andre/UoL

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levdoescode c03016d199 Week 7 notes completed

2022-12-24 17:55:31 -05:00

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Using Relational Databases

SELECT FROM WHERE

SELECT *
FROM Planets
WHERE diameter > 5;

Aproximate matching

SELECT *
FROM Planets
WHERE name LIKE '%er';

where '%er' is a wildcard, it's case insensite, it could be '%ER'

UPDATE

UPDATE *
SET name = 'Mars'
WHERE anem = 'Mers';

INSERT

INSERT INTO Planets (name, diameter)
VALUES
    ('Gethen', 9483),
    ('Athshe', 8210)

INSERT INTO Planets (name)
SELECT DISTINCT name
    FROM Moons;

Here we have a subquery and we insert the result of this query into the Planets table.

DELETE

DELETE FROM Planets
WHERE diameter < 2500;

DROP

DROP TABLE Planets;

TRUNCATE

TRUNCATE TABLE Planets;

Removes all entries but leaves the structure.

CREATE

CREATE DATABASE Planets;
CREATE TABLE Planets (
    PlanetName CHAR(8),
    dayLength INT,
    YearLength INT,
    PRIMARY KEY (PlanetName)
);

ALTER

ALTER TABLE Planets
ADD COLUMN
    Diameter INT;

Data exchange

SELECT *
FROM Planets
INTO OUTPUTFILE 'Planets.txt';

LOAD DATA INFILE 'Planets.txt'
    INTO TABLE Planets;

Agregate functions

We identify who they are for and we group them together

We then summarize the information by adding up the price.

This translates to SQL as:

SELECT *
    FROM Shopping
    WHERE
    BoughtFor = 'Mum';

<SOMETHING>
    FROM Shopping
    GROUP BY BoughtFor;

SELECT BoughtFor,
    SUM(Price)
    FROM Shopping
    GROUP BY BoughtFor;

This gives us the sum of groups

We also have

SUM
AVG
STD (deviation)
VARIANCE
MAX (Also works on other data types such as dates, most recent)
MIN (least recent or oldest)
COUNT
COUNT(DISTINCT)
GROUP_CONCAT (for strings)

SELECT Gender, COUNT(*) FROM Locations JOIN Actors ON Actor1 = ENName
GROUP BY Gender;

SELECT Gender, COUNT(*) FROM Locations JOIN Actors ON Actor2 = ENName
GROUP BY Gender;

SELECT Gender, COUNT(*) FROM Locations JOIN Actors ON Actor3 = ENName
GROUP BY Gender;

SELECT Actor1, COUNT(*) AS Appearances FROM Locations GROUP BY Actor1 ORDER BY Appearances DESC LIMIT 20;

(ASC/DESC)

In the Lab

LOAD DATA
    INFILE '/home/coder/project/SF_film_locations.csv'
    REPLACE
    INTO TABLE Locations
    FIELDS
        TERMINATED BY ','
        OPTIONALLY ENCLOSED BY '"'
        ESCAPED BY '"'
    IGNORE 1 ROWS;

LOAD DATA
    INFILE '/home/coder/project/wikidata-film-actors.csv'
    REPLACE
    INTO TABLE Locations
    FIELDS
        TERMINATED BY ','
        OPTIONALLY ENCLOSED BY '"'
        ESCAPED BY '"'
    IGNORE 1 ROWS;

LOAD DATA
    INFILE '/home/coder/project/wikidata-film-composers.csv'
    REPLACE
    INTO TABLE Locations
    FIELDS
        TERMINATED BY ','
        OPTIONALLY ENCLOSED BY '"'
        ESCAPED BY '"'
    IGNORE 1 ROWS;

Age of Actor1

SELECT DISTINCT Actor1, Year, DOB, FLOOR(DATEDIFF(MakeDate(Year, 1), DOB)/365) AS Age, Title AS Movie FROM Locations JOIN Actors ON Actor1 = ENName LIMIT 20;

Update the age of Charles Chaplin

UPDATE Actors SET DOB = '1889-04-16' WHERE ENName = 'Charles Chaplin';

Database libraries

Create a (persistent) connection
Send commands
Receive (and structure) response

Create a (persistent) connection

conn <- newCnnection(host, username, password, database) conn.connect()

Or both steps in one

conn <- connect(host, username, password, database)

Sending commands

resource <- conn.execute(query) resource.fetchData()

result <- conn.query(query)

Receive response

The result will usually be iterable.

Each row may be an object or an array.

Using PHP SQL libraries

$db = new mysqli(host, user, pwd, db);

$result = $db->query("SELECT * FROM Planets");

Returns a mysqli_result object

We can iterate through this response

foreach ($result as $moon) {
    echo $moon['radius'];
}

or treat it as a 2D array

$moons = $result->fetch_all();
echo $moons[5][2];

or provide an option to use keys

$moons = $result->fetch_all(MYSQL_ASSOC);
echo $moons[5]['radius'];

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