I want to see if there is a way to represent/model a nested parent-child relationship in a graph db platform like neo4j or arangodb.
In particular, I am trying to model the contractor/subcontractor relations over multiple contracts:
example contract relations image link
I can see how this can be done using a table where both the parent and the contract are represented. I can't see how to do this in a graph since there can be multiple A-B relations but for different contracts.
Using ArangoDB
The best thing to do here is create three collections, and I've created some sample data and sample queries to show you how it can work.
contracts: A document collection that contains contracts
companies: A document collection that contains companies
company_contracts: An edge collection that contains connections between contracts and companies
The goal is to store your contracts and companies in their respective collections and then store the relationshps in the company_contracts edge collection.
Because the companies are reused across multiple contracts, it will therefore be necessary to be able to filter on the relationships, based on the contract code.
Each contract has a key called code which contains an identifier for that contract (e.g. 'Contract 1' has a code of 1).
Note: I've also added a code field to each company, but that's not necessarily required for this example.
Each relationship that is added to the company_contracts edge collection will have a key added to it to identify what contract that edge is for, and this key is called contract_code.
This will be used in your AQL query to ensure you only select edges related to your contract in question.
To create the base data, you run this script in the arangodsh tool, just start it and then once you've provided your password and are connected, just paste this block of text in to create the sample collections and load some base data.
var contracts = db._create("contracts");
var companies = db._create("companies");
var company_contracts = db._createEdgeCollection("company_contracts");
var contract_1 = contracts.save({_key: "1", title:"Contract 1", code: 1})._id;
var contract_2 = contracts.save({_key: "2", title:"Contract 2", code: 2})._id;
var contract_3 = contracts.save({_key: "3", title:"Contract 3", code: 3})._id;
var company_a = companies.save({_key: "a", title:"Company A", code: "A"})._id;
var company_b = companies.save({_key: "b", title:"Company B", code: "B"})._id;
var company_c = companies.save({_key: "c", title:"Company C", code: "C"})._id;
var company_d = companies.save({_key: "d", title:"Company D", code: "D"})._id;
var company_e = companies.save({_key: "e", title:"Company E", code: "E"})._id;
company_contracts.save(contract_1, company_a, { contract_code: 1});
company_contracts.save(company_a, company_c, { contract_code: 1});
company_contracts.save(company_a, company_b, { contract_code: 1});
company_contracts.save(company_c, company_d, { contract_code: 1});
company_contracts.save(company_c, company_e, { contract_code: 1});
company_contracts.save(contract_2, company_c, { contract_code: 2});
company_contracts.save(contract_2, company_a, { contract_code: 2});
company_contracts.save(company_a, company_b, { contract_code: 2});
company_contracts.save(company_c, company_d, { contract_code: 2});
company_contracts.save(contract_3, company_b, { contract_code: 3});
company_contracts.save(company_b, company_c, { contract_code: 3});
company_contracts.save(company_b, company_a, { contract_code: 3});
Once you've done that, this is an example AQL query you could use to find all relationships for a given contract code:
LET contract_id = FIRST(FOR d IN contracts FILTER d.code == #contract_code RETURN d._id)
FOR v, e, p IN 1..10 OUTBOUND contract_id company_contracts
FILTER p.edges[*].contract_code ALL == #contract_code
RETURN p
If you pass a value of 1 as the value for the contract_code parameter, you'll get the result as shown by your sample document, and if you provide the values 2 or 3 it will show those results.
The query works by doing two things:
The LET query finds the _id of the contract you're interested in
The GRAPH query then finds all outbound connections from that contract, and it applies a filter to ALL edges in each path coming out of that contract, ensuring every single edge has a company_code key that matches the contract code you're working with
This FILTER ... ALL condition ensures you only get edges related to your contract.
The view of the results looks like this in the ArangoDB graph viewer for the results for Contract 1:
It is crucial for my application to be able to select multiple documents at random from a collection in firebase.
Since there is no native function built in to Firebase (that I know of) to achieve a query that does just this, my first thought was to use query cursors to select a random start and end index provided that I have the number of documents in the collection.
