Indexing
How to index and search JSON documents
In addition to indexing Redis hashes, Redis Stack can also index JSON documents.
Prerequisites
Before you can index and search JSON documents, you need a database with either:
- Redis Stack, which automatically includes JSON and searching and querying features
- Redis v6.x or later with the following modules installed and enabled:
- RediSearch v2.2 or later
- RedisJSON v2.0 or later
Create index with JSON schema
When you create an index with the FT.CREATE
command, include the ON JSON
keyword to index any existing and future JSON documents stored in the database.
To define the SCHEMA
, you can provide JSONPath expressions.
The result of each JSONPath expression is indexed and associated with a logical name called an attribute
(previously known as a field
).
You can use these attributes in queries.
Note: attribute
is optional for FT.CREATE
.
Use the following syntax to create a JSON index:
FT.CREATE {index_name} ON JSON SCHEMA {json_path} AS {attribute} {type}
For example, this command creates an index that indexes the name, description, price, and image vector embedding of each JSON document that represents an inventory item:
127.0.0.1:6379> FT.CREATE itemIdx ON JSON PREFIX 1 item: SCHEMA $.name AS name TEXT $.description as description TEXT $.price AS price NUMERIC $.embedding AS embedding VECTOR FLAT 6 DIM 4 DISTANCE_METRIC L2 TYPE FLOAT32
See Index limitations for more details about JSON index SCHEMA
restrictions.
Add JSON documents
After you create an index, Redis Stack automatically indexes any existing, modified, or newly created JSON documents stored in the database. For existing documents, indexing runs asynchronously in the background, so it can take some time before the document is available. Modified and newly created documents are indexed synchronously, so the document will be available by the time the add or modify command finishes.
You can use any JSON write command, such as JSON.SET
and JSON.ARRAPPEND
, to create or modify JSON documents.
The following examples use these JSON documents to represent individual inventory items.
Item 1 JSON document:
{
"name": "Noise-cancelling Bluetooth headphones",
"description": "Wireless Bluetooth headphones with noise-cancelling technology",
"connection": {
"wireless": true,
"type": "Bluetooth"
},
"price": 99.98,
"stock": 25,
"colors": [
"black",
"silver"
],
"embedding": [0.87, -0.15, 0.55, 0.03]
}
Item 2 JSON document:
{
"name": "Wireless earbuds",
"description": "Wireless Bluetooth in-ear headphones",
"connection": {
"wireless": true,
"type": "Bluetooth"
},
"price": 64.99,
"stock": 17,
"colors": [
"black",
"white"
],
"embedding": [-0.7, -0.51, 0.88, 0.14]
}
Use JSON.SET
to store these documents in the database:
127.0.0.1:6379> JSON.SET item:1 $ '{"name":"Noise-cancelling Bluetooth headphones","description":"Wireless Bluetooth headphones with noise-cancelling technology","connection":{"wireless":true,"type":"Bluetooth"},"price":99.98,"stock":25,"colors":["black","silver"],"embedding":[0.87,-0.15,0.55,0.03]}'
"OK"
127.0.0.1:6379> JSON.SET item:2 $ '{"name":"Wireless earbuds","description":"Wireless Bluetooth in-ear headphones","connection":{"wireless":true,"type":"Bluetooth"},"price":64.99,"stock":17,"colors":["black","white"],"embedding":[-0.7,-0.51,0.88,0.14]}'
"OK"
Because indexing is synchronous in this case, the documents will be available on the index as soon as the JSON.SET
command returns.
Any subsequent queries that match the indexed content will return the document.
Search the index
To search the index for JSON documents, use the FT.SEARCH
command.
You can search any attribute defined in the SCHEMA
.
