Tarea2_R

Instalacion de Paquetes

# Instalar y cargar RPostgreSQL si no está instalado
if (!requireNamespace("RPostgreSQL", quietly = TRUE)) {
  install.packages("RPostgreSQL")
}
library(RPostgreSQL)

Loading required package: DBI

# Instalar y cargar DBI si no está instalado
if (!requireNamespace("DBI", quietly = TRUE)) {
  install.packages("DBI")
}
library(DBI)

# Instalar y cargar DT si no está instalado
if (!requireNamespace("DT", quietly = TRUE)) {
  install.packages("DT")
}
library(DT)

Creación del Conector a DB

con <- dbConnect(RPostgres::Postgres(), 
                dbname = "ginabuvoli_db", 
                host = "localhost", 
                port = 5432, 
                user = "ginabuvoli_user", 
                password = "password")

dbListTables(conn = con)

[1] "courses"       "cd_facilities" "users"         "cd_members"   
[5] "cardano"       "cd_bookings"   "employees"    

Creación de Tablas e Inserción de Datos

query <- "CREATE TABLE IF NOT EXISTS cd_members
    (
       memid integer NOT NULL, 
       surname character varying(200) NOT NULL, 
       firstname character varying(200) NOT NULL, 
       address character varying(300) NOT NULL, 
       zipcode integer NOT NULL, 
       telephone character varying(20) NOT NULL, 
       recommendedby integer,
       joindate timestamp NOT NULL,
       CONSTRAINT members_pk PRIMARY KEY (memid),
       CONSTRAINT fk_members_recommendedby FOREIGN KEY (recommendedby)
            REFERENCES cd_members(memid) ON DELETE SET NULL
    );"
    
resultado <- dbSendQuery(con, query)
print('Tabla creada exitosamente')   

[1] "Tabla creada exitosamente"

query<-"INSERT INTO cd_members (memid, surname, firstname, address, zipcode, telephone, recommendedby, joindate) VALUES
(0, 'GUEST', 'GUEST', 'GUEST', 0, '(000) 000-0000', NULL, '2012-07-01 00:00:00'),
(1, 'Smith', 'Darren', '8 Bloomsbury Close, Boston', 4321, '555-555-5555', NULL, '2012-07-02 12:02:05'),
(2, 'Smith', 'Tracy', '8 Bloomsbury Close, New York', 4321, '555-555-5555', NULL, '2012-07-02 12:08:23'),
(3, 'Rownam', 'Tim', '23 Highway Way, Boston', 23423, '(844) 693-0723', NULL, '2012-07-03 09:32:15'),
(4, 'Joplette', 'Janice', '20 Crossing Road, New York', 234, '(833) 942-4710', 1, '2012-07-03 10:25:05'),
(5, 'Butters', 'Gerald', '1065 Huntingdon Avenue, Boston', 56754, '(844) 078-4130', 1, '2012-07-09 10:44:09'),
(6, 'Tracy', 'Burton', '3 Tunisia Drive, Boston', 45678, '(822) 354-9973', NULL, '2012-07-15 08:52:55'),
(7, 'Dare', 'Nancy', '6 Hunting Lodge Way, Boston', 10383, '(833) 776-4001', 4, '2012-07-25 08:59:12'),
(8, 'Boothe', 'Tim', '3 Bloomsbury Close, Reading, 00234', 234, '(811) 433-2547', 3, '2012-07-25 16:02:35'),
(9, 'Stibbons', 'Ponder', '5 Dragons Way, Winchester', 87630, '(833) 160-3900', 6, '2012-07-25 17:09:05'),
(10, 'Owen', 'Charles', '52 Cheshire Grove, Winchester, 28563', 28563, '(855) 542-5251', 1, '2012-08-03 19:42:37'),
(11, 'Jones', 'David', '976 Gnats Close, Reading', 33862, '(844) 536-8036', 4, '2012-08-06 16:32:55'),
(12, 'Baker', 'Anne', '55 Powdery Street, Boston', 80743, '844-076-5141', 9, '2012-08-10 14:23:22'),
(13, 'Farrell', 'Jemima', '103 Firth Avenue, North Reading', 57392, '(855) 016-0163', NULL, '2012-08-10 14:28:01'),
(14, 'Smith', 'Jack', '252 Binkington Way, Boston', 69302, '(822) 163-3254', 1, '2012-08-10 16:22:05'),
(15, 'Bader', 'Florence', '264 Ursula Drive, Westford', 84923, '(833) 499-3527', 9, '2012-08-10 17:52:03'),
(16, 'Baker', 'Timothy', '329 James Street, Reading', 58393, '833-941-0824', 13, '2012-08-15 10:34:25'),
(17, 'Pinker', 'David', '5 Impreza Road, Boston', 65332, '811 409-6734', 13, '2012-08-16 11:32:47'),
(20, 'Genting', 'Matthew', '4 Nunnington Place, Wingfield, Boston', 52365, '(811) 972-1377', 5, '2012-08-19 14:55:55'),
(21, 'Mackenzie', 'Anna', '64 Perkington Lane, Reading', 64577, '(822) 661-2898', 1, '2012-08-26 09:32:05'),
(22, 'Coplin', 'Joan', '85 Bard Street, Bloomington, Boston', 43533, '(822) 499-2232', 16, '2012-08-29 08:32:41'),
(24, 'Sarwin', 'Ramnaresh', '12 Bullington Lane, Boston', 65464, '(822) 413-1470', 15, '2012-09-01 08:44:42'),
(26, 'Jones', 'Douglas', '976 Gnats Close, Reading', 11986, '844 536-8036', 11, '2012-09-02 18:43:05'),
(27, 'Rumney', 'Henrietta', '3 Burkington Plaza, Boston', 78533, '(822) 989-8876', 20, '2012-09-05 08:42:35'),
(28, 'Farrell', 'David', '437 Granite Farm Road, Westford', 43532, '(855) 755-9876', NULL, '2012-09-15 08:22:05'),
(29, 'Worthington-Smyth', 'Henry', '55 Jagbi Way, North Reading', 97676, '(855) 894-3758', 2, '2012-09-17 12:27:15'),
(30, 'Purview', 'Millicent', '641 Drudgery Close, Burnington, Boston', 34232, '(855) 941-9786', 2, '2012-09-18 19:04:01'),
(33, 'Tupperware', 'Hyacinth', '33 Cheerful Plaza, Drake Road, Westford', 68666, '(822) 665-5327', NULL, '2012-09-18 19:32:05'),
(35, 'Hunt', 'John', '5 Bullington Lane, Boston', 54333, '(899) 720-6978', 30, '2012-09-19 11:32:45'),
(36, 'Crumpet', 'Erica', 'Crimson Road, North Reading', 75655, '(811) 732-4816', 2, '2012-09-22 08:36:38'),
(37, 'Smith', 'Darren', '3 Funktown, Denzington, Boston', 66796, '(822) 577-3541', NULL, '2012-09-26 18:08:45')
ON CONFLICT (memid) DO NOTHING
RETURNING *;
"
dbBegin(con)
resultado <- dbSendQuery(con, query)
dbCommit(con)
print('Registros insertados exitosamente')

[1] "Registros insertados exitosamente"

query <- "CREATE TABLE IF NOT EXISTS cd_facilities
    (
       facid integer NOT NULL, 
       name character varying(100) NOT NULL, 
       membercost numeric NOT NULL, 
       guestcost numeric NOT NULL, 
       initialoutlay numeric NOT NULL, 
       monthlymaintenance numeric NOT NULL, 
       CONSTRAINT facilities_pk PRIMARY KEY (facid)
    );"