This approach would work but only in a limited fashion since every document would be served up in sequence with its neighboring documents every time; however, if I was able to select a document by its index in its parent collection I could achieve a random document query but the problem is I can't find any documentation that describes how you can do this or even if you can do this.
Here's what I'd like to be able to do, consider the following firestore schema:
root/
posts/
docA
docB
docC
docD
Then in my client (I'm in a Swift environment) I'd like to write a query that can do this:
db.collection("posts")[0, 1, 3] // would return: docA, docB, docD
Is there anyway I can do something along the lines of this? Or, is there a different way I can select random documents in a similar fashion?
Please help.
Using randomly generated indexes and simple queries, you can randomly select documents from a collection or collection group in Cloud Firestore.
This answer is broken into 4 sections with different options in each section:
How to generate the random indexes
How to query the random indexes
Selecting multiple random documents
Reseeding for ongoing randomness
How to generate the random indexes
The basis of this answer is creating an indexed field that when ordered ascending or descending, results in all the document being randomly ordered. There are different ways to create this, so let's look at 2, starting with the most readily available.
Auto-Id version
If you are using the randomly generated automatic ids provided in our client libraries, you can use this same system to randomly select a document. In this case, the randomly ordered index is the document id.
Later in our query section, the random value you generate is a new auto-id (iOS, Android, Web) and the field you query is the __name__ field, and the 'low value' mentioned later is an empty string. This is by far the easiest method to generate the random index and works regardless of the language and platform.
By default, the document name (__name__) is only indexed ascending, and you also cannot rename an existing document short of deleting and recreating. If you need either of these, you can still use this method and just store an auto-id as an actual field called random rather than overloading the document name for this purpose.
Random Integer version
When you write a document, first generate a random integer in a bounded range and set it as a field called random. Depending on the number of documents you expect, you can use a different bounded range to save space or reduce the risk of collisions (which reduce the effectiveness of this technique).
You should consider which languages you need as there will be different considerations. While Swift is easy, JavaScript notably can have a gotcha:
32-bit integer: Great for small (~10K unlikely to have a collision) datasets
64-bit integer: Large datasets (note: JavaScript doesn't natively support, yet)
This will create an index with your documents randomly sorted. Later in our query section, the random value you generate will be another one of these values, and the 'low value' mentioned later will be -1.
How to query the random indexes
Now that you have a random index, you'll want to query it. Below we look at some simple variants to select a 1 random document, as well as options to select more than 1.
For all these options, you'll want to generate a new random value in the same form as the indexed values you created when writing the document, denoted by the variable random below. We'll use this value to find a random spot on the index.
Wrap-around
Now that you have a random value, you can query for a single document:
let postsRef = db.collection("posts")
queryRef = postsRef.whereField("random", isGreaterThanOrEqualTo: random)
.order(by: "random")
.limit(to: 1)
Check that this has returned a document. If it doesn't, query again but use the 'low value' for your random index. For example, if you did Random Integers then lowValue is 0:
let postsRef = db.collection("posts")
queryRef = postsRef.whereField("random", isGreaterThanOrEqualTo: lowValue)
.order(by: "random")
.limit(to: 1)
As long as you have a single document, you'll be guaranteed to return at least 1 document.
Bi-directional
The wrap-around method is simple to implement and allows you to optimize storage with only an ascending index enabled. One downside is the possibility of values being unfairly shielded. E.g if the first 3 documents (A,B,C) out of 10K have random index values of A:409496, B:436496, C:818992, then A and C have just less than 1/10K chance of being selected, whereas B is effectively shielded by the proximity of A and only roughly a 1/160K chance.
Rather than querying in a single direction and wrapping around if a value is not found, you can instead randomly select between >= and <=, which reduces the probability of unfairly shielded values by half, at the cost of double the index storage.
If one direction returns no results, switch to the other direction:
queryRef = postsRef.whereField("random", isLessThanOrEqualTo: random)
.order(by: "random", descending: true)
.limit(to: 1)
queryRef = postsRef.whereField("random", isGreaterThanOrEqualTo: random)
.order(by: "random")
.limit(to: 1)
Selecting multiple random documents
Often, you'll want to select more than 1 random document at a time. There are 2 different ways to adjust the above techniques depending on what trade offs you want.
