Extraer valor de una base de datos exige dominar SELECT. Con esta sentencia en MySQL obtienes exactamente lo que necesitas: desde todas las columnas hasta combinaciones calculadas, aplicando condiciones, funciones y límites para convertir datos en decisiones rápidas.
SELECT en MySQL: filtra, limita y transforma datos con eficiencia
¿Cómo usar SELECT en MySQL para extraer datos clave?
Elegir bien qué columnas traer evita ruido y acelera resultados. Con SELECT puedes pedir todo con un asterisco o especificar solo lo necesario. Además, LIMIT al final del query te permite una vista rápida y controlada de los datos.
Usa SELECT * para una inspección general rápida.
Selecciona columnas puntuales para claridad: name, email, gender.
Aplica LIMIT al final para traer un subconjunto. Evita el desorden.
Combina con DESC clients para ver la estructura física de la tabla.
Ejemplos:
-- Todas las columnas.SELECT*FROM clients;-- Una y varias columnas.SELECT name FROM clients;SELECT name, email, gender FROM clients;-- Límite de filas.SELECT name, email, gender FROM clients LIMIT10;
Datos relevantes: la tabla tiene alrededor de cien tuplas y las respuestas fueron prácticamente en cero segundos, lo que ilustra la eficiencia de MySQL con queries bien planteados.
¿Qué condiciones y filtros optimizan tus consultas?
La cláusula WHERE concentra las condiciones. Con operadores de igualdad, LIKE y AND puedes refinar resultados sin traer datos innecesarios. LIKE utiliza el wildcard % para coincidencias parciales de texto.
WHERE filtra por género: 'M' o 'F'.
LIKE encuentra cadenas parciales: '%texto%'.
AND combina condiciones para mayor precisión.
Resultados observados: 48 hombres al filtrar gender = 'M'.
Ejemplos:
-- Filtro por género.SELECT*FROM clients WHERE gender ='M';SELECT*FROM clients WHERE gender ='F';-- Búsqueda textual con LIKE.SELECT*FROM clients WHERE name LIKE'%Saave%';-- Varias columnas con filtros combinados.SELECT name, email, gender
FROM clients
WHERE gender ='F'AND name LIKE'%Lop%';
Hallazgos prácticos: el filtro por 'Lop' en nombres femeninos devolvió dos clientas (por ejemplo, Juana María López y Carmen López), validando la utilidad de LIKE para búsquedas flexibles.
¿Qué funciones y trucos aceleran el análisis?
Las funciones integradas multiplican el poder de SELECT. YEAR y NOW permiten trabajar con fechas; con AS renombras columnas para una lectura clara. Además, usar LIMIT como vista previa ayuda a inspeccionar formatos (mayúsculas, espacios, URLs largas) antes de procesar masivamente.
YEAR(fecha) extrae el año de un campo DATE.
NOW() devuelve fecha y hora actuales del sistema.
Cálculo de edad aproximada: YEAR(NOW()) - YEAR(birthdate). "No necesariamente correcto", pero útil como estimación.
AS crea un alias legible para los resultados.
Truco de productividad: flecha hacia arriba para recuperar el último query en consola.
Ejemplos:
-- Inspección de fechas y extracción de año.SELECT birthdate FROM clients;SELECTYEAR(birthdate)FROM clients;-- Año actual.SELECTYEAR(NOW());-- Nombre + edad aproximada, con alias y límite de muestra.SELECT name,YEAR(NOW())-YEAR(birthdate)AS edad
FROM clients
LIMIT10;
Ideas clave para escalar: diseñar SELECT como "tablas dinámicas" te permite combinar columnas existentes con columnas calculadas solo para la consulta. Con millones de usuarios, la eficiencia depende de dos frentes complementarios: una base bien diseñada con índices lógicos y queries puntuales que eviten trabajo exhaustivo. Así obtienes respuestas en milisegundos incluso con grandes volúmenes.
¿Te gustaría ver más patrones de filtrado y funciones para enriquecer tus SELECT en MySQL? Comparte tus dudas o casos de uso y los resolvemos juntos.
Traer solo una columna especifica (en este caso la columna “name”):
SELECT name FROM clients;
Traer varias columnas especificas (en este caso la columna “name” y “gender”):
SELECT name, email, gender FROM clients;
Limitar el numero de resultados (en este caso maximo 10 resultados):
SELECT name, email, gender FROM clients LIMIT10;
Condicionar los resultados a una caracteristica (en este caso todos los resultados que tengan gender con el valor “M”):
SELECT name, email, gender FROM clients WHERE gender='M';
Utilizar funciones para obtener datos especificos (en este caso todas las Mujeres que en su nombre tengan la cadena “Lop”):
SELECT name, email,YEAR(NOW())-YEAR(birthdate)AS edad, gender
FROM clients
WHERE gender='F'AND name LIKE'%Lop%';
BUEN APORTE!!
Gracias bro!!
Resumen de la clase:
-- Listar todas la tuplas de la tabla clientsSELECT*FROM clients;-- Listar todos los nombres de la tabla clientsSELECT name FROM clients;-- Listar todos los nombres, email y género de la tabla clientsSELECT name, email, gender FROM clients;-- Listar los 10 primeros resultados de la tabla clientsSELECT name, email, gender FROM clients LIMIT10;-- Listar todos los clientes de género MasculinoSELECT name, email, gender FROM clients WHERE gender ='M';-- Listar el año de nacimientos de los clientes, con la función YEAR()SELECTYEAR(birthdate)FROM clients;-- Mostrar el año actualSELECTYEAR(NOW());-- Listar los 10 primeros resultados de las edades de los clientesSELECTYEAR(NOW())-YEAR(birthdate)FROM clients LIMIT10;-- Listar nombre y edad de los 10 primeros clientesSELECT name,YEAR(NOW())-YEAR(birthdate)FROM clients LIMIT10;-- Listar clientes que coincidan con el nombre de "Saave"SELECT*FROM clients WHERE name LIKE'%Saave%';-- Listar clientes (nombre, email, edad y género). con filtro de genero = F y nombre que coincida con 'Lop'--Usando alias para nombrar la función como 'edad'SELECT name, email,YEAR(NOW())-YEAR(birthdate)AS edad, gender FROM clients WHERE gender ='F'AND name LIKE'%Lop%';
te recomiendo no juntar los comandos. Así vas a poder evitar errores :)
Muy bien, comentar el código es muy buena practica
Existen una pautas para facilitar la formulación de un Query, o dicho de otra forma para traducir una consulta a lenguaje SQL:
Qué quiero mostrar: SELECT
De donde tomare los datos: FROM
Como voy a filtrar esa información: WHERE
Si deseo ordenarla, desde que rubro me voy a apoyar: ORDER BY
Los filtros que deseo tengan mis datos: HAVING, LIKE
Excelente aporte. Muchas gracias!