# Ejecutar la consulta SQL para crear la tabla
resultado <- dbSendQuery(con, query)
print('Tabla creada exitosamente')

[1] "Tabla creada exitosamente"

query<-" INSERT INTO cd_facilities (facid, name, membercost, guestcost, initialoutlay, monthlymaintenance) VALUES
(0, 'Tennis Court 1', 5, 25, 10000, 200),
(1, 'Tennis Court 2', 5, 25, 8000, 200),
(2, 'Badminton Court', 0, 15.5, 4000, 50),
(3, 'Table Tennis', 0, 5, 320, 10),
(4, 'Massage Room 1', 35, 80, 4000, 3000),
(5, 'Massage Room 2', 35, 80, 4000, 3000),
(6, 'Squash Court', 3.5, 17.5, 5000, 80),
(7, 'Snooker Table', 0, 5, 450, 15),
(8, 'Pool Table', 0, 5, 400, 15)
ON CONFLICT (facid) DO NOTHING
RETURNING *;
"

dbBegin(con)
resultado <- dbSendQuery(con, query)
dbCommit(con)
print('Registros insertados exitosamente')

[1] "Registros insertados exitosamente"

query <- "CREATE TABLE IF NOT EXISTS cd_bookings
            (
               bookid integer NOT NULL, 
               facid integer NOT NULL, 
               memid integer NOT NULL, 
               starttime timestamp NOT NULL,
               slots integer NOT NULL,
               CONSTRAINT bookings_pk PRIMARY KEY (bookid),
               CONSTRAINT fk_bookings_facid FOREIGN KEY (facid) REFERENCES cd_facilities(facid),
               CONSTRAINT fk_bookings_memid FOREIGN KEY (memid) REFERENCES cd_members(memid)
            );"

# Ejecutar la consulta SQL para crear la tabla
resultado <- dbSendQuery(con, query)
print('Tabla cd_bookings creada exitosamente)

[1] "Tabla cd_bookings creada exitosamente"

query <- "
INSERT INTO cd_bookings (bookid, facid, memid, starttime, slots) VALUES
(0, 3, 1, '2012-07-03 11:00:00', 2),
(1, 4, 1, '2012-07-03 08:00:00', 2),
(2, 6, 0, '2012-07-03 18:00:00', 2),
(3, 7, 1, '2012-07-03 19:00:00', 2),
(4, 8, 1, '2012-07-03 10:00:00', 1),
(5, 8, 1, '2012-07-03 15:00:00', 1),
(6, 0, 2, '2012-07-04 09:00:00', 3),
(7, 0, 2, '2012-07-04 15:00:00', 3),
(8, 4, 3, '2012-07-04 13:30:00', 2),
(9, 4, 0, '2012-07-04 15:00:00', 2),
(10, 4, 0, '2012-07-04 17:30:00', 2),
(11, 6, 0, '2012-07-04 12:30:00', 2),
(12, 6, 0, '2012-07-04 14:00:00', 2),
(13, 6, 1, '2012-07-04 15:30:00', 2),
(14, 7, 2, '2012-07-04 14:00:00', 2),
(15, 8, 2, '2012-07-04 12:00:00', 1),
(16, 8, 3, '2012-07-04 18:00:00', 1),
(17, 1, 0, '2012-07-05 17:30:00', 3),
(18, 2, 1, '2012-07-05 09:30:00', 3),
(19, 3, 3, '2012-07-05 09:00:00', 2),
(20, 3, 1, '2012-07-05 19:00:00', 2),
(21, 4, 3, '2012-07-05 18:30:00', 2),
(22, 6, 0, '2012-07-05 13:00:00', 2),
(23, 6, 1, '2012-07-05 14:30:00', 2),
(24, 7, 2, '2012-07-05 18:30:00', 2),
(25, 8, 3, '2012-07-05 12:30:00', 1),
(26, 0, 0, '2012-07-06 08:00:00', 3),
(27, 0, 0, '2012-07-06 14:00:00', 3),
(28, 0, 2, '2012-07-06 15:30:00', 3),
(29, 2, 1, '2012-07-06 17:00:00', 3),
(30, 3, 1, '2012-07-06 11:00:00', 2),
(31, 4, 3, '2012-07-06 12:00:00', 2),
(32, 6, 1, '2012-07-06 14:00:00', 2),
(33, 7, 2, '2012-07-06 08:30:00', 2),
(34, 7, 2, '2012-07-06 13:30:00', 2),
(35, 8, 3, '2012-07-06 15:30:00', 1),
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(37, 0, 0, '2012-07-07 12:30:00', 3),
(38, 0, 2, '2012-07-07 14:30:00', 3),
(39, 1, 3, '2012-07-07 08:30:00', 3),
(40, 2, 1, '2012-07-07 09:00:00', 3),
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(76, 2, 1, '2012-07-09 09:00:00', 6),
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(226, 5, 0, '2012-07-17 13:30:00', 2),
(227, 6, 4, '2012-07-17 12:00:00', 2),
(228, 6, 0, '2012-07-17 14:00:00', 2),
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(3991, 2, 5, '2012-09-30 17:00:00', 3),
(3992, 2, 35, '2012-09-30 18:30:00', 3),
(3993, 3, 24, '2012-09-30 08:00:00', 2),
(3994, 3, 3, '2012-09-30 09:30:00', 2),
(3995, 3, 36, '2012-09-30 10:30:00', 2),
(3996, 3, 36, '2012-09-30 12:00:00', 2),
(3997, 3, 0, '2012-09-30 14:30:00', 2),
(3998, 3, 1, '2012-09-30 18:30:00', 2),
(3999, 4, 13, '2012-09-30 08:00:00', 2),
(4000, 4, 16, '2012-09-30 09:00:00', 2),
(4001, 4, 0, '2012-09-30 10:00:00', 2),
(4002, 4, 20, '2012-09-30 11:00:00', 2),
(4003, 4, 4, '2012-09-30 12:30:00', 2),
(4004, 4, 3, '2012-09-30 13:30:00', 2),
(4005, 4, 20, '2012-09-30 15:00:00', 2),
(4006, 4, 0, '2012-09-30 16:00:00', 2),
(4007, 4, 3, '2012-09-30 17:00:00', 2),
(4008, 4, 0, '2012-09-30 18:00:00', 2),
(4009, 5, 0, '2012-09-30 11:30:00', 2),
(4010, 5, 0, '2012-09-30 19:30:00', 2),
(4011, 6, 0, '2012-09-30 08:00:00', 2),
(4012, 6, 27, '2012-09-30 09:30:00', 2),
(4013, 6, 0, '2012-09-30 11:00:00', 2),
(4014, 6, 0, '2012-09-30 12:30:00', 2),
(4015, 6, 12, '2012-09-30 14:00:00', 2),
(4016, 6, 0, '2012-09-30 15:30:00', 2),
(4017, 6, 35, '2012-09-30 16:30:00', 2),
(4018, 6, 0, '2012-09-30 17:30:00', 2),
(4019, 6, 0, '2012-09-30 19:00:00', 2),
(4020, 7, 27, '2012-09-30 08:30:00', 2),
(4021, 7, 33, '2012-09-30 09:30:00', 2),
(4022, 7, 33, '2012-09-30 11:00:00', 2),
(4023, 7, 5, '2012-09-30 14:30:00', 2),
(4024, 7, 15, '2012-09-30 16:30:00', 2),
(4025, 7, 24, '2012-09-30 17:30:00', 2),
(4026, 7, 5, '2012-09-30 19:00:00', 2),
(4027, 8, 16, '2012-09-30 08:00:00', 1),
(4028, 8, 21, '2012-09-30 08:30:00', 2),
(4029, 8, 3, '2012-09-30 10:30:00', 1),
(4030, 8, 16, '2012-09-30 11:00:00', 1),
(4031, 8, 3, '2012-09-30 11:30:00', 1),
(4032, 8, 17, '2012-09-30 12:00:00', 1),
(4033, 8, 21, '2012-09-30 12:30:00', 1),
(4034, 8, 3, '2012-09-30 13:00:00', 1),
(4035, 8, 29, '2012-09-30 13:30:00', 1),
(4036, 8, 28, '2012-09-30 14:30:00', 1),
(4037, 8, 29, '2012-09-30 15:30:00', 1),
(4038, 8, 29, '2012-09-30 16:30:00', 2),
(4039, 8, 29, '2012-09-30 18:00:00', 1),
(4040, 8, 21, '2012-09-30 18:30:00', 1),
(4041, 8, 16, '2012-09-30 19:00:00', 1),
(4042, 8, 29, '2012-09-30 19:30:00', 1),
(4043, 8, 5, '2013-01-01 15:30:00', 1)
ON CONFLICT (bookid) DO NOTHING
RETURNING *;"