Rinse & Repeat
This method is straight forward. Simply repeat the process, including selecting a new random integer each time.
This method will give you random sequences of documents without worrying about seeing the same patterns repeatedly.
The trade-off is it will be slower than the next method since it requires a separate round trip to the service for each document.
Keep it coming
In this approach, simply increase the number in the limit to the desired documents. It's a little more complex as you might return 0..limit documents in the call. You'll then need to get the missing documents in the same manner, but with the limit reduced to only the difference. If you know there are more documents in total than the number you are asking for, you can optimize by ignoring the edge case of never getting back enough documents on the second call (but not the first).
The trade-off with this solution is in repeated sequences. While the documents are randomly ordered, if you ever end up overlapping ranges you'll see the same pattern you saw before. There are ways to mitigate this concern discussed in the next section on reseeding.
This approach is faster than 'Rinse & Repeat' as you'll be requesting all the documents in the best case a single call or worst case 2 calls.
Reseeding for ongoing randomness
While this method gives you documents randomly if the document set is static the probability of each document being returned will be static as well. This is a problem as some values might have unfairly low or high probabilities based on the initial random values they got. In many use cases, this is fine but in some, you may want to increase the long term randomness to have a more uniform chance of returning any 1 document.
Note that inserted documents will end up weaved in-between, gradually changing the probabilities, as will deleting documents. If the insert/delete rate is too small given the number of documents, there are a few strategies addressing this.
Multi-Random
Rather than worrying out reseeding, you can always create multiple random indexes per document, then randomly select one of those indexes each time. For example, have the field random be a map with subfields 1 to 3:
{'random': {'1': 32456, '2':3904515723, '3': 766958445}}
Now you'll be querying against random.1, random.2, random.3 randomly, creating a greater spread of randomness. This essentially trades increased storage to save increased compute (document writes) of having to reseed.
Reseed on writes
Any time you update a document, re-generate the random value(s) of the random field. This will move the document around in the random index.
Reseed on reads
If the random values generated are not uniformly distributed (they're random, so this is expected), then the same document might be picked a dispropriate amount of the time. This is easily counteracted by updating the randomly selected document with new random values after it is read.
Since writes are more expensive and can hotspot, you can elect to only update on read a subset of the time (e.g, if random(0,100) === 0) update;).
Posting this to help anyone that has this problem in the future.
If you are using Auto IDs you can generate a new Auto ID and query for the closest Auto ID as mentioned in Dan McGrath's Answer.
I recently created a random quote api and needed to get random quotes from a firestore collection.
This is how I solved that problem:
var db = admin.firestore();
var quotes = db.collection("quotes");
var key = quotes.doc().id;
quotes.where(admin.firestore.FieldPath.documentId(), '>=', key).limit(1).get()
.then(snapshot => {
if(snapshot.size > 0) {
snapshot.forEach(doc => {
console.log(doc.id, '=>', doc.data());
});
}
else {
var quote = quotes.where(admin.firestore.FieldPath.documentId(), '<', key).limit(1).get()
.then(snapshot => {
snapshot.forEach(doc => {
console.log(doc.id, '=>', doc.data());
});
})
.catch(err => {
console.log('Error getting documents', err);
});
}
})
.catch(err => {
console.log('Error getting documents', err);
});
The key to the query is this:
.where(admin.firestore.FieldPath.documentId(), '>', key)
And calling it again with the operation reversed if no documents are found.
I hope this helps!
Just made this work in Angular 7 + RxJS, so sharing here with people who want an example.
I used #Dan McGrath 's answer, and I chose these options: Random Integer version + Rinse & Repeat for multiple numbers. I also used the stuff explained in this article: RxJS, where is the If-Else Operator? to make if/else statements on stream level (just if any of you need a primer on that).
Also note I used angularfire2 for easy Firebase integration in Angular.
