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 TypeScript 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.ts
Replay: real traced execution (multi-file project)
const pairs: Array<[string, number]> = [["a", 1], ["b", 2], ["a", 3], ["c", 4], ["b", 5]];
const groups = new Map<string, number[]>();
for (const [key, value] of pairs) {
if (!groups.has(key)) {
groups.set(key, []);
}
groups.get(key)!.push(value);
}
const parts: string[] = [];
for (const [key, values] of groups) {
parts.push(`${key}: [${values.join(", ")}]`);
}
console.log(`{${parts.join(", ")}}`);
pairs ← [(a, 1), (b, 2), (a, 3), (c, 4), (b, 5)]
1const pairs: Array<[string, number]> = [["a", 1], ["b", 2], ["a", 3], ["c", 4], ["b", 5]];2const groups = new Map<string, number[]>();values this step[(a, 1), (b, 2), (a, 3), (c, 4), (b, 5)]pairsgroups ← {}
1const pairs: Array<[string, number]> = [["a", 1], ["b", 2], ["a", 3], ["c", 4], ["b", 5]];2const groups = new Map<string, number[]>();3for (const [key, value] of pairs) {values this step{}groupsgroups ← {a: [1]}
1const pairs: Array<[string, number]> = [["a", 1], ["b", 2], ["a", 3], ["c", 4], ["b", 5]];2const groups = new Map<string, number[]>();3for (const [key, value] of pairs) {values this step{} → {a: [1]}groupsakey1valuegroups ← {a: [1], b: [2]}
1const pairs: Array<[string, number]> = [["a", 1], ["b", 2], ["a", 3], ["c", 4], ["b", 5]];2const groups = new Map<string, number[]>();3for (const [key, value] of pairs) {values this step{a: [1]} → {a: [1], b: [2]}groupsbkey2valuegroups ← {a: [1, 3], b: [2]}
1const pairs: Array<[string, number]> = [["a", 1], ["b", 2], ["a", 3], ["c", 4], ["b", 5]];2const groups = new Map<string, number[]>();3for (const [key, value] of pairs) {values this step{a: [1], b: [2]} → {a: [1, 3], b: [2]}groupsakey3valuegroups ← {a: [1, 3], b: [2], c: [4]}
1const pairs: Array<[string, number]> = [["a", 1], ["b", 2], ["a", 3], ["c", 4], ["b", 5]];2const groups = new Map<string, number[]>();3for (const [key, value] of pairs) {values this step{a: [1, 3], b: [2]} → {a: [1, 3], b: [2], c: [4]}groupsckey4valuegroups ← {a: [1, 3], b: [2, 5], c: [4]}
1const pairs: Array<[string, number]> = [["a", 1], ["b", 2], ["a", 3], ["c", 4], ["b", 5]];2const groups = new Map<string, number[]>();3for (const [key, value] of pairs) {values this step{a: [1, 3], b: [2], c: [4]} → {a: [1, 3], b: [2, 5], c: [4]}groupsbkey5valuestdout ← {a: [1, 3], b: [2, 5], c: [4]}
1const pairs: Array<[string, number]> = [["a", 1], ["b", 2], ["a", 3], ["c", 4], ["b", 5]];2const groups = new Map<string, number[]>();values this step{a: [1, 3], b: [2, 5], c: [4]}stdout{a: [1, 3], b: [2, 5], c: [4]}groupsbucket 1 after collision ← c -> a, degradation risk ← long chains can degrade lookup toward O(n)
1const pairs: Array<[string, number]> = [["a", 1], ["b", 2], ["a", 3], ["c", 4], ["b", 5]];2const groups = new Map<string, number[]>();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.