dbBegin(con)
resultado <- dbSendQuery(con, query)
dbCommit(con)
print('Registros insertados exitosamente')

[1] "Registros insertados exitosamente"

EJERCICIOS

I. Simple SQL Queries

1. Retrieve everything from a table

How can you retrieve all the information from the cd_facilities table?

query <- "SELECT * FROM cd_facilities"

resultado <- dbSendQuery(con, query)

datos <- dbFetch(resultado)

dbClearResult(resultado)

datatable(datos)

2. Retrieve specific columns from a table

You want to print out a list of all of the facilities and their cost to members. How would you retrieve a list of only facility names and costs?

query <- "SELECT name, membercost FROM cd_facilities"

resultado <- dbSendQuery(con, query)

datos <- dbFetch(resultado)

dbClearResult(resultado)

datatable(datos)

3. Control which rows are retrieved

How can you produce a list of facilities that charge a fee to members?

query <- "SELECT * 
FROM cd_facilities 
WHERE membercost > 0"

resultado <- dbSendQuery(con, query)

datos <- dbFetch(resultado)

dbClearResult(resultado)

datatable(datos)

4. Control which rows are retrieved - part 2

How can you produce a list of facilities that charge a fee to members, and that fee is less than 1/50th of the monthly maintenance cost? Return the facid, facility name, member cost, and monthly maintenance of the facilities in question.

query <- "SELECT facid,name,membercost,monthlymaintenance 
FROM cd_facilities 
WHERE membercost < CAST((1.0/50) * monthlymaintenance AS numeric) 
AND membercost>0"

resultado <- dbSendQuery(con, query)

datos <- dbFetch(resultado)

dbClearResult(resultado)

datatable(datos)

5. Basic string searches

How can you produce a list of all facilities with the word ‘Tennis’ in their name?

query <- "SELECT *
FROM cd_facilities
WHERE name LIKE '%Tennis%'"

resultado <- dbSendQuery(con, query)

datos <- dbFetch(resultado)

dbClearResult(resultado)

datatable(datos)

6. Matching against multiple possible values

How can you retrieve the details of facilities with ID 1 and 5? Try to do it without using the OR operator.

query <- "SELECT *
FROM cd_facilities
WHERE facid IN (1,5)"

resultado <- dbSendQuery(con, query)

datos <- dbFetch(resultado)

dbClearResult(resultado)

datatable(datos)

7. Classify results into buckets

How can you produce a list of facilities, with each labelled as ‘cheap’ or ‘expensive’ depending on if their monthly maintenance cost is more than $100? Return the name and monthly maintenance of the facilities in question.

query <- "SELECT name,
          CASE
          WHEN monthlymaintenance > 100 THEN 'expensive'
          ELSE 'cheap'
          END AS cost
          FROM cd_facilities;"

resultado <- dbSendQuery(con, query)

datos <- dbFetch(resultado)

dbClearResult(resultado)

datatable(datos)

8. Working with dates

How can you produce a list of members who joined after the start of September 2012? Return the memid, surname, firstname, and joindate of the members in question.

query <- "SELECT memid,surname,firstname, joindate
          FROM cd_members
          WHERE joindate >= '2012-09-01'"

resultado <- dbSendQuery(con, query)

datos <- dbFetch(resultado)

dbClearResult(resultado)

datatable(datos)

9. Removing duplicates, and ordering results

How can you produce an ordered list of the first 10 surnames in the members table? The list must not contain duplicates.

query <- "SELECT DISTINCT surname
          FROM cd_members
          ORDER BY 1
          LIMIT 10"

resultado <- dbSendQuery(con, query)

datos <- dbFetch(resultado)

dbClearResult(resultado)

datatable(datos)

10. Combining results from multiple queries

You, for some reason, want a combined list of all surnames and all facility names. Yes, this is a contrived example :-). Produce that list!

query <- "SELECT surname
FROM cd_members
UNION
SELECT name
FROM cd_facilities"

resultado <- dbSendQuery(con, query)

datos <- dbFetch(resultado)

dbClearResult(resultado)

datatable(datos)

11. Simple aggregation

You’d like to get the signup date of your last member. How can you retrieve this information?

query <- "SELECT MAX(joindate) AS latest
FROM cd_members"

resultado <- dbSendQuery(con, query)

datos <- dbFetch(resultado)

dbClearResult(resultado)

datatable(datos)

12. More aggregation

You’d like to get the first and last name of the last member(s) who signed up - not just the date. How can you do that?

query <- "SELECT firstname, surname,joindate
          FROM cd_members
          WHERE joindate = (SELECT MAX(joindate) FROM cd_members);"

resultado <- dbSendQuery(con, query)

datos <- dbFetch(resultado)

dbClearResult(resultado)

datatable(datos)

II. Joins and Subqueries

1. Retrieve the start times of members’ bookings

How can you produce a list of the start times for bookings by members named ‘David Farrell’?

query <- "SELECT B.starttime
          FROM cd_members A
          LEFT JOIN cd_bookings B
          ON A.memid = B.memid
          WHERE A.firstname = 'David' 
          AND A.surname='Farrell'"

resultado <- dbSendQuery(con, query)

datos <- dbFetch(resultado)

dbClearResult(resultado)

datatable(datos)

2. Work out the start times of bookings for tennis courts

How can you produce a list of the start times for bookings for tennis courts, for the date ‘2012-09-21’? Return a list of start time and facility name pairings, ordered by the time.

query <- "SELECT A.starttime, B.name
          FROM cd_bookings A
          LEFT JOIN  cd_facilities B
          ON A.facid = B.facid
          WHERE DATE(A.starttime) = '2012-09-21'
          AND B.name LIKE '%Tennis Court%'
          ORDER BY A.starttime"

resultado <- dbSendQuery(con, query)

datos <- dbFetch(resultado)

dbClearResult(resultado)

datatable(datos)

3. Produce a list of all members who have recommended another member

How can you output a list of all members who have recommended another member? Ensure that there are no duplicates in the list, and that results are ordered by (surname, firstname).

