Sort with indexes
FaunaDB’s sorting is accomplished using indexes, specifically by
ordering of an index’s values
. The values
field in an index defines
one or more fields that are returned in the result set, and the fields
can be in ascending or descending order.
This tutorial demonstrates how to achieve various sorting goals using indexes:
This tutorial assumes that you have successfully prepared your database by creating the necessary collections and documents. |
Sort a single field
To sort a single field, we need to construct an appropriate index. For
this example, let’s sort the documents in the People
collection by the
first
field. Copy the following query, paste it into the Shell, and
run it:
CreateIndex({
name: "people_sort_by_first_asc",
source: Collection("People"),
values: [
{ field: ["data", "first"] },
{ field: ["ref"] }
]
})
The points of interest for this query:
-
It is a good practice to name an index after its collection, its purpose, which field(s) are involved in the purpose, and the sort direction.
-
We specify two fields for
values
:-
The
first
field, which exists in the document’sdata
field. -
The document’s
ref
, so that we can easily retrieve the document.
-
When you run the query, the result should be similar to:
{
"ref": Index("people_sort_by_first_asc"),
"ts": 1565314335810000,
"active": true,
"serialized": true,
"name": "people_sort_by_first_asc",
"source": Collection("People"),
"values": [
{
"field": [
"data",
"first"
]
},
{
"field": [
"ref"
]
}
],
"partitions": 8
}
Before we see the sorted results, let’s see the order we get when using using the collection index (created when we prepared our tutorial data). Copy the following query, paste it into the Shell, and run it:
Map(
Paginate(Match(Index("all_people"))),
Lambda(
"X",
Select(["data", "first"], Get(Var("X")))
)
)
The points of interest for this query are:
-
We use the
Map
function to process each of thePaginate
results with aLambda
function. -
We use the variable named
X
, just to provide a variable name viaVar
. You can use any variable name you like. -
We only need one variable for the
Lambda
function, because our index only returns one value for each document in the collection: the document’s Ref. If our index specified avalues
field, we would need to use one variable per field defined by thevalues
field. -
The
Lambda
function calls theGet
function to retrieve the document specified by theX
variable. To avoid returning everything in each document, theSelect
function is used to extract just thefirst
field from each document.
When you run the query, the output should be similar to:
{
"data": [
"Alan",
"Tim",
"Leslie",
"Marvin",
"Alan",
"Grace",
"Stephen"
]
}
The order you see depends on the order of each document’s ref during the creation query.
Now, let’s use our new index to see the names in order. Copy the following query, paste it into the Shell, and run it:
Paginate(Match(Index("people_sort_by_first_asc")))
There was no need to use Map
this time: our index contains the value
of the first
field, so there is no need to use the Get
function to
retrieve the document. This also reduces the number of read operations,
which could save you some money.
When you run this query, the output should be similar to:
{
"data": [
[
"Alan",
Ref(Collection("People"), "240166254282801673")
],
[
"Alan",
Ref(Collection("People"), "240166254282805769")
],
[
"Grace",
Ref(Collection("People"), "240166254282806793")
],
[
"Leslie",
Ref(Collection("People"), "240166254282803721")
],
[
"Marvin",
Ref(Collection("People"), "240166254282804745")
],
[
"Stephen",
Ref(Collection("People"), "240166254282807817")
],
[
"Tim",
Ref(Collection("People"), "240166254282802697")
]
]
}
What if we want to show the list in reverse order? For that, we need to construct another index. Copy the following query, paste it into the Shell, and run it:
CreateIndex({
name: "people_sort_by_first_desc",
source: Collection("People"),
values: [
{ field: ["data", "first"], reverse: true },
{ field: ["ref"] }
]
})
This query creates an index almost identical to the first index that we created. The only two differences are:
-
The index name indicates "desc"ending order.
-
The first field in
values
setsreverse
totrue
. This causes the index to sort by thefirst
field in descending order.
Let’s run a revised version of our "sort" query that uses descending order. Copy the following query, paste it into the shell, and run it:
Paginate(Match(Index("people_sort_by_first_desc")))
When you run this query, the result should be similar to:
{
"data": [
[
"Tim",
Ref(Collection("People"), "240166254282802697")
],
[
"Stephen",
Ref(Collection("People"), "240166254282807817")
],
[
"Marvin",
Ref(Collection("People"), "240166254282804745")
],
[
"Leslie",
Ref(Collection("People"), "240166254282803721")
],
[
"Grace",
Ref(Collection("People"), "240166254282806793")
],
[
"Alan",
Ref(Collection("People"), "240166254282801673")
],
[
"Alan",
Ref(Collection("People"), "240166254282805769")
]
]
}
Sort multiple fields
To sort on multiple fields, there are a couple of approaches. In this section, we demonstrate using a single index to sort multiple fields.
