Query API Reference

See the YQL query guide for examples, and the reference for details.

A positive integer, including 0. The maximum number of hits to return from the result set.

hits is capped at maxHits, default 400. maxHits can be set in a query profile.

Number of hits can also be set in YQL.

To implement pagination: The number of hits to skip when returning the result. A positive integer, including 0.

offset is capped at maxOffset, default 1000. maxOffset can be set in a query profile.

Offset can also be set in YQL.

A query profile id with format name:version, where version can be omitted or partially specified, e.g. myprofile:2.1. A query profile has default properties for a query. The default query profile is named default.

Set to true to enable grouping session cache. See the grouping reference for details.

A search chain id with format name:version, where version can be omitted or partially specified, e.g. mychain:2.1.3. The search chain initially invoked when processing the query. This search chain may invoke other chains.

Positive floating point number with an optional unit. Default unit is seconds (s), valid unit strings are e.g. ms and s. To set a timeout of one minute, the argument could be set to 60 s. Space between the number and the unit is optional.

It specifies the overall timeout of the query execution and can be defined in a query profile. Different classes of queries can then easily have a different latency budget/timeout using different profiles.

At timeout, the hits generated thus far are returned, refer to ranking.softtimeout.enable for details on HTTP status codes and response elements.

Refer to the Query API guide for more details on timeout handling.

An index name. The field which is searched for query terms which doesn't explicitly specify an index. Also see the defaultIndex query annotation.

Encoding names or aliases defined in the IANA character sets. Sets the encoding to use when returning a result. The query is always encoded as UTF-8, independently of how the result will be encoded.

The encodings big5, euc-jp, euc-kr, gb2312, iso-2022-jp and shift-jis also influences how tokenization is done in the absence of an explicit language setting.

A filter string in the Simple Query Language. Sets a filter to be combined with the model.queryString. Typical use of a filter is to add machine generated or preferences based filter terms to the user query. Terms which are passed in the filter are not bolded. The filter is parsed the same way as a query of type any, the full syntax is available. The positive terms (preceded by +) and phrases act as AND filters, the negative terms (preceded by -) act as NOT filters, while the unprefixed terms will be used to RANK the results. Unless the query has no positive terms, the filter will only restrict and influence ranking of the result set, never cause more matches than the query.

A language tag from RFC 5646. Sets the locale and language to use when parsing queries from a language tag, such as en-US. This attribute should always be set when it is known. If this parameter is not set, it will be guessed from the query and encoding, and default to english if it cannot be guessed.

A language tag from RFC 5646, but allowing underscore instead of dash as separator character. A legacy alternative to locale. When this value is accessed, underscores will be replaced by dashes in the returned value. Also see the language query term annotation.

A query string in the Simple Query Language. It is combined with model.filter. See the userQuery operator for how to combine with YQL. Can also be used without YQL.

A comma-delimited list of document type (schema) names, defaulting to all schemas if not set. See multiple schemas and federation.

Use model.sources to restrict to content cluster names or other source names.

Specification of which content nodes a query should be sent to. This is useful for debugging/monitoring and when using Rank phase statistics. Note that in a content cluster with flat distribution (i.e. no <group> element in services.xml), there is 1 implicit group.

If not set, defaults to all nodes in one group, selected by load balancing.

searchpath::ELEMENT [';' ELEMENT]*

ELEMENT::NODE ['/' GROUP]

NODE::EXP [',' EXP]*

EXP::NUM | RANGE

GROUP::NUM

RANGE::'['NUM ',' NUM ' >'

Examples:

• 7/3 = node 7, group 3.
• 7/ = node 7, any group.
• 7,1,9/0 = nodes 1,7 and 9, group 0.
• 1,[3,9>/0 = nodes 1,3,4,5,6,7,8, group 0.

A comma-separated list of content cluster names or other source names, defaulting to all sources/clusters if not set. The names of the sources to query, e.g. one or more content clusters and/or federated sources - see content cluster mapping. Also see federation.