For example, use this query to search for items with the word "earbuds" in the name:
127.0.0.1:6379> FT.SEARCH itemIdx '@name:(earbuds)'
1) "1"
2) "item:2"
3) 1) "$"
2) "{\"name\":\"Wireless earbuds\",\"description\":\"Wireless Bluetooth in-ear headphones\",\"connection\":{\"wireless\":true,\"connection\":\"Bluetooth\"},\"price\":64.99,\"stock\":17,\"colors\":[\"black\",\"white\"],\"embedding\":[-0.7,-0.51,0.88,0.14]}"
This query searches for all items that include "bluetooth" and "headphones" in the description:
127.0.0.1:6379> FT.SEARCH itemIdx '@description:(bluetooth headphones)'
1) "2"
2) "item:1"
3) 1) "$"
2) "{\"name\":\"Noise-cancelling Bluetooth headphones\",\"description\":\"Wireless Bluetooth headphones with noise-cancelling technology\",\"connection\":{\"wireless\":true,\"type\":\"Bluetooth\"},\"price\":99.98,\"stock\":25,\"colors\":[\"black\",\"silver\"], \"embedding\":[0.87,-0.15,0.55,0.03]}"
4) "item:2"
5) 1) "$"
2) "{\"name\":\"Wireless earbuds\",\"description\":\"Wireless Bluetooth in-ear headphones\",\"connection\":{\"wireless\":true,\"connection\":\"Bluetooth\"},\"price\":64.99,\"stock\":17,\"colors\":[\"black\",\"white\"],\"embedding\":[-0.7,-0.51,0.88,0.14]}"
Now search for Bluetooth headphones with a price less than 70:
127.0.0.1:6379> FT.SEARCH itemIdx '@description:(bluetooth headphones) @price:[0 70]'
1) "1"
2) "item:2"
3) 1) "$"
2) "{\"name\":\"Wireless earbuds\",\"description\":\"Wireless Bluetooth in-ear headphones\",\"connection\":{\"wireless\":true,\"connection\":\"Bluetooth\"},\"price\":64.99,\"stock\":17,\"colors\":[\"black\",\"white\"],\"embedding\":[-0.7,-0.51,0.88,0.14]}"
And lastly, search for the Bluetooth headphones that are most similar to an image whose embedding is [1.0, 1.0, 1.0, 1.0]:
127.0.0.1:6379> FT.SEARCH itemIdx '@description:(bluetooth headphones)=>[KNN 2 @embedding $blob]' PARAMS 2 blob \x01\x01\x01\x01 DIALECT 2
1) "2"
2) "item:1"
3) 1) "__embedding_score"
2) "1.08280003071"
1) "$"
2) "{\"name\":\"Noise-cancelling Bluetooth headphones\",\"description\":\"Wireless Bluetooth headphones with noise-cancelling technology\",\"connection\":{\"wireless\":true,\"type\":\"Bluetooth\"},\"price\":99.98,\"stock\":25,\"colors\":[\"black\",\"silver\"],\"embedding\":[0.87,-0.15,0.55,0.03]}"
2) "item:2"
3) 1) "__embedding_score"
2) "1.54409992695"
3) "$"
4) "{\"name\":\"Wireless earbuds\",\"description\":\"Wireless Bluetooth in-ear headphones\",\"connection\":{\"wireless\":true,\"connection\":\"Bluetooth\"},\"price\":64.99,\"stock\":17,\"colors\":[\"black\",\"white\"],\"embedding\":[-0.7,-0.51,0.88,0.14]}"
For more information about search queries, see Search query syntax.
FT.SEARCH
queries require attribute
modifiers. Don't use JSONPath expressions in queries because the query parser doesn't fully support them.
Index JSON arrays as TAG
If you want to index string or boolean values as TAG within a JSON array, use the JSONPath wildcard operator.
To index an item's list of available colors, specify the JSONPath $.colors.*
in the SCHEMA
definition during index creation:
127.0.0.1:6379> FT.CREATE itemIdx2 ON JSON PREFIX 1 item: SCHEMA $.colors.* AS colors TAG $.name AS name TEXT $.description as description TEXT
Now you can search for silver headphones:
127.0.0.1:6379> FT.SEARCH itemIdx2 "@colors:{silver} (@name:(headphones)|@description:(headphones))"
1) "1"
2) "item:1"
3) 1) "$"
2) "{\"name\":\"Noise-cancelling Bluetooth headphones\",\"description\":\"Wireless Bluetooth headphones with noise-cancelling technology\",\"connection\":{\"wireless\":true,\"type\":\"Bluetooth\"},\"price\":99.98,\"stock\":25,\"colors\":[\"black\",\"silver\"]}"
Index JSON arrays as TEXT
Starting with RediSearch v2.6.0, full text search can be done on an array of strings or on a JSONPath leading to multiple strings.
