Goldman Sachs online assessment 高盛 20分钟稳过分享

最近真是 OA 密集轰炸模式，一天排好几场，几乎没停过。昨天刚刚结束一轮 Goldman Sachs online assessment（HackerRank 平台），整体难度不算夸张，20 分钟就稳稳做完了，正好来和大家详细复盘一下，给还在准备的小伙伴一些参考。

这次的题目主要是两道 Coding，虽然不是那种超难 DP/图论，但也有一些细节容易掉坑。分享下思路和注意点。

Problem 1: Minimize Machine Usage

Problem Statement:
You are given a set of machines, each with a certain number of usages. The goal is to bring all usage counts down to zero through a series of operations.

• In one operation, you can select two machines and decrease each of their usage counts by one.
• You need to determine the minimum number of operations required to make all machines reach zero.

Key Insights:
This problem can be efficiently solved with a greedy strategy:

• In every step, pair the machine with the highest usage count with the machine that has the lowest usage count, and reduce both.
• Repeating this ensures that the “heaviest load” is being balanced by the “lightest load,” preventing unnecessary leftover usages.

Special Case Handling:

• If a machine’s usage count becomes very small, it can quickly be reduced to zero without wasting additional operations.

Implementation Details:

• The data size is not very large, so simulation with priority queues is feasible.
• A max heap can be used to always extract the machine with the largest usage count, and a min heap for the smallest one.
• Each operation decreases both selected values, and the total count of operations is accumulated until all values reach zero.

Answer:
The final result is simply the sum of all operations performed.
This greedy pairing guarantees the minimum number of steps.

Problem 2: Pods and Costs Placement

Problem Statement:
You are given a collection of elements, where each element has two attributes:

• pod
• cost

The task is to arrange these elements in an array according to the following rules:

1. Elements with a higher cost must be placed with higher priority.
2. After placing high-cost elements, the lower-cost elements should be assigned to the remaining available positions.

Key Insights:
This is a greedy + data structure problem.

• First, treat each element as a pair (pod, cost).
• Sort all elements in descending order of cost.
• Traverse the sorted list:
  • If the position of a high-cost element is available, it should be fixed there.
  • For lower-cost elements, if the intended position is already occupied, they must move to the next available free slot.

Optimization:
Naively scanning linearly for the next free position is inefficient. Instead:

• Use a map or disjoint set union (DSU/union-find) to keep track of the “next available position.”
• This allows jumping directly to the nearest empty slot without checking one by one.

Implementation Strategy:

1. Sort by cost (descending).
2. Insert elements in order, fixing high-cost ones first.
3. Maintain the next available slot pointer using DSU or a map for efficient placement of remaining elements.

Takeaway:
The problem combines greedy prioritization (cost ordering) with efficient data structure usage (map/DSU) to handle placement in logarithmic or near-constant time.

Goldman Sachs online assessment 整体难度与感受

说实话，这次 Goldman Sachs OA 算是比较友好的，不像有些公司的 OA 爱考花哨的概率题或者 tricky DP。这里的两道题逻辑都比较直观，难点主要在实现细节。

我用时大概 20 分钟，主要时间花在 debug 边界条件。比如：

Problem 1 里，机器次数为 0 的处理是否及时跳出循环。

Problem 2 里，空位分配如果写得不够严谨，可能会覆盖到已经放好的高 cost 元素。

这类细节一旦没踩稳，很容易浪费十几分钟 debug。

给准备高盛 OA 的小建议

1. 刷题方向：贪心、排序、map/heap 这种数据结构类的题要重点复习。
2. 节奏把握：Goldman Sachs 的 OA 时间并不算很紧张，但如果在细节上卡住，就会很危险。
3. 实战演练：尽量模拟真实环境，定时做题，把“卡点思维”提前练熟。

很多同学其实题目会做，但在实战里容易慌张，比如：

不知道什么时候该果断放弃 brute force。

debug 时陷入死循环，时间就被吃光。

没有规划好写代码的节奏，导致本来 15 分钟能写完的题，拖到 30 分钟还没过样例。

想冲击大厂但时间有限？

别担心，我们能为你提供全方位的支持：

OA 代写 & 笔试包过：HackerRank、牛客网、CodeSignal 等平台全覆盖，专业写手在线代写，保证所有测试用例 100% 通过，不通过不收费，远程无痕操作安全可靠。

面试助攻 & VO 辅助：实时语音提示 + 思路引导，让你在面试中从容应对，北美 CS 专家人工助攻，远超单纯刷题效果。

代面试（全程代面）：转接摄像头+变声技术，团队默契配合，提前多轮模拟，帮你轻松化身“无懈可击的候选人”，直通大厂 Offer。

全套护航 & Offer 保拿：从 OA 到技术面，再到签约谈判，全流程一站式服务，预付少量定金，Offer 到手再付尾款，风险极低。

更多支持：模拟面试、面经分享、编程代写、简历优化、算法辅导、Quant 面试辅助，甚至留学生入学代面，我们都能提供专业支持。

如果你也在备战大厂，不要一个人硬扛。找对帮手，少走弯路，拿 Offer 真的可以更快更稳！