GRACIAS!!!
Para tener muy en cuenta ->
Al signo porcentaje (%) en MySQL, se le conoce como Wildcard y se utiliza para denotar "lo que sea", en una cadena de caracteres
Gracias.
Gracias, la verdad tenia esa duda.
Seria un bueno tener varias clases o hasta un curso de puras funciones SQL y su utilidad.
Si, eso seria genial, alguien sabe si existe?
Je je siempre quise saber de donde trae los datos...
Saludos desde el pasado!
Saludos desde el presente!
Saludos desde el futuro.
Creo que like no es una función sino un operador, como lo son =, < o <= entre otros.
bien dicho, es un operador.. buena acotación
Notas de clase 📚📚📚
--Creacion de base de datos
CREATEDATABASE platzi_operation;--Creacion de base de datos usando un condicional
CREATEDATABASEIFNOTEXISTS platzi_operation;--MostarWarningsSHOW warnings;--Mostar bases de datos
SHOWDATABASES--Utilizar una base de datos
USE platzi_operation;--Mostrar tablas
SHOWTABLES;--Como saber que base de datos estoy usando,RTA:SELECTDATABASE();--Borrar tabla
DROPTABLE books
--Mostar tablas
SHOWTABLES;--Describe los campos de la base de datos
DESCRIBE books
DESC authors
--Mostar todo el esquema de la tabla(Incluyendo los comentarios)SHOWFULLCOLUMNSFROM books;--CREACIONDELPROYECTO[LIBRERIA]--Buena practica:Usar el nombre de la tabla en plural
--Tabla de libros
CREATETABLEIFNOTEXISTSbooks( book_id INTUNSIGNEDPRIMARYKEYAUTO_INCREMENT, author_id INTUNSIGNED, title VARCHAR(100)NOTNULL,`year`INTUNSIGNEDNOTNULLDEFAULT1900, language VARCHAR(2)NOTNULLDEFAULT'es'COMMENT'ISO 639-1 Lenguage', cover_url VARCHAR(500), price DOUBLE(6,2)DEFAULT10.0, sellable TINYINT(1)DEFAULT1, copies INTNOTNULLDEFAULT1, description TEXT);--Tabla de autores
CREATETABLEIFNOTEXISTSauthors( author_id INTUNSIGNEDPRIMARYKEYAUTO_INCREMENT, name VARCHAR(100)NOTNULL, nationality VARCHAR(3));--Tabla de clientes
CREATETABLEIFNOTEXISTSclients( client_id INTUNSIGNEDPRIMARYKEYAUTO_INCREMENT,`name`VARCHAR(50)NOTNULL, email VARCHAR(100)NOTNULLUNIQUE, birthdate DATETIME, gender ENUM('M','F','ND')NOTNULL, active TINYINT(1)NOTNULLDEFAULT1, created_at TIMESTAMPNOTNULLDEFAULTCURRENT_TIMESTAMP, updated_at TIMESTAMPNOTNULLDEFAULTCURRENT_TIMESTAMPONUPDATECURRENT_TIMESTAMP);--Tabla de operaciones
CREATETABLEIFNOTEXISTSoperations( operation_id INTUNSIGNEDPRIMARYKEYAUTO_INCREMENT, book_id INTUNSIGNED, client_id INTUNSIGNED,`type`ENUM('prestado','devuelto','vendido'), created_at TIMESTAMPNOTNULLDEFAULTCURRENT_TIMESTAMP, updated_at TIMESTAMPNOTNULLDEFAULTCURRENT_TIMESTAMPONUPDATECURRENT_TIMESTAMP, finshed TINYINT(1)NOTNULL);--Inserccion de datos
--Relleno de autores
INSERTINTOauthors(author_id, name, nationality)VALUES(NULL,'Juan Rulfo','MEX');INSERTINTOauthors(name, nationality)VALUES('Gabriel Garcia Marquez','COL');INSERTINTO authors
VALUES(NULL,'Juan Gabriel Vazquez','COL');--Relleno con TRUCASOOOOOOO:CHUNCKS50NumMagicINSERTINTOauthors(name, nationality)VALUES('Julio Cortázar','ARG'),('Isabel Allende','CHI'),('Octavio Paz','MEX'),('Juan Carlos Onetti','URY');--LlavePerdidaINSERTINTOauthors(author_id, name)VALUES(16,'Pablo Neruda');--AutoresINSERTINTO`authors`(name, nationality)VALUES('Sam Altman','USA'),('Freddy Vega','COL'),('Arthur Conan Doyle','GBR'),('Chuck Palahniuk','USA'),('Juan Rulfo','MEX'),('Henning Mankel','SWE'),('Jaideva Goswami','USA'),('John Foreman','USA'),('Stephen Hawking','USA'),('Stephen Dubner','USA'),('Edward Said','USA'),('Vladimir Vapnik','RUS'),('V P Menon','IND'),('Leonard Mlodinow','USA'),('Frank Shih','JAP'),('Maria Konnikova','RUS'),('Sebastian Gutierrez','ESP'),('Kurt Vonnegut','USA'),('Cedric Villani','FRA'),('Gerald Sussman','USA'),('Abraham Eraly','IND'),('Frank Kafka','AUT'),('John Pratt','USA'),('Robert Nisbet','USA'),('H. G. Wells',"ENG"),('Werner Heisenberg','DEU'),('Andy Oram',NULL),('Terence Tao',"AUS"),('Drew Conway',"USA"),('Nate Silver',"USA"),('Wes McKinney',"USA"),('Thomas Cormen',"USA"),('Siddhartha Deb',"IND"),('Albert Camus',"FRA"),('Adam Smith',"ENG"),('Ken Follett',"ENG"),('Fritjof Capra',"AUT"),('Richard Feynman',"USA"),('Ernest Hemingway',"USA"),('Frederick Forsyth',"ENG"),('Jeffery Archer',"ENG"),('Randy Pausch',"USA"),('Ayn Rand',"RUS"),('Michael Crichton',"USA"),('John Steinbeck',"USA"),('Edgar Allen Poe',"USA"),('Will Durant',NULL),('P L Deshpande',NULL),('John Grisham',"USA"),('V. S. Naipaul',NULL),('Joseph Heller',NULL),('BBC',NULL),('Bob Dylan',"USA"),('Madan Gupta',"IND"),('Alfred Stonier',NULL),('W. H. Greene',NULL),('Gary Bradsky',NULL),('Andrew Tanenbaum',NULL),('David Forsyth',NULL),('Schilling Taub',NULL),('Yashwant Kanetkar',NULL),('Jonathan Stroud',NULL),('Fyodor Dostoevsky',"RUS"),('Dan Brown',"USA"),('Amartya Sen',NULL),('Amitav Ghosh',NULL),('Lorraine Hansberry',NULL),('Bob Woodward',NULL),('Kuldip Nayar',NULL),('Sunita