If you want to index multiple string values as TEXT, use either a JSONPath leading to a single array of strings, or a JSONPath leading to multiple string values, using JSONPath operators such as wildcard, filter, union, array slice, and/or recursive descent.
To index an item's list of available colors, specify the JSONPath $.colors
in the SCHEMA
definition during index creation:
127.0.0.1:6379> FT.CREATE itemIdx3 ON JSON PREFIX 1 item: SCHEMA $.colors AS colors TEXT $.name AS name TEXT $.description as description TEXT
127.0.0.1:6379> JSON.SET item:3 $ '{"name":"True Wireless earbuds","description":"True Wireless Bluetooth in-ear headphones","connection":{"wireless":true,"type":"Bluetooth"},"price":74.99,"stock":20,"colors":["red","light blue"]}'
"OK"
Now you can do full text search for light colored headphones:
127.0.0.1:6379> FT.SEARCH itemIdx3 '@colors:(white|light) (@name|description:(headphones))' RETURN 1 $.colors
1) (integer) 2
2) "item:2"
3) 1) "$.colors"
2) "[\"black\",\"white\"]"
4) "item:3"
5) 1) "$.colors"
2) "[\"red\",\"light blue\"]"
Limitations
-
When a JSONPath may lead to multiple values and not only to a single array, e.g., when a JSONPath contains wildcards, etc., specifying
SLOP
orINORDER
inFT.SEARCH
will return an error, since the order of the values matching the JSONPath is not well defined, leading to potentially inconsistent results.For example, using a JSONPath such as
$..b[*]
on a JSON value such as{ "a": [ {"b": ["first first", "first second"]}, {"c": {"b": ["second first", "second second"]}}, {"b": ["third first", "third second"]} ] }
may match values in various orderings, depending on the specific implementation of the JSONPath library being used.
Since
SLOP
andINORDER
consider relative ordering among the indexed values, and results may change in future releases, an error will be returned. -
When JSONPath leads to multiple values:
- String values are indexed
null
values are skipped- Any other value type will cause an indexing failure
-
SORTBY
only sorts by the first value -
No
HIGHLIGHT
support -
RETURN
of a Schema attribute, whose JSONPath leads to multiple values, returns only the first value (as a JSON String) -
If a JSONPath is specified by the
RETURN
, instead of a Schema attribute, all values are returned (as a JSON String)
Handling phrases in different array slots:
When indexing, a predefined delta is used to increase positional offsets between array slots for multiple text values. This delta controls the level of separation between phrases in different array slots (related to the SLOP
parameter of FT.SEARCH
).
This predefined value is set by the configuration parameter MULTI_TEXT_SLOP
(at module load-time). The default value is 100.
Index JSON arrays as NUMERIC
Starting with RediSearch v2.6.1, search can be done on an array of numerical values or on a JSONPath leading to multiple numerical values.
If you want to index multiple numerical values as NUMERIC, use either a JSONPath leading to a single array of numbers, or a JSONPath leading to multiple numbers, using JSONPath operators such as wildcard, filter, union, array slice, and/or recursive descent.