query <- "SELECT DISTINCT m.firstname, m.surname
          FROM cd_members m
          JOIN cd_members r ON m.memid = r.recommendedby
          ORDER BY m.surname, m.firstname"  

resultado <- dbSendQuery(con, query)  
datos <- dbFetch(resultado)
dbClearResult(resultado)  
datatable(datos)

4. Produce a list of all members, along with their recommender

How can you output a list of all members, including the individual who recommended them (if any)? Ensure that results are ordered by (surname, firstname).

query <- "SELECT m1.firstname AS member_firstname,
           m1.surname AS member_surname,
           m2.firstname AS recommender_firstname,
           m2.surname AS recommender_surname
          FROM cd_members m1
          LEFT JOIN cd_members m2 ON m1.recommendedby = m2.memid
          ORDER BY m1.surname, m1.firstname;"  

resultado <- dbSendQuery(con, query)  
datos <- dbFetch(resultado)
dbClearResult(resultado)  
datatable(datos)

5. Produce a list of all members who have used a tennis court

How can you produce a list of all members who have used a tennis court? Include in your output the name of the court, and the name of the member formatted as a single column. Ensure no duplicate data, and order by the member name followed by the facility name.

query <- "SELECT DISTINCT CONCAT(m.firstname, ' ', m.surname) AS member_name,
                f.name AS facility_name
          FROM cd_bookings b
          JOIN cd_facilities f ON b.facid = f.facid
          JOIN cd_members m ON b.memid = m.memid
          WHERE f.name LIKE '%Tennis Court%'
          ORDER BY member_name, facility_name;"  

resultado <- dbSendQuery(con, query)  
datos <- dbFetch(resultado)
dbClearResult(resultado)  
datatable(datos)

6. Produce a list of costly bookings

How can you produce a list of bookings on the day of 2012-09-14 which will cost the member (or guest) more than $30? Remember that guests have different costs to members (the listed costs are per half-hour ‘slot’), and the guest user is always ID 0. Include in your output the name of the facility, the name of the member formatted as a single column, and the cost. Order by descending cost, and do not use any subqueries.

query <- "SELECT CONCAT(m.firstname, ' ', m.surname) AS member_name,
          f.name AS facility_name,
          CASE
             WHEN b.memid = 0 THEN b.slots * f.guestcost
             ELSE b.slots * f.membercost
          END AS cost
          FROM cd_bookings b
          JOIN cd_facilities f ON b.facid = f.facid
          LEFT JOIN cd_members m ON b.memid = m.memid
          WHERE DATE(b.starttime) = '2012-09-14'
            AND ((b.memid = 0 AND b.slots * f.guestcost > 30)
                 OR (b.memid != 0 AND b.slots * f.membercost > 30))
          ORDER BY cost DESC;"  

resultado <- dbSendQuery(con, query)  
datos <- dbFetch(resultado)
dbClearResult(resultado)  
datatable(datos)

7. Produce a list of all members, along with their recommender, using no joins.

How can you output a list of all members, including the individual who recommended them (if any), without using any joins? Ensure that there are no duplicates in the list, and that each firstname + surname pairing is formatted as a column and ordered.

query <- "SELECT DISTINCT
              m1.firstname || ' ' || m1.surname AS member_name,
              (SELECT m2.firstname || ' ' || m2.surname
          FROM cd_members m2
          WHERE m2.memid = m1.recommendedby) AS recommender_name
          FROM
              cd_members m1
          ORDER BY
              member_name;"  

resultado <- dbSendQuery(con, query)  
datos <- dbFetch(resultado)
dbClearResult(resultado)  
datatable(datos)

8. Produce a list of costly bookings, using a subquery

The Produce a list of costly bookings exercise contained some messy logic: we had to calculate the booking cost in both the WHERE clause and the CASE statement. Try to simplify this calculation using subqueries.

query <- "SELECT CONCAT(m.firstname, ' ', m.surname) AS member_name,
       f.name AS facility_name,
       cost.total_cost AS cost
        FROM cd_bookings b
        JOIN cd_facilities f ON b.facid = f.facid
        LEFT JOIN cd_members m ON b.memid = m.memid
        JOIN (
            SELECT b.bookid,
                   CASE
                       WHEN b.memid = 0 THEN b.slots * f.guestcost
                       ELSE b.slots * f.membercost
                   END AS total_cost
            FROM cd_bookings b
            JOIN cd_facilities f ON b.facid = f.facid
            WHERE DATE(b.starttime) = '2012-09-14'
        ) AS cost ON b.bookid = cost.bookid
        WHERE cost.total_cost > 30
        ORDER BY cost DESC;"  

resultado <- dbSendQuery(con, query)  
datos <- dbFetch(resultado)
dbClearResult(resultado)  
datatable(datos)

III. Modifying Data

1. Insert some data into a table

The club is adding a new facility - a spa. We need to add it into the facilities table. Use the following values:

• facid: 9, Name: ‘Spa’, membercost: 20, guestcost: 30, initialoutlay: 100000, monthlymaintenance: 800.

query <- "INSERT INTO cd_facilities (facid, name, membercost, guestcost, initialoutlay, monthlymaintenance)
          VALUES (9, 'Spa', 20, 30, 100000, 800)
          ON CONFLICT (facid) DO NOTHING"

dbBegin(con)
resultado <- dbSendQuery(con, query)


query2 <- "SELECT * FROM cd_facilities"
resultado2 <- dbSendQuery(con, query2)

datos <- dbFetch(resultado2)

dbClearResult(resultado)
dbClearResult(resultado2)

datatable(datos)

2. Insert multiple rows of data into a table

In the previous exercise, you learned how to add a facility. Now you’re going to add multiple facilities in one command. Use the following values:

• facid: 9, Name: ‘Spa’, membercost: 20, guestcost: 30, initialoutlay: 100000, monthlymaintenance: 800.

• facid: 10, Name: ‘Squash Court 2’, membercost: 3.5, guestcost: 17.5, initialoutlay: 5000, monthlymaintenance: 80.

query <- "INSERT INTO cd_facilities 
          (facid, name, membercost, guestcost,   initialoutlay, monthlymaintenance)
          VALUES 
          (9, 'Spa', 20, 30, 100000, 800),
          (10, 'Squash Court 2', 3.5, 17.5, 5000, 80)
          ON CONFLICT (facid) DO NOTHING;"


resultado <- dbSendQuery(con, query)


query2 <- "SELECT * FROM cd_facilities"
resultado2 <- dbSendQuery(con, query2)

datos <- dbFetch(resultado2)

dbClearResult(resultado)
dbClearResult(resultado2)

datatable(datos)

<PqResult>
  SQL  DELETE FROM cd_facilities
          WHERE facid IN (9,10);
  ROWS Fetched: 0 [complete]
       Changed: 2

3. Insert calculated data into a table

Let’s try adding the spa to the facilities table again. This time, though, we want to automatically generate the value for the next facid, rather than specifying it as a constant. Use the following values for everything else:

• Name: ‘Spa’, membercost: 20, guestcost: 30, initialoutlay: 100000, monthlymaintenance: 800.

query <- "INSERT INTO cd_facilities
        (facid, name, membercost, guestcost, initialoutlay, monthlymaintenance)
    SELECT (SELECT MAX(facid) FROM cd_facilities)+1, 'Spa', 20, 30, 100000, 800    
          ON CONFLICT (facid) DO NOTHING;"


resultado <- dbSendQuery(con, query)


query2 <- "SELECT * FROM cd_facilities"
resultado2 <- dbSendQuery(con, query2)

datos <- dbFetch(resultado2)

dbClearResult(resultado)
dbClearResult(resultado2)

datatable(datos)

