Prerequisites
Make sure you know how to connect to Firebase and run basic read/write operations before continuing. This earlier How to Firebase article will catch you up.
Firebase queries
Firebase queries are modifications of a ref. So you’ll create a ref as usual, but then you’ll add some query parameters to it. Once you add query parameters to a ref, you can’t take them off or change them… you’d need to create a new ref for that. This is important, because some query parameters are incompatible with one another, and a ref won’t let you add incompatible query parameters. So don’t shy away from creating and recreating refs over and over again to change queries.
Pro Tip
Query orders are NOT respected by the ref.on(‘value’, callback) event. value events return objects as JSON, and JSON does not have ordered children. I know… obnoxious. But that’s JSON for you. If you care to receive your data from Firebase in the specified order, make sure to use ref.on(‘child_added’, callback), because it will be called once for each existing child, and it will be called in order. So aggregated your children into an array manually, and you’ll have ordered children!
Specify how you want to order your query
An orderBy* parameter is required for any query. You can’t apply a query range, i.e., startAt(…), or a query limit, i.e., limitToLast(…), without first specifying how you want to order your query. So apply orderBy* first!
You have four options for ordering queries:
-
orderByKey
-
orderByChild
-
orderByPriority
-
orderByValue
The most common ordering method is ref.orderByKey(). It orders the ref’s children by their keys, usually push keys — which order by time.
The second most common way to order is ref.orderByChild(‘someChildName’). You’ll need to add a security rule like “.indexOn”: [“someChildNodeName”] for performance reasons if you want to order by a child attribute.
The less common methods are ref.orderByPriority() and ref.orderByValue(). Priorities aren’t quite deprecated yet, but they should be, because ref.orderByChild makes priority ordering unnecessary. Ordering by value is only relevant if your children are just values and not objects. So if your data structure were something like…
“animals”: {
“lkjdfa”: “chinchilla”,
“asdfkl”: “aardvark”,
“iouqer”: “gorilla”
}
The most common use cases would be as follows:
// Order users by key, which also orders them by creation timestamp
usersRef.orderByKey().on(‘child_added’, callback);
// Order users by email. Make sure to include the security rule …
// users: {“.indexOn”: [“email”]} …
usersRef.orderByChild(‘email’).equalTo(‘user-i-need-to-find@gmail.com’).once(‘value’).then(…)
Specify query ranges
Query ranges are optional and specify start and end points for your query. You’ve got three options:
-
startAt
-
endAt
-
equalTo
Use ref.startAt(‘someKey’) with a limitToFirst statement to read from the top of a list (ascending order) and to start somewhere in the middle of the list. Omitting the startAt while using a limitToFirst would cause the query to read from the very top of the list.
Use ref.endAt(‘someKey’) with a limitToLast statement to read from the bottom of a list (descending order) and to start somewhere in the middle of the list. Omitting the endAt while using a limitToLast would cause the query to read from the very bottom of the list.
Using ref.equalTo(‘someKey’) is effectively using a startAt and an endAt query combined. You’re not allowed to use more than one of these query range statements on a single ref, so Firebase provides the equalTo range to let you specify both.
Note that using startAt with limitToLast or endAt with limitToFirst produces unexpected behavior. You’ll see why in a few paragraphs… it’s harder to explain with words than with an example.
So let’s assume that we have an object with zero-indexed keys, much like a Javascript array. Numeric keys are a Firebase anti-pattern. Notice that we don’t have a key “10”, because keys are always alpha-sorted and “10” would sort like this: “0”, “1”, “10”, “2”, “3”…
Again, numeric keys are a Firebase anti-pattern. We should be using push keys… but push keys make for horrible demos, because humans don’t sort long alphanumeric keys in our heads.
“fruit”: {
“1”: “banana”,
“2”: “pear”,
“3”: “orange”,
“4”: “tomato”,
“5”: “mango”,
“6”: “pineapple”,
“7”: “strawberry”,
“8”: “grapefruit”,
“9”: “cranberry”
“10”: “tangerine”
}
Let’s assume a fruitRef that points to the “fruit” node. “If we call fruitRef.orderByKey().endAt(“5”), we’ll receive keys 1…5. If we call fruitRef.orderByKey().startAt(“5”), we’ll receive keys 5…10. It’s pretty straightforward. If we run fruitRef.orderByKey().equalTo(“5”)… well, you get the pattern… it returns key “5": “mango”.