Use model.restrict to restrict to schemas.

Selects the query language syntax of the model.queryString parameter: all, weakAnd, any, phrase, tokenize, web, yql - refer to simple query language reference. Also see YQL grammar.

See Geo search. Point (two-dimensional location) to use as base for location ranking.

Set a query rank feature input to a value. The key must be a query feature - query(anyname), and the value must be a double, string (to be hashed to a double), or a tensor matching the declared input type on tensor literal form - see the tensor user guide. Examples:

input.query(userageDouble)=42.1

input.query(stringToBeHashed)=abcd

input.query(myIndexedTensor)=[1.0, 2.0, 3.0]

input.query(myMappedTensor)={"Tablet Keyboard Cases": 0.8, "Keyboards":0.3}

Set to true to request all rank-features to be calculated and returned. The rank features will be returned in the summary field rankfeatures. This option is typically used for MLR training, should not to be used for production.

Sets rank profile to use for assigning rank scores for documents. The default rank profile will be used for backends which does not have the given rank profile.

Set a rank property that is passed to, and used by a feature executor for this query. Example: query=foo&ranking.properties.dotProduct.X={a:1,b:2}

By default, the hits available are returned on timeout. To return no hits at timeout instead, set ranking.softtimeout.enable=false.

Softtimeout uses ranking.softtimeout.factor of the timeout, default 70%. The rest of the time budget is spent on later ranking phases.

The factor is adaptive, per rank profile - the factor is adjusted based on remaining time after all ranking phases, unless overridden in the query using ranking.softtimeout.factor.

A timeout element is returned in the query response at timeout.

Example: query with 500ms timeout, use 300ms in first-phase ranking: &ranking.softtimeout.enable=true
&ranking.softtimeout.factor=0.6
&timeout=0.5

The ranking.softtimeout settings controls what the content nodes should do in the case where the latency budget has almost been used (timeout times a factor). Return the documents recalled and ranked with the first phase function within the time used, or simply don't produce a result:

• With soft timeout disabled, the Vespa container will return a 504 timeout without any results.
• When enabled, it will return the documents matched and ranked up until the timeout was reached, with a 200 OK response along with the reason the result set was degraded.

The container might respond with a timeout error with HTTP response code 504 even with soft timeout enabled if the timeout is set so low that the query does not make it to the content nodes, or the container does not have any time left after input and query processing to dispatch the query to the content nodes.

Read more about soft timeout in coverage degradation.

See ranking.softtimeout.enable.

A valid sort specification. Fields you want to sort on must be stored as document attributes in the index structure by adding attribute to the indexing statement.

Sets the time which will be used as now during execution.

[integer], an absolute time in seconds since epoch, or now-[number], to use a time [integer] seconds into the past, or now to use the current time.

Turns query cache on or off. Query is a two-phase process. If the query cache is on, the query is stored on the content nodes between the first and second phase, saving network bandwidth and also query setup time, at the expense of using more memory. It only affects the protocol phase two, see caches in Vespa. It does not cache the result, it just saves resources by not forwarding the query twice (one for the first protocol phase which is find the best k documents from all nodes, to the second phase which is to fill summary data and potentially ranking features listed in summary-features in the rank profile).

The summary-features are re-calculated but this setting avoids sending the query down once more. There is little downside of using it, and it can save resources and latency in cases where the query tree and query ranking features (e.g. tensors used in ranking) are large. As this is a protocol optimization, it also works with changing filter, it's not cached cross independent queries, it's just saving having to send the same query twice.

Specifies the number of hits that should be ranked in the second ranking phase. Overrides the rerank-count set in the rank profile.

Specifies the number of hits that should keep rank value. Overrides the keep-rank-count set in the rank profile.

Minimum rankscore for a document to be considered a hit. Overrides the rank-score-drop-limit set in the rank profile.

