Domain Specific Language (DSL)
Fusion Domain Specific Language (DSL) provides expected search results as a JSON response in a way that reduces search query complexity for the user.
Previously, users needed to understand complex syntax to express certain search queries in Fusion (for example, the best way to express a facet filter). DSL gives Fusion control over how to execute a query by transforming a structured query input into a Solr request, where we can add intelligence around the index and the user’s intent.
In Fusion 5.2.2, Fusion Domain Specific Language (DSL) functions are only available in beta release. |
Why Search DSL
Fusion Search Domain Specific Language (DSL) reduces search query complexity for the user. Fusion Search DSL supports expressive search queries and responses via a structured, modern JSON format.
Search DSL is an alternative to the current (now referred to as) “Legacy” format for performing search queries. Previously, users needed to understand complex syntax to express certain search queries in Fusion (for example, the best way to express a facet filter).
Compared to the legacy Solr parameter format, Search DSL is structured to more closely align with the central concepts of Fusion and provide a more usable alternative for expressing complex Fusion queries.
Search DSL gives Fusion control over how to execute a query by transforming a structured query input into a Solr request, at which time Fusion can add intelligence around the index and the user’s intent.
Limitations
Despite the advantages, there are still some important limitations to be aware of when deciding whether to use the Fusion Search DSL.
These limitations only apply to DSL queries. Legacy queries can still be issued separately from DSL queries without being subject to these limitations. |
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Head / Tail Rewrite. Support is currently limited when using DSL queries:
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In order to work on DSL queries, the
Improved Query
must be entered in as a JSON string representing the desiredmain
query that should be issued (this replaces thequeryDefinition.main
field in the rewritten DSL query) -
The query rewrites produced by the built-in head/tail rewrite job will NOT work on DSL queries, as the job only outputs legacy-style rewrites
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Query Stage Support. All query stages are fully supported
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Rules Support. All kinds of rules are fully supported with the exceptions noted below
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Set Params. Not supported
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Custom Rule. Not supported
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Request Format
This section describes each top-level field of a Search DSL request.
Overview
The Search DSL format is supported in the following endpoints:
query pipelines |
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query profiles |
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templating render |
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In all cases, it should be a POST with a Content-Type: application/json
header.
The below table briefly summarizes the function of each of the top-level fields.
Field | Description |
---|---|
|
Defines the logic of what to query for. The |
|
Defines how the results should be displayed and organized. A variety of fields are available here, such as |
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The faceting configuration for the query. Defines the fields to perform faceting on as well as the desired behavior of the returned facet values. Supports range facets in the |
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Accepts parameters used by some query stages as well as DSL hints. Should not be necessary for typical use cases. For example, |
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Allows arbitrary query parameters to be added to the underlying Solr query. Should not be necessary for most use cases - the other DSL fields should be used when possible, but this field can be used when those fields do not suffice. If the Security Trimming Stage is in use, this field can be used to supply the various parameters for that stage (username, user identity key, collection, shards, etc…). |
The following sections provide an example of each field in use.
More detailed information on each field can be found in the Fusion API Javadocs. |
queryDefinition
{
"queryDefinition": {
"userQuery": "cyberpunk novels",
"main": {
"type": "terms",
"field": "body_t",
"values": ["cyberpunk", "novels"],
"method": "booleanQuery"
},
"filters": [
{
"type": "singleTerm",
"field": "category_t",
"value": ["books"]
}
]
}
}
The queryDefinition
defines the logic of what to query for. The above example queries for “cyberpunk novels” against the body_t
field, additionally filtering to only show matches that have “books” in the category_t
field.
results
{
"results": {
"start": 20,
"size": 20,
"group": {
"field": "author",
"size": 5
}
}
}
The results
defines how the results should be displayed and organized. The above example is set to show the next 20 results starting from the 21st matched document (as with Solr, start
is 0-based). Additionally, results will be grouped by author, showing 5 results per group. In the DSL response, the head document of each group will show up in the results list with the other documents in the group in the head doc’s groupedDocs
field.
facets
{
"facets": {
"fields": [
{
"field": "category",
"limit": 5
},
{
"field": "brand",
"offset": "10"
}
],
"ranges": [
{
"field": "published_dt",
"gap": "+1YEAR",
"start": "2006-01-01T00:00:00Z",
"end": "2020-01-01T00:00:00Z"
}
]
}
}
The facets
field controls faceting for the query. In the above example, faceting is enabled on the category
field (limiting to show only 5 values), brand field (showing all values starting from the 11th value), and published_dt
field (showing 1 year increments between 2006 and 2020).
context
{
"context": {
"tags": "sometag",
"lw.rules.debug": "1"
}
}
The context
field accepts parameters used by various query stages as well as DSL hints. In the above example, the tags parameter has been specified for the Apply Rules stage which will cause only rules with the “sometag” tag to be triggered. The lw.rules.debug
parameter has also been specified to return extra rule triggering information in the response.
params
{
"params": {
"uid": "je985"
}
}
The params
field allows arbitrary query parameters to be added to the underlying Solr query and is also used to supply Security Trimming Stage parameters. In the above query, the user’s id has been supplied for the Security Trimming Stage.