For example, add to the item's list the available max_level
of volume (in decibels):
127.0.0.1:6379> JSON.SET item:1 $ '{"name":"Noise-cancelling Bluetooth headphones","description":"Wireless Bluetooth headphones with noise-cancelling technology","connection":{"wireless":true,"type":"Bluetooth"},"price":99.98,"stock":25,"colors":["black","silver"], "max_level":[60, 70, 80, 90, 100]}'
OK
127.0.0.1:6379> JSON.SET item:2 $ '{"name":"Wireless earbuds","description":"Wireless Bluetooth in-ear headphones","connection":{"wireless":true,"type":"Bluetooth"},"price":64.99,"stock":17,"colors":["black","white"], "max_level":[80, 100, 120]}'
OK
127.0.0.1:6379> JSON.SET item:3 $ '{"name":"True Wireless earbuds","description":"True Wireless Bluetooth in-ear headphones","connection":{"wireless":true,"type":"Bluetooth"},"price":74.99,"stock":20,"colors":["red","light blue"], "max_level":[90, 100, 110, 120]}'
OK
To index the max_level
array, specify the JSONPath $.max_level
in the SCHEMA
definition during index creation:
127.0.0.1:6379> FT.CREATE itemIdx4 ON JSON PREFIX 1 item: SCHEMA $.max_level AS dB NUMERIC
OK
You can now search for headphones with specific max volume levels, for example, between 70 and 80 (inclusive), returning items with at least one value in their max_level
array, which is in the requested range:
127.0.0.1:6379> FT.SEARCH itemIdx4 '@dB:[70 80]'
1) (integer) 2
2) "item:1"
3) 1) "$"
2) "{\"name\":\"Noise-cancelling Bluetooth headphones\",\"description\":\"Wireless Bluetooth headphones with noise-cancelling technology\",\"connection\":{\"wireless\":true,\"type\":\"Bluetooth\"},\"price\":99.98,\"stock\":25,\"colors\":[\"black\",\"silver\"],\"max_level\":[60,70,80,90,100]}"
4) "item:2"
5) 1) "$"
2) "{\"name\":\"Wireless earbuds\",\"description\":\"Wireless Bluetooth in-ear headphones\",\"connection\":{\"wireless\":true,\"type\":\"Bluetooth\"},\"price\":64.99,\"stock\":17,\"colors\":[\"black\",\"white\"],\"max_level\":[80,100,120]}"
You can also search for items with all values in a specific range. For example, all values are in the range [90, 120] (inclusive):
127.0.0.1:6379> FT.SEARCH itemIdx4 '-@dB:[-inf (90] -@dB:[(120 +inf]'
1) (integer) 1
2) "item:3"
3) 1) "$"
2) "{\"name\":\"True Wireless earbuds\",\"description\":\"True Wireless Bluetooth in-ear headphones\",\"connection\":{\"wireless\":true,\"type\":\"Bluetooth\"},\"price\":74.99,\"stock\":20,\"colors\":[\"red\",\"light blue\"],\"max_level\":[90,100,110,120]}"
Limitations
When JSONPath leads to multiple numerical values:
- Numerical values are indexed
null
values are skipped- Any other value type will cause an indexing failure
Index JSON arrays as GEO
Starting with RediSearch v2.6.1, search can be done on an array of geo (geographical) values or on a JSONPath leading to multiple geo values.
Prior to RediSearch v2.6.1, only a single geo value was supported per GEO attribute. The geo value was specified using a comma delimited string in the form "longitude,latitude". For example, "15.447083,78.238306".
With RediSearch v2.6.1, a JSON array of such geo values is also supported.
In order to index multiple geo values, user either a JSONPath leading to a single array of geo values, or a JSONPath leading to multiple geo values, using JSONPath operators such as wildcard, filter, union, array slice, and/or recursive descent.