Specifies the number of hits that should be re-ranked in the global ranking phase. Overrides the rerank-count set in the rank profile.

Rank profile equivalent: num-threads-per-search

Overrides the global persearch threads to a lower value.

Rank profile equivalent: min-hits-per-thread

After estimating the number of hits for a query, this number is used to decide how many search threads to use.

Rank profile equivalent: num-search-partitions

Number of logical partitions the corpus on a content node is divided in. A partition is the smallest unit a search thread will handle.

Rank profile equivalent: termwise-limit

If estimated number of hits > corpus * termwise-limit, document candidates are pruned with a TAAT evaluation for query terms not needed for ranking.

Rank profile equivalent: post-filter-threshold

Threshold value deciding if a query with an approximate nearestNeighbor operator combined with filters is evaluated using post-filtering.

Rank profile equivalent: approximate-threshold

Threshold value deciding if a query with an approximate nearestNeighbor operator combined with filters is evaluated by searching for approximate or exact nearest neighbors.

Rank profile equivalent: target-hits-max-adjustment-factor

Value used to control the auto-adjustment of targetHits used when evaluating an approximate nearestNeighbor operator with post-filtering.

Rank profile equivalent: match-phase: attribute

The attribute used to limit matches by if more than maxHits hits will be produced.

Rank profile equivalent: match-phase: max-hits

The max number of hits that should be generated on each content node during the match phase.

Rank profile equivalent: match-phase: order

Whether to keep the documents having the highest (false) or lowest (true) values of the match phase attribute.

Rank profile equivalent: diversity: attribute

The attribute to use when deciding diversity.

Rank profile equivalent: diversity: min-groups

The minimum number of groups that should be returned from the match phase grouped by the diversity attribute.

Probability to use when computing how many hits to fetch from each partition when merging and creating the final result set. See services for details.

Default: none.

Whether or not to bold query terms in schema fields defined with bolding: on or summary: dynamic.

The name of the summary class used to select fields in results.

Default: The default summary class of the schema.

The id of a deployed page template to use for this result. This should be used with the page result format.

Whether a result renderer should try to add optional timing information to the rendered page - see the result reference.

Controls how tensors are rendered in the result.

Requests specific multi-level result set statistics and/or hit groups to be returned in the result. Fields you want to retrieve statistics or hit groups for must be stored as document attributes in the index structure by adding attribute to the indexing statement.

Default is no grouping.

See the grouping guide for examples.

Comma-separated list of document summary field names - collapse (i.e. aggregate) results using the fields one after another. Collapsing is run in the container, not content node level. Define one or more collapsefields to remove duplicates if the corpus has few duplicates - this is more efficient than using grouping. Otherwise, use grouping.

Default is no field collapsing.

The number of hits to keep in each collapsed bucket - used for all collapsefields.

The number of hits to keep in each collapsed bucket - used for the specified field. This value takes precedence over the value specified in collapsesize.

A valid name of a document summary class. Use this summary class to fetch the fields used for collapsing.

Default: Use default summary or attributes.

Positive integer or -1 to disable.

The default number of groups to return when max is not specified.

Positive integer or -1 to disable.

The default number of hits to return when max is not specified.

Positive integer or -1 to disable.

A cost limit for grouping queries. Any query that may exceed this threshold will be preemptively failed by the container. The limit is defined as the total number of groups and document summaries a query may produce. A query that does not have an implicit or explicit max defined for all levels will always fail if limit is enabled. This parameter can only be overridden in a query profile.

See the grouping guide for practical examples.

The default precision scale factor when precision is not specified. The final precision value is calculated by multiplying the effective max value with the scale factor.

Sets the group (specified by g=<groupname>) of the documents to stream through.

Restricts streaming search using a selection expression instead of a group id.

If the selection is on the form id.group == "foo" or id.group == "bar" or id.group == ... this will only stream documents in those groups, which is efficient for a small number of groups.

