Many realtime apps have documents that act as counters. For example, you might count 'likes' on a post, or 'favorites' of a specific item.
In Cloud Firestore, you can only update a single document about once per second, which might be too low for some high-traffic applications.
Solution: Distributed counters
To support more frequent counter updates, create a distributed counter. Each counter is a document with a subcollection of "shards," and the value of the counter is the sum of the value of the shards.
Write throughput increases linearly with the number of shards, so a distributed counter with 10 shards can handle 10x as many writes as a traditional counter.
Web
// counters/${ID}
{
"num_shards": NUM_SHARDS,
"shards": [subcollection]
}
// counters/${ID}/shards/${NUM}
{
"count": 123
}
Swift
// counters/${ID}
struct Counter {
let numShards: Int
init(numShards: Int) {
self.numShards = numShards
}
}
// counters/${ID}/shards/${NUM}
struct Shard {
let count: Int
init(count: Int) {
self.count = count
}
}
Android
// counters/${ID}
public class Counter {
int numShards;
public Counter(int numShards) {
this.numShards = numShards;
}
}
// counters/${ID}/shards/${NUM}
public class Shard {
int count;
public Shard(int count) {
this.count = count;
}
}
The following code initializes a distributed counter:
Web
function createCounter(ref, num_shards) {
var batch = db.batch();
// Initialize the counter document
batch.set(ref, { num_shards: num_shards });
// Initialize each shard with count=0
for (let i = 0; i < num_shards; i++) {
let shardRef = ref.collection('shards').doc(i.toString());
batch.set(shardRef, { count: 0 });
}
// Commit the write batch
return batch.commit();
}
Swift
func createCounter(ref: DocumentReference, numShards: Int) {
ref.setData(["numShards": numShards]){ (err) in
for i in 0...numShards {
ref.collection("shards").document(String(i)).setData(["count": 0])
}
}
}
Android
public Task<Void> createCounter(final DocumentReference ref, final int numShards) {
// Initialize the counter document, then initialize each shard.
return ref.set(new Counter(numShards))
.continueWithTask(new Continuation<Void, Task<Void>>() {
@Override
public Task<Void> then(@NonNull Task<Void> task) throws Exception {
if (!task.isSuccessful()) {
throw task.getException();
}
List<Task<Void>> tasks = new ArrayList<>();
// Initialize each shard with count=0
for (int i = 0; i < numShards; i++) {
Task<Void> makeShard = ref.collection("shards")
.document(String.valueOf(i))
.set(new Shard(0));
tasks.add(makeShard);
}
return Tasks.whenAll(tasks);
}
});
}
To increment the counter, choose a random shard and increment the count in a transaction:
Web
function incrementCounter(db, ref, num_shards) {
// Select a shard of the counter at random
const shard_id = Math.floor(Math.random() * num_shards).toString();
const shard_ref = ref.collection('shards').doc(shard_id);
// Update count in a transaction
return db.runTransaction(t => {
return t.get(shard_ref).then(doc => {
const new_count = doc.data().count + 1;
t.update(shard_ref, { count: new_count });
});
});
}
Swift
func incrementCounter(ref: DocumentReference, numShards: Int) {
// Select a shard of the counter at random
let shardId = Int(arc4random_uniform(UInt32(numShards)))
let shardRef = ref.collection("shards").document(String(shardId))
// Update count in a transaction
db.runTransaction({ (transaction, errorPointer) -> Any? in
do {
let shardData = try transaction.getDocument(shardRef).data() ?? [:]
let shardCount = shardData["count"] as! Int
transaction.updateData(["count": shardCount + 1], forDocument: shardRef)
} catch {
// Error getting shard data
// ...
}
return nil
}) { (object, err) in
// ...
}
}
Android
public Task<Void> incrementCounter(final DocumentReference ref, final int numShards) {
int shardId = (int) Math.floor(Math.random() * numShards);
final DocumentReference shardRef = ref.collection("shards").document(String.valueOf(shardId));
return db.runTransaction(new Transaction.Function<Void>() {
@Override
public Void apply(Transaction transaction) throws FirebaseFirestoreException {
Shard shard = transaction.get(shardRef).toObject(Shard.class);
shard.count += 1;
transaction.set(shardRef, shard);
return null;
}
});
}
To get the total count, query for all shards and sum their count fields:
Web
function getCount(ref) {
// Sum the count of each shard in the subcollection
return ref.collection('shards').get().then(snapshot => {
let total_count = 0;
snapshot.forEach(doc => {
total_count += doc.data().count;
});
return total_count;
});
}
Swift
func getCount(ref: DocumentReference) {
ref.collection("shards").getDocuments() { (querySnapshot, err) in
var totalCount = 0
if err != nil {
// Error getting shards
// ...
} else {
for document in querySnapshot!.documents {
let count = document.data()["count"] as! Int
totalCount += count
}
}
print("Total count is \(totalCount)")
}
}
Android
public Task<Integer> getCount(final DocumentReference ref) {
// Sum the count of each shard in the subcollection
return ref.collection("shards").get()
.continueWith(new Continuation<QuerySnapshot, Integer>() {
@Override
public Integer then(@NonNull Task<QuerySnapshot> task) throws Exception {
int count = 0;
for (DocumentSnapshot snap : task.getResult()) {
Shard shard = snap.toObject(Shard.class);
count += shard.count;
}
return count;
}
});
}
Limitations
The solution shown above is a scalable way to create shared counters in Cloud Firestore, but you should be aware of the following limitations:
- Shard count - The number of shards controls the performance of the distributed counter. With too few shards, some transactions may have to retry before succeeding, which will slow writes. With too many shards, reads become slower and more expensive.
- Cost - The cost of reading a counter value increases linearly with the number of shards, because the entire shards subcollection must be loaded.
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