null
values are skipped- Other values will cause an indexing failure (bool, number, object, array, wrongly formatted GEO string, invalid coordinates)
For example, add to the item's list the vendor_id
, that is, where an item can be physically purchased:
127.0.0.1:6379> JSON.SET item:1 $ '{"name":"Noise-cancelling Bluetooth headphones","description":"Wireless Bluetooth headphones with noise-cancelling technology","connection":{"wireless":true,"type":"Bluetooth"},"price":99.98,"stock":25,"colors":["black","silver"], "max_level":[60, 70, 80, 90, 100], "vendor_id": [100,300]}'
OK
127.0.0.1:6379> JSON.SET item:2 $ '{"name":"Wireless earbuds","description":"Wireless Bluetooth in-ear headphones","connection":{"wireless":true,"type":"Bluetooth"},"price":64.99,"stock":17,"colors":["black","white"], "max_level":[80, 100, 120], "vendor_id": [100,200]}'
OK
127.0.0.1:6379> JSON.SET item:3 $ '{"name":"True Wireless earbuds","description":"True Wireless Bluetooth in-ear headphones","connection":{"wireless":true,"type":"Bluetooth"},"price":74.99,"stock":20,"colors":["red","light blue"], "max_level":[90, 100, 110, 120], "vendor_id": [100]}'
OK
Now add some vendors with their geographic locations:
127.0.0.1:6379> JSON.SET vendor:1 $ '{"id":100, "name":"Kwik-E-Mart", "location":["35.213,31.785", "35.178,31.768", "35.827,31.984"]}'
OK
127.0.0.1:6379> JSON.SET vendor:2 $ '{"id":200, "name":"Cypress Creek", "location":["34.638,31.79", "34.639,31.793"]}'
OK
127.0.0.1:6379> JSON.SET vendor:3 $ '{"id":300, "name":"Barneys", "location":["34.648,31.817", "34.638,31.806", "34.65,31.785"]}'
OK
To index the vendor_id
numeric array, specify the JSONPath $.vendor_id
in the SCHEMA
definition during index creation:
127.0.0.1:6379> FT.CREATE itemIdx5 ON JSON PREFIX 1 item: SCHEMA $.vendor_id AS vid NUMERIC
OK
To index the location
geo array, specify the JSONPath $.location
in the SCHEMA
definition during index creation:
127.0.0.1:6379> FT.CREATE vendorIdx ON JSON PREFIX 1 vendor: SCHEMA $.location AS loc GEO
OK
Now search for a vendor close to a specific location. For example, a customer is located at geo coordinates 34.5,31.5 and you want to get the vendors that are within the range of 40 km from our location:
127.0.0.1:6379> FT.SEARCH vendorIdx '@loc:[34.5 31.5 40 km]' return 1 $.id
1) (integer) 2
2) "vendor:2"
3) 1) "$.id"
1) "200"
4) "vendor:3"
5) 1) "$.id"
1) "300"
Now look for products offered by these vendors:
127.0.0.1:6379> FT.SEARCH itemIdx5 '@vid:[200 300]'
1) (integer) 2
2) "item:2"
3) 1) "$"
2) "{\"name\":\"Wireless earbuds\",\"description\":\"Wireless Bluetooth in-ear headphones\",\"connection\":{\"wireless\":true,\"type\":\"Bluetooth\"},\"price\":64.99,\"stock\":17,\"colors\":[\"black\",\"white\"],\"max_level\":[80,100,120],\"vendor_id\":[100,200]}"
4) "item:1"
5) 1) "$"
2) "{\"name\":\"Noise-cancelling Bluetooth headphones\",\"description\":\"Wireless Bluetooth headphones with noise-cancelling technology\",\"connection\":{\"wireless\":true,\"type\":\"Bluetooth\"},\"price\":99.98,\"stock\":25,\"colors\":[\"black\",\"silver\"],\"max_level\":[60,70,80,90,100],\"vendor_id\":[100,300]}"
Index JSON arrays as VECTOR
Starting with RediSearch 2.6.0, you can index a JSONPath leading to an array of numeric values as a VECTOR type in the index schema.
