LIMIT [limit];

Let's break down this statement:

  • SELECT [columns] tells SQL that we want to include the given columns in our output table; [columns] is a comma-separated list of column names, and * can be used to select all columns
  • FROM [table] tells SQL that the columns we want to select are from the given table; see the joins section to see how to select from multiple tables
  • WHERE [condition] filters the output table by only including rows whose values satisfy the given [condition], a boolean expression
  • ORDER BY [columns] orders the rows in the output table by the given comma-separated list of columns
  • LIMIT [limit] limits the number of rows in the output table by the integer [limit]

Note: We capitalize SQL keywords purely because of style convention. It makes queries much easier to read, though they will still work if you don't capitalize keywords.

Here are some examples:

Select all of Berkeley's scores from the big_game table, but only include scores from years past 2002:

sqlite> SELECT berkeley FROM big_game WHERE year > 2002;

Select the scores for both schools in years that Berkeley won:

sqlite> SELECT berkeley, stanford FROM big_game WHERE berkeley > stanford;

Select the years that Stanford scored more than 15 points:

sqlite> SELECT year FROM big_game WHERE stanford > 15;

SQL operators

Expressions in the SELECT, WHERE, and ORDER BY clauses can contain one or more of the following operators:

  • comparison operators: =, >, <, <=, >=, <> or != ("not equal")
  • boolean operators: AND, OR
  • arithmetic operators: +, -, *, /
  • concatenation operator: ||

Here are some examples:

Output the ratio of Berkeley's score to Stanford's score each year:

sqlite> select berkeley * 1.0 / stanford from big_game;

Output the sum of scores in years where both teams scored over 10 points:

sqlite> select berkeley + stanford from big_game where berkeley > 10 and stanford > 10;

Output a table with a single column and single row containing the value "hello world":

sqlite> SELECT "hello" || " " || "world";
hello world


To select data from multiple tables, we can use joins. There are many types of joins, but the only one we'll worry about is the inner join. To perform an inner join on two on more tables, simply list them all out in the FROM clause of a SELECT statement:

SELECT [columns] FROM [table1], [table2], ... WHERE [condition] ORDER BY [columns] LIMIT [limit];

We can select from multiple different tables or from the same table multiple times.

Let's say we have the following table that contains the names head football coaches at Cal since 2002:

  SELECT "Jeff Tedford" AS name, 2002 as start, 2012 as end UNION
  SELECT "Sonny Dykes"         , 2013         , 2016        UNION
  SELECT "Justin Wilcox"       , 2017         , null;

When we join two or more tables, the default output is a cartesian product. For example, if we joined big_game with coaches, we'd get the following:

If we want to match up each game with the coach that season, we'd have to compare columns from the two tables in the WHERE clause:

sqlite> SELECT * FROM big_game, coaches WHERE year >= start AND year <= end;
17|38|2014|Sonny Dykes|2013|2016
28|16|2003|Jeff Tedford|2002|2012
30|7|2002|Jeff Tedford|2002|2012

The following query outputs the coach and year for each Big Game win recorded in big_game:

sqlite> SELECT name, year FROM big_game, coaches
...>        WHERE berkeley > stanford AND year >= start AND year <= end;
Jeff Tedford|2003
Jeff Tedford|2002

In the queries above, none of the column names are ambiguous. For example, it is clear that the name column comes from the coaches table because there isn't a column in the big_game table with that name. However, if a column name exists in more than one of the tables being joined, or if we join a table with itself, we must disambiguate the column names using aliases.

For examples, let's find out what the score difference is for each team between a game in big_game and any previous games. Since each row in this table represents one game, in order to compare two games we must join big_game with itself:

sqlite> SELECT b.Berkeley - a.Berkeley, b.Stanford - a.Stanford, a.Year, b.Year
...>        FROM big_game AS a, big_game AS b WHERE a.Year < b.Year;

In the query above, we give the alias a to the first big_game table and the alias b to the second big_game table. We can then reference columns from each table using dot notation with the aliases, e.g. a.Berkeley, a.Stanford, and a.Year to select from the first table.

Required Questions

Getting to Know Your Fellow 61A Students

Last week, we asked you and your fellow students to complete a brief online survey through Google Forms, which involved relatively random but fun questions. In this lab, we will interact with the results of the survey by using SQL queries to see if we can find interesting things in the data.

