For AI agents: the complete documentation index is available at https://docs.dataplatform.ovh.net/llms.txt, the full documentation bundle is available at https://docs.dataplatform.ovh.net/llms-full.txt, and this page is available as Markdown at https://docs.dataplatform.ovh.net/legacy/api-reference-qb-json-format.md.
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    • ForePaaS JSON query format

    Warning

    This page describes the ForePaaS Legacy Platform, which no longer accepts new signups. If you are using OVHcloud Data Platform, see the Analytics Manager.

    The ForePaaS JSON query format uses multiple parameters as input and output to describe a query and its results.

    The following articles document each individual query parameters, and illustrate their impact using a simple example of the revenue of a company. The available dataset is given as follows:

    problematique

    Reference: 'data' parameter Reference: 'scale' parameter Reference: 'filter' parameter Reference: other parameters

    Complete reference of parameters

    The JSON configuration for a query takes in the following parameters.

    Parameter namerequiredexampledescription
    data.fieldsyes{ "income":["sum"],"expense":["sum"]}Fields to return and their compute mode(s) (can be: select, select_distinct, sum, min, max, avg, count, count_distinct)
    data.skipno10Number of rows to skip
    data.limitno100Number of rows returned
    data.hintsnotrue/falseTotal number of lines corresponding to the query (omitting data.limit)
    filterno{ "date": { "between": ["1420066800,1428962399"] }, "client_code": { "in": ["08KD", "09CC"] }, "creation_date": { "eq": ["2018-01-01"] }}Apply filter(s) on the data to query. Filters can be: in, not_in, between, not_between, eq, not_equal, like, not_like, is_null, is_not_null, gt (>), gte (>=), lt (<), lte (<=)
    scale.fieldsno["date",["client_code", "employee_id"]]Apply scale (group by) to the query. It can be a computed scale, or more than 1 scale.
    evol.scaleno"year"scale to apply for evolution (weekday;week; month; quarter; semester; year)
    evol.modeno"date""weekday"date : comparison with same dateweekday : comparison with respecting the same weekday.
    evol.depthno5How much evolutions you want to get back
    total.allno[]["client_code"]total queries per distinct scales (optional)
    total.xno["client_code"]Total queries for a specific attribute
    orderno{ "date":"asc"}order query output (asc or desc, asc by default)
    table_nameno"prim_vehicles"Force to query in a specific table
    database_nameno"data_prim""data_mart"Force to query in a specific layer