Limit results
Query orders and ranges are useful on their own, but they hit their stride when combined with limit statements. You’ll want to use limits for most of your queries to avoid pulling down any more data than necessary.
You’ve got two options for limits:
-
limitToLast
-
limitToFirst
Let’s refer back to the fruit “array” we used earlier and run through a few scenarios.
-
fruitRef.orderByKey().limitToLast(3): returns keys 8, 9, 10
-
fruitRef.orderByKey().limitToFirst(3): returns keys 1, 2, 3
-
fruitRef.orderByKey().startAt(“5”).limitToLast(3): returns keys 8, 9, 10
-
fruitRef.orderByKey().startAt(“5”).limitToLast(10): returns keys 5, 6, 7, 8, 9, 10 (bookend query)
-
fruitRef.orderByKey().startAt(“5”).limitToFirst(3): returns keys 5, 6, 7
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fruitRef.orderByKey().endAt(“5”).limitToLast(3): returns keys 3, 4, 5
-
fruitRef.orderByKey().endAt(“5”).limitToFirst(3): returns keys 1, 2, 3
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fruitRef.orderByKey().endAt(“5”).limitToFirst(10): returns keys 1, 2, 3, 4, 5 (bookend query)
Scenarios 3 and 4 require a little explanation. They both have startAt ranges starting at “5” and going to the end of the list. The limitToLast statements still read from the end of the list, so the startAt range acts like a bookend to the query. Think of startAt and endAt as ranges, less as starting and ending points. Notice that scenarios 7 and 8 are the inverse of 3 and 4.
A note on orderBy methods* We’re ordering by key in this example, but ordering by child, value or priority works the same. Firebase will first try to sort the keys/children/priorities/values numerically, and then it will sort them as strings… so if you have a mix of numbers and strings, the numbers will sort to the top and the strings to the bottom.
You’ll typically avoid this confusion by remembering that sorting on a mix of numbers and strings is ridiculous.
The REST API
All of the queries described above are also available as raw JSON via Firebase’s REST API. The REST API docs cover it all. Just know that if you can query it with the JavaScript SDK, you can query it with REST.
But the REST API does provide one extra feature that you’ll need: shallow queries.
Shallow queries are available only via REST, and they’re crucial for handling large datasets. Shallow queries let you query just the child keys from a particular node. Try hitting https://docs-examples.firebaseio.com/rest/retrieving-data.json in your browser. You should see something like this:
{
body: “Hello!”,
message: {
user: {
name: “Chris”
}
}
}
Now hit the same url but with shallow=true as a query paramter, https://docs-examples.firebaseio.com/rest/retrieving-data.json?shallow=true.
{
body: true,
message: true
}
See how you get just the top-level keys? This is the only way to query Firebase data that does not return entire objects. If your data is huge, use shallow REST queries to sort through large lists and decide exactly what data you need to query normally through the SDK.
Pagination Exercise
Firebase does not have built in pagination. Firebase collections are meant to be consumed as streams of data, so imagine running a query like fruitRef.orderByKey().limitToLast(3).on(‘child_added’, callback). Your callback will get called three times, once for each of the last three results. But imagine a scenario where users are adding more fruit in realtime… so pretty soon your callback will fire again for “11”: “artichoke” or whatever else your users are adding. If you’re listening to the child_removed event on the same query, you’ll get a callback there as well because “8”: “grapefruit” has just fallen off of the query.
The point is that you need to be thinking of streams and events instead of thinking of static pagination. Your apps are realtime. Firebase is realtime. We need to reason about pagination as moving up and down a flowing stream of data.
To test this out, let’s run the following code to load a bunch of data from the Star Wars API (SWAPI). You’ll need to run npm install axios firebase in a new folder to get the dependencies. You’ll also need to change the firebase.initializeApp(payload) payload to match the location of your service-account.json file and the databaseURL of your Firebase.