Deshpande',NULL),('William Dalrymple',NULL),('Various',NULL),('Sanjay Garg',NULL),('V P Kale',NULL),('Shashi Tharoor',"IND"),('Dominique Lapierre',NULL),('Bertrand Russell',"ENG"),('Sam Harris',NULL),('Earle Stanley Gardner',NULL),('Peter Drucker',NULL),('David Bodanis',NULL),('Victor Hugo',"FRA"),('Richard Gordon',NULL),('George Orwell',NULL),('Lee Iacoca',"USA"),('William S Maugham',NULL),('Robert Pirsig',NULL),('Robert Fisk',NULL),('Amir Aczel',NULL),('Samuel Huntington',NULL),('Richard Bach',NULL),('Braithwaite',NULL),('V S Naipaul',NULL),('Jawaharlal Nehru',NULL),('Gerald Durrell',NULL),('Simon Singh',"ENG"),('Hart Duda',NULL),('Thomas Friedman',NULL),('Keith Devlin',NULL),('James Gleick',NULL),('Joy Thomas',NULL),('Muhammad Rashid',NULL),('Ned Mohan',NULL),('Simon Haykin',NULL),('Alex Rutherford',NULL),('Michael Baz-Zohar',NULL),('Jim Corbett',NULL),('Jules Verne',NULL),('Deshpande P L',NULL),('Eric Raymond',NULL),('Sergio Franco',NULL),('Allen Downey',NULL),('Morris West',NULL),('Phillip Janert',NULL),('Carl Sagan',"USA"),('E T Bell',NULL),('Richard Dawkins',NULL),('Sudhanshu Ranjan',"IND"),('Kautiyla',NULL),('Palkhivala',NULL),('Sorabjee',NULL),('Hussain Zaidi',NULL),('Peter Ackroyd',NULL),('Nariman',NULL),('Jean Sassoon',NULL),('Peter Dickinson',NULL),('Machiavelli',NULL),('Aldous Huxley',"ENG"),('J K Rowling',"ENG"),('Steig Larsson',"SWE"),('Steve Eddins',NULL),('Charles Dickens',"ENG");--Insercion de libros
INSERTINTO`books`VALUES(1,1,'The Startup Playbook',2013,'en',NULL,10.00,1,5,'Advice from the experts'),(2,1,'The Startup Playbook',2014,'es',NULL,10.00,1,5,'Consejo de los expertos, traducido por Platzi'),(3,3,'Estudio en escarlata',1887,'es',NULL,5.00,1,10,'La primera novela de Sherlock Holmes'),(4,6,'Wallander: Asesinos sin rostro',1991,'es',NULL,15.00,1,3,''),(5,6,'Wallander: Los perros de Riga',1992,'es',NULL,15.00,1,3,''),(6,6,'Wallander: La leona blanca',1993,'es',NULL,15.00,1,3,''),(7,6,'Wallander: El hombre sonriente',1994,'es',NULL,15.00,1,3,''),(8,6,'Wallander: La falsa pista',1995,'es',NULL,15.00,1,3,''),(9,6,'Wallander: La quinta mujer',1996,'es',NULL,15.00,1,3,''),(10,6,'Wallander: Pisando los talones',1997,'es',NULL,15.00,1,3,''),(11,6,'Wallander: Cortafuegos',1998,'es',NULL,15.00,1,3,''),(12,5,'El llano en llamas',1953,'es',NULL,10.00,0,1,'Cuentos mexicanos'),(13,7,'Fundamentals of Wavelets',1900,'en',NULL,NULL,1,4,NULL),(14,8,'Data Smart',1900,'en',NULL,NULL,1,4,NULL),(15,9,'God Created the Integers',1900,'en',NULL,NULL,1,4,NULL),(16,10,'Superfreakonomics',1900,'en',NULL,NULL,1,4,NULL),(17,11,'Orientalism',1900,'en',NULL,NULL,1,4,NULL),(18,12,'The Nature of Statistical Learning Theory',1900,'en',NULL,NULL,1,4,NULL),(19,13,'Integration of the Indian States',1900,'en',NULL,NULL,1,4,NULL),(20,14,'The Drunkard's Walk',1900,'en',NULL,NULL,1,4,NULL),(21,15,'Image Processing & Mathematical Morphology',1900,'en',NULL,NULL,1,4,NULL),(22,16,'How to Think Like Sherlock Holmes',1900,'en',NULL,NULL,1,4,NULL),(23,17,'Data Scientists at Work',1900,'en',NULL,NULL,1,4,NULL),(24,18,'Slaughterhouse Five',1900,'en',NULL,NULL,1,4,NULL),(25,19,'Birth of a Theorem',1900,'en',NULL,NULL,1,4,NULL),(26,20,'Structure & Interpretation of Computer Programs',1900,'en',NULL,NULL,1,4,NULL),(27,21,'The Age of Wrath',1900,'en',NULL,NULL,1,4,NULL),(28,22,'The Trial',1900,'en',NULL,NULL,1,4,NULL),(29,23,'Statistical Decision Theory',1900,'en',NULL,NULL,1,4,NULL),(30,24,'Data Mining Handbook',1900,'en',NULL,NULL,1,4,NULL),(31,25,'The New Machiavelli',1900,'en',NULL,NULL,1,4,NULL),(32,26,'Physics & Philosophy',1900,'en',NULL,NULL,1,4,NULL),(33,27,'Making Software',1900,'en',NULL,NULL,1,4,NULL),(34,28,'Vol I Analysis',1900,'en',NULL,NULL,1,4,NULL),(35,29,'Machine Learning for Hackers',1900,'en',NULL,NULL,1,4,NULL),(36,30,'The Signal and the Noise',1900,'en',NULL,NULL,1,4,NULL),(37,31,'Python for Data Analysis',1900,'en',NULL,NULL,1,4,NULL),(38,32,'Introduction to Algorithms',1900,'en',NULL,NULL,1,4,NULL),(39,33,'The Beautiful and the Damned',1900,'en',NULL,NULL,1,4,NULL),(40,34,'The Outsider',1900,'en',NULL,NULL,1,4,NULL),(41,3,'The - Vol I Complete Sherlock Holmes',1900,'en',NULL,NULL,1,4,NULL),(42,3,'The - Vol II Complete Sherlock Holmes',1900,'en',NULL,NULL,1,4,NULL),(43,37,'The Wealth of Nations',1900,'en',NULL,NULL,1,4,NULL),(44,38,'The Pillars of the Earth',1900,'en',NULL,NULL,1,4,NULL),(45,39,'The Tao of Physics',1900,'en',NULL,NULL,1,4,NULL),(46,40,'Surely You's re JokingMrFeynman',1900,'en',NULL,NULL,1,4,NULL),(47,41,'A Farewell to Arms',1900,'en',NULL,NULL,1,4,NULL),(48,42,'The Veteran',1900,'en',NULL,NULL,1,4,NULL),(49,43,'False Impressions',1900,'en',NULL,NULL,1,4,NULL),(50,44,'The Last Lecture',1900,'en',NULL,NULL,1,4,NULL),(51,45,'Return of the