For example, assume that your JSON items include an array of vector embeddings, where each vector represents an image of a product. To index these vectors, specify the JSONPath $.embedding
in the schema definition during index creation:
127.0.0.1:6379> FT.CREATE itemIdx5 ON JSON PREFIX 1 item: SCHEMA $.embedding AS embedding VECTOR FLAT 6 DIM 4 DISTANCE_METRIC L2 TYPE FLOAT32
OK
127.0.0.1:6379> JSON.SET item:1 $ '{"name":"Noise-cancelling Bluetooth headphones","description":"Wireless Bluetooth headphones with noise-cancelling technology","price":99.98,"stock":25,"colors":["black","silver"],"embedding":[0.87,-0.15,0.55,0.03]}'
OK
127.0.0.1:6379> JSON.SET item:2 $ '{"name":"Wireless earbuds","description":"Wireless Bluetooth in-ear headphones","price":64.99,"stock":17,"colors":["black","white"],"embedding":[-0.7,-0.51,0.88,0.14]}'
OK
Now you can search for the two headphones that are most similar to the image embedding by using vector similarity search KNN query. (Note that the vector queries are supported as of dialect 2.) For example:
127.0.0.1:6379> FT.SEARCH itemIdx5 '*=>[KNN 2 @embedding $blob AS dist]' SORTBY dist PARAMS 2 blob \x01\x01\x01\x01 DIALECT 2
1) (integer) 2
2) "item:1"
3) 1) "dist"
2) "1.08280003071"
3) "$"
4) "{\"name\":\"Noise-cancelling Bluetooth headphones\",\"description\":\"Wireless Bluetooth headphones with noise-cancelling technology\",\"price\":99.98,\"stock\":25,\"colors\":[\"black\",\"silver\"],\"embedding\":[0.87,-0.15,0.55,0.03]}"
4) "item:2"
5) 1) "dist"
2) "1.54409992695"
3) "$"
4) "{\"name\":\"Wireless earbuds\",\"description\":\"Wireless Bluetooth in-ear headphones\",\"price\":64.99,\"stock\":17,\"colors\":[\"black\",\"white\"],\"embedding\":[-0.7,-0.51,0.88,0.14]}"
If you want to index multiple numeric arrays as VECTOR, use a JSONPath leading to multiple numeric arrays using JSONPath operators such as wildcard, filter, union, array slice, and/or recursive descent.
For example, assume that your JSON items include an array of vector embeddings, where each vector represents a different image of the same product. To index these vectors, specify the JSONPath $.embeddings[*]
in the schema definition during index creation:
127.0.0.1:6379> FT.CREATE itemIdx5 ON JSON PREFIX 1 item: SCHEMA $.embeddings[*] AS embeddings VECTOR FLAT 6 DIM 4 DISTANCE_METRIC L2 TYPE FLOAT32
OK
127.0.0.1:6379> JSON.SET item:1 $ '{"name":"Noise-cancelling Bluetooth headphones","description":"Wireless Bluetooth headphones with noise-cancelling technology","price":99.98,"stock":25,"colors":["black","silver"],"embeddings":[[0.87,-0.15,0.55,0.03]]}'
OK
127.0.0.1:6379> JSON.SET item:2 $ '{"name":"Wireless earbuds","description":"Wireless Bluetooth in-ear headphones","price":64.99,"stock":17,"colors":["black","white"],"embeddings":[[-0.7,-0.51,0.88,0.14],[-0.8,-0.15,0.33,-0.01]]}'
OK
Unlike the case with the NUMERIC type, setting a static path such as $.embedding
in the schema for the VECTOR type does not allow you to index multiple vectors stored under that field. Hence, if you set $.embedding
as the path to the index schema, specifying an array of vectors in the embedding
field in your JSON will cause an indexing failure.