Here is the code:
import { Component, OnInit } from '#angular/core';
import { Observable, merge, pipe } from 'rxjs';
import { map, switchMap, filter, take } from 'rxjs/operators';
import { AngularFirestore, QuerySnapshot } from '#angular/fire/firestore';
#Component({
selector: 'pp-random',
templateUrl: './random.component.html',
styleUrls: ['./random.component.scss']
})
export class RandomComponent implements OnInit {
constructor(
public afs: AngularFirestore,
) { }
ngOnInit() {
}
public buttonClicked(): void {
this.getRandom().pipe(take(1)).subscribe();
}
public getRandom(): Observable<any[]> {
const randomNumber = this.getRandomNumber();
const request$ = this.afs.collection('your-collection', ref => ref.where('random', '>=', randomNumber).orderBy('random').limit(1)).get();
const retryRequest$ = this.afs.collection('your-collection', ref => ref.where('random', '<=', randomNumber).orderBy('random', 'desc').limit(1)).get();
const docMap = pipe(
map((docs: QuerySnapshot<any>) => {
return docs.docs.map(e => {
return {
id: e.id,
...e.data()
} as any;
});
})
);
const random$ = request$.pipe(docMap).pipe(filter(x => x !== undefined && x[0] !== undefined));
const retry$ = request$.pipe(docMap).pipe(
filter(x => x === undefined || x[0] === undefined),
switchMap(() => retryRequest$),
docMap
);
return merge(random$, retry$);
}
public getRandomNumber(): number {
const min = Math.ceil(Number.MIN_VALUE);
const max = Math.ceil(Number.MAX_VALUE);
return Math.floor(Math.random() * (max - min + 1)) + min;
}
}
The other solutions are better but seems hard for me to understand, so I came up with another method
Use incremental number as ID like 1,2,3,4,5,6,7,8,9, watch out for delete documents else we
have an I'd that is missing
Get total number of documents in the collection, something like this, I don't know of a better solution than this
let totalDoc = db.collection("stat").get().then(snap=>snap.size)
Now that we have these, create an empty array to store random list of number, let's say we want 20 random documents.
let randomID = [ ]
while(randomID.length < 20) {
const randNo = Math.floor(Math.random() * totalDoc) + 1;
if(randomID.indexOf(randNo) === -1) randomID.push(randNo);
}
now we have our 20 random documents id
finally we fetch our data from fire store, and save to randomDocs array by mapping through the randomID array
const randomDocs = randomID.map(id => {
db.collection("posts").doc(id).get()
.then(doc => {
if (doc.exists) return doc.data()
})
.catch(error => {
console.log("Error getting document:", error);
});
})
I'm new to firebase, but I think with this answers we can get something better or a built-in query from firebase soon
After intense argument with my friend, we finally found some solution
If you don't need to set document's id to be RandomID, just name documents as size of collection's size.
For example, first document of collection is named '0'.
second document name should be '1'.
Then, we just read the size of collection, for example N, and we can get random number A in range of [0~N).
And then, we can query the document named A.
This way can give same probability of randomness to every documents in collection.
undoubtedly Above accepted Answer is SuperUseful but There is one case like If we had a collection of some Documents(about 100-1000) and we want some 20-30 random Documents Provided that Document must not be repeated. (case In Random Problems App etc...).
Problem with the Above Solution:
For a small number of documents in the Collection(say 50) Probability of repetition is high. To avoid it If I store Fetched Docs Id and Add-in Query like this:
queryRef = postsRef.whereField("random", isGreaterThanOrEqualTo: lowValue).where("__name__", isNotEqualTo:"PreviousId")
.order(by: "random")
.limit(to: 1)
here PreviousId is Id of all Elements that were fetched Already means A loop of n previous Ids.
But in this case, network Call would be high.
My Solution:
Maintain one Special Document and Keep a Record of Ids of this Collection only, and fetched this document First Time and Then Do all Randomness Stuff and check for previously not fetched on App site. So in this case network call would be only the same as the number of documents requires (n+1).
Disadvantage of My solution:
Have to maintain A document so Write on Addition and Deletion. But it is good If reads are very often then Writes which occurs in most cases.