First, take a look at fa18data.sql and examine the table defined in it. Note its structure. You will be working with:

  • students: The main results of the survey. Each column represents a different question from the survey, except for the first column, which is the time of when the result was submitted. This time is a unique identifier for each of the rows in the table.

    Column Name Question
    time The unique timestamp that identifies the submission
    number What's your favorite number between 1 and 100?
    color What is your favorite color?
    seven Choose the number 7 below.
    • 7
    • You're not the boss of me!
    • Choose this option instead
    • seven
    • the number 7 below.
    song If you could listen to only one of these songs for the rest of your life, which would it be?
    • "Smells Like Teen Spirit" by Nirvana
    • "The Middle" by Zedd
    • "Clair de Lune" by Claude Debussy
    • "Finesse ft. Cardi B" by Bruno Mars
    • "Down With The Sickness" by Disturbed
    • "Everytime We Touch" by Cascada
    • "All I want for Christmas is you" by Mariah Carey
    • "thank u, next" by Ariana Grande
    date Pick a day of the year!
    pet If you could have any animal in the world as a pet, what would it be?
    denero Choose your favorite photo of John DeNero! (Options shown under Question 2)
    smallest Try to guess the smallest unique positive INTEGER that anyone will put!
  • checkboxes: The results from the survey in which students could select more than one option from the numbers listed, which ranged from 0 to 10 and included 2018, 9000, and 9001. Each row has a time (which is again a unique identifier) and has the value 'True' if the student selected the column or 'False' if the student did not. The column names in this table are the following strings, referring to each possible number: '0', '1', '2', '4', '5', '6', '7', '8', '9', '10', '2018', '9000', '9001'.

Since the survey was anonymous, we used the timestamp that a survey was submitted as a unique identifier. A time in students matches up with a time in checkboxes. For example, the row in students whose time value is "11/9/2018 18:02:33" matches up with the row in checkboxes whose time value is "11/9/2018 18:02:33". These entries come from the same Google form submission and thus belong to the same student.

Note: If you are looking for your personal response within the data, you may have noticed that some of your answers are slightly different from what you had input. In order to make SQLite accept our data, and to optimize for as many matches as possible during our joins, we did the following things to clean up the data:

  • color and pet: We converted all the strings to be completely lowercase.
  • For some of the more "free-spirited" responses, we escaped the special characters so that they could be properly parsed.

You will write all of your solutions in the starter file lab12.sql provided. As with other labs, you can test your solutions with OK. In addition, you can use either of the following commands. You may need to refer to the Usage section to find the appropriate command for your OS:

sqlite3 < lab12.sql
sqlite3 --init lab12.sql

Q1: What Would SQL print?

Note: there is no submission for this question

First, load the tables into sqlite3. If you're on Windows or Mac OS X (Mavericks or older), use the following command:

$ ./sqlite3 --init lab12.sql

If you're on Ubuntu or Mac OS X (Yosemite or newer), use:

$ sqlite3 --init lab12.sql

Before we start, inspect the schema of the tables that we've created for you:

sqlite> .schema

This tells you the name of each of our tables and their attributes.

Let's also take a look at some of the entries in our table. There are a lot of entries though, so let's just output the first 20:

sqlite> SELECT * FROM students LIMIT 20;

If you're curious about some of the answers students put into the Google form, open up su18data.sql in your favorite text editor and take a look!

For each of the SQL queries below, think about what the query is looking for, then try running the query yourself and see!

sqlite> SELECT * FROM students LIMIT 30; -- This is a comment. * is shorthand for all columns!
selects first 30 records from students;
sqlite> SELECT color FROM students WHERE number = 16;
selects the color from students who said their favorite number was 16;
sqlite> SELECT song, pet FROM students WHERE color = "blue" AND date = "12/25";
selects the song and pet from students who said their favorite color was blue and picked December 25th;

Remember to end each statement with a ;! To exit out of SQLite, type .exit or .quit or hit Ctrl-C.

Q2: Obedience

To warm-up, let's ask a simple question related to our data: Is there a correlation between whether students do as they're told and their favorite images of the instructor?


Write an SQL query to create a table that contains the columns seven (this column representing "obedience") and denero (the image of Professor DeNero students selected) from the students table.