Primitive',1900,'en',NULL,NULL,1,4,NULL),(52,46,'Jurassic Park',1900,'en',NULL,NULL,1,4,NULL),(53,47,'A Russian Journal',1900,'en',NULL,NULL,1,4,NULL),(54,48,'Tales of Mystery and Imagination',1900,'en',NULL,NULL,1,4,NULL),(55,10,'Freakonomics',1900,'en',NULL,NULL,1,4,NULL),(56,39,'The Hidden Connections',1900,'en',NULL,NULL,1,4,NULL),(57,51,'The Story of Philosophy',1900,'en',NULL,NULL,1,4,NULL),(58,52,'Asami Asami',1900,'en',NULL,NULL,1,4,NULL),(59,47,'Journal of a Novel',1900,'en',NULL,NULL,1,4,NULL),(60,47,'Once There Was a War',1900,'en',NULL,NULL,1,4,NULL),(61,47,'The Moon is Down',1900,'en',NULL,NULL,1,4,NULL),(62,56,'The Brethren',1900,'en',NULL,NULL,1,4,NULL),(63,57,'In a Free State',1900,'en',NULL,NULL,1,4,NULL),(64,58,'Catch 22',1900,'en',NULL,NULL,1,4,NULL),(65,59,'The Complete Mastermind',1900,'en',NULL,NULL,1,4,NULL),(66,60,'Dylan on Dylan',1900,'en',NULL,NULL,1,4,NULL),(67,61,'Soft Computing & Intelligent Systems',1900,'en',NULL,NULL,1,4,NULL),(68,62,'Textbook of Economic Theory',1900,'en',NULL,NULL,1,4,NULL),(69,63,'Econometric Analysis',1900,'en',NULL,NULL,1,4,NULL),(70,64,'Learning OpenCV',1900,'en',NULL,NULL,1,4,NULL),(71,65,'Data Structures Using C & C++',1900,'en',NULL,NULL,1,4,NULL),(72,66,'A Modern Approach Computer Vision',1900,'en',NULL,NULL,1,4,NULL),(73,67,'Principles of Communication Systems',1900,'en',NULL,NULL,1,4,NULL),(74,68,'Let Us C',1900,'en',NULL,NULL,1,4,NULL),(75,69,'The Amulet of Samarkand',1900,'en',NULL,NULL,1,4,NULL),(76,70,'Crime and Punishment',1900,'en',NULL,NULL,1,4,NULL),(77,71,'Angels & Demons',1900,'en',NULL,NULL,1,4,NULL),(78,72,'The Argumentative Indian',1900,'en',NULL,NULL,1,4,NULL),(79,73,'Sea of Poppies',1900,'en',NULL,NULL,1,4,NULL),(80,72,'The Idea of Justice',1900,'en',NULL,NULL,1,4,NULL),(81,75,'A Raisin in the Sun',1900,'en',NULL,NULL,1,4,NULL),(82,76,'All the President's Men',1900,'en',NULL,NULL,1,4,NULL),(83,43,'A Prisoner of Birth',1900,'en',NULL,NULL,1,4,NULL),(84,78,'Scoop!',1900,'en',NULL,NULL,1,4,NULL),(85,79,'Ahe Manohar Tari',1900,'en',NULL,NULL,1,4,NULL),(86,80,'The Last Mughal',1900,'en',NULL,NULL,1,4,NULL),(87,81,'Vol 39 No. 1 Social Choice & Welfare',1900,'en',NULL,NULL,1,4,NULL),(88,52,'Radiowaril Bhashane & Shrutika',1900,'en',NULL,NULL,1,4,NULL),(89,52,'Gun Gayin Awadi',1900,'en',NULL,NULL,1,4,NULL),(90,52,'Aghal Paghal',1900,'en',NULL,NULL,1,4,NULL),(91,85,'Maqta-e-Ghalib',1900,'en',NULL,NULL,1,4,NULL),(92,86,'Manasa',1900,'en',NULL,NULL,1,4,NULL),(93,87,'India from Midnight to Milennium',1900,'en',NULL,NULL,1,4,NULL),(94,87,'The Great Indian Novel',1900,'en',NULL,NULL,1,4,NULL),(95,89,'O Jerusalem!',1900,'en',NULL,NULL,1,4,NULL),(96,89,'The City of Joy',1900,'en',NULL,NULL,1,4,NULL),(97,89,'Freedom at Midnight',1900,'en',NULL,NULL,1,4,NULL),(98,47,'The Winter of Our Discontent',1900,'en',NULL,NULL,1,4,NULL),(99,93,'On Education',1900,'en',NULL,NULL,1,4,NULL),(100,94,'Free Will',1900,'en',NULL,NULL,1,4,NULL),(101,87,'Bookless in Baghdad',1900,'en',NULL,NULL,1,4,NULL),(102,96,'The Case of the Lame Canary',1900,'en',NULL,NULL,1,4,NULL),(103,9,'The Theory of Everything',1900,'en',NULL,NULL,1,4,NULL),(104,98,'New Markets & Other Essays',1900,'en',NULL,NULL,1,4,NULL),(105,99,'Electric Universe',1900,'en',NULL,NULL,1,4,NULL),(106,100,'The Hunchback of Notre Dame',1900,'en',NULL,NULL,1,4,NULL),(107,47,'Burning Bright',1900,'en',NULL,NULL,1,4,NULL),(108,98,'The Age of Discontuinity',1900,'en',NULL,NULL,1,4,NULL),(109,103,'Doctor in the Nude',1900,'en',NULL,NULL,1,4,NULL),(110,104,'Down and Out in Paris & London',1900,'en',NULL,NULL,1,4,NULL),(111,72,'Identity & Violence',1900,'en',NULL,NULL,1,4,NULL),(112,80,'Beyond the Three Seas',1900,'en',NULL,NULL,1,4,NULL),(113,107,'Talking Straight',1900,'en',NULL,NULL,1,4,NULL),(114,108,'Vol 3 Maughams Collected Short Stories',1900,'en',NULL,NULL,1,4,NULL),(115,42,'The Phantom of Manhattan',1900,'en',NULL,NULL,1,4,NULL),(116,108,'Ashenden of The British Agent',1900,'en',NULL,NULL,1,4,NULL),(117,111,'Zen & The Art of Motorcycle Maintenance',1900,'en',NULL,NULL,1,4,NULL),(118,112,'The Great War for Civilization',1900,'en',NULL,NULL,1,4,NULL),(119,45,'We the Living',1900,'en',NULL,NULL,1,4,NULL),(120,114,'The Artist and the Mathematician',1900,'en',NULL,NULL,1,4,NULL),(121,93,'History of Western Philosophy',1900,'en',NULL,NULL,1,4,NULL),(122,72,'Rationality & Freedom',1900,'en',NULL,NULL,1,4,NULL),(123,117,'Clash of Civilizations and Remaking of the World Order',1900,'en',NULL,NULL,1,4,NULL),(124,39,'Uncommon Wisdom',1900,'en',NULL,NULL,1,4,NULL),(125,119,'One',1900,'en',NULL,NULL,1,4,NULL),(126,120,'To Sir With Love',1900,'en',NULL,NULL,1,4,NULL),(127,121,'Half A Life',1900,'en',NULL,NULL,1,4,NULL),(128,122,'The Discovery of