Response Format
This section describes each top-level field of a Search DSL response.
Overview
The below table briefly summarizes the function of each of the top-level fields. The following sections provide an example of each field in a real response (some parts omitted for brevity).
Field | Description |
---|---|
|
Holds the results list with pagination info, scoring, and hit count. When grouping is performed via the |
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Holds the returned facets and facet values. Each facet has an associated |
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Holds data returned by any rules that triggered. There are array fields for data from particular rule types: |
|
Holds all the spelling suggestions. Suggestions are provided for any misspelled words via the |
|
Assorted metadata about the query, such as timing and debug information. The |
results
{
"results": {
"list": {
"hits": 1024,
"maxScore": 1.0,
"pagination": {
"start": 10
}
"docs": [
{
"collection": "books",
"type": "generic",
"id": "281",
"score": 1.0,
"fields": {
"author": "Iain Banks"
"title": "Player of Games"
},
"groupedDocs": {
"hits": 228,
"docs": [
{
"collection": "books",
"type": "generic",
"id": "283",
"score": 1.0,
"fields": {
"author": "Iain Banks"
"title": "Consider Phlebas"
}
}
]
}
},
...additional docs...
]
}
}
}
The results
field holds the results list with pagination info, scoring, and hit count. In the above, grouping has been performed on the author
field.
facets
{
"facets": {
"field": {
"category": {
"label": "Category",
"counts": [
{
"name": "Sci-Fi",
"count": 7
},
{
"name": "Fantasy",
"count": 3
}
...additional values...
]
},
... additional field facets...
}
},
"range": {
"published_dt": {
"label": "Publication Date",
"gap": "+1YEAR",
"start": "2006-01-01T00:00:00Z",
"end": "2020-01-01T00:00:00Z",
"counts": [
...range values...
]
}
}
}
The facets
field holds the returned facets and facet values. In the above, we see facet results for the category
field and a range facet on the published_dt
field, each of which has a corresponding label
configured via a Set Facets rule for a user-friendly display name for the facet.
rules
{
"rules": {
"responseValues": {
"facet_labels": [
"category:Category,published_dt:Publication Date"
]
},
"jsonBlobs": {
"default": [
{
"someField": "someValue"
},
{
"someField": "someValue2"
}
]
}
}
}
The rules
field holds data returned by any rules that triggered. In the above, 3 rules have triggered. A Set Facets rule created a facet_labels entry defining the desired ordering and labels for the facets (the labels are also present in the facets
section of the response). Two JSON Blob rules of type default
have triggered, the first blob in the list having a higher precedence value than the second (and thus appearing first).
spellcheck
{
"spellcheck" : {
"correctlySpelled" : false,
"wordSuggestions" : {
"whiskeys" : {
"startOffset" : 6,
"endOffset" : 14,
"origFreq" : 0,
"wordFreqList" : [ {
"word" : "whiskey",
"freq" : 4764
}, {
"word" : "whiskies",
"freq" : 15963
}, {
"word" : "whisky",
"freq" : 2206
} ]
},
"scoch" : {
"startOffset" : 0,
"endOffset" : 5,
"origFreq" : 0,
"wordFreqList" : [ {
"word" : "scotch",
"freq" : 1556
}, {
"word" : "scott",
"freq" : 3340
}, {
"word" : "stock",
"freq" : 78
}, {
"word" : "shock",
"freq" : 9
} ]
}
},
"querySuggestions" : [ {
"query" : "scotch whiskey",
"hits" : 6320,
"corrections" : {
"whiskeys" : "whiskey",
"scoch" : "scotch"
}
} ]
}
}
The spellcheck
field holds all the spelling suggestions. Above, the query has misspelled “scotch whiskey” as “scoch whiskeys” and a number of suggestions are provided for each word as well as a collation with the fully corrected query.
meta
{
"meta": {
"timing": {
"total": 105,
"mainQuery": 14,
"pipeline": [
... pipeline stage timing info..
]
},
"debug": {
"solrParams": {
"fl": "*,score",
"facet": "true"
...additional solr params...
}
}
}
}
The meta
field holds assorted metadata about the query, such as timing and debug information. Above, in the timing.mainQuery
field we see that the underlying Solr query took 14 ms (taken from Solr’s QTime) while the total
field shows that the entire DSL query took 105 ms. The timings of individual pipeline stages are broken down in the pipeline
field. The debug
field here shows the various parameters that were sent in the underlying Solr query.