You can use listDocuments() property for get only Query list of documents id. Then generate random id using the following way and get DocumentSnapshot with get() property.
var restaurantQueryReference = admin.firestore().collection("Restaurant"); //have +500 docs
var restaurantQueryList = await restaurantQueryReference.listDocuments(); //get all docs id;
for (var i = restaurantQueryList.length - 1; i > 0; i--) {
var j = Math.floor(Math.random() * (i + 1));
var temp = restaurantQueryList[i];
restaurantQueryList[i] = restaurantQueryList[j];
restaurantQueryList[j] = temp;
}
var restaurantId = restaurantQueryList[Math.floor(Math.random()*restaurantQueryList.length)].id; //this is random documentId
Unlike rtdb, firestore ids are not ordered chronologically. So using Auto-Id version described by Dan McGrath is easily implemented if you use the auto-generated id by the firestore client.
new Promise<Timeline | undefined>(async (resolve, reject) => {
try {
let randomTimeline: Timeline | undefined;
let maxCounter = 5;
do {
const randomId = this.afs.createId(); // AngularFirestore
const direction = getRandomIntInclusive(1, 10) <= 5;
// The firestore id is saved with your model as an "id" property.
let list = await this.list(ref => ref
.where('id', direction ? '>=' : '<=', randomId)
.orderBy('id', direction ? 'asc' : 'desc')
.limit(10)
).pipe(take(1)).toPromise();
// app specific filtering
list = list.filter(x => notThisId !== x.id && x.mediaCounter > 5);
if (list.length) {
randomTimeline = list[getRandomIntInclusive(0, list.length - 1)];
}
} while (!randomTimeline && maxCounter-- >= 0);
resolve(randomTimeline);
} catch (err) {
reject(err);
}
})
I have one way to get random a list document in Firebase Firestore, it really easy. When i upload data on Firestore i creat a field name "position" with random value from 1 to 1 milions. When i get data from Fire store i will set Order by field "Position" and update value for it, a lot of user load data and data always update and it's will be random value.
For those using Angular + Firestore, building on #Dan McGrath techniques, here is the code snippet.
Below code snippet returns 1 document.
getDocumentRandomlyParent(): Observable<any> {
return this.getDocumentRandomlyChild()
.pipe(
expand((document: any) => document === null ? this.getDocumentRandomlyChild() : EMPTY),
);
}
getDocumentRandomlyChild(): Observable<any> {
const random = this.afs.createId();
return this.afs
.collection('my_collection', ref =>
ref
.where('random_identifier', '>', random)
.limit(1))
.valueChanges()
.pipe(
map((documentArray: any[]) => {
if (documentArray && documentArray.length) {
return documentArray[0];
} else {
return null;
}
}),
);
}
1) .expand() is a rxjs operation for recursion to ensure we definitely get a document from the random selection.
2) For recursion to work as expected we need to have 2 separate functions.
3) We use EMPTY to terminate .expand() operator.
import { Observable, EMPTY } from 'rxjs';
Ok I will post answer to this question even thou I am doing this for Android. Whenever i create a new document i initiate random number and set it to random field, so my document looks like
"field1" : "value1"
"field2" : "value2"
...
"random" : 13442 //this is the random number i generated upon creating document
When I query for random document I generate random number in same range that I used when creating document.
private val firestore: FirebaseFirestore = FirebaseFirestore.getInstance()
private var usersReference = firestore.collection("users")
val rnds = (0..20001).random()
usersReference.whereGreaterThanOrEqualTo("random",rnds).limit(1).get().addOnSuccessListener {
if (it.size() > 0) {
for (doc in it) {
Log.d("found", doc.toString())
}
} else {
usersReference.whereLessThan("random", rnds).limit(1).get().addOnSuccessListener {
for (doc in it) {
Log.d("found", doc.toString())
}
}
}
}
Based on #ajzbc answer I wrote this for Unity3D and its working for me.