For this demonstration, we’ll sort by last
and then first
. To do so,
we need to create an appropriate index. Copy the following query, paste
it into the Shell, and run it:
CreateIndex({
name: "people_sort_by_last_first_asc",
source: Collection("People"),
values: [
{ field: ["data", "last"] },
{ field: ["data", "first"] },
{ field: ["ref"] }
]
})
Now let’s see the results. Copy the following query, paste it into the Shell, and run it:
Paginate(Match(Index("people_sort_by_last_first_asc")))
When you run this query, the result should be similar to:
{
"data": [
[
"Cook",
"Stephen",
Ref(Collection("People"), "240166254282807817")
],
[
"Cook",
"Tim",
Ref(Collection("People"), "240166254282802697")
],
[
"Hopper",
"Grace",
Ref(Collection("People"), "240166254282806793")
],
[
"Lamport",
"Leslie",
Ref(Collection("People"), "240166254282803721")
],
[
"Minsky",
"Marvin",
Ref(Collection("People"), "240166254282804745")
],
[
"Perlis",
"Alan",
Ref(Collection("People"), "240166254282805769")
],
[
"Turing",
"Alan",
Ref(Collection("People"), "240166254282801673")
]
]
}
What if we want the first
name to be in descending order? We need
another index. Copy the following query, paste it into the Shell, and
run it:
CreateIndex({
name: "people_sort_by_last_asc_first_desc",
source: Collection("People"),
values: [
{ field: ["data", "last"] },
{ field: ["data", "first"], reverse: true },
{ field: ["ref"] }
]
})
Now, let’s see the results. Copy the following query, paste it into the Shell, and run it:
Paginate(Match(Index("people_sort_by_last_asc_first_desc")))
When you run this query, the result should be similar to:
{
"data": [
[
"Cook",
"Tim",
Ref(Collection("People"), "240166254282802697")
],
[
"Cook",
"Stephen",
Ref(Collection("People"), "240166254282807817")
],
[
"Hopper",
"Grace",
Ref(Collection("People"), "240166254282806793")
],
[
"Lamport",
"Leslie",
Ref(Collection("People"), "240166254282803721")
],
[
"Minsky",
"Marvin",
Ref(Collection("People"), "240166254282804745")
],
[
"Perlis",
"Alan",
Ref(Collection("People"), "240166254282805769")
],
[
"Turing",
"Alan",
Ref(Collection("People"), "240166254282801673")
]
]
}
The only notable difference is that, this time, the "Tim Cook" document appears before the "Stephen Cook" document.
Sort considerations
So far, we’ve looked at the "happy path" for sorting. Our indexes have been fully populated, all documents have had consistent values in the indexes fields, and the results have returned as we expected.
What happens when we’re not on the "happy path"? When we created our
Letters
collection, the extra
field was notably less consistent than
the other fields.
Let’s create an index to sort on the extra
field and see what sort of
results are achieved. Copy the following query, paste it into the Shell,
and run it:
CreateIndex({
name: "letters_sort_by_extra_asc",
source: Collection("Letters"),
values: [
{ field: ["data", "extra"] },
{ field: ["ref"] }
]
})
Now, let’s see the results. Copy the following query, paste it into the Shell, and run it:
Map(
Paginate(Match(Index("letters_sort_by_extra_asc"))),
Lambda(
["extra", "ref"],
Var("extra")
)
)
The points of interest for this query:
-
Our
letters_sort_by_extra_asc
index contains two fields invalues
, so ourLambda
function must accept two variables. -
Since our index contains the
extra
field invalues
, we don’t have to fetch the document to return that field. So, we don’t need to call theGet
function, we can just return the value of theextra
variable with theVar
function.
When you run this query, the output should be similar to:
"data": [
11,
24,
"",
"14th",
"16th",
"18th",
"19th",
"20th",
"21st",
"22nd",
"24 + 1",
"4th",
"9th",
"eighth",
"fifteenth",
"fifth",
"First",
"second",
"seventeenth",
"seventh",
"sixth",
"tenth",
"third",
"twenty-third",
null,
null
]
}
When FaunaDB orders values
in indexes, it organizes the output by
type and then sorts values of the same type. The type order is always
the same:
-
Nulls
-
Numbers
-
Booleans
-
Dates
-
Times
-
Refs
-
Objects
-
Arrays
-
Strings
Nulls always appear last in the output (or first, if the field
containing Nulls has reversed: true
set).
So, our output contains Numbers first, then Strings, then Nulls.
Conclusion
This tutorial has demonstrated how to sort documents, by single and multiple fields, using indexes. We’ve also seen how variation in field values can affect sort results.
While it may be a bit more work than you might expect, especially if you are familiar with SQL sorting, FaunaDB’s sorting can be comparable provided that you create all of the indexes required for your sorting situations.
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