I'm having a really hard time understanding how Nosql works so I hope someone can help me understand it a bit better.
I'm trying to make a simple chat application (One to one chat support and chat groups) and want to dislay a list of all the conversations that the current user is in. This is my table for it.
I tried getting the data in several ways. But what I currently have is this (Which should work according to the internet, but doesn't).
_membersRef.equalTo(1508, key: '1508').once().then((DataSnapshot snap) {
print(snap.value);
});
I also tried
_membersRef.startAt(1508).endAt(1508).once().then((DataSnapshot snap) {
print(snap.value);
});
What I want my code to do is return all records that have my account_id in them (1508 in this case). So it should return the record "one".
So if I change the uid in the code to 1509 it should return "One" and "two". How can I make this happen?
To get the key one try this:
_membersRef.orderByChild('1508').equalTo(true).once().then((DataSnapshot snap) {
print(snap.value);
});
the snapshot is at child members then you order it according to child 1508 which is equalTo(true).
Related
Firebase Realtime Database Overrides my Data at a location even when I use .push() method. The little-concrete knowledge I have about writing to Firebase Realtime database is that writing to Firebase real time database can be done in few several ways. Two of the most prominent are the
set() and 2. push() method.
The long story short, push() is used to create a new key for a data to be written and it adds data to the node.
So fine, firebase has being co-operating with me in my previous projects but in this, I have no idea what is going on. I have tried different blends of push and set to achieve my goal but no progress so far.
In the code below, what I want to achieve is 2 things, write to a location chatUID, message and time only once, but write severally '-MqBBXPzUup7czdG2xCI' all under the same node "firebaseGeneratedId1" ->
A better structure is below.
Help with code. Thanks.
UPDATE
Here is my code
The writers reference
_listeningMsgRef = _msgDatabase
.reference()
.child('users')
.child(userId)
.child('chats')
.child(chatUIDConcat);
When a user hits sendMessage, here is the function called
void sendMessage() {
_messageController.clear();
var timeSent = DateTime.now().toString();
//Send
Map msgMap = {
'message': msg,
'sender': userId,
'time': timeSent,
'chatUID': chatUIDConcat
};
//String _key = _listeningMsgRef.push().key;
_listeningMsgRef.child(chatUIDConcat).set().whenComplete(() {
SnackBar snackBar = const SnackBar(content: Text('Message sent'));
ScaffoldMessenger.of(context).showSnackBar(snackBar);
DatabaseReference push = _listeningMsgRef.child(chatUIDConcat).push().set(msgMap);
});
}
The idea about the sendMessage function, is to write
chatUID:"L8pacdUOOohuTlifrNYC3JALQgh2+q5D38xPXVBTwmwb5Hq..."
message: "I'm coming"
newMessage: "true"
sender: "L8pacdUOOohuTlifrNYC3JALQgh2"
When it is complete, then push new nodes under the user nodes.
EDIT:
I later figured out the issue. I wasn't able to achieve my goal because I was a bit tensed while doing that project. The issue was I was wanted to write new data into the '-MqBBXPzUup7czdG2xCI' node without overwriting the old data in it.
The solution is straight forward. I just needed to ensure I wrote data in that node as new nodes under it. Nothing much, thanks
Frank van Puffelen for your assistance.
Paths in Firebase Realtime Database are automatically created when you write any data under then, and deleted when you remove the last data under them.
So you don't need to first create the node for the chat room. Instead, it gets auto-created when you write the first message into it with _listeningMsgRef.child(chatUIDConcat).push().set(msgMap)
I'm working with Flutter and Firebase (Real-time database). There is some data stored in the db and I want to compare the email (child) of the parent and only want to display the parents containing that particular email. Currently, it is fetching all rows. I think fetching through key value pair would do the work. But I dont know the syntax and unable to find help regarding it. Please help me out.
void myfunc() {
databaseReference.once().then((DataSnapshot snapshot) {
print('Data : ${snapshot.value}');
});
}
try with
yourRef.orderByChild("email").equalTo('abs#abc.com');
Read Query Data
I have been trying to get arrays working in Firebase, and I am aware that there are a lot of references and discussions about this online, and I have read through all of these and none of it works.
First off, the Firebase side. The structure containing the array and two example strings inside it:
Firebase Structure
collection -> document -> fields
userData profileImages URLs (array)
: https://firebasestorage.googleapis.com/v0/b/app-138804.appspot.com/o/jRwscYWLs1DySLMz7jn5Yo2%2Fprofile%2Fimage_picker4459623138678.jpg?alt=media&token=ec1043b-0120-be3c-8e142417
: https://firebasestorage.googleapis.com/v0/b/app-138804.appspot.com/o/jRwscYWLs3872yhdjn5Yo2%2Fprofile%2Fimage_picker445929873mfd38678.jpg?alt=media&token=ec3213b-0120-be9c-8e112632
The first issue I am facing is writing to this array in the database:
Firestore.instance.collection('userData').document('profileImages').updateData({
'URLs': _uploadedFileURL,
});
Whenever I add data to this array, it just overwrites the existing data. I need to be able to keep all the existing data intact and simply add the current new line to the array.
