I have a collection with thousands of documents. Is there a way I can query the collection and return the first 500 documents? Then I want to load the next 500 documents (501-1000) and so on etc.
docDbClient.queryDocuments(collection._self, 'SELECT * FROM d ORDER BY d._ts DESC').toArray(function(error, arr) {});
Since skip and take are not part of the query language today (though marked as "planned" on UserVoice), you'd need to come up with an alternative approach. Cosmos DB has built-in paging (with continuation tokens), which allows you to read a chunk of data at a time. You can specify the maximum item count per page, and then, as you're ready for the next page, perform the next read with the continuation token received from the previous read.
Or you can come up with your own scheme, perhaps based on some specific property you have.
Related
I would like to create two queries, with pagination option. On the first one I would like to get the first ten records and the second one I would like to get the other all records:
.startAt(0)
.limit(10)
.startAt(9)
.limit(null)
Can anyone confirm that above code is correct for both condition?
Firestore does not support index or offset based pagination. Your query will not work with these values.
Please read the documentation on pagination carefully. Pagination requires that you provide a document reference (or field values in that document) that defines the next page to query. This means that your pagination will typically start at the beginning of the query results, then progress through them using the last document you see in the prior page.
From CollectionReference:
offset(offset) → {Query}
Specifies the offset of the returned results.
As Doug mentioned, Firestore does not support Index/offset - BUT you can get similar effects using combinations of what it does support.
Firestore has it's own internal sort order (usually the document.id), but any query can be sorted .orderBy(), and the first document will be relative to that sorting - only an orderBy() query has a real concept of a "0" position.
Firestore also allows you to limit the number of documents returned .limit(n)
.endAt(), .endBefore(), .startAt(), .startBefore() all need either an object of the same fields as the orderBy, or a DocumentSnapshot - NOT an index
what I would do is create a Query:
const MyOrderedQuery = FirebaseInstance.collection().orderBy()
Then first execute
MyOrderedQuery.limit(n).get()
or
MyOrderedQuery.limit(n).get().onSnapshot()
which will return one way or the other a QuerySnapshot, which will contain an array of the DocumentSnapshots. Let's save that array
let ArrayOfDocumentSnapshots = QuerySnapshot.docs;
Warning Will Robinson! javascript settings is usually by reference,
and even with spread operator pretty shallow - make sure your code actually
copies the full deep structure or that the reference is kept around!
Then to get the "rest" of the documents as you ask above, I would do:
MyOrderedQuery.startAfter(ArrayOfDocumentSnapshots[n-1]).get()
or
MyOrderedQuery.startAfter(ArrayOfDocumentSnapshots[n-1]).onSnapshot()
which will start AFTER the last returned document snapshot of the FIRST query. Note the re-use of the MyOrderedQuery
You can get something like a "pagination" by saving the ordered Query as above, then repeatedly use the returned Snapshot and the original query
MyOrderedQuery.startAfter(ArrayOfDocumentSnapshots[n-1]).limit(n).get() // page forward
MyOrderedQuery.endBefore(ArrayOfDocumentSnapshots[0]).limit(n).get() // page back
This does make your state management more complex - you have to hold onto the ordered Query, and the last returned QuerySnapshot - but hey, now you're paginating.
BIG NOTE
This is not terribly efficient - setting up a listener is fairly "expensive" for Firestore, so you don't want to do it often. Depending on your document size(s), you may want to "listen" to larger sections of your collections, and handle more of the paging locally (Redux or whatever) - Firestore Documentation indicates you want your listeners around at least 30 seconds for efficiency. For some applications, even pages of 10 can be efficient; for others you may need 500 or more stored locally and paged in smaller chucks.
If I have a collection, and collection contain several documents.
Every document contain field age
The id of collection is data
There are 20 documents.
db.collection('data').orderBy('age')
My question is:
How to get certain range of that documents which is already order by age.
Example:
After order by age
[doc5, doc12, doc9, doc4, doc1, doc15, doc7, doc14, doc11, doc17,
doc3, doc2, doc13, doc8, doc6, doc18, doc20, doc16, doc19, doc10]
Fourth to Sixth (doc4, doc1, doc15)
Eleventh to Twelfth (doc3, doc2)
Fourteenth (doc8)
Firestore does not offer (actually, no longer offers) client-side queries that let you jump to an offset within the query results. You have to start from the beginning, and manually skip each result that you're not interested in, keeping track of the current index as you go. Yes, this will cost you excess document reads, but you don't have an alternative if you're not able to assign index values of your own for each document.
