1. ARRAY, STRUCT 연습문제문제 1) array_exercise테이블에서 각 영화(title)별로 장르(genres)를 UNNEST 해서 보여주세요SELECT title, genres FROM `analystic-project.advanced.array_exercises` , UNNEST(genres) AS genres ;문제 2) array_exercises 테이블에서 각 영화(title)별로 배우(actor)와 배역(character)을 보여주세요. 배우와 배역은 별도의 컬럼으로 나와야합니다SELECT title, actors.actor, actors.character FROM `analystic-project.advanced.array_exercises` , UNNEST(actors) AS actors ;문제 3) 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, actors.actor, actors.character, genres FROM `analystic-project.advanced.array_exercises` , UNNEST(actors) AS actors, UNNEST(genres) genres ;문제 4) 앱 로그 데이터(app_logs) 배열 풀기SELECT user_id, event_date, event_name, user_pseudo_id, pr.key, pr.value.string_value, pr.value.int_value FROM `analystic-project.advanced.app_logs` , UNNEST(event_params) AS pr WHERE event_date = "2022-08-01" LIMIT 1000 ;2. PIVOT 연습문제 풀이문제 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 합니다SELECT order_date, COALESCE(SUM(IF(user_id = 1, amount, null)),0) AS user_1, COALESCE(SUM(IF(user_id = 2, amount, null)),0) AS user_2, COALESCE(SUM(IF(user_id = 3, amount, null)),0) AS user_3 FROM advanced.orders GROUP BY order_date ORDER BY order_date ;문제 2) 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 합니다SELECT user_id, COALESCE(SUM(IF(order_date = '2023-05-01', amount, null)),0) AS `2023-05-01`, COALESCE(SUM(IF(order_date = '2023-05-02', amount, null)),0) AS `2023-05-02`, COALESCE(SUM(IF(order_date = '2023-05-03', amount, null)),0) AS `2023-05-03`, COALESCE(SUM(IF(order_date = '2023-05-04', amount, null)),0) AS `2023-05-04`, COALESCE(SUM(IF(order_date = '2023-05-05', amount, null)),0) AS `2023-05-05`, FROM advanced.orders GROUP BY user_id ORDER BY user_id ;문제 3) 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 처리합니다SELECT user_id, MAX(IF(order_date = '2023-05-01' AND order_id is not null, 1, 0)) AS `2023-05-01`, MAX(IF(order_date = '2023-05-02' AND order_id is not null, 1, 0)) AS `2023-05-02`, MAX(IF(order_date = '2023-05-03' AND order_id is not null, 1, 0)) AS `2023-05-03`, MAX(IF(order_date = '2023-05-04' AND order_id is not null, 1, 0)) AS `2023-05-04`, MAX(IF(order_date = '2023-05-05' AND order_id is not null, 1, 0)) AS `2023-05-05`, FROM advanced.orders GROUP BY user_id ORDER BY user_id ;문제 4)user_id = 32888이 카트 추가하기(click_cart)를 누를때 어떤 음식(food_id)을 담았나요?WITH app_order_raw AS ( SELECT user_id, event_date, event_name, user_pseudo_id, pr.key, pr.value.string_value, pr.value.int_value FROM advanced.app_logs, UNNEST(event_params) AS pr WHERE event_date = '2022-08-01' ) SELECT user_id, event_date, event_name, user_pseudo_id, MAX(IF(key = 'firebase_screen', string_value, null)) AS firebase_screen, MAX(IF(key = 'food_id', int_value, null)) AS food_id, MAX(IF(key = 'session_id', string_value, null)) AS session_id, FROM app_order_raw GROUP BY user_id, event_date, event_name, user_pseudo_id ;3. 퍼널분석문제 1) 각 퍼널의 유저 수를 집계 / 데이터 기준: 2022-08-01 ~ 2022-08-18WITH funnel_data_raw AS ( SELECT event_date, event_timestamp, event_name, user_id, user_pseudo_id, MAX(IF(pr.key = 'firebase_screen', pr.value.string_value, null)) AS screen_name, CONCAT(event_name, '-', MAX(IF(pr.key = 'firebase_screen', pr.value.string_value, null))) AS event_name_with_screen FROM advanced.app_logs, UNNEST(event_params) AS pr WHERE event_date BETWEEN '2022-08-01' AND '2022-08-18' GROUP BY 1,2,3,4,5 ) SELECT 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 END AS step_number, COUNT(DISTINCT user_pseudo_id) AS cnt FROM funnel_data_raw WHERE event_name IN ('screen_view', 'click_payment') AND screen_name IN ('welcome', 'home', 'food_category', 'restaurant', 'cart') GROUP BY 1,2 ORDER BY 2 ;문제 2) 일자별 퍼널 유저 수 집계 WITH funnel_data_raw AS ( SELECT event_date, event_timestamp, event_name, user_id, user_pseudo_id, MAX(IF(pr.key = 'firebase_screen', pr.value.string_value, null)) AS screen_name, CONCAT(event_name, '-', MAX(IF(pr.key = 'firebase_screen', pr.value.string_value, null))) AS event_name_with_screen FROM advanced.app_logs, UNNEST(event_params) AS pr WHERE event_date BETWEEN '2022-08-01' AND '2022-08-18' GROUP BY 1,2,3,4,5 ) 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 END AS step_number, COUNT(DISTINCT user_pseudo_id) AS cnt FROM funnel_data_raw WHERE event_name IN ('screen_view', 'click_payment') AND screen_name IN ('welcome', 'home', 'food_category', 'restaurant', 'cart') GROUP BY 1,2,3 ORDER BY 1,3 ;문제 3) 일자별 퍼널 유저 수 집계형태를 PIVOT형태로 전환하기WITH funnel_data_raw AS ( SELECT event_date, event_timestamp, event_name, user_id, user_pseudo_id, MAX(IF(pr.key = 'firebase_screen', pr.value.string_value, null)) AS screen_name, CONCAT(event_name, '-', MAX(IF(pr.key = 'firebase_screen', pr.value.string_value, null))) AS event_name_with_screen FROM advanced.app_logs, UNNEST(event_params) AS pr WHERE event_date BETWEEN '2022-08-01' AND '2022-08-18' GROUP BY 1,2,3,4,5 ), daily_funnel_user_count as ( 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 END AS step_number, COUNT(DISTINCT user_pseudo_id) AS cnt FROM funnel_data_raw WHERE event_name IN ('screen_view', 'click_payment') AND screen_name IN ('welcome', 'home', 'food_category', 'restaurant', 'cart') GROUP BY 1,2,3 ORDER BY 1,3 ) SELECT event_date, MAX(IF(step_number = 1, cnt, null)) AS `screen_view-welcome`, MAX(IF(step_number = 2, cnt, null)) AS `screen_view-home`, MAX(IF(step_number = 3, cnt, null)) AS `screen_view-food_category`, MAX(IF(step_number = 4, cnt, null)) AS `screen_view-restaurant`, MAX(IF(step_number = 5, cnt, null)) AS `screen_view-cart`, MAX(IF(step_number = 6, cnt, null)) AS `click_payment-cart`, FROM daily_funnel_user_count GROUP BY ALL ORDER BY 1 ;