India',1900,'en',NULL,NULL,1,4,NULL),(129,52,'Apulki',1900,'en',NULL,NULL,1,4,NULL),(130,93,'Unpopular Essays',1900,'en',NULL,NULL,1,4,NULL),(131,42,'The Deceiver',1900,'en',NULL,NULL,1,4,NULL),(132,76,'Veil: Secret Wars of the CIA',1900,'en',NULL,NULL,1,4,NULL),(133,52,'Char Shabda',1900,'en',NULL,NULL,1,4,NULL),(134,128,'Rosy is My Relative',1900,'en',NULL,NULL,1,4,NULL),(135,108,'The Moon and Sixpence',1900,'en',NULL,NULL,1,4,NULL),(136,130,'A Short History of the World',1900,'en',NULL,NULL,1,4,NULL),(137,108,'The Trembling of a Leaf',1900,'en',NULL,NULL,1,4,NULL),(138,103,'Doctor on the Brain',1900,'en',NULL,NULL,1,4,NULL),(139,133,'Simpsons & Their Mathematical Secrets',1900,'en',NULL,NULL,1,4,NULL),(140,134,'Pattern Classification',1900,'en',NULL,NULL,1,4,NULL),(141,135,'From Beirut to Jerusalem',1900,'en',NULL,NULL,1,4,NULL),(142,133,'The Code Book',1900,'en',NULL,NULL,1,4,NULL),(143,112,'The Age of the Warrior',1900,'en',NULL,NULL,1,4,NULL),(144,138,'The Numbers Behind Numb3rs',1900,'en',NULL,NULL,1,4,NULL),(145,47,'A Life in Letters',1900,'en',NULL,NULL,1,4,NULL),(146,140,'The Information',1900,'en',NULL,NULL,1,4,NULL),(147,141,'Elements of Information Theory',1900,'en',NULL,NULL,1,4,NULL),(148,142,'Power Electronics - Rashid',1900,'en',NULL,NULL,1,4,NULL),(149,143,'Power Electronics - Mohan',1900,'en',NULL,NULL,1,4,NULL),(150,144,'Neural Networks',1900,'en',NULL,NULL,1,4,NULL),(151,47,'The Grapes of Wrath',1900,'en',NULL,NULL,1,4,NULL),(152,52,'Vyakti ani Valli',1900,'en',NULL,NULL,1,4,NULL),(153,12,'Statistical Learning Theory',1900,'en',NULL,NULL,1,4,NULL),(154,148,'Empire of the Mughal - The Tainted Throne',1900,'en',NULL,NULL,1,4,NULL),(155,148,'Empire of the Mughal - Brothers at War',1900,'en',NULL,NULL,1,4,NULL),(156,148,'Empire of the Mughal - Ruler of the World',1900,'en',NULL,NULL,1,4,NULL),(157,148,'Empire of the Mughal - The Serpent's Tooth',1900,'en',NULL,NULL,1,4,NULL),(158,148,'Empire of the Mughal - Raiders from the North',1900,'en',NULL,NULL,1,4,NULL),(159,153,'Mossad',1900,'en',NULL,NULL,1,4,NULL),(160,154,'Jim Corbett Omnibus',1900,'en',NULL,NULL,1,4,NULL),(161,155,'20000 Leagues Under the Sea',1900,'en',NULL,NULL,1,4,NULL),(162,156,'Batatyachi Chal',1900,'en',NULL,NULL,1,4,NULL),(163,156,'Hafasavnuk',1900,'en',NULL,NULL,1,4,NULL),(164,156,'Urlasurla',1900,'en',NULL,NULL,1,4,NULL),(165,68,'Pointers in C',1900,'en',NULL,NULL,1,4,NULL),(166,160,'The Cathedral and the Bazaar',1900,'en',NULL,NULL,1,4,NULL),(167,161,'Design with OpAmps',1900,'en',NULL,NULL,1,4,NULL),(168,162,'Think Complexity',1900,'en',NULL,NULL,1,4,NULL),(169,163,'The Devil's Advocate',1900,'en',NULL,NULL,1,4,NULL),(170,45,'Ayn Rand Answers',1900,'en',NULL,NULL,1,4,NULL),(171,45,'Philosophy: Who Needs It',1900,'en',NULL,NULL,1,4,NULL),(172,166,'Data Analysis with Open Source Tools',1900,'en',NULL,NULL,1,4,NULL),(173,167,'Broca's Brain',1900,'en',NULL,NULL,1,4,NULL),(174,168,'Men of Mathematics',1900,'en',NULL,NULL,1,4,NULL),(175,169,'Oxford book of Modern Science Writing',1900,'en',NULL,NULL,1,4,NULL),(176,170,'Judiciary and Democracy Justice',1900,'en',NULL,NULL,1,4,NULL),(177,171,'The Arthashastra',1900,'en',NULL,NULL,1,4,NULL),(178,172,'We the People',1900,'en',NULL,NULL,1,4,NULL),(179,172,'We the Nation',1900,'en',NULL,NULL,1,4,NULL),(180,174,'The Courtroom Genius',1900,'en',NULL,NULL,1,4,NULL),(181,175,'Dongri to Dubai',1900,'en',NULL,NULL,1,4,NULL),(182,176,'Foundation History of England',1900,'en',NULL,NULL,1,4,NULL),(183,80,'City of Djinns',1900,'en',NULL,NULL,1,4,NULL),(184,178,'India's LegalSystem',1900,'en',NULL,NULL,1,4,NULL),(185,179,'More Tears to Cry',1900,'en',NULL,NULL,1,4,NULL),(186,180,'The Ropemaker',1900,'en',NULL,NULL,1,4,NULL),(188,182,'The Prince',1900,'en',NULL,NULL,1,4,NULL),(189,183,'Eyeless in Gaza',1900,'en',NULL,NULL,1,4,NULL),(190,184,'Tales of Beedle the Bard',1900,'en',NULL,NULL,1,4,NULL),(191,185,'Girl with the Dragon Tattoo',1900,'en',NULL,NULL,1,4,NULL),(192,185,'Girl who kicked the Hornet's Nest',1900,'en',NULL,NULL,1,4,NULL),(193,185,'Girl who played with Fire',1900,'en',NULL,NULL,1,4,NULL),(194,28,'Structure and Randomness',1900,'en',NULL,NULL,1,4,NULL),(195,189,'Image Processing with MATLAB',1900,'en',NULL,NULL,1,4,NULL),(196,104,'Animal Farm',1900,'en',NULL,NULL,1,4,NULL),(197,70,'The Idiot',1900,'en',NULL,NULL,1,4,NULL),(198,192,'A Christmas Carol',1900,'en',NULL,NULL,1,4,NULL);--Insercion de clientes
