- SQL 학습 과정 중 4주차에 '재밌다'고 느낀다.
- '반복적' 학습이 핵심 !
나의 중장기 목표 '창업'에 있어서 SQL은 필수적 !
- 방대한 양의 데이터베이스를 다룰 수 있다.
노션 링크- C (Create): 데이터의 생성을 의미합니다
- R (Read): 저장된 데이터를 읽어오는 것을 의미해요
- U (Update): 저장된 데이터를 변경!
- D (Delete): 저장된 데이터를 삭제하는 것을 의미해요
'Connect to a database' (플러그 모양 클릭)
'MySQL' 클릭 후 '다음'
Server Host : -----(비공개)
Database : sparta
Username : ----
Password : ----
SHOW tables; #테이블 보기
SELECT * from orders
SELECT order_no, created_at, user_id, email from orders
# orders 테이블에서 결제수단이 카카오페이인 데이터만 가져와줘!
SELECT * from orders
WHERE payment_method = 'kakaopay'
# point_users 테이블에서 포인트가 5000점 이상인 데이터만 가져와줘!
SELECT * from point_users
WHERE point >= 5000
# orders 테이블에서 주문한 강의가 앱개발 종합반이면서, 결제수단이 카드인 데이터만 가져와줘!
SELECT * from orders
WHERE course_title = '앱개발 종합반' and payment_method = 'CARD'
SELECT * FROM point_users
WHERE `point` > 20000;
SELECT * FROM users
WHERE name = '황**'
SELECT * FROM orders
WHERE course_title = '웹개발 종합반' and payment_method = 'CARD';
SELECT * FROM orders
WHERE course_title != '웹개발 종합반'
SELECT * FROM orders
WHERE created_at BETWEEN '2020-07-13' and '2020-07-15'
SELECT * FROM checkins
WHERE week in (1,3)
SELECT * FROM users
# 앞에 뭐가 들어가든 뒤에 daum.net 로 끝나는 것 !
WHERE email like '%daum.net'
# a로 시작해서 t 로 끝나는 것 !
WHERE email like 'a%t'
SELECT * from orders
WHERE payment_method != 'CARD'
SELECT * from point_users
WHERE point BETWEEN 20000 and 30000
SELECT * from users
WHERE email LIKE 's%com'
SELECT * from users
WHERE email LIKE 's%com' and name = '이**'
SELECT * from orders
WHERE payment_method = 'kakaopay'
limit 5;
SELECT DISTINCT payment_method from orders
SELECT count(*) from orders # 286개
WHERE payment_method = 'kakaopay' # 56개
SELECT COUNT(DISTINCT (name)) FROM users # 54개
SELECT * FROM users
WHERE name = '남**'
SELECT * FROM users
WHERE updated_at BETWEEN '2020-07-12' and '2020-07-14'
and email LIKE '%gmail.com'
SELECT COUNT(*) FROM users
WHERE updated_at BETWEEN '2020-07-12' and '2020-07-14'
and email LIKE '%gmail.com';
SELECT * FROM orders
WHERE course_title LIKE '웹개발%'
and payment_method = 'kakaopay' and email LIKE '%naver.com'