<목차>이번주차 중요 키워드 ARRAY, STRUCT 연습문제 1~4 추가 인사이트 PIVOT 연습문제 1~4퍼널분석 연습문제 1주차 느낀점 및 하고싶은 말 (솔직후기) 🔐 이번주차 중요 키워드 : ARRAY(배열), STRUCT(구조체),pivot, 퍼널분석 ✅ ARRAY, STRUCT 연습문제 1<INPUT> advanced.array_exercises<OUTPUT> title | genre## 1) array_exercises 테이블에서 각 영화(title)별로 장르(genres)을 UNNEST해서 보여주세요. SELECT title, genre FROM advanced.array_exercises AS ae CROSS JOIN UNNEST (genres) AS genre  📊 추가 인사이트 정리Q. 어느 genre에서 가장 많은 영화가 있을까?A. action에서 가장 많은 영화가 있군, 나도 action 좋아하는데 2024년 베놈(venom)2 보러가야징 ㅎ ✅ ARRAY, STRUCT 연습문제 2<INPUT> 위와 동일한 데이터 셋 advanced.array_exercises<OUTPUT> title | actor | character## 2) 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 AS ae CROSS JOIN UNNEST (actors) as actor # actors = [STRUCT(STRING,STRING)], array 형태이므로 SAFE_OFFSET으로 직접 데이터에 접근해도 # 되지만, 새로운 컬럼으로 만들어지기 때문에 long format이 아니라 wide format으로 테이블이 만들어진다. actors[SAFE_OFFSET(0)].actor AS first_actor actors[SAFE_OFFSET(1)].character AS second_character   ✅ ARRAY, STRUCT 연습문제 3<INPUT> 위와 동일한 데이터 셋 advanced.array_exercises<OUTPUT> title | actor | character | genre### 3) array_exercises 테이블에서 각 영화(title)별로 배우(actor), 배역(character), 장르(genre)를 출력하세요. SELECT title, actor.actor as actor, actor.character as character, genre FROM advanced.array_exercises as ae cross join unnest(actors) as actor cross join unnest(genres) as genre ✅ ARRAY, STRUCT 연습문제 4<INPUT> 위와 동일한 데이터 셋 advanced.array_exercises <OUTPUT> user_id | event_date | event_timestamp | event_name | key | string_value | int_value | user_id_1 | user_id_2 | user_id ### 4) 앱 로그 데이터 풀어주세요. # 데이터 - 미리보기 - event_params의 데이터 유형 RECORD = STRUCT WITH app_log AS ( select user_id, event_date, event_timestamp, event_name, event_param.key as key, -- event_param.value as value, event_param.value.string_value as string_value, event_param.value.int_value as int_value -- event_params, from advanced.app_logs cross join unnest(event_params) as event_param where event_date = '2022-08-01' ) <추가 인사이트 코드 추가> select event_date, event_name, COUNT(DISTINCT user_id) as cnt from app_log GROUP BY ALL ORDER BY cnt DESC SELECT event_date, event_name, cnt, LAG(cnt) OVER (ORDER BY cnt DESC) as before_event_cnt, ROUND(1 - (cnt / LAG(cnt) OVER (ORDER BY cnt DESC)),2) as churn_rate FROM ( select event_date, event_name, COUNT(DISTINCT user_id) as cnt from app_log GROUP BY ALL ) ORDER BY cnt DESC 📊 추가 인사이트 정리 Q. 어디 event에서 가장 많이 이탈하고 있는지? 파악해주세요. A. 퍼널단계가 다음 표와 같은 순서이고, 데이터 정합성이 있다고 가정하고, 1- 리텐션율 = 이탈율이라 했을때 churn rate은 아래 3가지 단계에서 이탈율이 가장 높음 → 추후 더 자세히 살펴볼 필요가 있음  (1) click_restaurant_nearby > click_login, (2) screen_view > click_food_category (3) click_restaurant > click_banner    ✅ Pivot 연습문제 1<INPUT> advanced.orders<OUTPUT> order_date, user_id_1, user_id_2, user_id_3 -- 1) orders 테이블에서 유저(user_id)별로 주문금액(amount)의 합계를 PIVOT 해주세요. -- 날짜(order_date)를 행(row)으로, user_id를 열(column)으로 만들어야 합니다. SELECT order_date, SUM(IF (user_id = 1, sum_of_amount,0)) as user_id_1, SUM(IF (user_id = 2, sum_of_amount,0)) as user_id_2, SUM(IF (user_id = 3, sum_of_amount,0)) as user_id_3 FROM ( SELECT order_date, user_id, SUM(amount) as sum_of_amount FROM advanced.orders GROUP BY order_date, user_id ) GROUP BY order_date ORDER BY order_date ✅ Pivot 연습문제 2 <INPUT> advanced.orders<OUTPUT> user_id | 2023-05-01 | 2023-05-02 | 2023-05-03 | 2023-05-04 | 2023-05-05-- 2) orders 테이블에서, 날짜(order_date)별로 유저들의 주문금액(amount)의 합계를 pivot 해주세요. user_id를 행(row)으로, order_date를 열(column)으로 만들어야 합니다. with tbl_2 as ( select user_id, order_date, sum(amount) as amount from advanced.orders group by all order by 1,2 ) # 이름 지정 오류 해결법 : column alias 지정할떄, 영어제외하고 날짜형 백틱(`)을 통해 지정할 수 있음 # MAX 대신 ANY_VALUE() 함수는 그룹화 할 대상 중 임의의 값을 선택하는 함수(null 제외) 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 tbl_2 group by all ✅ Pivot 연습문제 3  <INPUT> advanced.orders<OUTPUT> user_id | 2023-05-01 | 2023-05-02 | 2023-05-03 | 2023-05-04 | 2023-05-05--3 ) order 테이블에서 사용자(user_id)별, 날짜(order_date)별 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, MAX(if(order_date = "2023-05-01", 1,0)) as `2023-05-01`, MAX(if(order_date = "2023-05-02", 1,0)) as `2023-05-02`, MAX(if(order_date = "2023-05-03", 1,0)) as `2023-05-03`, MAX(if(order_date = "2023-05-04", 1,0)) as `2023-05-04`, MAX(if(order_date = "2023-05-05", 1,0)) as `2023-05-05` from tbl_2 group by user_id ✅ Pivot 연습문제 4  <INPUT> advanced.app_logs <OUTPUT> event_date | event_timestamp | event_name | user_id |user_pseudo_id | firebase_screen | food_id | session_id--4 ) 앱 로그 데이터 배열 PIVOT 하기 # 참고로 unique key는 user_id + event_timestamp select -- * EXCEPT(event_params) #except(컬럼) : 컬럼을 제외하고 모두 다 보여주는..! 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 = "food_id", param.value.int_value, null)) as food_id, max(if(param.key = "session_id", param.value.string_value,null)) as session_id from advanced.app_logs cross join unnest(event_params) as param where event_date = '2022-08-01' group by all limit 100  ✅ 퍼널 분석 (Funnel) 연습문제 <INPUT> advanced.app_logs <OUTPUT> event_date | event_name_firebase_screen | step_number | user_cnt -- 퍼널 단계 : welcome, home, food_category, restaurant, cart, click_payment -- event_name, firebase_screen 연결되어 해당 퍼널의 값 | step_number | cnt -- 기간 : 2022-08-01 ~ 2022-08-18 -- 사용할 데이터 : advanced.app_logs with unnest_tbl as ( select -- * EXCEPT(event_params) #except(컬럼) : 컬럼을 제외하고 모두 다 보여주는..! 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 = "food_id", param.value.int_value, null)) as food_id, max(if(param.key = "session_id", param.value.string_value,null)) as session_id from advanced.app_logs cross join unnest(event_params) as param where event_date BETWEEN '2022-08-01' AND "2022-08-18" group by all ) , filter as ( select * EXCEPT(event_name, firebase_screen, event_timestamp), concat(event_name, '-', firebase_screen) as event_name_firebase_screen , DATETIME(TIMESTAMP_MICROS(event_timestamp), 'Asia/Seoul') as event_time from unnest_tbl where event_name IN ("screen_view", "click_payment") ) SELECT event_date, event_name_firebase_screen, CASE WHEN event_name_firebase_screen = "screen_view-welcome" then 1 WHEN event_name_firebase_screen = "screen_view-home" then 2 WHEN event_name_firebase_screen = "screen_view-food_category" then 3 WHEN event_name_firebase_screen = "screen_view-restaurant" then 4 WHEN event_name_firebase_screen = "screen_view-cart" then 5 WHEN event_name_firebase_screen = "click_payment-cart" then 6 ELSE NULL END AS step_number, COUNT(DISTINCT user_pseudo_id) as cnt FROM filter group by all having step_number IS NOT NULL order by event_date   👩‍💻 1주차 느낀점 및 하고싶은 말 (솔직후기)  (1) ARRAY, STRUCT - 빅쿼리 사용법은 처음이라 이 문법은 생소했습니다. 학습완료! (2) PIVOT - 태블로로 시각화할떄 long format으로 시각화하려다 보니 쿼리 로딩시간이 초과되어 alert을 받은 적이 있습니다. ㅎㅎ.. 이때 SQL로는 pivot하는 방법을 잘 몰랐는데 학습완료! (3) 퍼널 분석 - 퍼널분석의 큰 흐름은 대충 알고 있었는데 퍼널분석 종류나 집계기준 종류, 해석하는 법 등 퍼널 분석 결과를 어떻게 바라보아야 하는지 정리해주셔서 명쾌했다.쿼리 기초문법은 이론적으로 알고 있었으나 첫 데이터관련 인턴을 하면서, 실무에서 하는 업무는 그보다 더 복잡하고, 비즈니스적으로 어떻게 바라보아야 하고, 해석해야하는지 중요하다는 것을 알게되었습니다. 그러나, 실무에서 또한 의문점이 발생해도 명쾌한 해답을 얻기 어려웠습니다. 이에 데이터 분석가를 희망은 하고 있지만, 어떻게 공부해야 할지에 대한 지속적으로 의문이 들었습니다. 그때 마침, 카일스쿨님의 강의를 우연히 접하게 되었고, 그동안 조각조각이었던 개념들을 SQL로 작성하고, 시각화까지 하는방법들을 모두 보여주시면서 데이터분석에 대한 자신감이 붙을 수 있었던 것 같습니다. 카일스쿨님이 그동안 걸어오신 길이 모두 보이는 강의였습니다. 강의 만들어주셔서 정말 감사합니다. 🙏 

