I read this:

• How to optimize Firebase Realtime Database calls to improve performance?

Where it is said that to optimize performance we have to duplicate data. So I created a section in the database called users to hold all user objects:

users
 \
  uid
   \
    -- name: "john"
   \
    -- email: "[email protected]"
   \
    -- age: 22

And a section to hold only the uid of the users:

uids
 \
  --- uid: true
 \
  --- uid: true

I have over 1250 users. What I need is to select 10 random users and display their data in the UI. I do that by reading the uids node, and I generate 10 random uids. Now for each one I create database request to read the details of the users. The problem is that each request takes ~ 1 second. To get 10 users, it takes 10 seconds. That's too much. How can I optimize this process?

Code:

while (userList.size < 10) {
    val randomId = Random.nextInt(userIdsList.size)
    val randomUser = usersRef.child(questionIdsList[randomId]).get().await().getValue(User::class.java)
    if (!userList.contains(randomUser)) {
        userList.add(randomUser)
    }
}

It looks to me that .await() gets the users one after another and not in parallel. Any ideas?

CodePudding user response：

You are right, users come one by one, not in parallel. To achieve the parallelism you can use a couple of features from kotlinx-coroutines-play-services library:

val tasks: MutableList<Deferred<DataSnapshot>> = mutableListOf()
for (i in 1..10) {
    val randomId = Random.nextInt(i)
    val deferredTask = usersRef.child(questionIdsList[randomId]).get().asDeferred()
    tasks.add(deferredTask)
}

tasks.awaitAll().forEach { dataSnapshot ->
    val randomUser = dataSnapshot.getValue(User::class.java)
    if (!userList.contains(randomUser)) {
        userList.add(randomUser)
    }
}

Using asDeferred extension function we can convert a Task into a Deferred.

And then using awaitAll() extension function on Collection<Deferred<T>> we will wait while all users are loaded in parallel.