4.Update some existing data

We made a mistake when entering the data for the second tennis court. The initial outlay was 10000 rather than 8000: you need to alter the data to fix the error.

query <- " UPDATE cd_facilities 
          SET initialoutlay = 10000 
          WHERE name = 'Tennis Court 2';"

resultado <- dbSendQuery(con, query)

query2 <- "SELECT * FROM cd_facilities" 
resultado2 <- dbSendQuery(con, query2)

datos <- dbFetch(resultado2)

dbClearResult(resultado) 
dbClearResult(resultado2)

datatable(datos)

5. Update multiple rows and columns at the same time

We want to increase the price of the tennis courts for both members and guests. Update the costs to be 6 for members, and 30 for guests.

query <- " UPDATE cd_facilities
          SET membercost = 6,
              guestcost = 30
          WHERE name LIKE 'Tennis Court%';"

resultado <- dbSendQuery(con, query)

query2 <- "SELECT * FROM cd_facilities" 
resultado2 <- dbSendQuery(con, query2)

datos <- dbFetch(resultado2)

dbClearResult(resultado) 
dbClearResult(resultado2)

datatable(datos)

6. Update a row based on the contents of another row

We want to alter the price of the second tennis court so that it costs 10% more than the first one. Try to do this without using constant values for the prices, so that we can reuse the statement if we want to.

query <- " UPDATE cd_facilities AS t1

            SET membercost = t1.membercost * 1.1,
                guestcost = t1.guestcost * 1.1
            FROM (
                SELECT membercost, guestcost
                FROM cd_facilities
                WHERE name = 'Tennis Court 1'
            ) AS t2
            WHERE t1.name = 'Tennis Court 2';"

resultado <- dbSendQuery(con, query)

query2 <- "SELECT * FROM cd_facilities" 
resultado2 <- dbSendQuery(con, query2)

datos <- dbFetch(resultado2)

dbClearResult(resultado) 
dbClearResult(resultado2)

datatable(datos)

7. Delete all bookings

As part of a clearout of our database, we want to delete all bookings from the cd_bookings table. How can we accomplish this?

query <- "DELETE FROM cd_bookings;"

resultado <- dbSendQuery(con, query)

query2 <- "SELECT * FROM cd_bookings" 
resultado2 <- dbSendQuery(con, query2)

datos <- dbFetch(resultado2)

dbClearResult(resultado) 
dbClearResult(resultado2)

datatable(datos)

8. Delete a member from the cd_members table

We want to remove member 37, who has never made a booking, from our database. How can we achieve that?

query <- "DELETE FROM cd_members
          WHERE memid = 37
          AND NOT EXISTS (
              SELECT 1
              FROM cd_bookings
              WHERE memid = 37
          );          "

resultado <- dbSendQuery(con, query)

query2 <- "SELECT * FROM cd_members" 
resultado2 <- dbSendQuery(con, query2)

datos <- dbFetch(resultado2)

dbClearResult(resultado) 
dbClearResult(resultado2)

datatable(datos)

9. Delete based on a subquery

In our previous exercises, we deleted a specific member who had never made a booking. How can we make that more general, to delete all members who have never made a booking?

query <- "DELETE FROM cd_members
          WHERE NOT EXISTS (
              SELECT 1
              FROM cd_bookings
              WHERE cd_members.memid = cd_bookings.memid
          );"

dbClearResult(resultado) 
dbClearResult(resultado2)

resultado <- dbSendQuery(con, query)

query2 <- "SELECT * FROM cd_members" 
resultado2 <- dbSendQuery(con, query2)

datos <- dbFetch(resultado2)

dbClearResult(resultado) 
dbClearResult(resultado2)

datatable(datos)

IV. Aggregation

1. Count the number of facilities

For our first foray into aggregates, we’re going to stick to something simple. We want to know how many facilities exist - simply produce a total count.

dbClearResult(resultado) 
dbClearResult(resultado2)

query <- "SELECT COUNT(*) AS total_facilities
          FROM cd_facilities;"

resultado <- dbSendQuery(con, query)

datos <- dbFetch(resultado)

dbClearResult(resultado) 

datatable(datos)

2. Count the number of expensive facilities

Produce a count of the number of facilities that have a cost to guests of 10 or more.

dbClearResult(resultado) 
dbClearResult(resultado2)

query <- "SELECT COUNT(*) AS total_facilities
          FROM cd_facilities A
          WHERE A.guestcost > 10;"

resultado <- dbSendQuery(con, query)

datos <- dbFetch(resultado)

dbClearResult(resultado) 

datatable(datos)

3. Count the number of recommendations each member makes.

Produce a count of the number of recommendations each member has made. Order by member ID.

dbClearResult(resultado) 
dbClearResult(resultado2)

query <- "SELECT recommendedby AS member_id, COUNT(*) AS recommendation_count
          FROM cd_members
          WHERE recommendedby IS NOT NULL
          GROUP BY recommendedby
          ORDER BY member_id;"

resultado <- dbSendQuery(con, query)

datos <- dbFetch(resultado)

dbClearResult(resultado) 

datatable(datos)

4.List the total slots booked per facility

Produce a list of the total number of slots booked per facility. For now, just produce an output table consisting of facility id and slots, sorted by facility id.

dbClearResult(resultado) 
dbClearResult(resultado2)

query <- "SELECT facid, SUM(slots) AS total_slots_booked
          FROM cd_bookings
          GROUP BY facid
          ORDER BY facid;"

resultado <- dbSendQuery(con, query)

datos <- dbFetch(resultado)

dbClearResult(resultado) 

datatable(datos)

5.List the total slots booked per facility in a given month

Produce a list of the total number of slots booked per facility in the month of September 2012. Produce an output table consisting of facility id and slots, sorted by the number of slots.

dbClearResult(resultado) 
dbClearResult(resultado2)

query <- "SELECT facid, SUM(slots) AS total_slots_booked
          FROM cd_bookings
          WHERE starttime >= '2012-09-01' AND starttime < '2012-10-01'
          GROUP BY facid
          ORDER BY total_slots_booked ASC;"

resultado <- dbSendQuery(con, query)

datos <- dbFetch(resultado)

dbClearResult(resultado) 

datatable(datos)

6.List the total slots booked per facility per month

Produce a list of the total number of slots booked per facility per month in the year of 2012. Produce an output table consisting of facility id and slots, sorted by the id and month.

dbClearResult(resultado) 
dbClearResult(resultado2)

query <- "SELECT facid, EXTRACT(MONTH FROM starttime) AS month,   SUM(slots) AS total_slots_booked
          FROM cd_bookings
          WHERE EXTRACT(YEAR FROM starttime) = 2012
          GROUP BY facid, EXTRACT(MONTH FROM starttime)
          ORDER BY facid, month;"

resultado <- dbSendQuery(con, query)

datos <- dbFetch(resultado)

dbClearResult(resultado) 

datatable(datos)

7.Find the count of members who have made at least one booking

Find the total number of members (including guests) who have made at least one booking.

dbClearResult(resultado) 
dbClearResult(resultado2)

query <- "SELECT COUNT(DISTINCT memid) AS total_members_with_bookings
FROM cd_bookings;"

resultado <- dbSendQuery(con, query)

datos <- dbFetch(resultado)

dbClearResult(resultado) 

datatable(datos)