Array, Struct 연습문제-- genre unnest select title, genre from `advanced.array_exercises` cross join UNNEST(genres) as genre; -- actor unnest select title, actor.actor, actor.character from `advanced.array_exercises` cross join UNNEST(actors) as actor; -- actor, genre unnest select title, actor.actor, actor.character, genre from `advanced.array_exercises` cross join UNNEST(actors) as actor cross join UNNEST(genres) as genre;PIVOT 연습문제-- 일자 별 사용자의 이벤트 발생 횟수 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; -- 사용자 별 일일 이벤트 발생 횟수 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 order by user_id; -- 사용자 별 일일 이벤트 발생 여부 select user_id, max(if(order_date='2023-05-01', 1, 0)) as `2023-05-01`, max(if(order_date='2023-05-02', 1, 0)) as `2023-05-02`, max(if(order_date='2023-05-03', 1, 0)) as `2023-05-03`, max(if(order_date='2023-05-04', 1, 0)) as `2023-05-04`, max(if(order_date='2023-05-05', 1, 0)) as `2023-05-05` from `advanced.orders` group by user_id order by user_id;퍼널 연습문제with data_event_name_with_screen_step as ( with data_event_name_with_screen as ( with base as (select event_date, DATETIME(TIMESTAMP_MICROS(event_timestamp), 'Asia/Seoul') as event_time, event_name, user_id, user_pseudo_id, max(if(event_param.key = 'firebase_screen',event_param.value.string_value , null)) as firebase_screen 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 ) select * except(event_name, firebase_screen), concat(event_name, '-', firebase_screen) as event_name_with_screen from base ) select COUNT(DISTINCT user_pseudo_id) AS cnt, 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 from data_event_name_with_screen group by all having step_number is not null order by event_date ) -- 이벤트로 pivot select event_date, sum(if(event_name_with_screen='screen_view-welcome', cnt, 0)) as `screen_view-welcome`, sum(if(event_name_with_screen='screen_view-home', cnt, 0)) as `screen_view-home`, sum(if(event_name_with_screen='screen_view-food_category', cnt, 0)) as `screen_view-food_category`, sum(if(event_name_with_screen='screen_view-restaurant', cnt, 0)) as `screen_view-restaurant`, sum(if(event_name_with_screen='screen_view-cart', cnt, 0)) as `screen_view-cart`, sum(if(event_name_with_screen='click_payment-cart', cnt, 0)) as `click_payment-cart` from data_event_name_with_screen_step group by all order by event_date ; 이전 부터 쿼리로 퍼널 분석하기 좋은 방법이 없을까 생각을 했었는데 방향성을 알게 되어 좋은 것 같습니다.

useSignup 함수에서 mutationFn에 회원가입 함수를 넣어줘서 Omit으로 'mutationFn'를 제외하셨는데useLogin 함수에서는 mutationFn랑 onSuccess, onSettled 함수를 추가로 설정해주셨는데 Omit으로 onSuccess랑 onSettled를 추가하지 않았는데 왜 에러가 발생하지 않는건지 궁금합니다! useLogin에서 onSuccess에서 성공해서 토큰들을 설정해줬는데 onSettled에서 토큰을 또 설정해주는건가요?

2편 듣고있는데 .. ㅎㅎ 궁금합니다.