FirebaseFirestore db;
void Start()
{
db = FirebaseFirestore.DefaultInstance;
}
public void GetRandomDocument()
{
Query query1 = db.Collection("Sports").WhereGreaterThanOrEqualTo(FieldPath.DocumentId, db.Collection("Sports").Document().Id).Limit(1);
Query query2 = db.Collection("Sports").WhereLessThan(FieldPath.DocumentId, db.Collection("Sports").Document().Id).Limit(1);
query1.GetSnapshotAsync().ContinueWithOnMainThread((querySnapshotTask1) =>
{
if(querySnapshotTask1.Result.Count > 0)
{
foreach (DocumentSnapshot documentSnapshot in querySnapshotTask1.Result.Documents)
{
Debug.Log("Random ID: "+documentSnapshot.Id);
}
} else
{
query2.GetSnapshotAsync().ContinueWithOnMainThread((querySnapshotTask2) =>
{
foreach (DocumentSnapshot documentSnapshot in querySnapshotTask2.Result.Documents)
{
Debug.Log("Random ID: " + documentSnapshot.Id);
}
});
}
});
}
If you are using autoID this may also work for you...
let collectionRef = admin.firestore().collection('your-collection');
const documentSnapshotArray = await collectionRef.get();
const records = documentSnapshotArray.docs;
const index = documentSnapshotArray.size;
let result = '';
console.log(`TOTAL SIZE=====${index}`);
var randomDocId = Math.floor(Math.random() * index);
const docRef = records[randomDocId].ref;
result = records[randomDocId].data();
console.log('----------- Random Result --------------------');
console.log(result);
console.log('----------- Random Result --------------------');
Easy (2022). You need something like:
export const getAtRandom = async (me) => {
const collection = admin.firestore().collection('...').where(...);
const { count } = (await collection.count().get()).data();
const numberAtRandom = Math.floor(Math.random() * count);
const snap = await accountCollection.limit(1).offset(numberAtRandom).get()
if (accountSnap.empty) return null;
const doc = { id: snap.docs[0].id, ...snap.docs[0].data(), ref: snap.docs[0].ref };
return doc;
}
The next code (Flutter) will return one or up to ten random documents from a Firebase collection.
None of the documents will be repeated
Max 10 documents can be retrieved
If you pass a greater numberOfDocuments than existing documents in the collection, the loop will never end.
Future<Iterable<QueryDocumentSnapshot>> getRandomDocuments(int numberOfDocuments) async {
// Queried documents
final docs = <QueryDocumentSnapshot>[];
// Queried documents id's. We will use later to avoid querying same documents
final currentIds = <String>[];
do {
// Generate random id explained by #Dan McGrath's answer (autoId)
final randomId = FirebaseFirestore.instance.collection('random').doc().id;
var query = FirebaseFirestore.instance
.collection('myCollection') // Change this for you collection name
.where(FieldPath.documentId, isGreaterThanOrEqualTo: randomId)
.limit(1);
if (currentIds.isNotEmpty) {
// If previously we fetched a document we avoid fetching the same
query = query.where(FieldPath.documentId, whereNotIn: currentIds);
}
final querySnap = await query.get();
for (var element in querySnap.docs) {
currentIds.add(element.id);
docs.add(element);
}
} while (docs.length < numberOfDocuments); // <- Run until we have all documents we want
return docs;
}
I'm building a chat app with rooms feature in iOS, and had built a Firebase data design like this:
"members" : {
"userId1" : {
"roomId1" : true
},
"userId2" : {
"roomId1" : true
}
}
"rooms" : {
"roomId1" : {
"lastMessage" : "Last message",
"timeStamp" : 1494483604,
//users in this room
"users" : {
"userId1" : true,
"usreId2" : true
}
}
}
So to show list of conversations of a user, firstly I observe single event of type value of path members/userId to get list of rooms that user take part in.
Then for each roomId, I observe rooms/roomId to get data to show on the UI.
The question is if a user takes part in a great deal of rooms, is observing changes for all of them best practice ?
For example, if I have 30 conversations from roomId1 to roomId30, I want to update the latest messages on the UI whenever changes happened, is observing 30 references makes sense ?
Thank you.
It's not best practice but it's a practice that works. However, based on your structure it would be simpler to generate a query on the rooms node for any users/userIdx: true.
That will add and observer to one node and notify the app of any changes to rooms the user is part of.
