I am using firebase for data storage. The data structure is like this:
products:{
product1:{
name:"chocolate",
}
product2:{
name:"chochocho",
}
}
I want to perform an auto complete operation for this data, and normally i write the query like this:
"select name from PRODUCTS where productname LIKE '%" + keyword + "%'";
So, for my situation, for example, if user types "cho", i need to bring both "chocolate" and "chochocho" as result. I thought about bringing all data under "products" block, and then do the query at the client, but this may need a lot of memory for a big database. So, how can i perform sql LIKE operation?
Thanks
Update: With the release of Cloud Functions for Firebase, there's another elegant way to do this as well by linking Firebase to Algolia via Functions. The tradeoff here is that the Functions/Algolia is pretty much zero maintenance, but probably at increased cost over roll-your-own in Node.
There are no content searches in Firebase at present. Many of the more common search scenarios, such as searching by attribute will be baked into Firebase as the API continues to expand.
In the meantime, it's certainly possible to grow your own. However, searching is a vast topic (think creating a real-time data store vast), greatly underestimated, and a critical feature of your application--not one you want to ad hoc or even depend on someone like Firebase to provide on your behalf. So it's typically simpler to employ a scalable third party tool to handle indexing, searching, tag/pattern matching, fuzzy logic, weighted rankings, et al.
The Firebase blog features a blog post on indexing with ElasticSearch which outlines a straightforward approach to integrating a quick, but extremely powerful, search engine into your Firebase backend.
Essentially, it's done in two steps. Monitor the data and index it:
var Firebase = require('firebase');
var ElasticClient = require('elasticsearchclient')
// initialize our ElasticSearch API
var client = new ElasticClient({ host: 'localhost', port: 9200 });
// listen for changes to Firebase data
var fb = new Firebase('<INSTANCE>.firebaseio.com/widgets');
fb.on('child_added', createOrUpdateIndex);
fb.on('child_changed', createOrUpdateIndex);
fb.on('child_removed', removeIndex);
function createOrUpdateIndex(snap) {
client.index(this.index, this.type, snap.val(), snap.name())
.on('data', function(data) { console.log('indexed ', snap.name()); })
.on('error', function(err) { /* handle errors */ });
}
function removeIndex(snap) {
client.deleteDocument(this.index, this.type, snap.name(), function(error, data) {
if( error ) console.error('failed to delete', snap.name(), error);
else console.log('deleted', snap.name());
});
}
Query the index when you want to do a search:
<script src="elastic.min.js"></script>
<script src="elastic-jquery-client.min.js"></script>
<script>
ejs.client = ejs.jQueryClient('http://localhost:9200');
client.search({
index: 'firebase',
type: 'widget',
body: ejs.Request().query(ejs.MatchQuery('title', 'foo'))
}, function (error, response) {
// handle response
});
</script>
There's an example, and a third party lib to simplify integration, here.
I believe you can do :
admin
.database()
.ref('/vals')
.orderByChild('name')
.startAt('cho')
.endAt("cho\uf8ff")
.once('value')
.then(c => res.send(c.val()));
this will find vals whose name are starting with cho.
source
The elastic search solution basically binds to add set del and offers a get by wich you can accomplish text searches.
It then saves the contents in mongodb.
While I love and reccomand elastic search for the maturity of the project, the same can be done without another server, using only the firebase database.
That's what I mean:
(https://github.com/metaschema/oxyzen)
for the indexing part basically the function:
JSON stringifies a document.
removes all the property names and JSON to leave only the data
(regex).
removes all xml tags (therefore also html) and attributes (remember
old guidance, "data should not be in xml attributes") to leave only
the pure text if xml or html was present.
removes all special chars and substitute with space (regex)
substitutes all instances of multiple spaces with one space (regex)
splits to spaces and cycles:
for each word adds refs to the document in some index structure in
your db tha basically contains childs named with words with childs
named with an escaped version of "ref/inthedatabase/dockey"
then inserts the document as a normal firebase application would do
in the oxyzen implementation, subsequent updates of the document ACTUALLY reads the index and updates it, removing the words that don't match anymore, and adding the new ones.
subsequent searches of words can directly find documents in the words child. multiple words searches are implemented using hits
SQL"LIKE" operation on firebase is possible
let node = await db.ref('yourPath').orderByChild('yourKey').startAt('!').endAt('SUBSTRING\uf8ff').once('value');
This query work for me, it look like the below statement in MySQL
select * from StoreAds where University Like %ps%;
query = database.getReference().child("StoreAds").orderByChild("University").startAt("ps").endAt("\uf8ff");
Related
I've been trying out GunJs for a couple of days now and I'm really enjoying it. As a starter project I've followed the Fireship chat dapp video aimed at building your own chat.
Here's the issue, now that I've finished the tutorial I would like to create my own chat. However, for some reason if I get a 'chat' node within my own app it seems to pick up on the same 'chat' node as the tutorial one that is online.
onMount(() => {
// Get Messages in large chat
db.get('chat')
.map()
.once(async (data, id) => {
if (data) {
// key for E2E - to do: change for web3
const key = '#foo';
var message = {
//transform the data
who: await db.user(data).get('alias'),
what: (await SEA.decrypt(data.what, key)) + '',
when: GUN.state.is(data, 'what'),
};
if (message.what) {
messages = [...messages.slice(-100), message]
}
}
})
})
This is also the case if I change the encryption key (then the messages just become undefined). Multiple questions arise from this:
Are graph node names unique within the whole of GunDb?
