Hash Tables

Group by Key

Build buckets keyed by a shared field, preserving the first-seen key order.

Algorithm

Canonical pairs (a,1), (b,2), (a,3), (c,4), (b,5) print {a: [1, 3], b: [2, 5], c: [4]}. The replay uses the same input in every language, so this C++ DSA implementation can be compared directly with the rest of the DSA track.

bucket map Each key owns a list. A new key creates a bucket; a repeated key appends to the existing bucket.

Basic Implementation

basic.cpp
Replay: real traced execution (multi-file project)
#include <iostream>
#include <map>
#include <string>
#include <vector>
using namespace std;

int main() {
    vector<pair<string, int>> pairs = {{"a", 1}, {"b", 2}, {"a", 3}, {"c", 4}, {"b", 5}};
    map<string, vector<int>> groups;
    vector<string> order;
    for (auto [key, value] : pairs) {
        if (groups.find(key) == groups.end()) {
            order.push_back(key);
        }
        groups[key].push_back(value);
    }
    cout << "{";
    for (size_t i = 0; i < order.size(); i++) {
        const string& key = order[i];
        if (i > 0) cout << ", ";
        cout << key << ": [";
        for (size_t j = 0; j < groups[key].size(); j++) {
            if (j > 0) cout << ", ";
            cout << groups[key][j];
        }
        cout << "]";
    }
    cout << "}\n";
}

  1. pairs ← [(a, 1), (b, 2), (a, 3), (c, 4), (b, 5)]

    1#include <iostream>2#include <map>
    values this step[(a, 1), (b, 2), (a, 3), (c, 4), (b, 5)]pairs

  2. groups ← {}

    8vector<pair<string, int>> pairs = {{"a", 1}, {"b", 2}, {"a", 3}, {"c", 4}, {"b", 5}};9map<string, vector<int>> groups;10vector<string> order;
    values this step{}groups

  3. groups ← {a: [1]}

    8vector<pair<string, int>> pairs = {{"a", 1}, {"b", 2}, {"a", 3}, {"c", 4}, {"b", 5}};9map<string, vector<int>> groups;10vector<string> order;
    values this step{} → {a: [1]}groupsakey1value

  4. groups ← {a: [1], b: [2]}

    8vector<pair<string, int>> pairs = {{"a", 1}, {"b", 2}, {"a", 3}, {"c", 4}, {"b", 5}};9map<string, vector<int>> groups;10vector<string> order;
    values this step{a: [1]} → {a: [1], b: [2]}groupsbkey2value

  5. groups ← {a: [1, 3], b: [2]}

    8vector<pair<string, int>> pairs = {{"a", 1}, {"b", 2}, {"a", 3}, {"c", 4}, {"b", 5}};9map<string, vector<int>> groups;10vector<string> order;
    values this step{a: [1], b: [2]} → {a: [1, 3], b: [2]}groupsakey3value

  6. groups ← {a: [1, 3], b: [2], c: [4]}

    8vector<pair<string, int>> pairs = {{"a", 1}, {"b", 2}, {"a", 3}, {"c", 4}, {"b", 5}};9map<string, vector<int>> groups;10vector<string> order;
    values this step{a: [1, 3], b: [2]} → {a: [1, 3], b: [2], c: [4]}groupsckey4value

  7. groups ← {a: [1, 3], b: [2, 5], c: [4]}

    8vector<pair<string, int>> pairs = {{"a", 1}, {"b", 2}, {"a", 3}, {"c", 4}, {"b", 5}};9map<string, vector<int>> groups;10vector<string> order;
    values this step{a: [1, 3], b: [2], c: [4]} → {a: [1, 3], b: [2, 5], c: [4]}groupsbkey5value

  8. stdout ← {a: [1, 3], b: [2, 5], c: [4]}

    1#include <iostream>2#include <map>
    values this step{a: [1, 3], b: [2, 5], c: [4]}stdout{a: [1, 3], b: [2, 5], c: [4]}groups

  9. bucket 1 after collision ← c -> a, degradation risk ← long chains can degrade lookup toward O(n)

    1#include <iostream>2#include <map>
    values this stepa → c -> abucket 1 after collisionlong chains can degrade lookup toward O(n)degradation riskresize or rehash when load factor growsmitigationcnew key

Complexity

  • Time: O(n) average
  • Space: O(k + n) for buckets and values

Implementation notes

  • Keep output formatting deterministic. Do not rely on unordered hash-map printing when the lesson needs cross-language comparison.
  • The trace highlights the hash table state after each write and includes a collision contrast where one bucket chain grows, showing why long chains can degrade lookup and why real tables resize or rehash.