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With Fusion, your data is indexed in a set of collections in Fusion’s Solr core. A primary collection holds your searchable content, such as your product catalog, knowledge base, blog articles, product reviews, and so on. A set of secondary collections are associated with your primary collection to hold related data that Fusion can use to enhance the relevancy of your search results. This topic shows you how different types of data flow through Fusion to be indexed in your primary and secondary collections.

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1. Index your content

No matter where your content is located, Fusion can index it. The Fusion collection where your searchable content is indexed is called the primary collection. Secondary collections are automatically created to hold related data, such as signals, machine learning job output, and so on. There are a few ways to index your searchable content to the primary collection:
  • Connectors: Lucidworks has a wide variety of connectors for many types of data sources. Find your connector. Once the connector fetches your data, parsers read it before passing it to the index pipeline.
    • The gRpc remote framework is configured on the client side and only works with V2 type connectors.
    • V1 classic connectors support ingesting data using IP white lists, VPN tunnels, and public channels.
  • The Parallel Bulk Loader (PBL): The PBL can send your data to an index pipeline or directly to the primary collection, depending on whether the data requires transformation before indexing. It does not support parsers and is not recommended for production environments.
  • Import Data with the REST API: Send your content to an index profile using the Fusion REST API. Index profiles are saved configurations of parsers and index pipelines.
It is often possible to get documents into Fusion by configuring a datasource with the appropriate connector.But if there are obstacles to using connectors, it can be simpler to index documents with a REST API call to an index profile or pipeline.

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Push documents to Fusion using index profiles

Index profiles allow you to send documents to a consistent endpoint (the profile alias) and change the backend index pipeline as needed. The profile is also a simple way to use one pipeline for multiple collections without any one collection “owning” the pipeline.You can send documents directly to an index using the Index Profiles REST API. The request path is:
/api/apps/APP_NAME/index/INDEX_PROFILE
These requests are sent as a POST request. The request header specifies the format of the contents of the request body. Create an index profile in the Fusion UI.To send a streaming list of JSON documents, you can send the JSON file that holds these objects to the API listed above with application/json as the content type. If your JSON file is a list or array of many items, the endpoint operates in a streaming way and indexes the docs as necessary.

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Send data to an index profile that is part of an app

Accessing an index profile through an app lets a Fusion admin secure and manage all objects on a per-app basis. Security is then determined by whether a user can access an app. This is the recommended way to manage permissions in Fusion.The syntax for sending documents to an index profile that is part of an app is as follows:
curl -u USERNAME:PASSWORD -X POST -H 'content-type: application/json' https://FUSION_HOST:FUSION_PORT/api/apps/APP_NAME/index/INDEX_PROFILE --data-binary @my-json-data.json
Spaces in an app name become underscores. Spaces in an index profile name become hyphens.
To prevent the terminal from displaying all the data and metadata it indexes—useful if you are indexing a large file—you can optionally append ?echo=false to the URL.Be sure to set the content type header properly for the content being sent. Some frequently used content types are:
  • Text: application/json, application/xml
  • PDF documents: application/pdf
  • MS Office:
    • DOCX: application/vnd.openxmlformats-officedocument.wordprocessingml.document
    • XLSX: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    • PPTX: application/vnd.vnd.openxmlformats-officedocument.presentationml.presentation
    • More types: http://filext.com/faq/office_mime_types.php

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Example: Send JSON data to an index profile under an app

In $FUSION_HOME/apps/solr-dist/example/exampledocs you can find a few sample documents. This example uses one of these, books.json.To push JSON data to an index profile under an app:
  1. Create an index profile. In the Fusion UI, click Indexing > Index Profiles and follow the prompts.
  2. From the directory containing books.json, enter the following, substituting your values for username, password, and index profile name: 
    curl -u USERNAME:PASSWORD -X POST -H 'content-type: application/json' https://FUSION_HOST:FUSION_PORT/api/apps/APP_NAME/index/INDEX_PROFILE?echo=false --data-binary @books.json
  3. Test that your data has made it into Fusion:
    1. Log into the Fusion UI.
    2. Navigate to the app where you sent your data.
    3. Navigate to the Query Workbench.
    4. Search for *:*.
    5. Select relevant Display Fields, for example author and name.

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Example: Send JSON data without defining an app

In most cases it is best to delegate permissions on a per-app basis. But if your use case requires it, you can push data to Fusion without defining an app.To send JSON data without app security, issue the following curl command:
curl -u USERNAME:PASSWORD -X POST -H 'content-type: application/json' https://FUSION_HOST:FUSION_PORT/api/index/INDEX_PROFILE --data-binary @my-json-data.json

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Example: Send XML data to an index profile with an app

To send XML data to an app, use the following:
curl -u USERNAME:PASSWORD -X POST -H 'content-type: application/xml' https://FUSION_HOST:FUSION_PORT/api/apps/APP_NAME/index/INDEX_PROFILE --data-binary @my-xml-file.xml
In Fusion 5, documents can be created on the fly using the PipelineDocument JSON notation.