Now you can search for the two headphones that are most similar to an image embedding by using vector similarity search KNN query. (Note that the vector queries are supported as of dialect 2.) The distance between a document to the query vector is defined as the minimum distance between the query vector to a vector that matches the JSONPath specified in the schema. For example:
127.0.0.1:6379> FT.SEARCH itemIdx5 '*=>[KNN 2 @embeddings $blob AS dist]' SORTBY dist PARAMS 2 blob \x01\x01\x01\x01 DIALECT 2
1) (integer) 2
2) "item:2"
3) 1) "dist"
2) "0.771500051022"
3) "$"
4) "{\"name\":\"Wireless earbuds\",\"description\":\"Wireless Bluetooth in-ear headphones\",\"price\":64.99,\"stock\":17,\"colors\":[\"black\",\"white\"],\"embeddings\":[[-0.7,-0.51,0.88,0.14],[-0.8,-0.15,0.33,-0.01]]}"
4) "item:1"
5) 1) "dist"
2) "1.08280003071"
3) "$"
4) "{\"name\":\"Noise-cancelling Bluetooth headphones\",\"description\":\"Wireless Bluetooth headphones with noise-cancelling technology\",\"price\":99.98,\"stock\":25,\"colors\":[\"black\",\"silver\"],\"embeddings\":[[0.87,-0.15,0.55,0.03]]}"
Note that 0.771500051022
is the L2 distance between the query vector and [-0.8,-0.15,0.33,-0.01]
, which is the second element in the embedding array, and it is lower than the L2 distance between the query vector and [-0.7,-0.51,0.88,0.14]
, which is the first element in the embedding array.
For more information on vector similarity syntax, see Vector fields.
Index JSON objects
You cannot index JSON objects. If the JSONPath expression returns an object, it will be ignored.
To index the contents of a JSON object, you need to index the individual elements within the object in separate attributes.
For example, to index the connection
JSON object, define the $.connection.wireless
and $.connection.type
fields as separate attributes when you create the index:
127.0.0.1:6379> FT.CREATE itemIdx3 ON JSON SCHEMA $.connection.wireless AS wireless TAG $.connection.type AS connectionType TEXT
"OK"
After you create the new index, you can search for items with the wireless TAG set to true
:
127.0.0.1:6379> FT.SEARCH itemIdx3 '@wireless:{true}'
1) "2"
2) "item:2"
3) 1) "$"
2) "{\"name\":\"Wireless earbuds\",\"description\":\"Wireless Bluetooth in-ear headphones\",\"connection\":{\"wireless\":true,\"connection\":\"Bluetooth\"},\"price\":64.99,\"stock\":17,\"colors\":[\"black\",\"white\"]}"
4) "item:1"
5) 1) "$"
2) "{\"name\":\"Noise-cancelling Bluetooth headphones\",\"description\":\"Wireless Bluetooth headphones with noise-cancelling technology\",\"connection\":{\"wireless\":true,\"type\":\"Bluetooth\"},\"price\":99.98,\"stock\":25,\"colors\":[\"black\",\"silver\"]}"
You can also search for items with a Bluetooth connection type:
127.0.0.1:6379> FT.SEARCH itemIdx3 '@connectionType:(bluetooth)'
1) "2"
2) "item:1"
3) 1) "$"
2) "{\"name\":\"Noise-cancelling Bluetooth headphones\",\"description\":\"Wireless Bluetooth headphones with noise-cancelling technology\",\"connection\":{\"wireless\":true,\"type\":\"Bluetooth\"},\"price\":99.98,\"stock\":25,\"colors\":[\"black\",\"silver\"]}"
4) "item:2"
5) 1) "$"
2) "{\"name\":\"Wireless earbuds\",\"description\":\"Wireless Bluetooth in-ear headphones\",\"connection\":{\"wireless\":true,\"type\":\"Bluetooth\"},\"price\":64.99,\"stock\":17,\"colors\":[\"black\",\"white\"]}"
Field projection
FT.SEARCH
returns the entire JSON document by default. If you want to limit the returned search results to specific attributes, you can use field projection.
Return specific attributes
When you run a search query, you can use the RETURN
keyword to specify which attributes you want to include in the search results. You also need to specify the number of fields to return.
For example, this query only returns the name
and price
of each set of headphones:
127.0.0.1:6379> FT.SEARCH itemIdx '@description:(headphones)' RETURN 2 name price
1) "2"
2) "item:1"
3) 1) "name"
2) "Noise-cancelling Bluetooth headphones"
3) "price"
4) "99.98"
4) "item:2"
5) 1) "name"
2) "Wireless earbuds"
3) "price"
4) "64.99"
Project with JSONPath
You can use JSONPath expressions in a RETURN
statement to extract any part of the JSON document, even fields that were not defined in the index SCHEMA
.
