var Component=(()=>{var x=Object.create;var m=Object.defineProperty;var C=Object.getOwnPropertyDescriptor;var q=Object.getOwnPropertyNames;var I=Object.getPrototypeOf,T=Object.prototype.hasOwnProperty;var w=t=>m(t,"__esModule",{value:!0});var M=(t,r)=>()=>(r||t((r={exports:{}}).exports,r),r.exports),j=(t,r)=>{w(t);for(var h in r)m(t,h,{get:r[h],enumerable:!0})},O=(t,r,h)=>{if(r&&typeof r=="object"||typeof r=="function")for(let n of q(r))!T.call(t,n)&&n!=="default"&&m(t,n,{get:()=>r[n],enumerable:!(h=C(r,n))||h.enumerable});return t},N=t=>O(w(m(t!=null?x(I(t)):{},"default",t&&t.__esModule&&"default"in t?{get:()=>t.default,enumerable:!0}:{value:t,enumerable:!0})),t);var k=M((W,S)=>{S.exports=_jsx_runtime});var A={};j(A,{Highlight:()=>l,default:()=>E,frontmatter:()=>H});var e=N(k()),H={title:"HashMaps",date:"2024-12-07",lastmod:"2026-07-31",tags:["Algorithms","hash table","array"],draft:!1,summary:"3 Problems",images:[],layout:"QuestionsPostLayout",readTime:"3 Popular Problems",canonicalUrl:"https://codewithlucian.com/coding/hashing",thumbnail:"/static/images/codingInterview/hashmap2.svg"},l=({children:t,color:r})=>(0,e.jsx)("span",{style:{backgroundColor:r,borderRadius:"2px",color:"#fff",padding:"0.2rem"},children:t});function _(t={}){let{wrapper:r}=t.components||{};return r?(0,e.jsx)(r,Object.assign({},t,{children:(0,e.jsx)(h,{})})):h();function h(){let n=Object.assign({section:"section",p:"p",h2:"h2",a:"a",span:"span",strong:"strong",h4:"h4",hr:"hr",ol:"ol",li:"li",ul:"ul",code:"code",h3:"h3",blockquote:"blockquote",em:"em"},t.components),{ProgressProvider:g,ProgressWrapper:f,TopicScope:y,SimpleCollapsibleSection:s,SimpleSectionTitle:c,TextContainer:o,Image:b,CollapsibleQuestionsWrapper:v,CollapsibleSection:d,SectionTitle:u,TabItem:i,Tabs:p}=n;return v||a("CollapsibleQuestionsWrapper",!0),d||a("CollapsibleSection",!0),b||a("Image",!0),g||a("ProgressProvider",!0),f||a("ProgressWrapper",!0),u||a("SectionTitle",!0),s||a("SimpleCollapsibleSection",!0),c||a("SimpleSectionTitle",!0),i||a("TabItem",!0),p||a("Tabs",!0),o||a("TextContainer",!0),y||a("TopicScope",!0),(0,e.jsxs)(n.section,{className:"h0Wrapper headingWrapper",children:[" "," ",(0,e.jsxs)(g,{slug:"hashmap",children:[(0,e.jsx)(f,{}),(0,e.jsx)(y,{children:(0,e.jsx)(n.p,{children:"Covers hash-map fundamentals and the existing guided problems: key-value storage, hashing, collisions, lookup complexity, and recognizing when a hash-based solution improves an algorithm."})}),(0,e.jsxs)(n.h2,{id:"theory",children:[(0,e.jsx)(n.a,{href:"#theory","aria-hidden":"true",tabIndex:"-1",children:(0,e.jsx)(n.span,{className:"icon icon-link"})}),"Theory"]}),(0,e.jsxs)(s,{children:[(0,e.jsxs)(c,{children:["What is a ",(0,e.jsx)(n.strong,{children:"hashmap"}),"?"]}),(0,e.jsxs)(o,{children:[(0,e.jsxs)(n.h4,{id:"definition",children:[(0,e.jsx)(n.a,{href:"#definition","aria-hidden":"true",tabIndex:"-1",children:(0,e.jsx)(n.span,{className:"icon icon-link"})}),"Definition"]}),(0,e.jsxs)(n.p,{children:["A ",(0,e.jsx)(n.strong,{children:"hash map"})," (or hash table) is a data structure that maps keys to values, enabling highly efficient lookups. While there are various ways to implement a hash table, we\u2019ll focus on a simple yet common implementation."]}),(0,e.jsx)(n.hr,{})]})]}),(0,e.jsxs)(s,{children:[(0,e.jsx)(c,{children:"How does it work?"}),(0,e.jsxs)(o,{children:[(0,e.jsx)(b,{alt:"hashing",src:"/static/images/codingInterview/HashMap.svg",className:"m-2 p-2",width:800,height:250}),(0,e.jsx)(n.ol,{children:(0,e.jsxs)(n.li,{children:[(0,e.jsx)(n.strong,{children:"Insert Operation"}),":"]})}),(0,e.jsxs)(n.ul,{children:[(0,e.jsxs)(n.li,{children:[(0,e.jsx)(l,{color:"#1877F2",children:"Compute the Hash Code"}),": For a given key (which could be a string or any data type), calculate its hash code. The hash code is typically an integer or long value. 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We traverse the array once."]})}),(0,e.jsx)(n.p,{children:(0,e.jsx)(n.strong,{children:"Space Complexity:"})}),(0,e.jsx)(n.ul,{children:(0,e.jsxs)(n.li,{children:[(0,e.jsx)(n.code,{children:"O(N)"})," in the worst case, as we might need to store all 'n' numbers in the hashmap."]})}),(0,e.jsxs)(n.h4,{id:"code-solution",children:[(0,e.jsx)(n.a,{href:"#code-solution","aria-hidden":"true",tabIndex:"-1",children:(0,e.jsx)(n.span,{className:"icon icon-link"})}),"Code Solution"]}),(0,e.jsxs)(p,{children:[(0,e.jsx)(i,{label:"Python",language:"python",code:`def twoSum(self, nums: List[int], target: int) -> List[int]: num_dict = {} for i, num in enumerate(nums): complement = target - num if complement in num_dict: return [num_dict[complement], i] num_dict[num] = i return []`}),(0,e.jsx)(i,{label:"Javascript",language:"javascript",code:`var twoSum = function(nums, target) { const numMap = new Map(); for (let i = 0; i < nums.length; i++) { const complement = target - nums[i]; if (numMap.has(complement)) { return [numMap.get(complement), i]; } numMap.set(nums[i], i); } return []; };`}),(0,e.jsx)(i,{label:"Java",language:"javascript",code:`public int[] twoSum(int[] nums, int target) { HashMap numMap = new HashMap<>(); for (int i = 0; i < nums.length; i++) { int complement = target - nums[i]; if (numMap.containsKey(complement)) { return new int[]{numMap.get(complement), i}; } numMap.put(nums[i], i); } return new int[0]; }`})]}),(0,e.jsx)(n.hr,{})]})]}),(0,e.jsxs)(s,{children:[(0,e.jsx)(c,{children:"Solution Q2"}),(0,e.jsxs)(o,{children:[(0,e.jsxs)(n.p,{children:[(0,e.jsx)(n.strong,{children:"Solution Overview:"})," The solution involves comparing the character frequency of each letter in both strings. 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