You should get the following output:

sqlite> SELECT * FROM obedience LIMIT 10;
the number 7 below.|Image 4
the number 7 below.|Image 3
You're not the boss of me!|Image 4
the number 7 below.|Image 3
seven|Image 2
7|Image 4
the number 7 below.|Image 1
the number 7 below.|Image 3
Choose this option instead|Image 4
the number 7 below.|Image 2
SELECT seven, denero FROM students; Video walkthrough:

Use Ok to test your code:

python3 ok -q obedience

Q3: The Smallest Unique Positive Integer

Who successfully managed to guess the smallest unique positive integer value? Let's find out!

Unfortunately we have not learned how to do aggregations in SQL, which can help us count the number of times a specific value was selected, just yet. As such, we can only hand inspect our data to determine it. However, an anonymous elf has informed us that the smallest unique positive value is greater than 13!

Write an SQL query to create a table with the columns time and smallest that we can inspect to determine what the smallest integer value is. In order to make it easier for us to inspect these values, use WHERE to restrict the answers to numbers greater than 13, ORDER BY to sort the numerical values, and LIMIT your result to the first 20 values that are greater than the number 13.

The first 5 lines of your output should look like this:

sqlite> SELECT * FROM smallest_int LIMIT 5;
11/10/2018 14:31:14|14
11/10/2018 15:26:58|14
11/10/2018 1:05:12|14
11/11/2018 10:47:34|14
11/11/2018 18:19:04|14
CREATE TABLE smallest_int AS
SELECT time, smallest FROM students WHERE smallest > 13 ORDER BY smallest LIMIT 20; Video walkthrough: Note: Minor difference, walkthrough uses smallest > 15 instead of 13.

Use Ok to test your code:

python3 ok -q smallest-int

After you've successfully passed the Ok test, take a look at the table smallest_int that you just created and manually find the smallest unique integer value! If you're curious how to do this with aggregations, check out Question 8.

To do this, try the following:

$ sqlite3 --init lab12.sql
sqlite> SELECT * FROM smallest_int; -- No LIMIT this time!

Q4: Matchmaker, Matchmaker

Did you take 61A with the hope of finding your soul mate? Well you're in luck! With all this data in hand, it's easy for us to find your perfect match. If two students want the same pet and have the same taste in music, they are clearly meant to be together! In order to provide some more information for the potential lovebirds to converse about, let's include the favorite colors of the two individuals as well!

In order to match up students, you will have to do a join on the students table with itself. When you do a join, SQLite will match every single row with every single other row, so make sure you do not match anyone with themselves, or match any given pair twice!

Important Note: When pairing the first and second person, make sure that the first person responded first (i.e. they have an earlier time). This is to ensure your output matches our tests.

Hint: When joining table names where column names are the same, use dot notation to distinguish which columns are from which table: [table_name].[column name]. This sometimes may get verbose, so it’s stylistically better to give tables an alias using the AS keyword. The syntax for this is as follows:

SELECT <[alias1].[column name1], [alias2].[columnname2]...>
    FROM <[table_name1] AS [alias1],[table_name2] AS [alias2]...> ...

The query in the football example from earlier uses this syntax.

Write a SQL query to create a table that has 4 columns:

  • The shared preferred pet of the couple
  • The shared favorite song of the couple
  • The favorite color of the first person
  • The favorite color of the second person

You should get the following output:

sqlite> SELECT * FROM matchmaker LIMIT 10;
cat|Clair de Lune|blue|forest green
cat|Clair de Lune|blue|pink
cat|Clair de Lune|blue|green
cat|Clair de Lune|blue|light pink and tiffany blue
tiger|The Middle|green|blue
tiger|The Middle|green|periwinkle
dog|Smells Like Teen Spirit|blue|black
dog|Smells Like Teen Spirit|blue|gray
dog|Smells Like Teen Spirit|blue|blue
dog|Smells Like Teen Spirit|blue|orange
CREATE TABLE matchmaker AS
SELECT,, a.color, b.color FROM students AS a, students AS b WHERE a.time < b.time AND = AND =; Video walkthrough:

Use Ok to test your code:

python3 ok -q matchmaker

Optional Questions

The following questions are for extra practice -- they can be found in the lab12_extra.sql file. It is recommended that you complete these problems, but you do not need to turn them in for credit.