8.List facilities with more than 1000 slots booked

Produce a list of facilities with more than 1000 slots booked. Produce an output table consisting of facility id and slots, sorted by facility id.

dbClearResult(resultado) 
dbClearResult(resultado2)

query <- "SELECT facid, SUM(slots) AS total_slots_booked
          FROM cd_bookings
          GROUP BY facid
          HAVING SUM(slots) > 1000
          ORDER BY facid;"

resultado <- dbSendQuery(con, query)

datos <- dbFetch(resultado)

dbClearResult(resultado) 

datatable(datos)

9.Find the total revenue of each facility

Produce a list of facilities along with their total revenue. The output table should consist of facility name and revenue, sorted by revenue. Remember that there’s a different cost for guests and members!

dbClearResult(resultado) 
dbClearResult(resultado2)

query <- "SELECT f.name AS facility_name, 
       SUM(CASE WHEN b.memid = 0 THEN b.slots * f.guestcost
                ELSE b.slots * f.membercost END) AS revenue
        FROM cd_bookings b
        JOIN cd_facilities f ON b.facid = f.facid
        GROUP BY f.name
        ORDER BY revenue ASC;"

resultado <- dbSendQuery(con, query)

datos <- dbFetch(resultado)

dbClearResult(resultado) 

datatable(datos)

10.Find facilities with a total revenue less than 1000

Produce a list of facilities with a total revenue less than 1000. Produce an output table consisting of facility name and revenue, sorted by revenue. Remember that there’s a different cost for guests and members!

dbClearResult(resultado) 
dbClearResult(resultado2)

query <- "SELECT f.name AS facility_name, 
       SUM(CASE WHEN b.memid = 0 THEN b.slots * f.guestcost
                ELSE b.slots * f.membercost END) AS revenue
        FROM cd_bookings b
        JOIN cd_facilities f ON b.facid = f.facid
        GROUP BY f.name
        HAVING SUM(CASE WHEN b.memid = 0 THEN b.slots * f.guestcost
                        ELSE b.slots * f.membercost END) < 1000
        ORDER BY revenue;"

resultado <- dbSendQuery(con, query)

datos <- dbFetch(resultado)

dbClearResult(resultado) 

datatable(datos)

11.Output the facility id that has the highest number of slots booked

Output the facility id that has the highest number of slots booked. For bonus points, try a version without a LIMIT clause. This version will probably look messy!

dbClearResult(resultado) 
dbClearResult(resultado2)

query <- "SELECT 
    facid, 
    SUM(slots) AS Total_Slots
FROM 
    cd_bookings
GROUP BY 
    facid
ORDER BY 
    SUM(slots) DESC
LIMIT 1;"


resultado <- dbSendQuery(con, query)

datos <- dbFetch(resultado)

dbClearResult(resultado) 

datatable(datos)

12.List the total slots booked per facility per month, part 2

Produce a list of the total number of slots booked per facility per month in the year of 2012. In this version, include output rows containing totals for all months per facility, and a total for all months for all facilities. The output table should consist of facility id, month and slots, sorted by the id and month. When calculating the aggregated values for all months and all facids, return null values in the month and facid columns.

dbClearResult(resultado) 
dbClearResult(resultado2)

query <- "SELECT 
              facid, 
              EXTRACT(MONTH FROM starttime) AS month, 
              SUM(slots) AS slots
          FROM 
              cd_bookings
          WHERE
              starttime >= '2012-01-01'
              AND starttime < '2013-01-01'
          GROUP BY 
              ROLLUP(facid, month)
          ORDER BY 
              facid, 
              month;"

resultado <- dbSendQuery(con, query)

datos <- dbFetch(resultado)

dbClearResult(resultado) 

datatable(datos)

13.List the total hours booked per named facility

Produce a list of the total number of hours booked per facility, remembering that a slot lasts half an hour. The output table should consist of the facility id, name, and hours booked, sorted by facility id. Try formatting the hours to two decimal places.

query <- "SELECT 
                facs.facid, 
                facs.name,
                TRIM(TO_CHAR(SUM(bks.slots) / 2.0, '9999999999999999D99')) AS Total_Hours
            FROM 
                cd_bookings bks
            INNER JOIN 
                cd_facilities facs ON facs.facid = bks.facid
            GROUP BY 
                facs.facid, 
                facs.name
            ORDER BY 
                facs.facid;"

resultado <- dbSendQuery(con, query)

datos <- dbFetch(resultado)

dbClearResult(resultado) 

datatable(datos)

14.List each member’s first booking after September 1st 2012

Produce a list of each member name, id, and their first booking after September 1st 2012. Order by member ID.

query <- "SELECT 
                mems.surname, 
                mems.firstname, 
                mems.memid, 
                MIN(bks.starttime) AS starttime
            FROM 
                cd_bookings bks
            INNER JOIN 
                cd_members mems ON mems.memid = bks.memid
            WHERE 
                starttime >= '2012-09-01'
            GROUP BY 
                mems.surname, 
                mems.firstname, 
                mems.memid
            ORDER BY 
                mems.memid;"

resultado <- dbSendQuery(con, query)

datos <- dbFetch(resultado)

dbClearResult(resultado) 

datatable(datos)

15.Produce a list of member names, with each row containing the total member count

Produce a list of member names, with each row containing the total member count. Order by join date, and include guest members.

query <- "SELECT 
              COUNT(*) OVER() AS total_members,
              firstname,
              surname
          FROM 
              cd_members
          ORDER BY 
              joindate;"

resultado <- dbSendQuery(con, query)

datos <- dbFetch(resultado)

dbClearResult(resultado) 

datatable(datos)

16.Produce a numbered list of members

Produce a monotonically increasing numbered list of members (including guests), ordered by their date of joining. Remember that member IDs are not guaranteed to be sequential.

query <- "SELECT 
              ROW_NUMBER() OVER(ORDER BY joindate) AS row_number,
              firstname,
              surname
          FROM 
              cd_members
          ORDER BY 
              joindate;"

resultado <- dbSendQuery(con, query)

datos <- dbFetch(resultado)

dbClearResult(resultado) 

datatable(datos)

17.Output the facility id that has the highest number of slots booked, again

Output the facility id that has the highest number of slots booked. Ensure that in the event of a tie, all tieing results get output.

query <- "SELECT 
                facid, 
                total 
            FROM 
                (
                    SELECT 
                        facid, 
                        SUM(slots) AS total, 
                        RANK() OVER (ORDER BY SUM(slots) DESC) AS rank
                    FROM 
                        cd_bookings
                    GROUP BY 
                        facid
                ) AS ranked
            WHERE 
                rank = 1;"

resultado <- dbSendQuery(con, query)

datos <- dbFetch(resultado)

dbClearResult(resultado) 

datatable(datos)

18.Rank members by (rounded) hours used

Produce a list of members (including guests), along with the number of hours they’ve booked in facilities, rounded to the nearest ten hours. Rank them by this rounded figure, producing output of first name, surname, rounded hours, rank. Sort by rank, surname, and first name.

query <- "SELECT 
              firstname, 
              surname,
              ((SUM(bks.slots) + 10) / 20) * 10 AS hours,
              RANK() OVER (ORDER BY ((SUM(bks.slots) + 10) / 20) * 10 DESC) AS rank
          FROM 
              cd_bookings bks
          INNER JOIN 
              cd_members mems ON bks.memid = mems.memid
          GROUP BY 
              mems.memid
          ORDER BY 
              rank, 
              surname, 
              firstname;"

resultado <- dbSendQuery(con, query)

datos <- dbFetch(resultado)

dbClearResult(resultado) 

datatable(datos)