For example
Given a structure
rooms
room_0
room_name: "My Room"
users:
uid_0: true
uid_1: true
uid_2: true
room_1
room_name: "Romper Room"
users:
uid_0: true
uid_2: true
and some code to add an observer to watch for uid_1
let roomsRef = self.ref.child("rooms")
roomsRef.queryOrdered(byChild: "users/uid_1").queryEqual(toValue: true)
.observe(.childAdded, with: { (snapshot) in
let roomDict = snapshot.value as! [String: AnyObject]
let roomName = roomDict["room_name"] as! String
print(roomName)
})
When this code is first run, it will print out
My Room
because the user is part of My Room (room_0) and not part of room_1.
If you then add uid_1: true to room_1 it will print
Romper Room
You should use observe to update db changes, so you can update UI based on the observation.
Take a look at this document:
https://firebase.google.com/docs/database/ios/read-and-write
In my React-Native app, I have an array of specific users whose values I want to pull from Firebase. What is the most efficient way to go about this? Currently I am looping through the array and making a new request for each (relevant code below):
const usersRef = new Firebase(`${ config.FIREBASE_ROOT }/users`)
for (var key in usersArray) {
var userRef = usersRef.child(key);
//do stuff here
}
However, I feel this isn't very efficient and it makes several requests to the database. Is there a way I can pass in the array and get those items from Firebase, all in one call? Thanks.
Firebase data structure:
{
"items" : [ {
"description" : "fuzzy socks",
"type" : "toy"
}, {
"description" : "bouncy ball",
"type" : "toy"
}, {
"description" : "scrabble",
"type" : "game"
}, {
"description" : "construction paper",
"type" : "crafts"
} ],
"users" : [ {
"itemList" : [ 1, 2, 3, 4 ],
"description" : "brown",
}, {
"itemList" : [ 5, 6, 7 ],
"description" : "green",
}, {
"itemList" : [ 8, 9, 10 ],
"description" : "blue",
}, {
"itemList" : [ 11, 12, 13 ],
"description" : "yellow",
} ]
}
Simplified use case: In one use case, I only want to get information about 2 of the users (out of all the users I have stored in Firebase--assume it's many more than just the 4 in the structure above). So, I have the array importantUsers:
var importantUsers = [0, 3]
Then, I want to send a request to Firebase that only queries the database for the values associated with these userID values (so somehow pass in the array to Firebase for a result). Return values would be something like this:
0: itemList: [1,2,3,4], description: brown
3: itemList: [11,12,13], description: yellow
My motivation for querying the database for multiple users at once (rather than creating a separate ref for user 0 and user 3) is to not have multiple calls made to Firebase. Is there any way to go about this?
So what you are after is an sql 'in' type query. Select in [0,2]. To select a number of users from a list.
The additional challenge in your question is that users you are interested in are random so you can't use .startAt and .endAt, and there is no other relation between the users.
Firebase does not have direct support for 'in', 'and' or 'or' kinds of query but there are a number of ways to make it happen.
How about this: flag the users you want and then with a single query, read them in.
First, you'll start with a typical Firebase /users node with the addition of a 'selected' child node (this can be omitted initially but I am showing it here as a placeholder)
users
uid_0
name: "Bud"
selected: false
uid_1
name: "Henry"
selected: false
uid_2
name: "Billy"
selected: false
Then, we need some random uid's, say uid_0 and uid_2 and store those in an array. Keep in mind that we would be using the Firebase generated uid but we'll use uid_0, uid_1 etc for simplicity.
With just two users, you could just observeSingleEventOfType on each of the two nodes, no big deal.
However, if we needed 100 random users or 1000, doing 1000 separate queries or observeSingleEvent's should be avoided. But, setValue is blisteringly fast (no returned data) so....
Get our users ref
let usersRef = myRootRef.ChildbyAppendingPath("users")
We know the path to each of the 100 users we want by iterating over the array to build those refs and set selected to true
for uid in uidArray {
let thisUserRef = usersRef.childByAppendingPath(uid)
let selectedRef = thisUserRef.childByAppendingPath("selected")
selectedRef.setValue(true)
}
Then, you can query for all users in the usersRef where the selected child = true.
Once you have them, to clean up, iterate over the returned users and set the selected to false or nil
The cool thing about this is that setValue can blast through 100 or 1000 users very quickly with no overhead, setting their selected child to true. Then a single query can return the values you want.
