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 Ruby 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.rb
Replay: real traced execution (multi-file project)
pairs = [["a", 1], ["b", 2], ["a", 3], ["c", 4], ["b", 5]]
groups = {}
pairs.each do |key, value|
  groups[key] ||= []
  groups[key] << value
end
parts = groups.map { |key, values| "#{key}: [#{values.join(', ')}]" }
puts "{#{parts.join(', ')}}"
  1. pairs ← [(a, 1), (b, 2), (a, 3), (c, 4), (b, 5)]

    1pairs = [["a", 1], ["b", 2], ["a", 3], ["c", 4], ["b", 5]]2groups = {}
    values this step[(a, 1), (b, 2), (a, 3), (c, 4), (b, 5)]pairs
  2. groups ← {}

    1pairs = [["a", 1], ["b", 2], ["a", 3], ["c", 4], ["b", 5]]2groups = {}3pairs.each do |key, value|
    values this step{}groups
  3. groups ← {a: [1]}

    1pairs = [["a", 1], ["b", 2], ["a", 3], ["c", 4], ["b", 5]]2groups = {}3pairs.each do |key, value|
    values this step{} {a: [1]}groupsakey1value
  4. groups ← {a: [1], b: [2]}

    1pairs = [["a", 1], ["b", 2], ["a", 3], ["c", 4], ["b", 5]]2groups = {}3pairs.each do |key, value|
    values this step{a: [1]} {a: [1], b: [2]}groupsbkey2value
  5. groups ← {a: [1, 3], b: [2]}

    1pairs = [["a", 1], ["b", 2], ["a", 3], ["c", 4], ["b", 5]]2groups = {}3pairs.each do |key, value|
    values this step{a: [1], b: [2]} {a: [1, 3], b: [2]}groupsakey3value
  6. groups ← {a: [1, 3], b: [2], c: [4]}

    1pairs = [["a", 1], ["b", 2], ["a", 3], ["c", 4], ["b", 5]]2groups = {}3pairs.each do |key, value|
    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]}

    1pairs = [["a", 1], ["b", 2], ["a", 3], ["c", 4], ["b", 5]]2groups = {}3pairs.each do |key, value|
    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]}

    1pairs = [["a", 1], ["b", 2], ["a", 3], ["c", 4], ["b", 5]]2groups = {}
    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)

    1pairs = [["a", 1], ["b", 2], ["a", 3], ["c", 4], ["b", 5]]2groups = {}
    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.