Simple question:
Will all obersvers automatically removed when I use goOffline (disconnect to firebase) ?
If not, is there another way to do it, because removeAllOberserves doesn't seem to work or must I keep an array of single handles?
UPDATE
I answer myself.
removeAllOberserves works well, if you call it with the reference you used to set the observer!
Example:
Firebase *userThreadRef;
userThreadRef = [userRef appendPathComponent: ThreadsPath];
[userThreadRef observeEventType: FEventTypeChildAdded withBlock: ^(FDataSnapshot *snapshot) {
...
}];
....
[userThreadRef removeAllObservers];
Do not use a new reference like this:
Firebase *newUserThreadRef = [userRef appendPathComponent: ThreadsPath];
[newUserThreadRef removeAllObservers];
Will all observers automatically removed when I use goOffline (disconnect to firebase) ?
No. Calling goOffline() will not automatically remove observers/listeners.
is there another way to do it, because removeAllOberserves doesn't seem to work or must I keep an array of single handles?
It's hard to say without seeing your code, but likely your expectations are just wrong.
You'll need to call removeAllObservers() on each reference. The All in the method name is for the fact that it removes the observers for all event types, not for all references.
Related
When writing event based cloud functions for firebase firestore it's common to update fields in the affected document, for example:
When a document of users collection is updated a function will trigger, let's say we want to determine the user info state and we have a completeInfo: boolean property, the function will have to perform another update so that the trigger will fire again, if we don't use a flag like needsUpdate: boolean to determine if excecuting the function we will have an infinite loop.
Is there any other way to approach this behavior? Or the situation is a consequence of how the database is designed? How could we avoid ending up in such scenario?
I have a few common approaches to Cloud Functions that transform the data:
Write the transformed data to a different document than the one that triggers the Cloud Function. This is by far the easier approach, since there is no additional code needed - and thus I can't make any mistakes in it. It also means there is no additional trigger, so you're not paying for that extra invocation.
Use granular triggers to ensure my Cloud Function only gets called when it needs to actually do some work. For example, many of my functions only need to run when the document gets created, so by using an onCreate trigger I ensure my code only gets run once, even if it then ends up updating the newly created document.
Write the transformed data into the existing document. In that case I make sure to have the checks for whether the transformation is needed in place before I write the actual code for the transformation. I prefer to not add flag fields, but use the existing data for this check.
A recent example is where I update an amount in a document, which then needs to be fanned out to all users:
exports.fanoutAmount = functions.firestore.document('users/{uid}').onWrite((change, context) => {
let old_amount = change.before && change.before.data() && change.before.data().amount ? change.before.data().amount : 0;
let new_amount = change.after.data().amount;
if (old_amount !== new_amount) {
// TODO: fan out to all documents in the collection
}
});
You need to take care to avoid writing a function that triggers itself infinitely. This is not something that Cloud Functions can do for you. Typically you do this by checking within your function if the work was previously done for the document that was modified in a previous invocation. There are several ways to do this, and you will have to implement something that meets your specific use case.
I would take this approach from an execution time perspective, this means that the function for each document will be run twice. Each time when the document is triggered, a field lastUpdate would be there with a timestamp and the function only updates the document if the time is older than my time - eg 10 seconds.
I am using the firebase-tools shell CLI to test Firestore cloud functions.
My functions respond to the onCreate trigger for all documents in a certain collection, by using a wildcard, and then mutate that document with an update call.
firestore
.document(`myCollection/{documentId}`)
.onCreate(event => {
const ref = event.data.ref
return ref.update({ some: "mutation"})
})
In the shell I run something like this, (passing some fake auth data required by my database permissions):
myFunction({some: "data"}, { auth: { variable: { uid: "jj5BpbX2PxU7fQn87z10d4Ks6oA3" } } } )
Hoever this results in an error, because the update tries to mutate a document that is not in the database.
Error: no entity to update
In the documentation about unit testing it is explained how you would create mocks for event.data in order to execute the function without touching the actual database.
However I am trying to invoke a real function which should operate on the database. A mock would not make sense, otherwise this is nothing more then a unit test.
I'm wondering what the strategy should be for invoking a function like this?
By using an existing id of a document the function can execute successfully, but this seems cumbersome because you need look it up in the database for every test, and it might not be there anymore at some point.
I think it would be very helpful if the shell would somehow create a new document from the data you pass in, and run the trigger from that. Would this be possible maybe, or is there another way?
The Cloud Functions emulator can only emulate events that could happen within your project. It doesn't emulate the actual change to the database that would have triggered it.
As you're discovering, when your function depends on that actual change previously occurring, you can run into problems. The fact of the matter is that it's entirely possible that the created document may have already been deleted by the time you're handling the event in the function (imagine a user acts quickly to delete, but the event is delayed for whatever reason).
All that said, perhaps you want to use set() with SetOptions that indicate you want to merge instead of overwrite. Bear in mind that if the document was previously deleted (with good reason) before the event triggered, you'll unconditionally recreate the document, which may not be what the user wanted.
I'm doing the newbie tutorial 'simple-todo' and noticed that once I added security in step 9, I was no longer able to delete tasks created before that.
The issue is that my remove method is checking to make sure that the ID it receives is a string, and the to-do tasks that were made earlier via the console return an object when I use this_.id.
In other words:
Tasks created via the terminal, this._id -> ObjectId("57a128afbe5fd7e7ba9a6fca")
Tasks created with the Tasks.insert method, this._id -> "57a128afbe5fd7e7ba9a6fca"
And the new remove method doesn't like the ObjectId part. How can I get just the ID? I would figure it'd be something like this._id._id, but that's undefined. The workaround was to remove the check from the "remove" method, which is less secure.