For example, the following query uses the JSONPath expression $.stock
to return each item's stock in addition to the name and price attributes.
127.0.0.1:6379> FT.SEARCH itemIdx '@description:(headphones)' RETURN 3 name price $.stock
1) "2"
2) "item:1"
3) 1) "name"
2) "Noise-cancelling Bluetooth headphones"
3) "price"
4) "99.98"
5) "$.stock"
6) "25"
4) "item:2"
5) 1) "name"
2) "Wireless earbuds"
3) "price"
4) "64.99"
5) "$.stock"
6) "17"
Note that the returned property name is the JSONPath expression itself: "$.stock"
.
You can use the AS
option to specify an alias for the returned property:
127.0.0.1:6379> FT.SEARCH itemIdx '@description:(headphones)' RETURN 5 name price $.stock AS stock
1) "2"
2) "item:1"
3) 1) "name"
2) "Noise-cancelling Bluetooth headphones"
3) "price"
4) "99.98"
5) "stock"
6) "25"
4) "item:2"
5) 1) "name"
2) "Wireless earbuds"
3) "price"
4) "64.99"
5) "stock"
6) "17"
This query returns the field as the alias "stock"
instead of the JSONPath expression "$.stock"
.
Highlight search terms
You can highlight relevant search terms in any indexed TEXT
attribute.
For FT.SEARCH
, you have to explicitly set which attributes you want highlighted after the RETURN
and HIGHLIGHT
parameters.
Use the optional TAGS
keyword to specify the strings that will surround (or highlight) the matching search terms.
For example, highlight the word "bluetooth" with bold HTML tags in item names and descriptions:
127.0.0.1:6379> FT.SEARCH itemIdx '(@name:(bluetooth))|(@description:(bluetooth))' RETURN 3 name description price HIGHLIGHT FIELDS 2 name description TAGS '<b>' '</b>'
1) "2"
2) "item:1"
3) 1) "name"
2) "Noise-cancelling <b>Bluetooth</b> headphones"
3) "description"
4) "Wireless <b>Bluetooth</b> headphones with noise-cancelling technology"
5) "price"
6) "99.98"
4) "item:2"
5) 1) "name"
2) "Wireless earbuds"
3) "description"
4) "Wireless <b>Bluetooth</b> in-ear headphones"
5) "price"
6) "64.99"
Aggregate with JSONPath
You can use aggregation to generate statistics or build facet queries.
The LOAD
option accepts JSONPath expressions. You can use any value in the pipeline, even if the value is not indexed.
This example uses aggregation to calculate a 10% price discount for each item and sorts the items from least expensive to most expensive:
127.0.0.1:6379> FT.AGGREGATE itemIdx '*' LOAD 4 name $.price AS originalPrice APPLY '@originalPrice - (@originalPrice * 0.10)' AS salePrice SORTBY 2 @salePrice ASC
1) "2"
2) 1) "name"
2) "Wireless earbuds"
3) "originalPrice"
4) "64.99"
5) "salePrice"
6) "58.491"
3) 1) "name"
2) "Noise-cancelling Bluetooth headphones"
3) "originalPrice"
4) "99.98"
5) "salePrice"
6) "89.982"
FT.AGGREGATE
queries require attribute
modifiers. Don't use JSONPath expressions in queries, except with the LOAD
option, because the query parser doesn't fully support them.
Index limitations
Schema mapping
During index creation, you need to map the JSON elements to SCHEMA
fields as follows:
- Strings as
TEXT
,TAG
, orGEO
. - Numbers as
NUMERIC
. - Booleans as
TAG
. - JSON array
- Array of strings as
TAG
orTEXT
. - Array of numbers as
NUMERIC
orVECTOR
. - Array of geo coordinates as
GEO
. null
values in such arrays are ignored.
- Array of strings as
- You cannot index JSON objects. Index the individual elements as separate attributes instead.
null
values are ignored.
Sortable tags
If you create an index for JSON documents with a JSONPath leading to an array or to multiple values, only the first value is considered by the sort.