19.Find the top three revenue generating facilities

Produce a list of the top three revenue generating facilities (including ties). Output facility name and rank, sorted by rank and facility name.

query <- "SELECT 
                name, rank 
            FROM (SELECT facs.name AS name, 
                        RANK() OVER (ORDER BY SUM(CASE
                        WHEN memid = 0 THEN slots * facs.guestcost
                        ELSE slots * membercost
                        END) DESC) AS rank
                    FROM 
                        cd_bookings bks
                    INNER JOIN 
                        cd_facilities facs ON bks.facid = facs.facid
                    GROUP BY 
                        facs.name
                        ) AS subq
                    WHERE 
                        rank <= 3
                    ORDER BY 
                        rank;"

resultado <- dbSendQuery(con, query)

datos <- dbFetch(resultado)

dbClearResult(resultado) 

datatable(datos)

20.Classify facilities by value

Classify facilities into equally sized groups of high, average, and low based on their revenue. Order by classification and facility name.

query <- "SELECT name, 
          CASE 
              WHEN class = 1 THEN 'high'
              WHEN class = 2 THEN 'average'
              ELSE 'low'
          END AS revenue
          FROM 
              (SELECT facs.name AS name, 
                NTILE(3) OVER (ORDER BY SUM(CASE
                                  WHEN memid = 0 THEN slots * facs.guestcost
                                  ELSE slots * membercost
                                  END) DESC) AS class
                  FROM 
                      cd_bookings bks
                  INNER JOIN 
                      cd_facilities facs ON bks.facid = facs.facid
                  GROUP BY 
                      facs.name
                      ) AS subq
                  ORDER BY 
                      class, 
                      name;"

resultado <- dbSendQuery(con, query)

datos <- dbFetch(resultado)

dbClearResult(resultado) 

datatable(datos)

21.Calculate the payback time for each facility

Based on the 3 complete months of data so far, calculate the amount of time each facility will take to repay its cost of ownership. Remember to take into account ongoing monthly maintenance. Output facility name and payback time in months, order by facility name. Don’t worry about differences in month lengths, we’re only looking for a rough value here!

query <- "SELECT 
              facs.name AS name,
              facs.initialoutlay / ((SUM(CASE
                            WHEN memid = 0 THEN slots * facs.guestcost
                            ELSE slots * membercost
                            END) / 3) - facs.monthlymaintenance) AS months
                  FROM 
                      cd_bookings bks
                  INNER JOIN 
                      cd_facilities facs ON bks.facid = facs.facid
                  GROUP BY 
                      facs.facid
                  ORDER BY 
                      name;"

resultado <- dbSendQuery(con, query)

datos <- dbFetch(resultado)

dbClearResult(resultado) 

datatable(datos)

22.Calculate a rolling average of total revenue

For each day in August 2012, calculate a rolling average of total revenue over the previous 15 days. Output should contain date and revenue columns, sorted by the date. Remember to account for the possibility of a day having zero revenue. This one’s a bit tough, so don’t be afraid to check out the hint!

query <- "SELECT  dategen.date,
    ( SELECT 
            SUM(CASE
                WHEN memid = 0 THEN slots * facs.guestcost
                ELSE slots * membercost
              END) AS rev
        FROM 
            cd_bookings bks
        INNER JOIN 
            cd_facilities facs ON bks.facid = facs.facid
        WHERE 
            bks.starttime > dategen.date - INTERVAL '14 days'
            AND bks.starttime < dategen.date + INTERVAL '1 day'
    ) / 15 AS revenue
      FROM 
          (
              SELECT 
                  CAST(generate_series(timestamp '2012-08-01', '2012-08-31', '1 day') AS DATE) AS date
          ) AS dategen
      ORDER BY 
          dategen.date;"

resultado <- dbSendQuery(con, query)

datos <- dbFetch(resultado)

dbClearResult(resultado) 

datatable(datos)

V. Working with Timestamps

1. Produce a timestamp for 1 a.m. on the 31st of August 2012

Produce a timestamp for 1 a.m. on the 31st of August 2012.

query <- "SELECT timestamp '2012-08-31 01:00:00';"

resultado <- dbSendQuery(con, query)

datos <- dbFetch(resultado)

dbClearResult(resultado) 

datatable(datos)

2. Subtract timestamps from each other

Find the result of subtracting the timestamp ‘2012-07-30 01:00:00’ from the timestamp ‘2012-08-31 01:00:00’

query <- "SELECT timestamp '2012-08-31 01:00:00' - timestamp '2012-07-30 01:00:00' AS interval;"

resultado <- dbSendQuery(con, query)

datos <- dbFetch(resultado)

dbClearResult(resultado) 

datatable(datos)

3. Generate a list of all the dates in October 2012

Produce a list of all the dates in October 2012. They can be output as a timestamp (with time set to midnight) or a date.

query <- "SELECT generate_series(timestamp '2012-10-01', timestamp '2012-10-31', interval '1 day') AS ts;"

resultado <- dbSendQuery(con, query)

datos <- dbFetch(resultado)

dbClearResult(resultado) 

datatable(datos)

4. Get the day of the month from a timestamp

Get the day of the month from the timestamp ‘2012-08-31’ as an integer.

query <- "SELECT EXTRACT(day FROM timestamp '2012-08-31');"

resultado <- dbSendQuery(con, query)

datos <- dbFetch(resultado)

dbClearResult(resultado) 

datatable(datos)

5. Work out the number of seconds between timestamps

Work out the number of seconds between the timestamps ‘2012-08-31 01:00:00’ and ‘2012-09-02 00:00:00’

query <- "SELECT EXTRACT(epoch FROM (timestamp '2012-09-02 00:00:00' - '2012-08-31 01:00:00'));"

resultado <- dbSendQuery(con, query)

datos <- dbFetch(resultado)

dbClearResult(resultado) 

datatable(datos)

6. Work out the number of days in each month of 2012

For each month of the year in 2012, output the number of days in that month. Format the output as an integer column containing the month of the year, and a second column containing an interval data type.

query <- "SELECT EXTRACT(month FROM cal.month) AS month,
       (cal.month + INTERVAL '1 month') - cal.month AS length
        FROM (
            SELECT generate_series(timestamp '2012-01-01', timestamp '2012-12-01', INTERVAL '1 month') AS month
        ) cal
        ORDER BY month;"

resultado <- dbSendQuery(con, query)

datos <- dbFetch(resultado)

dbClearResult(resultado) 

datatable(datos)

7. Work out the number of days remaining in the month

For any given timestamp, work out the number of days remaining in the month. The current day should count as a whole day, regardless of the time. Use ‘2012-02-11 01:00:00’ as an example timestamp for the purposes of making the answer. Format the output as a single interval value.

query <- "SELECT (date_trunc('month', ts.testts) + INTERVAL '1 month') - date_trunc('day', ts.testts) AS remaining
FROM (SELECT TIMESTAMP '2012-02-11 01:00:00' AS testts) ts;"

resultado <- dbSendQuery(con, query)

datos <- dbFetch(resultado)

dbClearResult(resultado) 

datatable(datos)

8. Work out the end time of bookings

Return a list of the start and end time of the last 10 bookings (ordered by the time at which they end, followed by the time at which they start) in the system.