The COUNT Aggregator

Note: We haven't covered aggregation yet (as of 11/13), but you can come back tomorrow (11/14) and do these problems then, or you can read ahead and try them now!

How many people liked each pet? What is the biggest date chosen this semester? How many obedient people chose Image 1 for Professor DeNero? Is there a difference between last semester's average favorite number and this semester's?

To answer these types of questions, we can bring in SQL aggregation, which allows us to accumulate values across rows in our SQL database!

In order to perform SQL aggregation, we can group rows in our table by one or more attributes. Once we have groups, we can aggregate over the groups in our table and find things like:

  • the maximum value (MAX),
  • the minimum value (MIN),
  • the number of rows in the group (COUNT),
  • the average over all of the values (AVG),

and more! SELECT statements that use aggregation are usually marked by two things: an aggregate function (MAX, MIN, COUNT, AVG, etc.) and a GROUP BY clause. GROUP BY [column(s)] groups together rows with the same value in each column(s). In this section we will only use COUNT, which will count the number of rows in each group, but feel free to check out this link for more!

For example, the following query will print out the top 10 favorite numbers with their respective counts:

sqlite> SELECT number, COUNT(*) AS count FROM students GROUP BY number

This SELECT statement first groups all of the rows in our table students by number. Then, within each group, we perform aggregation by COUNTing all the rows. By selecting number and COUNT(*), we then can see the highest number and how many students picked that number. We have to order by our COUNT(*), which is saved in the alias count, by DESCending order, so our highest count starts at the top, and we limit our result to the top 10.

Q5: Let's Count

Let's have some fun with this! For each query below, we created its own table in lab12_extra.sql, so fill in the corresponding table and run it using Ok. Try working on this on your own or with a neighbor before toggling to see the solutions.

Hint: You may find that there isn't a particular attribute you should have to perform the COUNT aggregation over. If you are only interested in counting the number of rows in a group, you can just say COUNT(*).

What are the top 10 pets this semester?

sqlite> SELECT * FROM fa18favpets;
CREATE TABLE fa18favpets AS
SELECT pet, COUNT(*) AS count FROM students GROUP BY pet ORDER BY count DESC LIMIT 10;

How many people marked exactly the word 'dog' as their ideal pet this semester?

sqlite> SELECT * FROM fa18dog;
SELECT pet, COUNT(*) FROM students WHERE pet = 'dog';

Although close, our query doesn't give us an entirely accurate picture of what people's favorite pets are. For example, a dog would not be counted the same as dog. Let's see how many people actually want a dog this semester by using LIKE, which compares substrings. We can use it inside WHERE, as in WHERE [column_name] LIKE '%[word]%' to find how many people would like some type of dog.

sqlite> SELECT * from fa18alldogs;
CREATE TABLE fa18alldogs AS
SELECT pet, COUNT(*) FROM students WHERE pet LIKE '%dog%';

We can find the student's favorite for any column (try it yourself in the interpreter), but let's go back to our Obedience question. Let's see how many obedient students this semester picked each image of Professor Denero. We can do this by selecting only the rows that have seven = '7' then GROUP BY denero, and finally we can COUNT them.

sqlite> SELECT * FROM obedienceimages LIMIT 5;
7|Image 1|20
7|Image 2|22
7|Image 3|36
7|Image 4|44
7|Image 5|16
CREATE TABLE obedienceimages AS
SELECT seven, denero, COUNT(*) FROM students WHERE seven = '7' GROUP BY denero;

The possibilities are endless, so have fun experimenting!

Use Ok to test your code:

python3 ok -q lets-count

Q6: The Smallest Unique Positive Integer (Part 2)

Now, let's revisit the previous problem of finding the smallest positive integer that anyone chose, and take a closer look at the COUNT aggregate.

Write a SQL query that uses the COUNT aggregate to create a table that pairs the attribute smallest with the number of times it was chosen by a student (this is the aggregation part).

Hint: Think about what attribute you need to GROUP BY.

After you've defined your table, you should get something like:

sqlite> SELECT * FROM smallest_int_count LIMIT 25;
CREATE TABLE smallest_int_count AS
SELECT smallest, COUNT(*) FROM students GROUP BY smallest;

Use Ok to test your code:

python3 ok -q smallest-int-count

It looks like the number 15 only had one person choose it! Were you the lucky student that put it down?