1. ARRAY, STRUCT 연습문제문제 1) array_exercise테이블에서 각 영화(title)별로 장르(genres)를 UNNEST 해서 보여주세요SELECT title, genres FROM `analystic-project.advanced.array_exercises` , UNNEST(genres) AS genres ;문제 2) array_exercises 테이블에서 각 영화(title)별로 배우(actor)와 배역(character)을 보여주세요. 배우와 배역은 별도의 컬럼으로 나와야합니다SELECT title, actors.actor, actors.character FROM `analystic-project.advanced.array_exercises` , UNNEST(actors) AS actors ;문제 3) 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, actors.actor, actors.character, genres FROM `analystic-project.advanced.array_exercises` , UNNEST(actors) AS actors, UNNEST(genres) genres ;문제 4) 앱 로그 데이터(app_logs) 배열 풀기SELECT user_id, event_date, event_name, user_pseudo_id, pr.key, pr.value.string_value, pr.value.int_value FROM `analystic-project.advanced.app_logs` , UNNEST(event_params) AS pr WHERE event_date = "2022-08-01" LIMIT 1000 ;2. PIVOT 연습문제 풀이문제 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 합니다SELECT order_date, COALESCE(SUM(IF(user_id = 1, amount, null)),0) AS user_1, COALESCE(SUM(IF(user_id = 2, amount, null)),0) AS user_2, COALESCE(SUM(IF(user_id = 3, amount, null)),0) AS user_3 FROM advanced.orders GROUP BY order_date ORDER BY order_date ;문제 2) 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 합니다SELECT user_id, COALESCE(SUM(IF(order_date = '2023-05-01', amount, null)),0) AS `2023-05-01`, COALESCE(SUM(IF(order_date = '2023-05-02', amount, null)),0) AS `2023-05-02`, COALESCE(SUM(IF(order_date = '2023-05-03', amount, null)),0) AS `2023-05-03`, COALESCE(SUM(IF(order_date = '2023-05-04', amount, null)),0) AS `2023-05-04`, COALESCE(SUM(IF(order_date = '2023-05-05', amount, null)),0) AS `2023-05-05`, FROM advanced.orders GROUP BY user_id ORDER BY user_id ;문제 3) 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 처리합니다SELECT user_id, MAX(IF(order_date = '2023-05-01' AND order_id is not null, 1, 0)) AS `2023-05-01`, MAX(IF(order_date = '2023-05-02' AND order_id is not null, 1, 0)) AS `2023-05-02`, MAX(IF(order_date = '2023-05-03' AND order_id is not null, 1, 0)) AS `2023-05-03`, MAX(IF(order_date = '2023-05-04' AND order_id is not null, 1, 0)) AS `2023-05-04`, MAX(IF(order_date = '2023-05-05' AND order_id is not null, 1, 0)) AS `2023-05-05`, FROM advanced.orders GROUP BY user_id ORDER BY user_id ;문제 4)user_id = 32888이 카트 추가하기(click_cart)를 누를때 어떤 음식(food_id)을 담았나요?WITH app_order_raw AS ( SELECT user_id, event_date, event_name, user_pseudo_id, pr.key, pr.value.string_value, pr.value.int_value FROM advanced.app_logs, UNNEST(event_params) AS pr WHERE event_date = '2022-08-01' ) SELECT user_id, event_date, event_name, user_pseudo_id, MAX(IF(key = 'firebase_screen', string_value, null)) AS firebase_screen, MAX(IF(key = 'food_id', int_value, null)) AS food_id, MAX(IF(key = 'session_id', string_value, null)) AS session_id, FROM app_order_raw GROUP BY user_id, event_date, event_name, user_pseudo_id ;3. 퍼널분석문제 1) 각 퍼널의 유저 수를 집계 / 데이터 기준: 2022-08-01 ~ 2022-08-18WITH funnel_data_raw AS ( SELECT event_date, event_timestamp, event_name, user_id, user_pseudo_id, MAX(IF(pr.key = 'firebase_screen', pr.value.string_value, null)) AS screen_name, CONCAT(event_name, '-', MAX(IF(pr.key = 'firebase_screen', pr.value.string_value, null))) AS event_name_with_screen FROM advanced.app_logs, UNNEST(event_params) AS pr WHERE event_date BETWEEN '2022-08-01' AND '2022-08-18' GROUP BY 1,2,3,4,5 ) SELECT 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 END AS step_number, COUNT(DISTINCT user_pseudo_id) AS cnt FROM funnel_data_raw WHERE event_name IN ('screen_view', 'click_payment') AND screen_name IN ('welcome', 'home', 'food_category', 'restaurant', 'cart') GROUP BY 1,2 ORDER BY 2 ;문제 2) 일자별 퍼널 유저 수 집계 WITH funnel_data_raw AS ( SELECT event_date, event_timestamp, event_name, user_id, user_pseudo_id, MAX(IF(pr.key = 'firebase_screen', pr.value.string_value, null)) AS screen_name, CONCAT(event_name, '-', MAX(IF(pr.key = 'firebase_screen', pr.value.string_value, null))) AS event_name_with_screen FROM advanced.app_logs, UNNEST(event_params) AS pr WHERE event_date BETWEEN '2022-08-01' AND '2022-08-18' GROUP BY 1,2,3,4,5 ) 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 END AS step_number, COUNT(DISTINCT user_pseudo_id) AS cnt FROM funnel_data_raw WHERE event_name IN ('screen_view', 'click_payment') AND screen_name IN ('welcome', 'home', 'food_category', 'restaurant', 'cart') GROUP BY 1,2,3 ORDER BY 1,3 ;문제 3) 일자별 퍼널 유저 수 집계형태를 PIVOT형태로 전환하기WITH funnel_data_raw AS ( SELECT event_date, event_timestamp, event_name, user_id, user_pseudo_id, MAX(IF(pr.key = 'firebase_screen', pr.value.string_value, null)) AS screen_name, CONCAT(event_name, '-', MAX(IF(pr.key = 'firebase_screen', pr.value.string_value, null))) AS event_name_with_screen FROM advanced.app_logs, UNNEST(event_params) AS pr WHERE event_date BETWEEN '2022-08-01' AND '2022-08-18' GROUP BY 1,2,3,4,5 ), daily_funnel_user_count as ( 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 END AS step_number, COUNT(DISTINCT user_pseudo_id) AS cnt FROM funnel_data_raw WHERE event_name IN ('screen_view', 'click_payment') AND screen_name IN ('welcome', 'home', 'food_category', 'restaurant', 'cart') GROUP BY 1,2,3 ORDER BY 1,3 ) SELECT event_date, MAX(IF(step_number = 1, cnt, null)) AS `screen_view-welcome`, MAX(IF(step_number = 2, cnt, null)) AS `screen_view-home`, MAX(IF(step_number = 3, cnt, null)) AS `screen_view-food_category`, MAX(IF(step_number = 4, cnt, null)) AS `screen_view-restaurant`, MAX(IF(step_number = 5, cnt, null)) AS `screen_view-cart`, MAX(IF(step_number = 6, cnt, null)) AS `click_payment-cart`, FROM daily_funnel_user_count GROUP BY ALL ORDER BY 1 ;4. 새롭게 배웠던 점쿼리를 활용하여 PIVOT 형태로 데이터를 변환 할 수 있는 스킬을 습득함."GROUP BY ALL" 이라는 방식으로 전체 집계를 할 수 있다는 방법을 처음 알게 됨.`` (백틱) 기호를 사용하면 특수문자 '-'와 한글까지 컬럼명으로 사용할 수 있다는 것을 처음 알게 됨.실무에서 FROM절에 UNNEST() 함수 앞에 ',' 를 왜(Why) 써야되는지에 대한 궁금했는데, CROSS JOIN의 약자로 사용하고 있다는 것을 처음 알게 됨.ARRAY와 STRUCT 구조의 차이점과 해당 데이터타입 구조의 데이터를 추출하기 위한 방법을 명확하게 알게 됨.5. 느낀점사소하지만 스킬적인 부분으로 새롭게 배웠던 부분은 따로 잘 정리해두어 업무에 바로 사용해볼 예정. 또한 데이터 탐색 방법으로 Funnel 사용하는데 있어, Open 퍼널과 Closed 퍼널 방식의 종류를 배울 수 있어 뿌듯했음.

