search_core/Documentation/source/configuration/searching.rst

Searching

size

Used by: Elasticsearch connection while building search query.

Defined how many search results should be fetched to be available in search result.

Example:

plugin.tx_searchcore.settings.searching.size = 50

Default if not configured is 10.

facets

Used by: Elasticsearch connection while building search query.

Define aggregations for Elasticsearch, have a look at the official docs: https://www.elastic.co/guide/en/elasticsearch/reference/5.2/search-aggregations-bucket-terms-aggregation.html Currently only the term facet is provided.

Example:

plugin.tx_searchcore.settings.searching.facets {
    contentTypes {
        field = CType
    }
}

The above example will provide a facet with options for all found CType results together with a count.

filter

Used by: While building search request.

Define filter that should be set for all requests.

Example:

plugin.tx_searchcore.settings.searching.filter {
    property = value
}

For Elasticsearch the fields have to be filterable, e.g. need a mapping as keyword.

minimumShouldMatch

Used by: Elasticsearch connection while building search query.

Define the minimum match for Elasticsearch, have a look at the official docs: https://www.elastic.co/guide/en/elasticsearch/reference/5.2/query-dsl-minimum-should-match.html

Example:

plugin.tx_searchcore.settings.searching.minimumShouldMatch = 50%

boost

Used by: Elasticsearch connection while building search query.

Define fields that should boost the score for results.

Example:

plugin.tx_searchcore.settings.searching.boost {
    search_title = 3
    search_abstract = 1.5
}

For further information take a look at https://www.elastic.co/guide/en/elasticsearch/guide/2.x/_boosting_query_clauses.html

fieldValueFactor

Used by: Elasticsearch connection while building search query.

Define a field to use as a factor for scoring. The configuration is passed through to elastic search field_value_factor, see: https://www.elastic.co/guide/en/elasticsearch/reference/5.2/query-dsl-function-score-query.html#function-field-value-factor

Example:

plugin.tx_searchcore.settings.searching.field_value_factor {
    field = rootlineLevel
    modifier = reciprocal
    factor = 2
    missing = 1
}

mapping.filter

Allows to configure filter more in depth. If a filter with the given key exists, the TypoScript will be added.

E.g. you submit a filter in form of:

<f:comment>
    Due to TYPO3 7.x fluid limitations, we build this input ourself.
    No longer necessary in 8 and above
</f:comment>
<select name="tx_searchcore_search[searchRequest][filter][month][from]" class="_control" >
    <option value="">Month</option>
    <f:for each="{searchResult.facets.month.options}" as="month">
        <f:if condition="{month.count}">
            <option
                value="{month.displayName -> f:format.date(format: 'Y-m')}"
                {f:if(condition: '{searchRequest.filter.month.from} == {month.displayName -> f:format.date(format: \'Y-m\')}', then: 'selected="true"')}
            >{month.displayName -> f:format.date(format: '%B %Y')}</option>
        </f:if>
    </f:for>
</select>
<select name="tx_searchcore_search[searchRequest][filter][month][to]" class="_control" >
    <option value="">Month</option>
    <f:for each="{searchResult.facets.month.options}" as="month">
        <f:if condition="{month.count}">
            <option
                value="{month.displayName -> f:format.date(format: 'Y-m')}"
                {f:if(condition: '{searchRequest.filter.month.from} == {month.displayName -> f:format.date(format: \'Y-m\')}', then: 'selected="true"')}
            >{month.displayName -> f:format.date(format: '%B %Y')}</option>
        </f:if>
    </f:for>
</select>

This will create a distance filter with subproperties. To make this filter actually work, you can add the following TypoScript, which will be added to the filter:

mapping {
    filter {
        month {
            type = range
            field = released
            raw {
                format = yyyy-MM
            }

            fields {
                gte = from
                lte = to
            }
        }
    }
}

fields has a special meaning here. This will actually map the properties of the filter to fields in elasticsearch. In above example they do match, but you can also use different names in your form. On the left hand side is the elasticsearch field name, on the right side the one submitted as a filter.

The field, in above example released, will be used as the elasticsearch field for filtering. This way you can use arbitrary filter names and map them to existing elasticsearch fields.

Everything that is configured inside raw is passed, as is, to search service, e.g. elasticsearch.

fields

Defines the fields to fetch and search from elasticsearch. With the following sub keys:

query defines the fields to search in. Default is _all from 5.x times of elasticsearch. Configure a comma separated list of fields to search in. This is necessary if you have configured special mapping for some fields, or just want to search some fields. The most hits get ranked highest. The following is an example configuration:

fields {
    query = _all, city
}

The following sub properties configure the fields to fetch from elasticsearch:

First stored_fields which is a list of comma separated fields which actually exist and will be added. Typically you will use _source to fetch the whole indexed fields.

Second is script_fields, which allow you to configure scripted fields for elasticsearch. An example might look like the following:

fields {
    script_fields {
        distance {
            condition = {request.filter.distance.location}
            script {
                params {
                    lat = {request.filter.distance.location.lat -> f:format.number()}
                    lon = {request.filter.distance.location.lon -> f:format.number()}
                }
                lang = painless
                inline = doc["location"].arcDistance(params.lat,params.lon) * 0.001
            }
        }
    }
}

In above example we add a single script_field called distance. We add a condition when this field should be added. The condition will be parsed as Fluidtemplate and is casted to bool via PHP. If the condition is true, or no condition exists, the script_field will be added to the query. The condition will be removed and everything else is submitted one to one to elasticsearch, except each property is run through Fluidtemplate, to allow you to use information from search request, e.g. to insert latitude and longitude from a filter, like in the above example.

sort

Sort is handled like fields.

mode

Used by: Controller while preparing action.

Define to switch from search to filter mode.

Example:

plugin.tx_searchcore.settings.searching {
    mode = filter
}

Only filter is allowed as value. Will submit an empty query to switch to filter mode.

dataProcessing

Used by: All connections while indexing, due to implementation inside SearchService.

Configure modifications on each document before returning search result. Same as provided by TYPO3 for t3tsref:cobj-fluidtemplate through t3tsref:cobj-fluidtemplate-properties-dataprocessing.

All processors are applied in configured order. Allowing to work with already processed data.

Example:

plugin.tx_searchcore.settings.searching.dataProcessing {
    1 = Codappix\SearchCore\DataProcessing\CopyToProcessor
    1 {
        to = search_spellcheck
    }

    2 = Codappix\SearchCore\DataProcessing\CopyToProcessor
    2 {
        to = search_all
    }
}

The above example will copy all existing fields to the field search_spellcheck. Afterwards all fields, including search_spellcheck will be copied to search_all.

Also data processors are available while indexing too, see dataProcessing.