If you want to perform the query on a backend, you have offset() available, but the documents skipped are still counted as reads, and is neither an efficient or cheap way of skipping unwanted results.
Dataloader is able to batch and cache requests, but it can only be used by either calling load(key) or loadMany(keys).
The problem I am having is that sometimes I do not know they keys of the items I want to load in advance.
I am using an sql database and this works fine when the current object has a foreign key from a belongsTo relation with another model.
For example a user that belongs to a group and so has a groupId. To resolve the group you would just call groupLoader.load(groupId).
On the other hand, if I wanted to resolve the users within a group, of which there could be many I would want a query such as
SELECT * from users where user.groupId = theParticularGroupId
but a query such as this doesn't use the keys of the users and so I am not sure how make use of dataloader.
I could do another request to get the keys like
SELECT id from users where user.groupId = theParticularGroupId
and then call loadMany with those keys... But I could have just requested the data directly instead.
I noticed that dataloader has a prime(key, value) function which can be used to prime the cache, however that can only be done once the data is already fetched. At which point many queries would already have been sent, and duplicate data could have been fetched.
Another example would be the following query
query {
groups(limit: 10) {
id
...
users {
id
name
...
}
}
}
I cannot know the keys if I am searching for say the first or last 10 groups. Then once I have these 10 groups. I cannot know the keys of their users, and if each resolver would resolve the users using a query such as
SELECT * from users where user.groupId = theParticularGroupId
that query will be executed 10 times. Once the data is loaded I could now prime the cache, but the 10 requests have already been made.
Is there any way around this issue? Perhaps a different pattern or database structure or maybe dataloader isn't even the right solution.
You'll want a dataloader instance for the lookup you can do, in this case you have a group ID and you want the users:
import DataLoader from 'dataloader';
const userIdsForGroupLoader = new DataLoader(groupIds => batchGetUsersIdsForGroups(groupIds));
Now your batchGetUsersForGroups function is essentially has to convert an array of group IDs to an array of arrays of users (one array of user IDs for each group).
You'd start off with an IN query:
SELECT id from users where user.groupId in (...groupIds)
This will give you a single result set of users, which you'll have to manipulate, by grouping them by their groupId, the array should be ordered according to the original array of groupIds. Make sure you return an empty array for groupIds that don't have any users.
Note that in this we're only returning the user ids, but you can batch fetch the users in one go once you have them. You could tweak it slightly to return the users themselves, you'll have to decide for yourself if that's the right approach.
Everything I mention in this article can be achieved using clever use of Dataloader. But the key takeaway is that the values you pass to the load/loadMany functions don't have to correspond to the IDs of the objects you're trying to return.
Ok, so I've been reading and reading and searching and searching and strangely it doesn't seem like my scenario has been really covered anywhere.
I have an app that creates a list of products. I want a simple view that can sort the products and page through them.
Fore reference here is a simple representation of the data in Firebase.
app
stock
unique_id
name
url
imageUrl
price
When creating the list I have multiple threads using the push method on my firebase references:
new Firebase(firebaseUrl).child('stock').push({
name: "name",
price: 123
});
This gives me a lovely "hash" collection on the stock property of the app.
So what I'd now like to do is have a table to sort and page through the records that were placed in the stock hash.
I make a GET request to my server to a url like /stock?limit=10&skip=10&sort=name%20asc. This particular url would be the second page where the table contained 10 records per page and was sorted by the name property in ascending order.
Currently in my query handler I have this:
var firebaseRef = new Firebase(firebaseUrl).child('stock');
if (this.sortDesc) {
firebaseRef = firebaseRef
.orderByChild(this.sortProperty)
.endAt()
.limitToFirst(this.limitAmount);
} else {
firebaseRef = firebaseRef
.orderByChild(this.sortProperty)
.limitToFirst(this.limitAmount);
if (this.skipAmount > 0) {
firebaseRef = firebaseRef.startAt(this.skipAmount);
}
}
firebaseRef.once('value', function (snapshot) {
var results = [];
snapshot.forEach(function (childSnapshot) {
results.push(childSnapshot.val());
});
callback(null, results);
});
I'm running into a couple of problems. I'm going to split this into two cases, ascending and descending queries.