다른 문제들은 미리 다 혼자 풀면 해결 가능했는데, 맨 마지막 문제는 혼자 시도해서 답은 맞게 나왔으나 쿼리 접근 방식이 상이했습니다.WITH 구문으로 2~3개의 데이터를 미리 구축해두고 거기서 퍼널 분석을 하시던데, 해당 쿼리의 경우 좀 더 익숙해지면 정말 실무에서도 바로바로 써먹을 수 있겠다는 생각이 들더군요!피벗은 case when으로 작성했었는데, max와 if로 작성하는 방법을 알아가서 좋았습니다.다음주 강의도 열심히 들어보겠습니다! 감사합니다.   SELECT title, genreFROM advanced.array_exercisesCROSS JOIN UNNEST(genres) as genre;  SELECT title, act.actor as actor, act.character as characterFROM advanced.array_exercisesCROSS JOIN UNNEST(actors) as act  SELECT title, act.actor as actor, act.character as character, genreFROM advanced.array_exercisesCROSS JOIN UNNEST(actors) as actCROSS JOIN UNNEST(genres) as genre;  WITH base AS ( SELECT user_id, event_date, event_name, user_pseudo_id, events.key, events.value FROM advanced.app_logs CROSS JOIN UNNEST(event_params) AS events)SELECT event_date, event_name, COUNT(DISTINCT user_id) AS cntFROM baseGROUP BY ALLORDER BY cnt DESC  SELECT order_date, MAX(IF(user_id=1, amount, 0)) as user_1, MAX(IF(user_id=2, amount, 0)) as user_2, MAX(IF(user_id=3, amount, 0)) as user_3FROM advanced.ordersGROUP BY order_dateORDER BY order_date;  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 2023-05-05FROM advanced.ordersGROUP BY user_idORDER BY user_id;  SELECT user_id, MAX(IF(order_date = '2023-05-01', 1, 0)) AS 2023-05-01, MAX(IF(order_date = '2023-05-02', 1, 0)) AS 2023-05-02, MAX(IF(order_date = '2023-05-03', 1, 0)) AS 2023-05-03, MAX(IF(order_date = '2023-05-04', 1, 0)) AS 2023-05-04, MAX(IF(order_date = '2023-05-05', 1, 0)) AS 2023-05-05,FROM advanced.ordersGROUP BY user_idORDER BY user_id;  SELECT user_id , event_date , event_timestamp , event_name , user_pseudo_id , MAX(IF(events.key = 'firebase_screen', events.value.string_value, NULL)) AS firebase_screen , MAX(IF(events.key = 'food_id', events.value.int_value, NULL)) AS food_id , MAX(IF(events.key = 'session_id', events.value.int_value, NULL)) AS session_idFROM advanced.app_logsCROSS JOIN UNNEST(event_params) AS eventsWHERE user_id = 32888 AND event_name = 'click_cart'GROUP BY ALL  #정석 방법WITH 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) , DATETIME(TIMESTAMP_MICROS(event_timestamp), 'Asia/Seoul') AS event_datetime , CONCAT(event_name, '-', firebase_screen) AS event_name_with_screen FROM base WHERE event_name IN ('screen_view', 'click_payment'))SELECT 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 cntFROM filter_event_and_concat_event_and_screenGROUP BY ALLHAVING step_number IS NOT NULL  #내가 시도한 방법SELECT CONCAT(event_name, param.value.string_value) , COUNT(DISTINCT user_pseudo_id)FROM advanced.app_logsCROSS JOIN UNNEST(event_params) AS paramWHERE event_name IN ('screen_view', 'click_payment')AND param.value.string_value IN ('welcome', 'home', 'food_category', 'restaurant', 'cart')AND event_date BETWEEN '2022-08-01' AND '2022-08-18'GROUP BY event_name, param.value.string_value 

제가 유저들끼리 커뮤니티 만들고자 하는데 이때부터 강의 보면 될까요? 여러가지 다 보고있는데 어디서부터 딱 봐야할지 모르겠습니다.! 인프런 서비스 운영 관련 문의는 1:1 문의하기를 이용해주세요.

왜 인지는 모르겠지만, 8강을 시작하면서밑에 있는 코드의 GetController()에서 NULL을 반환하고 있어 게임 플레이가 안되던 문제가 있었습니다.void AABCharacterPlayer::SetCharacterControl(ECharacterControlType NewCharacterControlType) { UABCharacterControlData* NewCharacterControl = CharacterControlManager[NewCharacterControlType]; check(NewCharacterControl); SetCharacterControlData(NewCharacterControl); APlayerController* PlayerController = CastChecked<APlayerController>(GetWorld()->GetFirstPlayerController()); if (UEnhancedInputLocalPlayerSubsystem* Subsystem = ULocalPlayer::GetSubsystem<UEnhancedInputLocalPlayerSubsystem>(PlayerController->GetLocalPlayer())) { Subsystem->ClearAllMappings(); UInputMappingContext* NewMappingContext = NewCharacterControl->InputMappingContext; if (NewMappingContext) { Subsystem->AddMappingContext(NewMappingContext, 0); } } CurrentCharacterControlType = NewCharacterControlType; }아직 Pawn이 컨트롤러를 얻은 시점이 아니라서 NULL 값으로 반환된다고 합니다. GetWorld()->GetFirstPlayerController()를 호출해서 컨트롤러를 반환할수 있던데, Pawn이 컨트롤러를 얻은 시점이 언제인가요?

안녕하세요, AWS에 대한 기본 개념을 강사님의 강의를 통해 정말 많이 배우고 있는 학생입니다.Auto Scaling Group의 원하는 용량을 1로 설정하였을 때 인스턴스가 1개만 생성되기를 기대하였으나,2개가 생성되고 최종적으로 1개가 종료되는 현상을 확인할 수 있었는데요. 2개 인스턴스 가용영역이 다른 것으로 보아 이와 관련이 있지 않을까라고만 추측하고 있어 이렇게 질문드리게 되었습니다. 강사님 강의에서는 1로 설정하더라도 위와 같은 현상이 보이지 않았는데 혹시 제가 설정을 잘못한 것인지 궁금합니다.

ARRAY, STRUCT-- array_exercises 테이블 -- 영화(title)별로 장르(genres) UNNEST SELECT movie_id, title, genre FROM `advanced.array_exercises`, CROSS JOIN UNNEST(genres) AS genre -- array_exercises 테이블 -- 영화(title) 별로 배우(actor), 배역(character) UNNEST SELECT title, actors.actor, actors.character FROM `advanced.array_exercises` CROSS JOIN UNNEST(actors) AS actors -- array_exercises 테이블 -- 영화(title) 별로 배우(actor), 배역(character), 장르(genre) UNNEST SELECT title, actor.actor, actor.character, genre FROM `advanced.array_exercises` CROSS JOIN UNNEST(actors) AS actor CROSS JOIN UNNEST(genres) AS genre -- 앱 로그 데이터(app_logs) UNNEST SELECT event_date, 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, user_pseudo_id, platform 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 ALL ORDER BY order_date -- 2. 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, 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 ALL ORDER BY user_id -- 3. 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, MAX(IF(order_date = "2023-05-01", 1, 0)) AS `2023-05-01`, MAX(IF(order_date = "2023-05-02", 1, 0)) AS `2023-05-02`, MAX(IF(order_date = "2023-05-03", 1, 0)) AS `2023-05-03`, MAX(IF(order_date = "2023-05-04", 1, 0)) AS `2023-05-04`, MAX(IF(order_date = "2023-05-05", 1, 0)) AS `2023-05-05`, FROM advanced.orders GROUP BY ALL ORDER BY user_id -- 4.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 = "food_id", param.value.int_value, NULL)) AS food_id, MAX(IF(param.key = "session_id", param.value.string_value, NULL)) AS session_id, FROM advanced.app_logs CROSS JOIN UNNEST(event_params) AS param GROUP BY ALL ) SELECT event_date, COUNT(user_id) AS user_cnt FROM base WHERE event_name = "click_cart" GROUP BY ALL FUNNELwith base as ( select event_date, event_timestamp, event_name, user_id, user_pseudo_id, platform, -- event_param max(if(event_param.key = 'firebase_screen', event_param.value.string_value, null)) as firebase_screen, -- max(if(event_param.key = 'food_id', event_param.value.int_value, null)) as food_id, 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 order by 1, 3 SELECT event_date, MAX(IF(event_name_with_screen ="screen_view-welcome", cnt, NULL)) AS `screen_view-welcome`, MAX(IF(event_name_with_screen ="screen_view-home", cnt, NULL)) AS `screen_view-home`, MAX(IF(event_name_with_screen ="screen_view-food_category", cnt, NULL)) AS `screen_view-food_category`, MAX(IF(event_name_with_screen ="screen_view-restaurant", cnt, NULL)) AS `screen_view-restaurant`, MAX(IF(event_name_with_screen ="screen_view-cart", cnt, NULL)) AS `screen_view-cart`, MAX(IF(event_name_with_screen ="click_payment-cart", cnt, NULL)) AS `click_payment-cart` FROM main GROUP BY ALL ORDER BY all