INSERTINTO`clients`(name, email, birthdate, gender, active)VALUES('Maria Dolores Gomez','Maria Dolores.95983222J@random.names','1971-06-06','F',1),('Adrian Fernandez','Adrian.55818851J@random.names','1970-04-09','M',1),('Maria Luisa Marin','Maria Luisa.83726282A@random.names','1957-07-30','F',1),('Pedro Sanchez','Pedro.78522059J@random.names','1992-01-31','M',1),('Pablo Saavedra','Pablo.93733268B@random.names','1960-07-21','M',1),('Marta Carrillo','Marta.55741882W@random.names','1981-06-15','F',1),('Javier Barrio','Javier.54966248C@random.names','1971-04-24','M',1),('Milagros Garcia','Milagros.90074144A@random.names','1964-12-05','F',1),('Carlos Quiros','Carlos.63291957M@random.names','1954-08-28','M',1),('Carmen De la Torre','Carmen.57408761W@random.names','1966-05-14','F',1),('Laura Moron','Laura.57774589S@random.names','1954-03-02','F',1),('Maria Dolores Larrea','Maria Dolores.71788005Z@random.names','1990-09-04','F',1),('Maria Dolores Sanz','Maria Dolores.30948169J@random.names','2001-08-30','F',1),('Jose Maria Bermudez','Jose Maria.24963969E@random.names','1998-05-23','M',1),('Carlos Blanco','Carlos.94783133H@random.names','1952-08-07','M',1),('Juan Carlos Jurado','Juan Carlos.71650477A@random.names','1990-12-12','M',1),('David Gonzalez','David.54332034P@random.names','1976-05-03','M',1),('Antonia Aranda','Antonia.91560262E@random.names','1979-10-25','F',1),('Maria Moreno','Maria.58935447V@random.names','1997-01-12','F',1),('David Casals','David.06746883V@random.names','1999-07-13','M',1),('Mario Romero','Mario.46091382A@random.names','1985-03-29','M',1),('Maria angeles Alba','Maria angeles.91808919A@random.names','1959-09-14','F',1),('Rafael Espinola','Rafael.67605541P@random.names','1998-10-11','M',1),('Montserrat alvarez','Montserrat.31114289G@random.names','1994-11-06','F',1),('Maria Carmen Gomez','Maria Carmen.64351051H@random.names','1968-06-30','F',1),('Maria Cruz Morillas','Maria Cruz.81385695B@random.names','1978-10-29','F',1),('Josefa Roldan','Josefa.51417560W@random.names','1993-08-09','F',1),('Monica Pla','Monica.18992324M@random.names','1972-06-08','F',1),('Juana Maria Lopez','Juana Maria.51072683X@random.names','1990-07-15','F',1),('Maria Carmen Ponce','Maria Carmen.41619980P@random.names','1984-07-26','F',1),('Juan Carlos Rios','Juan Carlos.45673504N@random.names','1967-05-04','M',1),('Isabel Alfaro','Isabel.77316882J@random.names','1980-07-25','F',1),('Maria Isabel Armas','Maria Isabel.42010289F@random.names','1950-11-21','F',1),('Maria Teresa Castillo','Maria Teresa.91228389Q@random.names','2002-11-08','F',1),('Andres Planells','Andres.09981449R@random.names','1992-06-19','M',1),('Silvia Perez','Silvia.91812407H@random.names','1969-02-15','F',1),('Pablo Gonzalez','Pablo.11605676Z@random.names','2000-10-11','M',1),('Maria Antonia Jimenez','Maria Antonia.98071058R@random.names','1998-06-23','F',1),('Jesus Rodriguez','Jesus.86679475L@random.names','1961-01-17','M',1),('Carmen Rodriguez','Carmen.81799536J@random.names','1973-02-17','F',1),('Maria Dolores Rodriguez','Maria Dolores.75444599E@random.names','1962-08-14','F',1),('Jordi Campos','Jordi.76000917Q@random.names','1956-09-23','M',1),('Carlos Caceres','Carlos.97628163V@random.names','1993-05-16','M',1),('Carmen Robles','Carmen.29258188A@random.names','1955-06-19','F',1),('Sara Rodriguez','Sara.16181250Z@random.names','2001-06-07','F',1),('Maria Carmen Rivera','Maria Carmen.59955426S@random.names','2000-05-27','F',1),('Alberto Cabanas','Alberto.40633755T@random.names','1991-10-27','M',1),('Jose Sanchez','Jose.52243847Z@random.names','1976-12-06','M',1),('Isabel Martinez','Isabel.90843261T@random.names','1962-07-01','F',1),('David Sanchez','David.14910073R@random.names','1975-05-18','M',1),('Sergio Sebastian','Sergio.09345984A@random.names','1959-08-30','M',1),('Manuel Cabrera','Manuel.38738750B@random.names','1993-08-23','M',1),('Marina Gabaldon','Marina.12101665P@random.names','1959-03-25','F',1),('Rafael Galvez','Rafael.87947175M@random.names','1988-09-02','M',1),('Francisco Villar','Francisco.13922268T@random.names','1952-04-25','M',1),('Francisco Garcia','Francisco.34242509V@random.names','1989-01-22','M',1),('Esther Pina','Esther.36300729J@random.names','1977-11-07','F',1),('Maria Jesus Noya','Maria Jesus.95839533M@random.names','1996-08-07','F',1),('Paula Ropero','Paula.53630073F@random.names','1998-09-04','F',1),('Maria Carmen Iglesias','Maria Carmen.24044144J@random.names','1977-06-12','F',1),('Albert Galvez','Albert.10067957Y@random.names','1971-05-17','M',1),('Carmen Lopez','Carmen.09399409E@random.names','1987-03-07','F',1),('Francisco Jose Leon','Francisco Jose.07598657D@random.names','1965-12-11','M',1),('Francisca Gonzalez','Francisca.19675393C@random.names','1957-12-23','F',1),('Daniel Garcia','Daniel.01386486T@random.names','1979-05-29','M',1),('Ana Maria Martinez','Ana Maria.91340418N@random.names','1980-09-14','F',1),('Maria Aguilar','Maria.41749884P@random.names','2000-07-31','F',1),('oscar Penas','oscar.31681177B@random.names','1981-10-02','M',1),('Adrian Vela','Adrian.66561884E@random.names','1978-12-10','M',1),('Francisco