[Algorithm] 350. Intersection of Two Arrays II
Given two arrays, write a function to compute their intersection.
Example 1:
Input: nums1 = [1,2,2,1], nums2 = [2,2] Output: [2,2]
Example 2:
Input: nums1 = [4,9,5], nums2 = [9,4,9,8,4] Output: [4,9]
Note:
- Each element in the result should appear as many times as it shows in both arrays.
- The result can be in any order.
Not good enough approach
var intersect = function(nums1, nums2) { let r = []; // get larger array const len1 = nums1.length; const len2 = nums2.length; // larger & smaller const larger = len1 > len2 ? nums1: nums2; const smaller = len1 > len2 ? nums2: nums1; // conver larger array to object let hashed = {}; for (let n of larger) { if (n in hashed) { hashed[n]++; } else { hashed[n] = 1; } } // loop over smaller array for (let n of smaller) { if (`${n}` in hashed) { r.push(n); hashed[n] = hashed[n]-1; if (hashed[n] === 0) { delete hashed[n]; } } } return r; };
The reason that code above is not good enough is because, \
1. we use larger array as lookup, this cause more memory usage. -- actually we need to use smaller array as lookup
2. we use 'len1, len2, samller, larger' extra storage, we can actully swap nums1 and nums by one extra function call.
var intersect = function(nums1, nums2) { if (nums1.length > nums2.length) { return intersect(nums2, nums1); } // conver samller array to object let hashed = {}; for (let n of nums2) { if (n in hashed) { hashed[n]++; } else { hashed[n] = 1; } } let r = []; // loop over smaller array for (let n of nums1) { if (hashed[n] > 0) { r.push(n); hashed[n] = hashed[n]-1; } } return r; }
Follow up:
- What if the given array is already sorted? How would you optimize your algorithm?
- What if nums1's size is small compared to nums2's size? Which algorithm is better?
- What if elements of nums2 are stored on disk, and the memory is limited such that you cannot load all elements into the memory at once?
Will write another post for the follow up questions.
分类:
Algorithms
【推荐】国内首个AI IDE,深度理解中文开发场景,立即下载体验Trae
【推荐】编程新体验,更懂你的AI,立即体验豆包MarsCode编程助手
【推荐】抖音旗下AI助手豆包,你的智能百科全书,全免费不限次数
【推荐】轻量又高性能的 SSH 工具 IShell:AI 加持,快人一步
· SQL Server 2025 AI相关能力初探
· Linux系列:如何用 C#调用 C方法造成内存泄露
· AI与.NET技术实操系列(二):开始使用ML.NET
· 记一次.NET内存居高不下排查解决与启示
· 探究高空视频全景AR技术的实现原理
· 阿里最新开源QwQ-32B,效果媲美deepseek-r1满血版,部署成本又又又降低了!
· Manus重磅发布:全球首款通用AI代理技术深度解析与实战指南
· 开源Multi-agent AI智能体框架aevatar.ai,欢迎大家贡献代码
· 被坑几百块钱后,我竟然真的恢复了删除的微信聊天记录!
· AI技术革命,工作效率10个最佳AI工具
2018-12-14 [Algorithm] Linked List Data Structure in JavaScript
2017-12-14 [React] Use Prop Collections with Render Props
2016-12-14 [JS Compse] 4. A collection of Either examples compared to imperative code
2015-12-14 [AngularJS] Services, Factories, and Providers -- value & Providers
2015-12-14 [AngularJS] Services, Factories, and Providers -- Service vs Factory
2014-12-14 [MongoDB] Query, update, index and group