本帖最后由 匿名 于 2026-5-30 19:13 编辑

都是地裡的原題了，感覺就是有其他強者或是not a good fit，所以大機率是掛在HM round

Past experience deep dive
SD: hotel reservation system: 各種failure cases都問得很深入，每個deep dive 我都有回答到面試官看起來滿意

Coding Stock prices: 總共四個部分，面試官說part 4是bonus, 所以可以不用寫出來，用講的就好。細節的話地裡其他篇有

Coding Social Likes: 印象中也是2~3 parts
HM round, BQ

------------------------------------------

| User 1 | User 2 | 1 likes 2 | 2 likes 1 |

------------------------------------------

| Jack  | Rachel  | 5         |...

本帖最后由 匿名 于 2026-5-30 19:13 编辑

都是地裡的原題了，感覺就是有其他強者或是not a good fit，所以大機率是掛在HM round

Past experience deep dive
SD: hotel reservation system: 各種failure cases都問得很深入，每個deep dive 我都有回答到面試官看起來滿意

Coding Stock prices: 總共四個部分，面試官說part 4是bonus, 所以可以不用寫出來，用講的就好。細節的話地裡其他篇有

Coding Social Likes: 印象中也是2~3 parts
HM round, BQ

------------------------------------------

| User 1 | User 2 | 1 likes 2 | 2 likes 1 |

------------------------------------------

| Jack  | Rachel  | 5         |        3  |

------------------------------------------

| Mark | Ellen    | 3         |        1  |

------------------------------------------

| Rachel | Ellen  | 6         |        4  |

------------------------------------------

| Jack | Mark     | 0         |        6  |

------------------------------------------

| Mark | Rachel   | 1         |        1  |

Part 1:

Write a transform function for the given data, that can support the below function:

GetLikesCount(user1, user2)

IngestData(user1, user2, 1likes2, 2likes1)

'''

{

"Jack": {

"Rachel": 5,

},

"Rachel": {

"Jack": 3,

}

}

'''

Part 2:

Return recommendations for each person on the social network.

To recommend a friend for someone, we will take their best friend's best friend.

A person's best friend is whomever they have liked the most. So for example, Jack's best friend is Rachel. To recommend a friend for someone, we will take their best friend's best friend. To continue our example: Jack's best friend is Rachel. Rachel's best friend is Ellen. So we will recommend Ellen as a friend for Jack.

GetFriendRecommendation(user)