Quick Start
The following exercise builds on the Attivio Quick Start Tutorial and takes a closer look at building JSON REST API requests which include multi-level facets.
1. Deploy the Attivio Factbook Project
Open the Attivio Quick Start Tutorial in a new tab in your browser, follow the instructions to deploy the Factbook project, and return to this page when complete.
2. Create a REST request using Postman
Download and install the free third-party Postman REST API client from https://www.getpostman.com/.
In Postman, create a POST request with URL http://{server}:17000/rest/searchApi/search.
Add basic authentication and headers as shown below:
Paste the JSON request below in the request body section. Filters are added in this example for simplicity.
{
"workflow": "search",
"query": "london",
"queryLanguage": "simple",
"locale": "en",
"facets": [ "table(childFacet=country(childFacet=language))" ],
"filters":["table:city"],
"rows": 0,
"fields": [ ".id", "title", "text", "date" ],
"restParams": {
"highlight": [ "true" ]
}
}
Click the Send button to post the request to the Attivio REST Query API endpoint.
3. Response body
The JSON response body should appear as below:
{
"totalHits": 3, //total documents matched
"totalTime": 206,
//These are the overall facets requested which contains buckets and children
"facets": [
{
"name": "table",
"field": "table",
"label": "Table",
"count": 3,
//buckets are different values facet. In this case, we only see city because of request filters.
"buckets": [
{
"value": "city",
"count": 3,
"filter": "table:FACET(city)",
//Level 2 Facets - country. The documents from table facet will be filtered based on country.
"children": {
"name": "country",
"field": "country",
"buckets": [
//first bucket value for country
{
"value": "Canada",
"count": 1,
"filter": "AND(table:FACET(city), country:FACET(Canada))", //documents containing table as city and country as Canada.
//Level 3 facets - language. The documents from table and country facets will be filtered again based on the language.
"children": {
"name": "language",
"field": "language",
"label": "Primary Language",
//different languages found in those documents.
"buckets": [
{
"value": "Italian",
"count": 1,
"filter": "AND(table:FACET(city), country:FACET(Canada), language:FACET(Italian))" //documents containing table as city, country as Canada and language as Italian.
}
]
}
},
//Second bucket value for country
{
"value": "South Africa",
"count": 1,
"filter": "AND(table:FACET(city), country:FACET(\"South Africa\"))",
"children": {
"name": "language",
"field": "language",
"label": "Primary Language",
"buckets": [
{
"value": "English",
"count": 1,
"filter": "AND(table:FACET(city), country:FACET(\"South Africa\"), language:FACET(English))"
}
]
}
},
//Third bucket value for country
{
"value": "United Kingdom",
"count": 1,
"filter": "AND(table:FACET(city), country:FACET(\"United Kingdom\"))",
"children": {
"name": "language",
"field": "language",
"label": "Primary Language",
"buckets": [
{
"value": "English",
"count": 1,
"filter": "AND(table:FACET(city), country:FACET(\"United Kingdom\"), language:FACET(English))"
}
]
}
}
]
}
}
]
}
],
"facetFilters": [],
"facetTime": 5,
"highlightTime": 0,
"resultTime": 1,
"searchTime": 196
}
4. Experiment with different facet combinations as below
You can create any number of such combinations with different facets.
Filter, discrete, schema
"facets": [ "size(filter=small(\"size:>120\"), childFacet=table(childFacet=.fields))" ],
Range, filter
"facets": [ "size(range=(\"< 150 \",0,150), range = (\"> 150 \",150,600),sortBy=COUNT, primarySort=ASC, minBucketCount=1, childFacet=peeps(filter=Chinese(\"country:China\")))" ],
Filter, filter
"facets": [ "peeps(filter=Chinese(\"country:China\"), childFacet=size(filter=small(\"size:>120\")))" ],
Schema, filter
"facets": [ ".fields(maxBuckets=10, childFacet=peeps(filter=Chinese(\"country:China\")))" ],
5. Reference for different types of facets
See the Facets page for more details on the options available for facet requests.