Seems almost reverse in logic to write out to then read back in but I am pretty sure it's considerably better than iterating over an array and generating 1000 queries or observers.
(Firebase folks can check me on that one)
One other thought is that if a user is say, clicking on other users in a list, you could set selected = true as they are clicking and then query for those when the user is done.
You could use bindAsArray or bindAsObject from ReactFire
var ref = new Firebase("https://<YOUR-FIREBASE-APP>.firebaseio.com/items");
this.bindAsArray(ref, "items");
Then you could loop over that array/object as needed without extra queries
I have two parse classes; Companies and Ratings. It is a one to many relationship. Companies can have many Ratings. This is the statement I would perform in SQL:
SELECT Companies.name, Ratings.rating
FROM Companies
INNER JOIN Ratings
ON Ratings.name_id = Companies.name_id
ORDER BY Companies.name
I want the equivalent of this in Parse, but I'm not sure of how to go about it. Here is what I've currently tried:
function getRatings() {
var tableA = new Parse.Query(Companies);
var tableB = new Parse.Query(Ratings);
tableB.equalTo("name_id", tableA.name_id);
tableB.find({
success: function(results) {
$scope.$apply(function() {
$scope.companies = results.map(function(obj) {
return {
id: obj.get("name_id"),
name: obj.get(tableA.name),
rating: obj.get("rating"),
parseObject: obj
};
});
});
},
error: function(error) {
alert("Error: " + error.code + " " + error.message);
}
});
}
I am calling this function when the controller loads. This code displays the rating in my output, but not the name of the company.
I am trying to get all the companies listed in the companies object, then pair them with all the ratings they have in the ratings object. Their common key is name_id. This is the code I am using within my Angular view:
<div class="span12">
<div ng-repeat="company in companies | filter: query | orderBy: orderList"
class="well company-description">
<h1>{{company.name}}</h1>
<h3>Rating: {{company.rating}}</h3>
</div>
</div>
If I am way off base on this, please let me know
Get rid of the name_id column in the Ratings class. This isn't how you're supposed to define relationship using Parse.
There are a couple of options for you to choose.
Option 1
Using the Parse data browser, add a new column under the Companies class, called ratings. It should be a column of type Relation and point to Ratings as the target class. (Let me know if you need more information on how to do this.)
Then, when you create or edit a company, add ratings as follows:
var Companies = Parse.Object.extend("Companies");
var Ratings = Parse.Object.extend("Ratings");
var company = new Companies({name: "Some Company"});
company.relation("ratings").add(new Ratings({stars: 5}));
company.save();
Then, when querying Companies, do so as follows:
new Parse.Query(Companies).find({
success: function(companies) {
for (var i = 0; i < companies.length; i++) {
companies[i].relation("ratings").query().find({
success: function(ratings) {
// Finally, I have the ratings for this company
}
}
}
}
});
Option 2
Using the Parse data browser, add a new column under the Companies class, called ratings. It should be a column of type Array.
Then, when you create or edit a company, add ratings as follows:
var Companies = Parse.Object.extend("Companies");
var Ratings = Parse.Object.extend("Ratings");
var company = new Companies({
name: "Some Company",
ratings: [new Ratings({stars: 5})]
});
company.save();
Then, when querying Companies, do so as follows:
new Parse.Query(Companies).include("ratings").find({
success: function(companies) {
// Yay, I have access to ratings via companies[0].get("ratings")
}
});
include("ratings") tells Parse to include the actual objects, rather than pointers to objects for the given key.
Conclusion
Option 1 is better if you are expecting to have a large amount of ratings for each company, and if you don't always plan on retrieving all the ratings each time you query the companies.
Option 2 is better if the number of ratings for each company is relatively small, and you always want ratings to come back when you query companies.
I found out how to resolve the Uncaught You can't add an unsaved Parse.Object to a relation. error.
var addRating = new Ratings({stars: rating}); // save rating first, then associate it with a company
addRating.save({
success: function() {
var addCompany = new Companies({name: name});
addCompany.relation("ratings").add(addRating);
addCompany.save();
}
});
The rating has to be saved first, then the company relation can be added later on... makes sense, but took me awhile to figure it out! :S