Ascending query
The orderByChild and limitToFirst seems to work correctly in the sorting ascending case. This means I can change which property has an ascending sort and how many results to return. What I am not able to get to work is skipping n records for paging to work. In the example query above I'm going to the second page. I do not get results 11-20, but I instead get the same 10 records as the first page.
Descending query
In this case I cannot begin to figure out how to tell Firebase to order by a property of the object identified by the unique key in a descending fashion. The closest I've read is to use endAt() and then limit. Docs say the limit is deprecated plus this still doesn't help me with any paging.
I tired to do doodles picturing how this would work. I came up with: order by the property, start at the 'end' of the collection, and then limit back to the page size. While this still wouldn't solve paging I would expect it to give me the last n records where n was the size of the page. I get no results.
I suppose I could say use firebaseRef = firebaseRef .orderByChild(this.sortProperty).limitToLast(this.limitAmount + this.skipAmount); and in the result callback use the forEach loop to take the first (or would it be the last; I'm not sure how that iteration would work) n records where n=this.limitAmount. This just seems inefficient. Wouldn't it be better to limit the query instead of using CPU cycles to limit data that had come over the wire or is this the relational DB query thought pattern overriding the correct thought process for NoSQL?
Further Confusion
After posting this I've still been working on a solution. I've had some things get close, but I'm also running into this filtering issue. How could I filter a set of items to one property by still sorting on another? Jeez! I want to have the ability for a user to get all the stock that isn't sold out and order it by price.
Finally
Why hasn't this basic example been fleshed out on any of the Firebase "Getting Started" pages? Being able to show tabular data, page through it, sort, and filter seem like something that EVERY web developer would come across. I'm using ng-table in an Angular app to drive the view, but it still seems that regardless of platform that the queries that I'm trying to generate would be practical on any platform that Firebase supports. Perhaps I'm missing something! Please educate me!
Firebase and NoSQL
I've come up with this simple scenario that I often run into with web applications. I want to show tabular data, filter, page, and sort it. Very simple. Very common. Writing a SQL statement for this would be dead easy. Why is the query so complicated for something like Firebase. Is this common with all NoSQL solutions? There is no relational data being stored thus the need for a relational database seems unnecessary. Yet, it seems like I could hack together a little flat file to do this storage since the ability to make Firebase do these simple tasks is not made clear in its API or Docs. FRUSTRATED!!!
What's the fastest way to check for the existence of a mongodb doc?
Should I just use find and if it returns nothing?
EDIT:
collection.findOne {#attribute}, (err, doc) ->
if err then console.log err
if interaction
#exists
else
#does not
If you are just testing for a single document, use findOne (or the equivalent in your driver); most drivers implement this in the most efficient possible way (by setting a negative limit of 1 on the request, which asks mongo to return immediately after finding one document, even if more might match, and not to create a cursor that won't ever be used by the client).
If you have an index that can serve your query, you can use field selection to select (a subset of) the fields in the index; this will make use of Mongo's "covered index" functionality to avoid a lookup to the underlying collection data. Be sure to set {_id: 0} in your field selector unless _id is in your index.
Covered Index is what you want. If the info you know about the document is indexed, then you can use this facility to query and retrieve info from the index only (in RAM) and will not go to disk to get the reference document. Explained in the mongo docs here.
http://www.mongodb.org/display/DOCS/mongo%20wire%20protocol#MongoWireProtocol-OPQUERY
numberToReturn : Limits the number of documents in the first CONTRIB:OP_REPLY message to the query. However, the database will still establish a cursor and return the cursorID to the client if there are more results than numberToReturn. If the client driver offers 'limit' functionality (like the SQL LIMIT keyword), then it is up to the client driver to ensure that no more than the specified number of document are returned to the calling application. If numberToReturn is 0, the db will used the default return size. If the number is negative, then the database will return that number and close the cursor. No futher results for that query can be fetched. If numberToReturn is 1 the server will treat it as -1 (closing the cursor automatically).