Once this is working, I then need to be able to return all of the strings in this array without needing to know how many of them there will be.
For this part, I basically have nothing at this point. I could show some of the things I have tried based on suggestions from other articles on this, but none of it is even close to working correctly.
im assuming that _uploadedFileURL is a String, and you are updating the property URLs, that's why your data gets overwritten, because you are changing the URLs value to a single string which is _uploadedFileURL. to solve this issue, simply get the current data inside profileImages before commiting the update. like so
final DocumentSnapshot currentData = await Firestore.instance.collection('userData').document('profileImages').get();
Firestore.instance.collection('userData').document('profileImages').updateData({
'URLs': [
...currentData.data['URLs'],
_uploadedFileURL
],
});
and for the second part of your question, all you need is to query for the profileImages
Future<List<String>> _getProfileImages() {
final document = Firestore.instance.collection('userData').document('profileImages').get();
return document.data['profileImages]
}
the result of the get method will be a DocumentSnapshot, and inside the data property will access the profileImages which is a List<String>.
Ok guys and girls I have worked this out. Part 1: appending data to an array in Firebase.
Firestore.instance.collection('userData').document('profileImages').updateDataupdateData({
'URLs':FieldValue.arrayUnion([_uploadedFileURL]),
});
Where _uploadedFileURL is basically a string, for these purposes. Now I have read that arrayUnion, which is super groovy, is only available in Cloud Firestore, and not the Realtime Database. I use Cloud Firestore so it works for me but if you are having issues this might be why.
Now what is extra groovy about Cloud Firestore is that you can similarly remove an element from the array using:
Firestore.instance.collection('userData').document('profileImages').updateDataupdateData({
'URLs':FieldValue.arrayRemove([_uploadedFileURL]),
});
So how to get this data back out again. A simple way I have found to get that data and chuck it into a local array is like so:
List imageURLlist = [];
DocumentReference document = Firestore.instance.collection('userData').document('profileImages');
DocumentSnapshot snapshot = await document.get();
setState(() {
imageURLlist = snapshot.data['URLs'];
});
From here at least you have the data, can add to it, can remove from it and this can be a platform for you to figure out what you want to do with it.
I'm currently creating a dashboard application for my main application, this dashboard is able to display in charts the demography of the users that uses the app. I use Firebase Database as the backend. The JSON tree of my DB is as shown below. My question is, how do I get the amount of data with a specific value of a key? Example: the number of children with the value 'Pria' for the key 'jk' is 2.
My Backend JSON Tree:
So far, I'm able to get all of the data using:
DatabaseReference itemRef = FirebaseDatabase.instance.reference().child('data_pengguna');
And I've also tried the codes below, but it doesn't seem to work:
int jmlPria;
FirebaseDatabase.instance
.reference()
.child('data_pengguna')
.orderByChild('jk')
.equalTo('Pria')
.once()
.then((onValue) {
Map data = onValue.value;
jmlPria = data.length;
});
But I haven't successfully filtered the data and put it inside a variable, can anyone help me?
Many thanks in advance.
That last snippet looks correct, jmlPria should have the number of children.
But the value of jmlPria will only be set to the latest value inside the then() callback. Make sure that Text($jmlPria) is inside the then() callback. Outside of that, jmlPria will not have the correct value.
Also see Doug's great blog post on asynchronous programming.
I've read the Firebase docs on Stucturing Data. Data storage is cheap, but the user's time is not. We should optimize for get operations, and write in multiple places.
So then I might store a list node and a list-index node, with some duplicated data between the two, at very least the list name.
I'm using ES6 and promises in my javascript app to handle the async flow, mainly of fetching a ref key from firebase after the first data push.
let addIndexPromise = new Promise( (resolve, reject) => {
let newRef = ref.child('list-index').push(newItem);
resolve( newRef.key()); // ignore reject() for brevity
});
addIndexPromise.then( key => {
ref.child('list').child(key).set(newItem);
});
How do I make sure the data stays in sync in all places, knowing my app runs only on the client?
For sanity check, I set a setTimeout in my promise and shut my browser before it resolved, and indeed my database was no longer consistent, with an extra index saved without a corresponding list.
Any advice?
Great question. I know of three approaches to this, which I'll list below.
I'll take a slightly different example for this, mostly because it allows me to use more concrete terms in the explanation.
