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Fusion 5.12
    Fusion 5.12

    Query Pipelines

    A Query Pipeline transforms a set of inputs into a Solr query request and it can execute requests and manipulate the Solr response as well, via a set of modularized operations called Query Stages. The objects sent from stage to stage are Request objects and Response objects.

    Fusion stores pipeline names and definitions, allowing a pipeline to be reused across applications. Pipeline definitions can be modified, so that as an application evolves, the pipelines used by that application can evolve accordingly. During application development, the Fusion UI can be used to develop and debug a Query Pipeline.

    The available stage types allow setting specific parameters for the query, such as the number of results to return or the query parser to use. You can also define facets and recommendations to be returned with the results. If Access Control Lists (ACLs) are in use, you can apply a security-trimming stage to apply user access restrictions to the results.

    For details about the available REST APIs, see Query Pipelines API and Query Stages API.

    Default Query Pipelines

    When you create a new app with a default collection, the collection includes a default query pipeline. When you create a new collection in an existing app, Fusion also creates a default query pipeline for the new collection. The pipeline name is the same as the collection name.

    The default query pipeline has the following pre-configured stages:

    To perform query rewriting, this stage searches for matching instances of:

    Custom Query Pipelines

    Using the Query Workbench or the REST API, you can develop custom pipelines to suit any search application. Start with any of Fusion’s built-in query pipelines, then add, remove, and re-order the pipeline stages as needed to produce the appropriate query results.

    Asynchronous query pipeline processing

    Query pipeline processing performance can be improved by enabling asynchronous processing for certain stages that make requests to secondary collections, external databases, and so on. The following stages support asynchronous processing:

    This feature uses the fork-and-join model, where any of the stages above can create a fork on the pipeline. The parallel processes are joined again using the Merge Async Results stage at a later point in the pipeline.