Alcalde','Francisco.52899588W@random.names','1967-03-11','M',1),('Maria Dolores Perez','Maria Dolores.47800073R@random.names','2003-11-10','F',1),('Juan Jose Tejada','Juan Jose.30429668R@random.names','1990-06-15','M',1),('Cristobal Nogues','Cristobal.01001763K@random.names','2003-10-01','M',1),('Maria Luisa Sanchez','Maria Luisa.91748033K@random.names','2000-02-03','F',1),('Adrian Orta','Adrian.11458937S@random.names','1952-03-20','M',1),('Maria Pilar Martin','Maria Pilar.93607154Y@random.names','1996-08-29','F',1),('Jesus Perez','Jesus.91931655B@random.names','1954-06-01','M',1),('Jesus Perez','Jesus.15757299E@random.names','1956-08-29','M',1),('Esther Capdevila','Esther.96440550D@random.names','1970-10-12','F',1),('David Nieves','David.40697907M@random.names','1965-04-02','M',1),('Antonia Giron','Antonia.32080105G@random.names','1983-01-22','F',1),('Juan Casero','Juan.94063877H@random.names','1974-06-29','M',1),('Manuel De Pablo','Manuel.01279669H@random.names','1973-03-23','M',1),('angel Palomo','angel.28890315S@random.names','1991-07-04','M',1),('Laura Herrera','Laura.98555932N@random.names','1966-12-12','F',1),('Maria Josefa Benitez','Maria Josefa.36743977M@random.names','1987-04-17','F',1),('Luis Saez','Luis.08103734Y@random.names','1983-03-28','M',1),('Susana Nevado','Susana.09442372K@random.names','1961-12-26','F',1),('Miguel Gomez','Miguel.01631964E@random.names','1965-05-16','M',1),('Julio Mayordomo','Julio.77582185B@random.names','1968-06-05','M',1),('Sonia Mari','Sonia.06246888L@random.names','1994-10-13','F',1),('Antonia Beltran','Antonia.96371304Q@random.names','1967-11-17','F',1),('Mercedes Perez','Mercedes.80944345P@random.names','1958-11-05','F',1),('Concepcion Velez','Concepcion.56896097P@random.names','1964-04-05','F',1),('Diego Correa','Diego.44862413Q@random.names','1999-09-15','M',1),('Juan Antonio Galan','Juan Antonio.95710220K@random.names','1982-11-20','M',1),('Manuel Cerezo','Manuel.25853412D@random.names','1991-03-12','M',1),('Rosa Maria Singh','Rosa Maria.41642169W@random.names','1956-12-31','F',1),('Angeles Mena','angeles.88859550Q@random.names','1987-09-22','F',1),('Jose Hidalgo','Jose.05903641R@random.names','1973-08-13','M',1);--Comando on duplicate
/* 🚫Nunca usa ON DUPLICATE KEY IGNORE ALL⛔
PROHIBIDISIMOOOOOOOOOOOOOOOOOOOO */INSERTINTOclients(name, email, birthdate, gender, active)VALUES('Royer G','royjuni3431@gmail.com','2002-02-16','M',0)ONDUPLICATEKEYIGNOREAll;INSERTINTOclients(name, email, birthdate, gender, active)VALUES('Royer G','royjuni3431@gmail.com','2002-02-16','M',0)ONDUPLICATEKEYUPDATE active =VALUES(active);--Truco para la presentacion de los datos \G(Mas legible)SELECT*FROM clients WHERE client_id =101\GSELECT*FROM clients\G--Queries anidados
/*
El laberinto de la Soledad, Octavio Paz, 1952
Vuelta al Laberinto de la Soledad, Octavio Paz, 1960
*/INSERTINTObooks(title, author_id)VALUES('El Laberinto de la Soledad',6)INSERTINTObooks(title, author_id, year)VALUES('Vuelda al Laberinto de la Soledad',(SELECT author_id FROM authors
WHERE name ='Octavio Paz'LIMIT1),1960);--Como realizar el shema y la insercion de la data desde un arrivo(s)--Creacion de esquema
/* bash $ mysql -u root -p < all_shema.sql */--Inserccion de datos
/* bash $ mysql -u root -p -D platzi_operation < all_data.sql */--Su majestad SELECT 👑 [TablasDinamicas-Temporales]SELECT*FROM clients;SELECT name FROM clients;SELECT name, email, gender FROM clients;--Limitando los resultados
SELECT name, email, gender FROM clients LIMIT10;--Condicionando la consulta
SELECT name, email, gender FROM clients WHERE gender ='M';SELECT birthdate FROM clients;--Usando funciones de MysqlSELECTYEAR(birthdate)FROM clients;SELECT name,YEAR(NOW())-YEAR(birthdate)FROM clients LIMIT10;--Condicionando con LIKESELECT*FROM clients WHERE name LIKE'%Saave%';--Consutas mas complejas
SELECT name, email,YEAR(NOW())-YEAR(birthdate)AS'edad', gender FROM clients WHERE gender ='F'AND name LIKE'%Lop%';--Extraer la hora de mi pc usando MYSQLSELECTNOW();SELECTNOW(YEAR());
Como necesito limpiar pantalla en el cmd!!!ja
En cmd se utiliza el comando **cls ** y en ubuntu el comando **clear **
utiliza: control + L
QUERY que imprime el name, email y client_id de los clientes menores de edad:
SELECT client_id, name, email,YEAR(NOW())-YEAR(birthdate)as age
FROM clients
WHEREYEAR(NOW())-YEAR(birthdate)<18;```
¡Saludos, 7 años después!🚀🖐
ya con mysql 8
Conceptos introducidos en clase: SELECT: la herramientas mas importante de SQL pues con el logramos extraer los datos. WHERE: agrega condicionantes a nuestro SELECT para traer datos mas especificos. LIKE: busca coincidencias de texto. FUNCIONES: realizan tareas ya programadas y muy puntuales. LIMIT n: Trae un n numero limite de coincidencias de nuestro select de forma aleatorea.
