시간관리의 실패로 퀄리티있는 학습을 못 한 것 같습니다. 과제 제출 시간 이후에 복습하며 다시 꼼꼼하게 살피겠습니다!

ARRAY, STRUCT

CREATE OR REPLACE TABLE advanced.array_exercises AS SELECT movie_id, title, actors, genres
FROM (
SELECT
1 AS movie_id,
'Avengers: Endgame' AS title, ARRAY<STRUCT<actor STRING, character STRING>>[
STRUCT('Robert Downey Jr.', 'Tony Stark'),
STRUCT('Chris Evans', 'Steve Rogers')
] AS actors,
ARRAY<STRING>['Action', 'Adventure', 'Drama'] AS genres
UNION ALL SELECT
2,
'Inception',
ARRAY<STRUCT<actor STRING, character STRING>>[
STRUCT('Leonardo DiCaprio', 'Cobb'),
STRUCT('Joseph Gordon-Levitt', 'Arthur') ],
ARRAY<STRING>['Action', 'Adventure', 'Sci-Fi'] UNION ALL
SELECT
3,
'The Dark Knight',
ARRAY<STRUCT<actor STRING, character STRING>>[
STRUCT('Christian Bale', 'Bruce Wayne'),
STRUCT('Heath Ledger', 'Joker') ],
ARRAY<STRING>['Action', 'Crime', 'Drama'] )

1. array_exercises 테이블에서 각 영화(title)별로 장르(genres)를 UNNEST해서 보여주세요.

SELECT 
	title, 
	genre
FROM `advanced.array_exercises`
CROSS JOIN UNNEST(genres) AS genre

1. array_exercises 테이블에서 각 영화(title)별로 배우(actor)와 배역(character)을 보여주세요. 배우와 배역은 별도의 컬럼으로 나와야 합니다.

SELECT
  title, actor.actor, actor.character
FROM `advanced.array_exercises`, 
UNNEST(actors) as actor

1. array_exercises 테이블에서 각 영화(title)별로 배우(actor), 배역(character), 장르 (genre)를 출력하세요. 한 Row에 배우, 배역, 장르가 모두 표시되어야 합니다.

SELECT
  title,
  actor.actor AS actor,
  actor.character AS character,
  genre
FROM advanced.array_exercises
CROSS JOIN UNNEST(actors) AS actor
CROSS JOIN UNNEST(genres) AS genre

1. 앱 로그 데이터(app_logs)의 배열을 풀어주세요.

SELECT
  event_timestamp,
  event_name,
  event_param.key AS key,
  event_param.value.string_value AS string_value,
  event_param.value.int_value AS int_value,
  user_id
FROM `advanced.app_logs`
CROSS JOIN UNNEST(event_params) AS event_param

PIVOT

1. orders 테이블에서 유저(user_id)별로 주문 금액(amount)의 합계를 PIVOT해주세요. 날짜(order_date)를 행(Row)으로, user_id를 열(Column)으로 만들어야 합니다.

SELECT
  order_date,
  SUM(IF(user_id = 1, amount, 0)) AS user_1,
  SUM(IF(user_id = 2, amount, 0)) AS user_2,
  SUM(IF(user_id = 3, amount, 0)) AS user_3,
FROM `advanced.orders`

GROUP BY order_date
ORDER BY order_date

1. orders 테이블에서 날짜(order_date)별로 유저들의 주문 금액(amount)의 합계를 PIVOT 해주세요. user_id를 행(Row)으로, order_date를 열(Column)으로 만들어야 합니다.

SELECT
  user_id,
  MAX(IF(order_date = "2023-05-01", amount, 0)) AS `2023-05-01`,
  MAX(IF(order_date = "2023-05-02", amount, 0)) AS `2023-05-02`,
  MAX(IF(order_date = "2023-05-03", amount, 0)) AS `2023-05-03`,
  MAX(IF(order_date = "2023-05-04", amount, 0)) AS `2023-05-04`,
  MAX(IF(order_date = "2023-05-05", amount, 0)) AS `2023-05-05`
FROM `advanced.orders`
GROUP BY user_id
ORDER BY user_id

1. orders 테이블에서 사용자(user_id)별, 날짜(order_date)별로 주문이 있다면 1, 없다면 0으로 PIVOT 해주세요. user_id를 행(Row)으로, order_date를 열(Column)로 만들고 주문을 많이 해도 1로 처리합니다.

SELECT
  user_id,
  SUM(IF(order_date = "2023-05-01", amount, 0)) AS `2023-05-01`,
  SUM(IF(order_date = "2023-05-02", amount, 0)) AS `2023-05-02`,
  SUM(IF(order_date = "2023-05-03", amount, 0)) AS `2023-05-03`,
  SUM(IF(order_date = "2023-05-04", amount, 0)) AS `2023-05-04`,
  SUM(IF(order_date = "2023-05-05", amount, 0)) AS `2023-05-05`
FROM `advanced.orders`
GROUP BY user_id

1. 앱 로그 PIVOT

WITH base AS (
  SELECT
    event_date,
    event_timestamp,
    event_name,
    user_id,
    user_pseudo_id,
    MAX(IF(param.key = "firebase_screen", param.value.string_value, NULL)) AS firebase_screen,
    MAX(IF(param.key = "sesstion_id", param.value.string_value, NULL)) AS sesstion_id
  FROM `advanced.app_logs`
  CROSS JOIN UNNEST(event_params) AS param
  WHERE event_date = "2022-08-01"
  GROUP BY ALL
)

SELECT
  event_date,
  COUNT(user_id) AS user_cnt
FROM base
WHERE
  event_name = "click_cart"
GROUP BY event_date

Funnel

WITH base AS (
  SELECT
    event_date,
    event_timestamp,
    event_name,
    user_id,
    user_pseudo_id,
    platform,
    MAX(IF(event_param.key = "firebase_screen", event_param.value.string_value, NULL)) AS firebase_screen,
    MAX(IF(event_param.key = "session_id", event_param.value.string_value, NULL)) AS session_id
  FROM advanced.app_logs
  CROSS JOIN UNNEST(event_params) AS event_param
  WHERE
    event_date BETWEEN "2022-08-01" AND "2022-08-18"
  GROUP BY ALL
), filter_event_and_concat_event_and_screen AS (
  SELECT
    * EXCEPT(event_name, firebase_screen, event_timestamp),
    CONCAT(event_name, "-", firebase_screen) AS event_name_with_screen,
    DATETIME(TIMESTAMP_MICROS(event_timestamp), 'Asia/Seoul') AS event_datetime
  FROM base
  WHERE
    event_name IN ("screen_view", "click_payment")
)

SELECT
  event_date,
  event_name_with_screen,
  CASE 
    WHEN event_name_with_screen = "screen_view-welcome" THEN 1
    WHEN event_name_with_screen = "screen_view-home" THEN 2
    WHEN event_name_with_screen = "screen_view-food_category" THEN 3
    WHEN event_name_with_screen = "screen_view-restaurant" THEN 4
    WHEN event_name_with_screen = "screen_view-cart" THEN 5
    WHEN event_name_with_screen = "click_payment-cart" THEN 6
  ELSE NULL
  END AS step_number,
  COUNT(DISTINCT user_pseudo_id) AS cnt
FROM filter_event_and_concat_event_and_screen
GROUP BY ALL
HAVING step_number IS NOT NULL