Now check your Firebase Realtime Database viewer at /swapi/people to make sure that you have 10 Star Wars characters stored in the collection. They’re currently indexed by their SWAPI person number. I would typically recommend using push keys with peopleRef.push(res.person), but SWAPI has person ID numbers already, so matching those won’t hurt. Just don’t try to create your own ID system… when in doubt, use push keys.
We’re going to demonstrate two ways to paginate through this list, each with its own costs and benefits.
Cursor pagination
Cursor pagination scales forever, but you have to step forwards or backwards through the pages one at a time. You don’t know how many total pages you have, and you can’t skip pages.
In this example we have 10 records indexed 1…10 and a page length of 2 records per page. You simply request 3 records, pop the third record off to use as a cursor, and add the first 2 records to the page.
The following example recursively gets all of the pages and spits out an array of pages. Try running this code on your own machine to see it in action. Make sure to edit the path to your service-account.json if it’s different, and definitely change your databaseURL to match your Firebase. Also make sure that you’ve run load-swapi-data.js to populate your swapi/people node.
Keys-based pagination
Keys-based pagination differs from cursor pagination in that you first request all of the child keys using a REST call and then create page breaks from the list of keys. It’s great when you have a limited number of child records, because you know exactly how many pages you have and you can jump backwards and forwards through the pagination.
The following example uses keys-based pagination to return an array of all of the pages. Note, this is just an example. You’d never request all of the data right off the bat like this. In regular, non-demo practice you’ll create a list of page keys and only request the data as needed when your user jumps to a specific page.
Try running this locally like you did for the cursor pagination code to see it in action.
A quick summary, because this can be confusing
Let’s be clear. These queries can be tricky to compose. I played around for about an hour to get both of these pagination examples working, and it wasn’t the first time that I’ve written these kinds of pagination.
Here’s what you need to remember:
-
Always specify your orderBy* parameter first
-
Use limitToFirst to read from the top of the list (ascending sort order)
-
Use limitToLast to read from the bottom of the list (descending sort order)
-
If you’re using limitToFirst, use startAt to start reading from the middle of the list. Otherwise, limitToFirst will default to reading from the very top of the list.
-
If you’re using limitToLast, use endAt to start reading from the middle of the list. Otherwise, limitToLast will default to reading from the very bottom of the list.
-
Don’t pair up limitToFirst with endAt. It just “bookends” the query.
-
Don’t pair up limitToLast with startAt. It just “bookends” the query.
That’s Firebase queries! Play around with these pagination examples and you’ll get the hang of it.
Quiz
Review value and child_added events in the docs and answer the following questions.
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Which event is best for returning a single item?
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Which event is best for returning lists of items?
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Can the *value *event be used to retrieve a shallow copy of a node?
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Which event consistently returns sorted data?
Create a demo folder and wire up a Node.js file to read data from your Firebase. Complete the following tasks in Node.js.
- Create a list of items using push keys that looks something like this (but with your own push keys… they’re unique):
{
-KIhlFRg9KB7eDjVVGYr: 1,
-KIhlFRle3WO2N0xcX20: 2,
-KIhlFRnXobs-JZXqn1c: 3,
-KIhlFRnXobs-JZXqn1d: 4,
-KIhlFRnXobs-JZXqn1e: 5,
-KIhlFRnXobs-JZXqn1f: 6,
-KIhlFRnXobs-JZXqn1g: 7,
-KIhlFRnXobs-JZXqn1h: 8,
-KIhlFRnXobs-JZXqn1i: 9,
-KIhlFRnXobs-JZXqn1j: 10
}
- Create a series of queries and use the child_added listener to return the following record sets. Use ref.orderByValue() as necessary.
- 1, 2, 3, 4
- 4, 5, 6, 7
- The last four records ending in record 9 (records 6, 7, 8, 9)
- The first four records starting with record 2 (records 2, 3, 4, 5)
-
Add a security rule (“.indexOn”: [“.value”]) to your list node to get rid of the FIREBASE WARNING messages you’re likely seeing.
-
Stretch Task: Implement pagination with the REST and cursor methods, but instead of querying all of the pages at once as seen in the earlier examples, try querying one page at a time. Maybe the REST pagination function can take a specific page number and return just those results, and the cursor method can read out the first three pages and stop.