 학습하는 분들께 도움이 되고, 더 좋은 답변을 드릴 수 있도록 질문전에 다음을 꼭 확인해주세요.1. 강의 내용과 관련된 질문을 남겨주세요.2. 인프런의 질문 게시판과 자주 하는 질문(링크)을 먼저 확인해주세요.(자주 하는 질문 링크: https://bit.ly/3fX6ygx)3. 질문 잘하기 메뉴얼(링크)을 먼저 읽어주세요.(질문 잘하기 메뉴얼 링크: https://bit.ly/2UfeqCG)질문 시에는 위 내용은 삭제하고 다음 내용을 남겨주세요.=========================================[질문 템플릿]1. 강의 내용과 관련된 질문인가요? (예/아니오)2. 인프런의 질문 게시판과 자주 하는 질문에 없는 내용인가요? (예/아니오)3. 질문 잘하기 메뉴얼을 읽어보셨나요? (예/아니오)[질문 내용]여기에 질문 내용을 남겨주세요. 안녕하세요. 다형성1섹션에서 <다형성과 메서드 오버라이딩> 9분 관련 질문입니다. '메소드 상속은 일방통행(자식 → 부모)인데, 어떻게 부모에서 오버라이딩 된 자식함수를 찾아가는가?'가 질문입니다. 다른분들이 질문을 남겨주신 것과 비슷한데, 제가 내린 결론이 맞는지 여쭤보고 싶습니다. 제가 내린 결론은 다음과 같습니다.오버라이딩은 런타임에 호출메서드를 결정하는 동적 디스패치를 수행한다.즉, 메서드 호출 시점에 오버라이딩을 체크해서, 오버라이딩이면 동적 디스패치가 수행된다.동적 디스패치를 수행하면, 참조변수타입이 아닌 실제 객체를 기준으로 메서드가 호출된다. (오버라이딩이 아니면 동적 디스패치는 수행되지 않는다.) poly.method()호출호출 시점에 호출된 메서드가 오버라이딩이면 동적 디스패치 수행동적 디스패치를 수행하면 참조변수타입이 아닌 실제 객체를 기준으로(new Child) 메서드가 호출됨. (오버라이딩이 안된 메서드면 동적 디스패치 수행x)객체 주소 x001로 이동(부모, 자식 다 있음.) → 실제 객체 오버라이딩 된 메서드로 바로 이동.(부모로 갔다 가는게 아님) 이것이 맞는지 여쭤보고 싶습니다.제가 검색한 바에 의하면, 먼저 부모로 가서 자식으로 내려가는게 아니라, 오버라이딩 된 함수의 경우 동적 디스패치 수행으로 바로 오버라이딩된 함수로 (vmt 우선순위 변경) 바로 이동하는 것으로 결론이 되었는데제가 내린 결론은 강의 자료 그림상 부모에서 자식으로 내려가는 화살표와는 다르다 보니 여쭤봅니다. 부모로 갔다가 화살표가 자식으로 내려가는걸까요?처음부터 오버라이딩된 함수의 경우 동적디스패치 수행으로 바로 오버라이딩 된 함수로 가는게 아닌걸까요?   

학습하는 분들께 도움이 되고, 더 좋은 답변을 드릴 수 있도록 질문전에 다음을 꼭 확인해주세요.1. 강의 내용과 관련된 질문을 남겨주세요.2. 인프런의 질문 게시판과 자주 하는 질문(링크)을 먼저 확인해주세요.(자주 하는 질문 링크: https://bit.ly/3fX6ygx)3. 질문 잘하기 메뉴얼(링크)을 먼저 읽어주세요.(질문 잘하기 메뉴얼 링크: https://bit.ly/2UfeqCG)질문 시에는 위 내용은 삭제하고 다음 내용을 남겨주세요.=========================================[질문 템플릿]1. 강의 내용과 관련된 질문인가요? (예/아니오)2. 인프런의 질문 게시판과 자주 하는 질문에 없는 내용인가요? (예/아니오)3. 질문 잘하기 메뉴얼을 읽어보셨나요? (예/아니오)[질문 내용]@Test void bulkAgePlus(){ memberRepository.save(new Member("AAA", 10, null)); memberRepository.save(new Member("BBB", 15, null)); memberRepository.save(new Member("CCC", 20, null)); memberRepository.save(new Member("DDD", 25, null)); memberRepository.save(new Member("EEE", 30, null)); int count = memberRepository.bulkAgePlus(18); em.flush(); em.clear(); List<Member> result = memberRepository.findByUsername("EEE"); Member findMember = result.get(0); assertThat(count).isEqualTo(3); assertThat(findMember.getAge()).isEqualTo(31); } 여기서 벌크성 연산을 할경우 엔티티 매니저를 거치지 않고 바로 업데이트를 하기에 findById 호출 전에 flush, clear하지 않으면 업데이트 이전에 save된 값이 나오는 것으로 알고 있어(캐쉬된 값) flush, clear를 해주는 것으로 알고 있는데 이때 em.flush()를 해버리면 벌크 연산 값이 아닌 그 이전 값이(save에서 저장한 값 EEE라 가정하면 31이 아닌 30) db에 업데이트 되는 꼴이라 벌크성 연산이 db에 유효하게 저장되려면 em.clear()만 실행 해야되는거 아닌가요?