Say we have a chat application, where we store two entities: messages and users. In the screen where we show the messages, we also show the name of the user. So to minimize the number of reads, we store the name of the user with each chat message too.
users
so:209103
name: "Frank van Puffelen"
location: "San Francisco, CA"
questionCount: 12
so:3648524
name: "legolandbridge"
location: "London, Prague, Barcelona"
questionCount: 4
messages
-Jabhsay3487
message: "How to write denormalized data in Firebase"
user: so:3648524
username: "legolandbridge"
-Jabhsay3591
message: "Great question."
user: so:209103
username: "Frank van Puffelen"
-Jabhsay3595
message: "I know of three approaches, which I'll list below."
user: so:209103
username: "Frank van Puffelen"
So we store the primary copy of the user's profile in the users node. In the message we store the uid (so:209103 and so:3648524) so that we can look up the user. But we also store the user's name in the messages, so that we don't have to look this up for each user when we want to display a list of messages.
So now what happens when I go to the Profile page on the chat service and change my name from "Frank van Puffelen" to just "puf".
Transactional update
Performing a transactional update is the one that probably pops to mind of most developers initially. We always want the username in messages to match the name in the corresponding profile.
Using multipath writes (added on 20150925)
Since Firebase 2.3 (for JavaScript) and 2.4 (for Android and iOS), you can achieve atomic updates quite easily by using a single multi-path update:
function renameUser(ref, uid, name) {
var updates = {}; // all paths to be updated and their new values
updates['users/'+uid+'/name'] = name;
var query = ref.child('messages').orderByChild('user').equalTo(uid);
query.once('value', function(snapshot) {
snapshot.forEach(function(messageSnapshot) {
updates['messages/'+messageSnapshot.key()+'/username'] = name;
})
ref.update(updates);
});
}
This will send a single update command to Firebase that updates the user's name in their profile and in each message.
Previous atomic approach
So when the user change's the name in their profile:
var ref = new Firebase('https://mychat.firebaseio.com/');
var uid = "so:209103";
var nameInProfileRef = ref.child('users').child(uid).child('name');
nameInProfileRef.transaction(function(currentName) {
return "puf";
}, function(error, committed, snapshot) {
if (error) {
console.log('Transaction failed abnormally!', error);
} else if (!committed) {
console.log('Transaction aborted by our code.');
} else {
console.log('Name updated in profile, now update it in the messages');
var query = ref.child('messages').orderByChild('user').equalTo(uid);
query.on('child_added', function(messageSnapshot) {
messageSnapshot.ref().update({ username: "puf" });
});
}
console.log("Wilma's data: ", snapshot.val());
}, false /* don't apply the change locally */);
Pretty involved and the astute reader will notice that I cheat in the handling of the messages. First cheat is that I never call off for the listener, but I also don't use a transaction.
If we want to securely do this type of operation from the client, we'd need:
security rules that ensure the names in both places match. But the rules need to allow enough flexibility for them to temporarily be different while we're changing the name. So this turns into a pretty painful two-phase commit scheme.
change all username fields for messages by so:209103 to null (some magic value)
change the name of user so:209103 to 'puf'
change the username in every message by so:209103 that is null to puf.
that query requires an and of two conditions, which Firebase queries don't support. So we'll end up with an extra property uid_plus_name (with value so:209103_puf) that we can query on.
client-side code that handles all these transitions transactionally.
This type of approach makes my head hurt. And usually that means that I'm doing something wrong. But even if it's the right approach, with a head that hurts I'm way more likely to make coding mistakes. So I prefer to look for a simpler solution.
Eventual consistency
Update (20150925): Firebase released a feature to allow atomic writes to multiple paths. This works similar to approach below, but with a single command. See the updated section above to read how this works.
The second approach depends on splitting the user action ("I want to change my name to 'puf'") from the implications of that action ("We need to update the name in profile so:209103 and in every message that has user = so:209103).
I'd handle the rename in a script that we run on a server. The main method would be something like this:
function renameUser(ref, uid, name) {
ref.child('users').child(uid).update({ name: name });
var query = ref.child('messages').orderByChild('user').equalTo(uid);
query.once('value', function(snapshot) {
snapshot.forEach(function(messageSnapshot) {
messageSnapshot.update({ username: name });
})
});
}
Once again I take a few shortcuts here, such as using once('value' (which is in general a bad idea for optimal performance with Firebase). But overall the approach is simpler, at the cost of not having all data completely updated at the same time. But eventually the messages will all be updated to match the new value.
Not caring
The third approach is the simplest of all: in many cases you don't really have to update the duplicated data at all. In the example we've used here, you could say that each message recorded the name as I used it at that time. I didn't change my name until just now, so it makes sense that older messages show the name I used at that time. This applies in many cases where the secondary data is transactional in nature. It doesn't apply everywhere of course, but where it applies "not caring" is the simplest approach of all.
Summary
While the above are just broad descriptions of how you could solve this problem and they are definitely not complete, I find that each time I need to fan out duplicate data it comes back to one of these basic approaches.
To add to Franks great reply, I implemented the eventual consistency approach with a set of Firebase Cloud Functions. The functions get triggered whenever a primary value (eg. users name) gets changed, and then propagate the changes to the denormalized fields.
It is not as fast as a transaction, but for many cases it does not need to be.