query <- "SELECT starttime, starttime + slots * (INTERVAL '30 minutes') AS endtime
FROM cd_bookings
ORDER BY endtime DESC, starttime DESC
LIMIT 10;"

resultado <- dbSendQuery(con, query)

datos <- dbFetch(resultado)

dbClearResult(resultado) 

datatable(datos)

9. Return a count of bookings for each month

Return a count of bookings for each month, sorted by month

query <- "SELECT DATE_TRUNC('month', starttime) AS month, COUNT(*) AS count
FROM cd_bookings
GROUP BY month
ORDER BY month;"

resultado <- dbSendQuery(con, query)

datos <- dbFetch(resultado)

dbClearResult(resultado) 

datatable(datos)

10. Work out the utilisation percentage for each facility by month

Work out the utilisation percentage for each facility by month, sorted by name and month, rounded to 1 decimal place. Opening time is 8am, closing time is 8.30pm. You can treat every month as a full month, regardless of if there were some dates the club was not open.

query <- "SELECT name,
       month,
       ROUND((100 * slots) / EXTRACT(day FROM (DATE_TRUNC('month', month + INTERVAL '1 month') - DATE_TRUNC('month', month))) * 24 * 2.0, 1) AS utilisation
FROM (
    SELECT facs.name AS name,
           DATE_TRUNC('month', starttime) AS month,
           SUM(slots) AS slots
    FROM cd_bookings bks
    INNER JOIN cd_facilities facs ON bks.facid = facs.facid
    GROUP BY facs.facid, month
) AS inn
ORDER BY name, month;"

resultado <- dbSendQuery(con, query)

datos <- dbFetch(resultado)

dbClearResult(resultado) 

datatable(datos)

VI. String Operations

1. Format the names of members

Output the names of all members, formatted as ‘Surname, Firstname’

query <- "SELECT surname || ', ' || firstname AS name FROM cd_members;"

resultado <- dbSendQuery(con, query)

datos <- dbFetch(resultado)

dbClearResult(resultado) 

datatable(datos)

2. Find facilities by a name prefix

Find all facilities whose name begins with ‘Tennis’. Retrieve all columns.

query <- "SELECT * FROM cd_facilities WHERE name LIKE 'Tennis%';"

resultado <- dbSendQuery(con, query)

datos <- dbFetch(resultado)

dbClearResult(resultado) 

datatable(datos)

3. Perform a case-insensitive search

Perform a case-insensitive search to find all facilities whose name begins with ‘tennis’. Retrieve all columns.

query <- "SELECT * FROM cd_facilities WHERE UPPER(name) LIKE 'TENNIS%';"

resultado <- dbSendQuery(con, query)

datos <- dbFetch(resultado)

dbClearResult(resultado) 

datatable(datos)

4. Find telephone numbers with parentheses

You’ve noticed that the club’s member table has telephone numbers with very inconsistent formatting. You’d like to find all the telephone numbers that contain parentheses, returning the member ID and telephone number sorted by member ID.

query <- "SELECT memid, telephone FROM cd_members WHERE telephone ~ '[()]';"

resultado <- dbSendQuery(con, query)

datos <- dbFetch(resultado)

dbClearResult(resultado) 

datatable(datos)

5. Pad zip codes with leading zeroes

The zip codes in our example dataset have had leading zeroes removed from them by virtue of being stored as a numeric type. Retrieve all zip codes from the members table, padding any zip codes less than 5 characters long with leading zeroes. Order by the new zip code.

query <- "SELECT LPAD(CAST(zipcode AS CHAR(5)), 5, '0') AS zip FROM cd_members ORDER BY zip;"

resultado <- dbSendQuery(con, query)

datos <- dbFetch(resultado)

dbClearResult(resultado) 

datatable(datos)

6. Count the number of members whose surname starts with each letter of the alphabet

You’d like to produce a count of how many members you have whose surname starts with each letter of the alphabet. Sort by the letter, and don’t worry about printing out a letter if the count is 0.

query <- "SELECT SUBSTR(mems.surname, 1, 1) AS letter, COUNT(*) AS count 
FROM cd_members mems
GROUP BY letter
ORDER BY letter;"

resultado <- dbSendQuery(con, query)

datos <- dbFetch(resultado)

dbClearResult(resultado) 

datatable(datos)

7. Clean up telephone numbers

The telephone numbers in the database are very inconsistently formatted. You’d like to print a list of member ids and numbers that have had ‘-’,‘(’,‘)’, and ’ ’ characters removed. Order by member id.

query <- "SELECT memid, TRANSLATE(telephone, '-() ', '') AS telephone
FROM cd_members
ORDER BY memid;"

resultado <- dbSendQuery(con, query)

datos <- dbFetch(resultado)

dbClearResult(resultado) 

datatable(datos)

VII. Recursive Queries

1. Find the upward recommendation chain for member ID 27

Find the upward recommendation chain for member ID 27: that is, the member who recommended them, and the member who recommended that member, and so on. Return member ID, first name, and surname. Order by descending member id.

query <- "WITH RECURSIVE recommenders(recommender) AS (
                SELECT recommendedby FROM cd_members WHERE memid = 27
                UNION ALL
                SELECT mems.recommendedby
                    FROM recommenders recs
                    INNER JOIN cd_members mems
                        ON mems.memid = recs.recommender
            )
            SELECT recs.recommender, mems.firstname, mems.surname
                FROM recommenders recs
                INNER JOIN cd_members mems
                    ON recs.recommender = mems.memid
            ORDER BY memid DESC;"

resultado <- dbSendQuery(con, query)

datos <- dbFetch(resultado)

dbClearResult(resultado) 

datatable(datos)

2. Find the downward recommendation chain for member ID 1

Find the downward recommendation chain for member ID 1: that is, the members they recommended, the members those members recommended, and so on. Return member ID and name, and order by ascending member id.

query <- "WITH RECURSIVE RECOMMENDEDS(memid) AS (
            SELECT memid FROM cd_members WHERE recommendedby = 1
            UNION ALL
            SELECT mems.memid
                FROM RECOMMENDEDS RECS
                INNER JOIN cd_members mems
                    ON mems.recommendedby = RECS.memid
          )
          SELECT RECS.memid, mems.firstname, mems.surname
            FROM RECOMMENDEDS RECS
            INNER JOIN cd_members mems
                ON RECS.memid = mems.memid
          ORDER BY memid;
          "

resultado <- dbSendQuery(con, query)

datos <- dbFetch(resultado)

dbClearResult(resultado) 

datatable(datos)

3. Produce a CTE that can return the upward recommendation chain for any member

Produce a CTE that can return the upward recommendation chain for any member. You should be able to select recommender from recommenders where member=x. Demonstrate it by getting the chains for members 12 and 22. Results table should have member and recommender, ordered by member ascending, recommender descending.

query <- "WITH RECURSIVE recommenders(recommender, member) AS (
            SELECT recommendedby, memid
                FROM cd_members
            UNION ALL
            SELECT mems.recommendedby, recs.member
                FROM recommenders recs
                INNER JOIN cd_members mems
                    ON mems.memid = recs.recommender
          )
          SELECT recs.member member, recs.recommender, mems.firstname, mems.surname
            FROM recommenders recs
            INNER JOIN cd_members mems      
                ON recs.recommender = mems.memid
            WHERE recs.member = 22 OR recs.member = 12
          ORDER BY recs.member ASC, recs.recommender DESC;"

resultado <- dbSendQuery(con, query)

datos <- dbFetch(resultado)

dbClearResult(resultado) 

datatable(datos)