ARRAY / STRUCT 연습문제1# ARRAY, STRUCT 연습 문제1 -- genres 배열을 UNNEST하여 펼치고, 각 장르를 개별 행으로 분리하여 영화 제목별 장르를 나타냈습니다. SELECT title, genre FROM `bqmaster.advanced.array_exercises`, UNNEST(genres) AS genre연습문제2# ARRAY, STRUCT 연습 문제1 -- genres 배열을 UNNEST하여 펼치고, 각 장르를 개별 행으로 분리하여 영화 제목별 장르를 나타냈습니다. SELECT title, genre FROM `bqmaster.advanced.array_exercises`, UNNEST(genres) AS genre연습문제3# ARRAY, STRUCT 연습 문제1 -- genres 배열을 UNNEST하여 펼치고, 각 장르를 개별 행으로 분리하여 영화 제목별 장르를 나타냈습니다. SELECT title, genre FROM `bqmaster.advanced.array_exercises`, UNNEST(genres) AS genre연습문제4# ARRAY, STRUCT 연습 문제1 -- genres 배열을 UNNEST하여 펼치고, 각 장르를 개별 행으로 분리하여 영화 제목별 장르를 나타냈습니다. SELECT title, genre FROM `bqmaster.advanced.array_exercises`, UNNEST(genres) AS genre PIVOT 연습문제1# PIVOT 연습 문제1 -- 날짜별로 사용자별 amount 합산을 나타냈습니다. -- IF 문을 사용해 user_id가 1, 2, 3인 경우에만 amount를 집계하고, 나머지는 0으로 처리했습니다. -- 데이터셋 특성상 SUM과 MAX 모두 사용할 수 있습니다. 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 `bqmaster.advanced.orders` GROUP BY ALL ORDER BY order_date연습문제2# PIVOT 연습 문제2 -- 사용자별로 날짜별 amount 합산을 나타냈습니다. -- IF 문을 사용해 order_date가 지정된 날짜에 해당하는 경우에만 amount를 집계하고, 나머지는 0으로 처리했습니다. -- 데이터셋 특성상 SUM과 MAX 모두 사용할 수 있습니다. 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 `bqmaster.advanced.orders` GROUP BY ALL ORDER BY user_id연습문제3# PIVOT 연습 문제3 -- 사용자별로 날짜별 주문 여부를 나타냈습니다. -- IF 문을 사용해 해당 날짜에 주문이 있는 경우 1, 없는 경우 0으로 표시하고, MAX를 사용해 날짜별로 최대값(1 또는 0)을 반환합니다. -- 데이터셋 특성상 SUM과 MAX 모두 사용할 수 있습니다. SELECT user_id, MAX(IF(order_date = '2023-05-01', 1, 0)) AS `2023-05-01`, MAX(IF(order_date = '2023-05-02', 1, 0)) AS `2023-05-02`, MAX(IF(order_date = '2023-05-03', 1, 0)) AS `2023-05-03`, MAX(IF(order_date = '2023-05-04', 1, 0)) AS `2023-05-04`, MAX(IF(order_date = '2023-05-05', 1, 0)) AS `2023-05-05`, FROM `bqmaster.advanced.orders` GROUP BY ALL ORDER BY user_id연습문제4# PIVOT 연습 문제4 -- user_id가 32888인 사용자가 click_cart 이벤트 발생 시의 데이터를 나타냈습니다. -- event_params 배열을 UNNEST하여 param으로 분리한 후, firebase_screen, food_id, session_id를 개별 컬럼으로 표시했습니다. 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 = 'food_id', param.value.int_value, NULL)) AS food_id, MAX(IF(param.key = 'session_id', param.value.string_value, NULL)) AS session_id FROM `bqmaster.advanced.app_logs`, UNNEST(event_params) AS param GROUP BY ALL ) SELECT * FROM base WHERE 1=1 AND user_id = 32888 AND event_name = 'click_cart' FUNNEL연습문제1# FUNNEL 연습 문제1 -- WITH 구문을 사용해 base 테이블을 생성하여 이벤트 이름과 화면 이름을 포함한 event_name_with_screen 컬럼을 만들었습니다. -- event_date는 2022-08-01에서 2022-08-18 사이로 설정했습니다. WITH base AS ( SELECT event_date, CONCAT(event_name, '-', param.value.string_value) AS event_name_with_screen, user_pseudo_id FROM `bqmaster.advanced.app_logs`, UNNEST(event_params) AS param WHERE 1=1 AND event_name IN ('screen_view', 'click_payment') AND param.key = 'firebase_screen' AND event_date BETWEEN '2022-08-01' AND '2022-08-18' ) # 일자 상관 없이 퍼널의 유저 수를 집계 SELECT 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, COUNT(DISTINCT user_pseudo_id) AS user_cnt FROM base GROUP BY ALL HAVING step IS NOT NULL ORDER BY step # 일자별 퍼널의 유저 수를 집계 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, COUNT(DISTINCT user_pseudo_id) AS user_cnt FROM base GROUP BY ALL HAVING step IS NOT NULL ORDER BY event_date, step연습문제2# FUNNEL 연습 문제2 -- 윈도우 함수를 사용해 이탈률을 계산해 봤습니다. -- LAG을 사용하여 이전 사용자수 값을 가져와 계산에 활용했습니다. WITH base AS ( SELECT event_date, CONCAT(event_name, '-', param.value.string_value) AS event_name_with_screen, user_pseudo_id FROM `bqmaster.advanced.app_logs`, UNNEST(event_params) AS param WHERE 1=1 AND event_name IN ('screen_view', 'click_payment') AND param.key = 'firebase_screen' AND event_date BETWEEN '2022-08-01' AND '2022-08-18' ), add_step AS ( SELECT 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 funnel_step, COUNT(DISTINCT user_pseudo_id) AS user_cnt FROM base GROUP BY ALL HAVING funnel_step IS NOT NULL ), add_total_user_cnt AS ( SELECT *, LAG(user_cnt) OVER(ORDER BY funnel_step) AS previous_step_user_cnt FROM add_step ) SELECT *, ROUND((previous_step_user_cnt - user_cnt) / previous_step_user_cnt, 2) AS bounce_rate FROM add_total_user_cnt ORDER BY funnel_step연습문제3# FUNNEL 연습 문제3 -- PIVOT을 사용해 화면별로 사용자 수를 컬럼으로 나열하여 각 화면별 날짜별 사용자 수를 확인할 수 있도록 구성했습니다. WITH base AS ( SELECT event_date, CONCAT(event_name, '-', param.value.string_value) AS event_name_with_screen, user_pseudo_id FROM `bqmaster.advanced.app_logs`, UNNEST(event_params) AS param WHERE 1=1 AND event_name IN ('screen_view', 'click_payment') AND param.key = 'firebase_screen' AND event_date BETWEEN '2022-08-01' AND '2022-08-18' ), add_user_cnt AS ( SELECT event_date, event_name_with_screen, COUNT(DISTINCT user_pseudo_id) AS user_cnt FROM base GROUP BY ALL ) SELECT event_date, MAX(IF(event_name_with_screen = 'screen_view-welcome', user_cnt, NULL)) AS screen_view_welcome, MAX(IF(event_name_with_screen = 'screen_view-home', user_cnt, NULL)) AS screen_view_home, MAX(IF(event_name_with_screen = 'screen_view-food_category', user_cnt, NULL)) AS screen_view_food_category, MAX(IF(event_name_with_screen = 'screen_view-restaurant', user_cnt, NULL)) AS screen_view_restaurant, MAX(IF(event_name_with_screen = 'screen_view-cart', user_cnt, NULL)) AS screen_view_cart, MAX(IF(event_name_with_screen = 'click_payment-cart', user_cnt, NULL)) AS click_payment_cart FROM add_user_cnt GROUP BY ALL ORDER BY event_date

