I have a .net app that uses Firestore as a database and It's using Firestore Query to find some data. The problem is data fields that include Turkish characters but if someone uses my app and wants to search for data and if don't use Turkish characters, the query can not find this data.
For example, if I want to search my name on my app and my name is saved like "Ertuğrul" and if the user searches like "Ertugrul", the query can not find it. I need it to find it. Is there a way to do that?
My code that uses query is here:
QRef = DataBase.Collection("CollName").Document("DocName").Collection("CollName")
.WhereGreaterThanOrEqualTo("NameSurname", $"{NameSurname}")
.WhereLessThanOrEqualTo("NameSurname", $"{NameSurname}\uF7FF");
Firestore queries always return documents where a particular field holds a perfect match. If you want to be able to search for "Ertuğrul" as well as for "Ertugrul", then besides the "NameSurname" field you should consider adding a new field called "NameSurnameWithoutSpecialCharacters" and store each name without those Turkish characters.
When a user searches, simply verify if the searched term contains "special" characters. If it does, search on the "NameSurname", otherwise search on the newly created field.
Related
im trying to make a sort of chat app with the following architecture:
Its currently working as follows: in a root doc, there is an array of chat objects. Each chat object spawns a message doc, which contains an array of message objects. Same logic for comments.
Im thinking about a function to update all posts relative to the associated user, IE if a user changes their name all associated comments will be updated. Is this possible with the WhereIn() function? Or should i edit the architecture to something more like each document being its own message/comment? Thanks!
An in clause checks if a specific field is equal to one of a set of values, which doesn't apply here.
You might be thinking of array-contains, but that wouldn't work in your current structure either. The array-contains only matches exact an item in the array if it completely/exactly matches the value in the query.
The common way to allow such a query is to add a participants array field to each document where you store the UIDs of all participants in that doc. Then you can do an array-contains query against that.
Assuming I have a list of data I would like to store with Firebase realtime database, and search it later.
What would be the best way to store the data and query it to get the best performance?
My data is a list of names (containing a lot of names).
["Bob", "Rob", ...]
Note that I have multiple clients searching in a given time.
If the names are supposed to be unique and order doesn't matter, you'll want to store them as a mathematical set. In the Firebase Realtime Database you'll model this as:
"usernames": {
"Bob": true,
"Rob": true
}
A few things of note about this model:
We use the names as keys, which means that each name is by definition unique (since each key can exist only once in its containing node).
The true values have no specific meaning. They are just needed, since Firebase can't store a key without a value.
Certain characters (such as . and /) cannot be used in keys. If a name contains such characters, you will have to filter them out (or encode them) in the key. For example someone named Jes.sie will have to be stored as Jes.sie (lossy) or e.g. Jes%2Esie (with URL encoding).
In such cases you could store the original unfiltered/unencoded name as the value. So: "Jes%2Esie": "Jes.sie".
A few more general notes about (text) searching in the Firebase Realtime Database:
Firebase can only do prefix matches, it has no support for searching strings that contain or end with a certain substrings. This means that in the original data it can search for everything starting with an B (with orderByKey().startAt("R").endAt("R\uF7FF")), but it can't search for everything ending with ob.
Searches are case-sensitive. If you want to be able to search case-insensitive, consider storing the keys as all-lowercase:
"usernames": {
"bob": "Bob",
"rob": "Rob",
"jes%2esie": "Jes.sie"
}
If you need better support for text-search, consider integrating a third-party search engine. Common recommendations are Elastic-search (self-hosted) or Algolia (cloud-based).
For more information on many of these topics, see:
this article on NoSQL data modeling
the video series Firebase for SQL developers
Cloud Firestore Case Insensitive Sorting Using Query (while written for Firestore, the same applies here)
Consider the following data in Firestore:
I also have a set of selected by the user he's interested in: ['python', 'sql', 'swift']
How to get all the documents from my collection where tags field contains at least one of tags selected by the user? I'm aware that Firestore doesn't have such operator out of the box. Probably I need to rethink the way I store data somehow? Please point me to the right direction.
With the way you have your data structured, you will need to make one array-contains type query for each of the tags the user is interested in, then merge the results of each of those queries in your app code.
Assuming I have a list of data I would like to store with Firebase realtime database, and search it later.
What would be the best way to store the data and query it to get the best performance?
My data is a list of names (containing a lot of names).
["Bob", "Rob", ...]
Note that I have multiple clients searching in a given time.
If the names are supposed to be unique and order doesn't matter, you'll want to store them as a mathematical set. In the Firebase Realtime Database you'll model this as:
"usernames": {
"Bob": true,
"Rob": true
}
A few things of note about this model:
We use the names as keys, which means that each name is by definition unique (since each key can exist only once in its containing node).
The true values have no specific meaning. They are just needed, since Firebase can't store a key without a value.
Certain characters (such as . and /) cannot be used in keys. If a name contains such characters, you will have to filter them out (or encode them) in the key. For example someone named Jes.sie will have to be stored as Jes.sie (lossy) or e.g. Jes%2Esie (with URL encoding).
In such cases you could store the original unfiltered/unencoded name as the value. So: "Jes%2Esie": "Jes.sie".
A few more general notes about (text) searching in the Firebase Realtime Database:
Firebase can only do prefix matches, it has no support for searching strings that contain or end with a certain substrings. This means that in the original data it can search for everything starting with an B (with orderByKey().startAt("R").endAt("R\uF7FF")), but it can't search for everything ending with ob.
Searches are case-sensitive. If you want to be able to search case-insensitive, consider storing the keys as all-lowercase:
"usernames": {
"bob": "Bob",
"rob": "Rob",
"jes%2esie": "Jes.sie"
}
If you need better support for text-search, consider integrating a third-party search engine. Common recommendations are Elastic-search (self-hosted) or Algolia (cloud-based).
For more information on many of these topics, see:
this article on NoSQL data modeling
the video series Firebase for SQL developers
Cloud Firestore Case Insensitive Sorting Using Query (while written for Firestore, the same applies here)
I'm learning angularjs, firebase, angularfire by building a sample app. It's a dictionary app that any one can add a word, add several explanation to the word, add several common usage to the word, add example centences to the word. People can freely add new word via this web app. OR people can freely realtime search a word and display the content of that word. When I build the app.
I found everytime when I search a word, I have to load all the data and then check if the query string exist in the data and then display the content if exist. So, it's quite heavy if the library become very big.
How can I query a string if it exist from the server side and if exist, just download that piece of data?
Here is a very simple example that is on the firebase site (Retreiving data). I suggest you take a look at that page, there is a lot more info there about this subject. Now the example:
var ref = new Firebase("https://dinosaur-facts.firebaseio.com/dinosaurs");
ref.orderByChild([the child node to compare to]).equalTo([what you are searching]).on("child_added", function(snapshot) {
//do something with the data in snapshot
});