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Remove documents

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Example 1

The following example removes content:
curl -u USERNAME:PASSWORD -X POST -H 'content-type: application/vnd.lucidworks-document' https://FUSION_HOST:FUSION_PORT/api/apps/APP_NAME/index/INDEX_PROFILE --data-binary @del-json-data.json

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Example 2

A more specific example removes data from books.json. To delete “The Lightning Thief” and “The Sea of Monsters” from the index, use their id values in the JSON file.The del-json-data.json file to delete the two books:
[{ "id": "978-0641723445","commands": [{"name": "delete","params": {}}]},{ "id": "978-1423103349","commands": [{"name": "delete","params": {}}, {"name": "commit","params": {}}]}]
You can use ?echo=false to turn off the response to the terminal.

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Example 3

Another example to delete items using the Push API is:
curl -u admin:XXX -X POST  'http://FUSION_HOST:FUSION_PORT/api/apps/APP/index/INDEX' -H 'Content-Type: application/vnd.lucidworks-document' -d '[
  {
    "id": "1663838589-44",
    "commands":
    [
      {
        "name": "delete",
        "params":
        {}
      },
      {
        "name": "commit",
        "params":
        {}
      }
    ]
  }, ...
]'

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Send documents to an index pipeline

Although sending documents to an index profile is recommended, if your use case requires it, you can send documents directly to an index pipeline.For more information about index pipeline REST API reference documentation, see Fusion 5.x Index Pipelines API.

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Specify a parser

When you push data to a pipeline, you can specify the name of the parser by adding a parserId querystring parameter to the URL. For example: https://FUSION_HOST:FUSION_PORT/api/index-pipelines/INDEX_PIPELINE/collections/COLLECTION_NAME/index?parserId=PARSER.If you do not specify a parser, and you are indexing outside of an app (https://FUSION_HOST:FUSION_PORT/api/index-pipelines/...), then the _system parser is used.If you do not specify a parser, and you are indexing in an app context (https://FUSION_HOST:FUSION_PORT/api/apps/APP_NAME/index-pipelines/...), then the parser with the same name as the app is used.

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Indexing CSV Files

In the usual case, to index a CSV or TSV file, the file is split into records, one per row, and each row is indexed as a separate document.
Indexing your content Index your content The index pipeline consists of one or more configurable index pipeline stages, each performing a different type of transformation on the incoming data. Each connector has a default index pipeline, but you can modify these or create new ones. The last stage in any index pipeline should be the Solr Indexer stage, which submits the documents to Solr for indexing.

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2. Index your signals

Signals are event records that provide historical data about user behavior, such as clicks, likes, purchases, and so on. You don’t need to index signals about query responses; Fusion indexes response signals automatically by default. If you are using App Studio or App Insights, then you need to index request signals. Learn more about signal types and required fields. To index your signals, you send them to Fusion using the Signals API, which points to the hidden index pipeline designed especially for signals. Indexing your signals Index your signals Raw signals are indexed in a secondary collection called COLLECTION_NAME_signals. For example, if your primary collection is called Products, then the raw signals collection is Products_signals. When you Enable or Disable Signals, Fusion creates jobs and secondary collections for analyzing and aggregating your raw signals. Some of this data enables query rewriting and automatic boosting, while other data becomes useful when you enable recommendations.
You can enable and disable signals using the Fusion UI or the REST API.
When you disable signals, the aggregation jobs are deleted, but the _signals and _signals_aggr collections are not, your legacy signal data remains intact.

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Using the UI

When you create a collection using the Fusion UI, signals are enabled and a signals collection created by default. You can also enable and disable signals for existing collections using the Collections Manager.Enable signals for a collection
  1. In the Fusion workspace, navigate to Collections > Collections Manager.
  2. Hover over the primary collection for which you want to enable signals.
  3. Click Configure to open the drop-down menu. Enable Signals
  4. Click Enable Signals.
    The Enable Signals window appears, with a list of collections and jobs that are created when you enable signals.     Enable Signals
  5. Click Enable Signals.
Disable signals for a collection
  1. In the Fusion workspace, navigate to Collections > Collections Manager.
  2. Hover over the primary collection for which you want to disable signals.
  3. Click Configure to open the drop-down menu.
  4. Click Disable Signals.
    The Disable Signals window appears, with a list of jobs that are created when you enable signals.
  5. Click Disable Signals.
    Your _signals and _signals_aggr collections remain intact so that you can access your legacy signals data.

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Using the Collection Features API

Using the API, the /collections/{collection}/features/{feature} endpoint enables or disables signals for any collection:Check whether signals are enabled for a collection
curl -u USERNAME:PASSWORD http://localhost:{api-port}/api/collections/COLLECTION_NAME/features/signals
Enable signals for a collection
curl -u USERNAME:PASSWORD -X PUT -H "Content-type: application/json" -d '{"enabled" : true}' http://localhost:{api-port}/api/collections/COLLECTION_NAME/features/signals
Disable signals for a collection
curl -u USERNAME:PASSWORD -X PUT -H "Content-type: application/json" -d '{"enabled" : false}' http://localhost:{api-port}/api/collections/COLLECTION_NAME/features/signals
Fusion jobs that index signals-related data Enable signals jobs

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4. Fusion jobs that index recommendations

When you enable recommendations, another set of jobs and secondary collections is created. Fusion jobs that index recommendations Enable recommendations jobs The default recommendation jobs read data from different collections depending on the type of recommendations being generated:
For more recommendations, try Identify Trending Items or Queries.

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What’s next?

See Query Data Flow to learn about querying your content and recommendations.
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