ARRAY(배열) / STRUCT(구조체)# 1. array_exercises 테이블에서 각 영화(title)별로 장르(genres)를 UNNEST해서 보여주세요 SELECT title, genre # UNNEST에서 사용한 새로운 컬럼으로 사용 / 기존 ARRAY_COULMN은 사용 X FROM advanced.array_exercises CROSS JOIN UNNEST(genres) AS genre; # 2. 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 CROSS JOIN UNNEST(actors) AS actor; # 3. 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, actor.character, genre FROM advanced.array_exercises CROSS JOIN UNNEST(actors) AS actor CROSS JOIN UNNEST(genres) AS genre; # 4. 앱 로그 데이터(app_logs)의 배열을 풀어주세요 SELECT user_id, event_date, event_name, user_pseudo_id, event_param.key, event_param.value.string_value, event_param.value.int_value FROM advanced.app_logs CROSS JOIN UNNEST(event_params) AS event_param WHERE event_date = "2022-08-01"; PIVOT(피봇): 축을 중심으로 회전한다# 1. orders테이블에서 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 ALL ORDER BY order_date; # 2. 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, 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 ALL ORDER BY user_id; # 3. 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, MAX(IF(order_date = "2023-05-01", 1, 0)) AS `2023-05-01`, MAX(IF(order_date = "2023-05-02", 1, 0)) AS `2023-05-02`, MAX(IF(order_date = "2023-05-03", 1, 0)) AS `2023-05-03`, MAX(IF(order_date = "2023-05-04", 1, 0)) AS `2023-05-04`, MAX(IF(order_date = "2023-05-05", 1, 0)) AS `2023-05-05` FROM advanced.orders GROUP BY ALL ORDER BY user_id; # 4. app_log를 pivot하기 WITH base AS( SELECT user_id, event_date, event_name, event_timestamp, user_pseudo_id, MAX(if(event_param.key = "firebase_screen", event_param.value.string_value, NULL)) AS firebase_screen, MAX(if(event_param.key ="food_id", event_param.value.int_value, NULL)) AS food_id, MAX(if(event_param.key ="session_id", event_param.value.string_value, NULL)) AS session_id FROM avdanced.app_logs CROSS JOIN UNNEST (event_params) AS event_param WHERE event_date ='2022-08-01' GROUP BY ALL ) SELECT event_date, COUNT(user_id) AS cnt FROM base WHERE event_name = 'click_cart' GROUP BY ALL; 퍼널(Funnel): 깔때기 의미 → 넓은 시작점에서 점점 좁하지는 흐름WITH 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 fire_screen, -- MAX(IF(event_param.key = "food_id", event_param.value.int_value, NULL)) AS food_id, 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 ), fiter_event_and_concat_event_and_screen AS ( -- event_name + screen (필요한 이벤트만 WHERE 조건에 걸어서 사용) SELECT * EXCEPT(event_name, fire_screen, event_timestamp), CONCAT(event_name, "-", fire_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") ) -- step_number + COUNT -- step_number : CASE WHEN을 사용해 숫자 지정 SELECT 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 fiter_event_and_concat_event_and_screen GROUP BY ALL HAVING step_number IS NOT NULL WHERE user_pseudo_id = "1350836585.3421064109" -- 일자별 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 fiter_event_and_concat_event_and_screen GROUP BY ALL HAVING step_number IS NOT NULL ORDER BY event_date;  

31강에서 수업 코드를 잘 따라 쳐서 수업 내용과 똑같은 결과를 확인 할 수 있게 되었는데요. 한 가지 의문점이 들어 질문을 남깁니다. 수업의 마지막 내용인 클린 코드 책이 이미 대출이 되있어 B사용자가 대출을 하려 했으나 대출을 클릭하는 순간 서버 내부 오류입니다. 라는 내용의 경고창이 뜨는걸 확인했는데 영상의 내용에는 진작 대출되어 있는 책입니다 라는 IllegalArgumentException으로 예외처리를 했어서 서버 내부 오류입니다 라는 내용이 아니라 진작 대출되어 있는 책입니다 떠야 하는게 아닌가요? 다음 강의에서 확인할 수 있으려나요~? 

section4 UIKit을 다루는 방법의 코드자료는 제공되지 않는 것인가요?

1. ARRAY, STRUCT 연습 문제-- 1.array_exercises 테이블에서 각 영화(title)별로 장르(genres)를 UNNEST해서 보여주세요 SELECT movie_id, title, genre FROM `advanced.array_exercises`, CROSS JOIN UNNEST(genres) AS genre -- 2.array_exercises 테이블에서 각 영화(title) 별로 배우(actor)와 배역(character)을 보여주세요. 배우와 배역은 별도의 컬럼으로 나와야 합니다. SELECT title, actors.actor, actors.character FROM `advanced.array_exercises` CROSS JOIN UNNEST(actors) AS actors -- 3.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, actor.character, genre FROM `advanced.array_exercises` CROSS JOIN UNNEST(actors) AS actor CROSS JOIN UNNEST(genres) AS genre -- 4.앱 로그 데이터(app_logs)의 배열을 풀어주세요 SELECT event_date, 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, user_pseudo_id, platform FROM `advanced.app_logs` CROSS JOIN UNNEST(event_params) AS event_param2. PIVOT 연습 문제-- 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 ALL ORDER BY order_date -- 2. 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, 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 ALL ORDER BY user_id -- 3. 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, MAX(IF(order_date = "2023-05-01", 1, 0)) AS `2023-05-01`, MAX(IF(order_date = "2023-05-02", 1, 0)) AS `2023-05-02`, MAX(IF(order_date = "2023-05-03", 1, 0)) AS `2023-05-03`, MAX(IF(order_date = "2023-05-04", 1, 0)) AS `2023-05-04`, MAX(IF(order_date = "2023-05-05", 1, 0)) AS `2023-05-05`, FROM advanced.orders GROUP BY ALL ORDER BY user_id -- 4.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 = "food_id", param.value.int_value, NULL)) AS food_id, MAX(IF(param.key = "session_id", param.value.string_value, NULL)) AS session_id, FROM advanced.app_logs CROSS JOIN UNNEST(event_params) AS param GROUP BY ALL ) SELECT event_date, COUNT(user_id) AS user_cnt FROM base WHERE event_name = "click_cart" GROUP BY ALL 3. 퍼널 쿼리 연습 문제WITH base AS ( select event_date, event_timestamp, event_name, user_id, user_pseudo_id, platform, MAX(IF(param.key = "firebase_screen", param.value.string_value, NULL)) AS firebase_screen, MAX(IF(param.key = "food_id", param.value.int_value, NULL)) AS food_id, MAX(IF(param.key = "session_id", param.value.string_value, NULL)) AS session_id, FROM `advanced.app_logs` CROSS JOIN UNNEST(event_params) AS param WHERE 1=1 AND 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 1=1 AND event_name IN ("screen_view", "click_payment") ), MAIN AS ( 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 ) -- 피벗 쿼리 만들기 SELECT event_date, MAX(IF(event_name_with_screen ="screen_view-welcome", cnt, NULL)) AS `screen_view-welcome`, MAX(IF(event_name_with_screen ="screen_view-home", cnt, NULL)) AS `screen_view-home`, MAX(IF(event_name_with_screen ="screen_view-food_category", cnt, NULL)) AS `screen_view-food_category`, MAX(IF(event_name_with_screen ="screen_view-restaurant", cnt, NULL)) AS `screen_view-restaurant`, MAX(IF(event_name_with_screen ="screen_view-cart", cnt, NULL)) AS `screen_view-cart`, MAX(IF(event_name_with_screen ="click_payment-cart", cnt, NULL)) AS `click_payment-cart` FROM main GROUP BY ALL ORDER BY event_date  

suspend fun searchByKeyword(keyword: String): Array<String> = coroutineScope { val dbResultsDeferred = async { searchFromDB(keyword) } val serverResultsDeferred = async { searchFromServer(keyword) } return@coroutineScope arrayOf(*dbResultsDeferred.await(), *serverResultsDeferred.await()) }안녕하세요 "일시 중단 함수의 사용" 학습 중 나온 코드에 대해 질문 드립니다.강의에서는 "coroutineScope을 사용하면, 일시중단 함수 내부에 coroutineScope 객체를 만들 수 있다."라고 하셨는데, 이 부분이 이해가 잘 안갑니다.먼저 coroutineScope {}를 선언하고, async 비동기 작업 -> delay 일시중단 순으로 진행되는데 일시중단 함수 내부에 coroutineScope 객체를 만들 수 있는 것이 이해가 잘 가지 않습니다.제가 정리하기로는, "coroutineScope을 사용하면, 일시중단 함수 내부에 coroutineScope 객체를 만들 수 있다."라기 보다는 위 그림처럼 "하나의 coroutineScope에 2개의 비동기 작업과 각각의 일시중단 함수를 포함하는 것"으로 받아들여지는데 제가 어느 부분을 놓치고 있는건지 잘 모르겠습니다. 감사합니다. ^^  

(사진)