Are JavaScript Map Objects Indexed to Optimize map.get? [duplicate]

Answer 1

Yes, as you would expect from such a data type, a Map does utilize a hash-table under the hood.

Proof by source:

As always, the proof is in the source:

Excerpt from V8 source file src/objects.h class JSMap:

// The JSMap describes EcmaScript Harmony maps
class JSMap : public JSCollection {
 public:
  DECLARE_CAST(JSMap)

  static void Initialize(Handle<JSMap> map, Isolate* isolate);
  static void Clear(Handle<JSMap> map);

  // Dispatched behavior.
  DECLARE_PRINTER(JSMap)
  DECLARE_VERIFIER(JSMap)

 private:
  DISALLOW_IMPLICIT_CONSTRUCTORS(JSMap);
};

As we can see, JSMap extends JSCollection.

Now if we take a look at the declaration for JSCollection:

Excerpt from V8 source file src/objects.h class JSCollection:

class JSCollection : public JSObject {
 public:
  // [table]: the backing hash table
  DECL_ACCESSORS(table, Object)

  static const int kTableOffset = JSObject::kHeaderSize;
  static const int kSize = kTableOffset + kPointerSize;

 private:
  DISALLOW_IMPLICIT_CONSTRUCTORS(JSCollection);
};

Here we can see that it uses a hash table, with a nice comment to clarify it.

---

There was some question as to if that hash table refers only to object properties, and not to the get method. As we can from the source code to Map.prototype.get, a hash map is being used.

Excerpt from V8 source file src/js/collection.js MapGet:

function MapGet(key) {
  if (!IS_MAP(this)) {
    throw MakeTypeError(kIncompatibleMethodReceiver,
                        'Map.prototype.get', this);
  }
  var table = %_JSCollectionGetTable(this);
  var numBuckets = ORDERED_HASH_TABLE_BUCKET_COUNT(table);
  var hash = GetExistingHash(key);
  if (IS_UNDEFINED(hash)) return UNDEFINED;
  var entry = MapFindEntry(table, numBuckets, key, hash);
  if (entry === NOT_FOUND) return UNDEFINED;
  return ORDERED_HASH_MAP_VALUE_AT(table, entry, numBuckets);
}

Excerpt from V8 source file src/js/collection.js MapFindEntry:

function MapFindEntry(table, numBuckets, key, hash) {
  var entry = HashToEntry(table, hash, numBuckets);
  if (entry === NOT_FOUND) return entry;
  var candidate = ORDERED_HASH_MAP_KEY_AT(table, entry, numBuckets);
  if (key === candidate) return entry;
  var keyIsNaN = NumberIsNaN(key);
  while (true) {
    if (keyIsNaN && NumberIsNaN(candidate)) {
      return entry;
    }
    entry = ORDERED_HASH_MAP_CHAIN_AT(table, entry, numBuckets);
    if (entry === NOT_FOUND) return entry;
    candidate = ORDERED_HASH_MAP_KEY_AT(table, entry, numBuckets);
    if (key === candidate) return entry;
  }
  return NOT_FOUND;
}

Proof by benchmarking:

There is another way to test if it uses a hash map. Make many entries, and test what the longest and shortest lookup times are. Something like this:

'use strict';

let m = new Map();
let a = [];

for (let i = 0; i < 10000000; i++) {
    let o = {};
    m.set(o, i);
    a.push(o);
}

let lookupLongest = null;
let lookupShortest = null;

a.forEach(function(item) {
    let dummy;
    let before = Date.now();
    dummy = m.get(item);
    let after = Date.now();
    let diff = after - before;
    if (diff > lookupLongest || lookupLongest === null) {
        lookupLongest = diff;
    }
    if (diff < lookupShortest || lookupShortest === null) {
        lookupShortest = diff;
    }
});
console.log('Longest Lookup Time:', lookupLongest);
console.log('Shortest Lookup Time:', lookupShortest);

After a few seconds, I get the following output:

$ node test.js
Longest Lookup Time: 1
Shortest Lookup Time: 0

Such close lookup times would certainly not be possible if it where looping though every entry.