Link: https://www.meteor.com/tutorials/blaze/security-with-methods
You can use this._id._str to get the Hex part of the ObjectId.
I would suggest that your method only uses the string, and do a check in the client to see if you need to use this._id or this._id._str
In Meteor, I got a collection that the client subscribes to. In some cases, instead of publishing the documents that exists in the collection on the server, I want to send down some bogus data. Now that's fine using the this.added function in the publish.
My problem is that I want to treat the bogus doc as if it were a real document, specifically this gets troublesome when I want to update it. For the real docs I run a RealDocs.update but when doing that on the bogus doc it fails since there is no representation of it on the server (and I'd like to keep it that way).
A collection API that allowed me to pass something like local = true this would be fantastic but I have no idea how difficult that would be to implement and I'm not to fond of modifying the core code.
Right now I'm stuck at either creating a BogusDocs = new Meteor.Collection(null) but that makes populating the Collection more difficult since I have to either hard code fixtures in the client code or use a method to get the data from the server and I have to make sure I call BogusDocs.update instead of RealDocs.update as soon as I'm dealing with bogus data.
Maybe I could actually insert the data on the server and make sure it's removed later, but the data really has nothing to do with the server side collection so I'd rather avoid that.
Any thoughts on how to approach this problem?
After some further investigation (the evented mind site) it turns out that one can modify the local collection without making calls to the server. This is done by running the same methods as you usually would, but on MyCollection._collection instead of just on Collection. MyCollection.update() would thus become MyCollection._collection.update(). So, using a simple wrapper one can pass in the usual arguments to a update call to update the collection as usual (which will try to call the server which in turn will trigger your allow/deny rules) or we can add 'local' as the last argument to only perform the update in the client collection. Something like this should do it.
DocsUpdateWrapper = function() {
var lastIndex = arguments.length -1;
if (arguments[lastIndex] === 'local') {
Docs._collection.update(arguments.slice(0, lastIndex);
} else {
Docs.update(arguments)
}
}
(This could of course be extended to a DocsWrapper that allows for insertion and removals too.)(Didnt try this function yet but it should serve well as an example.)
The biggest benefit of this is imo that we can use the exact same calls to retrieve documents from the local collection, regardless of if they are local or living on the server too. By adding a simple boolean to the doc we can keep track of which documents are only local and which are not (An improved DocsWrapper could check for that bool so we could even omit passing the 'local' argument.) so we know how to update them.
There are some people working on local storage in the browser
https://github.com/awwx/meteor-browser-store
You might be able to adapt some of their ideas to provide "fake" documents.
I would use the transform feature on the collection to make an object that knows what to do with itself (on client). Give it the corruct update method (real/bogus), then call .update rather than a general one.
You can put the code from this.added into the transform process.
You can also set up a local minimongo collection. Insert on callback
#FoundAgents = new Meteor.Collection(null, Agent.transformData )
FoundAgents.remove({})
Meteor.call 'Get_agentsCloseToOffer', me, ping, (err, data) ->
if err
console.log JSON.stringify err,null,2
else
_.each data, (item) ->
FoundAgents.insert item
Maybe this interesting for you as well, I created two examples with native Meteor Local Collections at meteorpad. The first pad shows an example with plain reactive recordset: Sample_Publish_to_Local-Collection. The second will use the collection .observe method to listen to data: Collection.observe().
On my meteor project users can post events and they have to choose (via an autocomplete) in which city it will take place. I have a full list of french cities and it will never be updated.
I want to use a collection and publish-subscribes based on the input of the autocomplete because I don't want the client to download the full database (5MB). Is there a way, for performance, to tell meteor that this collection is "static"? Or does it make no difference?
Could anyone suggest a different approach?
When you "want to tell the server that a collection is static", I am aware of two potential optimizations:
Don't observe the database using a live query because the data will never change
Don't store the results of this query in the merge box because it doesn't need to be tracked and compared with other data (saving memory and CPU)
(1) is something you can do rather easily by constructing your own publish cursor. However, if any client is observing the same query, I believe Meteor will (at least in the future) optimize for that so it's still just one live query for any number of clients. As for (2), I am not aware of any straightforward way to do this because it could potentially mess up the data merging over multiple publications and subscriptions.
To avoid using a live query, you can manually add data to the publish function instead of returning a cursor, which causes the .observe() function to be called to hook up data to the subscription. Here's a simple example:
Meteor.publish(function() {
var sub = this;
var args = {}; // what you're find()ing
Foo.find(args).forEach(function(document) {
sub.added("client_collection_name", document._id, document);
});
sub.ready();
});
This will cause the data to be added to client_collection_name on the client side, which could have the same name as the collection referenced by Foo, or something different. Be aware that you can do many other things with publications (also, see the link above.)
UPDATE: To resolve issues from (2), which can be potentially very problematic depending on the size of the collection, it's necessary to bypass Meteor altogether. See https://stackoverflow.com/a/21835534/586086 for one way to do it. Another way is to just return the collection fetch()ed as a method call, although this doesn't have the benefits of compression.
From Meteor doc :
"Any change to the collection that changes the documents in a cursor will trigger a recomputation. To disable this behavior, pass {reactive: false} as an option to find."
I think this simple option is the best answer
You don't need to publish your whole collection.
1.Show autocomplete options only after user has inputted first 3 letters - this will narrow your search significantly.
2.Provide no more than 5-10 cities as options - this will keep your recordset really small - thus no need to push 5mb of data to each user.
Your publication should look like this:
Meteor.publish('pub-name', function(userInput){
var firstLetters = new RegExp('^' + userInput);
return Cities.find({name:firstLetters},{limit:10,sort:{name:1}});
});