If any other selection is used, this will stream through all groups, which is very costly.

If set, limit backend bucket concurrency to the specified number of buckets. Can be used to explicitly control resource usage for extremely large streaming search locations. This is an expert option.

A positive number. Default is no tracing.

Collect trace information for debugging when running a query. Higher numbers give progressively more detail on query transformations, searcher execution and content node(s) query execution. See query tracing for details and examples.

Tracing is subject to change at any time, the below is a guide:

Set to a positive number to collect query execution information for debugging when running a query. Higher numbers give progressively more detail on content node query execution. Tuning this parameter is useful if we want to get more information from the content nodes without gathering lots of trace information from the container chain.

Explanation is subject to change at any time, the below is a guide:

Note that you might get the same at trace.level 5 and above. Default is no explanation.

Tracing with trace.explainLevel also requires that trace.level is positive.

Turns on performance profiling of the content node query execution for matching, first-phase ranking, and second-phase ranking. How profiling is performed is based on whether trace.profileDepth is positive or negative:

The performance profiling output is subject to change at any time. Default is no information.

Tracing with trace.profileDepth also requires that trace.level is positive.

Turns on profiling of matching of the content node query execution. This exposes information about how time spent on matching is distributed between individual search iterators. The profiling output is tagged match_profiling and is subject to change at any time. Default is no information. See trace.profileDepth for semantics of this parameter.

Tracing with trace.profiling.matching.depth requires that trace.level is positive.

Turns on profiling of the first-phase ranking of the content node query execution. This exposes information about how time spent on first-phase ranking is distributed between individual rank features. The profiling output is tagged first_phase_profiling and is subject to change at any time. Default is no information. See trace.profileDepth for semantics of this parameter.

Tracing with trace.profiling.firstPhaseRanking.depth also requires that trace.level is positive.

Turns on profiling of the second-phase ranking of the content node query execution. This exposes information about how time spent on second-phase ranking is distributed between individual rank features. The profiling output is tagged second_phase_profiling and is subject to change at any time. Default is no information. See trace.profileDepth for semantics of this parameter.

Tracing with trace.profiling.secondhaseRanking.depth also requires that trace.level is positive.

Enable to get timing information already at trace.level=1. This is useful for debugging latency spent at different components in the container search chain without rendering a lot of string data which is associated with higher trace levels.

Whether to include the query in any trace messages. This is useful for avoiding query serialization with very large queries to avoid impact from it on performance and excessively large traces.

Turn rule evaluation off for this query.

A rule base name - the name of the rule base to use for these queries.

The amount of rule evaluation trace output to show, higher number means more details. This is useful to see a trace from rule evaluation without having to see trace from all other searchers at the same time.

Any allowed collection of recall terms. Sets a recall parameter to be combined with the query. This is identical to filter, except that recall terms are not exposed to the ranking framework and thus not ranked. As such, one can not use unprefixed terms; they must either be positive or negative.

The id of the user making the query. The content of the argument is made available to the search chain, but it triggers no features in Vespa apart from being propagated to the access log.

Make this an estimation query. No hits will be returned, and total hit count will be set to an estimate of what executing the query as a normal query would give.

Ignore metric collection for this query request, useful for warm-up queries.

Replace all instances of OR in the query tree with weakAnd.

Used in combination with weakAnd.replace. Sets the targetHits of the new weakAnds to the specified value.

When sorting on a single-value numeric attribute with fast-search an optimization is activated to return early, with an inaccurate total-hits count. Set sorting.degrading to false to disable this optimization.

This optimization sets the primary sorting attribute as the match phase attribute, and match phase maxHits equal to max(10000, maxHits+maxOffset). maxHits and maxOffset can be set in a query profile.

Sets whether this query should never be served from a cache. Vespa has few caches, and this parameter does not control any of them. Therefore, this parameter has no effect

A string with JSON. Refer to the select reference for details.

A string with JSON. Refer to the select reference for details.