How do you handle conflicts where two gun-based apps call on the same node name?
Is this problem generally solved through filtering using 'header' props?
How do I make it pick up on only my data?
Even if I've read most of the docs, there seems to be something I'm missing in my comprehension of how the graph is generally seperated between apps. Any insight on how this works would be much appreciated.
Are graph node names unique within the whole of GunDb?
Yes.
How do you handle conflicts where two gun-based apps call on the same node name?
You don't. The expected result will be, they will overwrite each other.
Is this problem generally solved through filtering using 'header' props?
I don't think it's the right way to do it.
How do I make it pick up on only my data?
Use your own relay server.
Conclusion :
gunDB doesn't really care about the who fetch / put the data. If you want to protect your data, use your own relay server (not a public one), and put data in your user space. user space is readonly to the public, but read/write for the owner.
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.
I have a users table on Firebase and each user has an email prop.
Structure looks like:
Users -> User UID (looks like n8haBbjgablobA2ranfuabu3aaaga2af) -> User Obj which includes email prop.
I'd like to get an array of all the users' emails (~1m).
How can I most efficiently do this?
Ps.:
I tried:
usersRef.startAt(0).endAt(20).once("value", function(snapshot) {
console.log('FIRST 20');
console.log(snapshot.val()); // null
});
But that fails.
Probably the most efficient approach in terms of data reads would be to denormalize your data. You could store the email addresses both in the individual user nodes and in an emailAddresses node. Then you could just query the emailAddresses node directly for your list of emails.
Still ~1m email address nodes would probably be too much all at once. I'd probably grab it in chunks... I'm guessing.
Update
"Grabbing in chunks" is essentially pagination. I would try to use something off the shelf before trying to roll my own pagination solution.
Pagination libraries to check out:
Firebase Utils Pagination: This is developed by Firebase, but they say it is experimental and not ready for production use. But, it's probably still worth messing around with.
firebase-paginator: this is developed by a community member and it seems pretty solid.
If you want to roll your own pagination, check out:
#kato's response in this StackOverflow answer He makes an interesting point about the potential problem with paginating a real time data set, but then provides some good starter code
Here's a good blog entry that talks about the code that I think is a part of the firebase-paginator library I linked to above
Everybody in their answers said that it was an easy thing, yet had no working solutions. Here's what I came up with:
usersRef.orderByChild('uid').limitToFirst(100).once('value', function (snapshot) {
var users = snapshot.val()
var uids = Object.keys(users);
var lastUid = uids[uids.length - 1];
// could be another property than uid, for example email, or username. Ps.: Consider that the last ID from the previous chunk will be duplicated.
usersRef.orderByChild('uid').startAt(lastUid).limitToFirst(100).once('value', function (snapshot) {
var users = snapshot.val()
var uids = Object.keys(users);
console.log(uids);
var lastUid = uids[uids.length - 1];
// re-run function until done
})
})
Since this is a one-time deal, an option is to simply iterate over each node in the parent 'data' node capturing the child data, stripping out the email address and dumping that to a file.
the event you want is
child_added: retrieve lists of items or listen for additions to a list
of items. This event is triggered once for each existing child and
then again every time a new child is added to the specified path. The
listener is passed a snapshot containing the new child's data.
and the code to iterate all of the child nodes in the data node is
var dataRef = firebase.database().ref('myRootRef/data');
datRef.on('child_added', function(data) {
//data.val() will contain the child data, such as the email address
//append it to a text file here (for example), save to disk etc.
});
The key here is that this event is triggered once for each child, similar to iterating over all of the indexes in an array.
This will retrieve each child and present it to your app, one child at a time, iterating over all the children within the node.
It's going to take a while with that many nodes to chew through.
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.
I was searching for an easy and simple database for a little highscore system for a some games I'm developing in javascript.
I saw Orchestrate.io in github's student developer pack. I found a suitable drivermodule nodejs orchestrate and have integrated them.
The problem comes with querying orchestrate for my data. I have managed saving scores and querying them with db.list('collection'), but this seems to not responding with all data. It appered to me that some values are not returned.
I read about the db.search('collection','query') function. But I don't really understand how I could return all data because I don't want to query in a specific way.
My objects are as simple as follows:
{"name":"Jack","score":1337}
As I understand, one has to send a key, when putting such values to an orchestrate-collection. But I'd like to query the whole collection and get the values in a descendant order in regard to the score.
As for now I end up sorting the result on the client-side.
I hope you guys can give me some hints for a query that can sort for specific values!
You have the option to use a SearchBuilder
db.newSearchBuilder() //Build a search object
.collection('collection') //Set the collection to be searched
.sort(score, 'desc') //Set the order of the results
.query("*") //Empty search
.then(function (res) { //Callback function for results
//Do something with the results
})
Source
By default, .list uses a pagination limit of 10. You can either increase that, e.g.:
db.list('collection', { limit: 100 })
Or use .links, .links.next (from the docs):
db.list('collection', { limit: 10 })
.then(function (page1) {
// Got First Page
if (page1.links && page1.links.next) {
page1.links.next.get().then(function (page2) {
// Got Second Page
})
}
})