Calculando una lista de 10 registros con los usuarios que son menores de edad.
mmm… El alias no funciona para eso. Para ello debes escribir explicitamente el campo o calculo que quieras verificar
Comprendido.
SELECT name, email, gender FROM clients WHERE gender ='f';SELECT birthdate FROM clients WHERE gender ='f';SELECTYEAR(birthdate)FROM clients WHERE gender ='f';SELECTNOW(),YEAR(birthdate)FROM clients WHERE gender ='f';SELECTYEAR(NOW()),YEAR(birthdate)FROM clients WHERE gender ='f';SELECTYEAR(NOW())-YEAR(birthdate)ASEDADFROM clients WHERE gender ='f';SELECT name,YEAR(NOW())-YEAR(birthdate)ASEDADFROM clients WHERE gender ='f'LIMIT10;SELECT name,YEAR(NOW())-YEAR(birthdate)ASEDAD, birthdate FROM clients WHERE name LIKE'%saave%';SELECT name,email,YEAR(NOW())-YEAR(birthdate)ASEDAD, birthdate, gender FROM clients WHERE gender ='F' and name LIKE'%lop%';
Lenguaje DML
Lenguaje de manipulación de datos proporcionado por los sistemas gestores de base de datos que permite tareas de consultas o modificación de datos.
Select
select *from table where field ='value';
Insert
insert into table(field1, field2)values(value1, value2);
Update
udate table field ='value to modify' where field = value;
Delete
deletefrom table where field = value;
Con select lo que se hace es crear tablas temporales que se mostrarán en un momento dado selecciona todos los campos de clientes.
Select es la herramienta que se utiliza para sacar los datos de las tablas y convertir en esos datos en información.
Traer toda la información de la tabla no es necesariamente útil, es muy poco probable que sólo una tabla contenga toda la información que requerimos para contestar a ciertas preguntas que nos exige el modelo de negocios.
Realizar un DESC name_tabla nos da una noción como es la estructura de la tablas y después realizar un SELECT * FROM name_tabla LIMIT 10 nos da una noción de cómo se guardan los datos. Esto es muy funcional cuando la bases de datos no la hemos construido nosotros.
la esencia del SELECT lo es crear tablas temporales que se mostrarán en un momento dado con todos los campos que deseamos mostrar.
A summary of SQL and the structure of and SQL Statement.
SQL: Structured Query Language. It´s a language used to access and manipulate data stored in tables. Each table contains columns for the different fields, and rows for the diferrent records.
Structure of an SQL statement:
SQL statement is composed of an ordener list of clauses such as SELECT, FROM, WHERE, etc. And must always end with a semicolon (;)
Select all data in a table
SELECT*FROM employees;
Select specific columns
SELECT name, age
FROM students;
Select without duplicate rows
SELECTDISTINCT name
FROM students;
Sort rows
SELECT name, age
FROM friends
ORDERBY name, age DESC;-- ASC is the default
The statement above displays names and ages of friends sorted alphabetically by name in ascending order and when two friends share the same name, the rows are sorted by age in descending order.
Limit the number of rows
SELECT name, grade
FROM course_grades
ORDERBY grade DESCLIMIT5;
Filter rows
SELECT product
FROM inventory
WHERE code ='ABC123';
The WHERE clause states a conditions to hlod true for all the rows to be returned. The query above will only sjow the products whose code is ABC123.
Conditions: numeric comparison
SELECT product
FROM inventory
WHERE amount <=10;
Columns or fields that contain numeric values can be used in conditions with math comparison operators such as:
=, <, <=, >=, <>
Conditions: string comparison
SELECT productName
FROM inventory
WHERE productName <'B';
The query above shows all products whose name will star with the letter A (name comes before 'B' in dictionary oder)
Note that string values in the condition should be put between single quotes. Also note that any uppercase letter is smaller any lovercase letter.
Conditions: list possible values
SELECT product
FROM inventory
WHERE amount IN(1,5,10);
If a columns can contain one of several possible values, you can filter them by using the IN o NOT IN operators.
The query above shows all product that have either 1,5 or 10 units left in the inventory.
Condition: inclusive ranges
SELECT product
FROM inventory
WHERE amount BETWEEN5AND9;
To math rows with values within a fiven range, use BETWEEN operator. It works for numbers, strings, dates and time stamps.
To match rows with values outside of a given range, use NOT BETWEEN.
-- This expressionamount BETWEEN5AND9-- is esquivalent to this oneamount >=5AND amount <=9
Conditions: combining with AND
SELECT product
FROM inventory
WHERE amount <5AND price >1;
Conditions: Combining with OR
SELECT product
FROM inventory
WHERE amount <5OR price >1;
Conditions: mixing AND and OR
SELECT product
FROM inventory
WHERE amount <5OR name ='paper'AND price >1;
When using both AND and OR. It´s important to know that AND has higher precedence. That means that like in maths where multiplication is evaluated before addition, the AND will be evaluated before the OR.
The query above mathces all products that are named paper whose price is algo higher than 1. In addition to products that have more than 5 units left in the inventory.
If we want the OR to be evaluated first, we can use brackets().
SELECT product
FROM inventory
WHERE(amount <5OR name ='paper')AND price >1;
This query will matches all products that have more than 5 units or named paper, and in both cases the price has to be higher than 1.
¿Que pasa con los datos que se generan con el nuevo query, como la edad? donde se almacenan?
El SELECT sirve para realizar consultas de datos de las tablas en la base de datos. Se crea una tabla, pero existe por el instante en el que se muestra. No se almacena.
Como dice kevin, te muestra la info, Ahora que si quieres almacenarlos depende donde lo uses en la terminal puedes mandar tu salida a un archivo, en un visual lo puedes capturar o mandar a excel, en una aplicación tu decides como guardar o usar la información.
Saludos desde el pasado jajajajajaja!!! me encanta su estilo.