Oms API Read Run Output table value

Read a "page" of output table values from model run.

• Page is part of output table values defined by zero-based "start" row number and row count. If row count <= 0 then all rows below start row number returned.

• Dimension(s) and enum-based parameters returned as enum codes. If dimension type or parameter type is simple (integer or boolean) then string value used (ex.: "true", "1234").

• Values can be from output table expressions, accumulators or derived accumulators.

• Method verb must be POST and Content-Type header "application/json".

JSON body POSTed to specify output table name, page size, row count, filters and row order. It is expected to be JSON representation of db.ReadLayout structure from Go library.

Method:

POST /api/model/:model/run/:run/table/value

For example:

curl -v -X POST -H "Content-Type: application/json" http://localhost:4040/api/model/modelOne/run/Default/table/value -d @test.json
curl -v -X POST -H "Content-Type: application/json" http://localhost:4040/api/model/modelOne/run/2019_01_17_19_59_52_998/table/value -d @test.json

Arguments:

:model - (required) model digest or model name

Model can be identified by digest or by model name. It is recommended to use digest because it is uniquely identifies model. It is possible to use model name, which is more human readable than digest, but if there are multiple models with same name in database than result is undefined.

:run - (required) model run digest, run stamp or run name

Model run can be identified by run digest, run stamp or run name. It is recommended to use digest because it is uniquely identifies model run. Run stamp, if not explicitly specified as model run option, automatically generated as timestamp string, ex.: 2016_08_17_21_07_55_123. It is also possible to use name, which is more human readable than digest, but if there are multiple runs with same name in database than result is undefined.

JSON body arguments:

For example:

{
  "Name": "salarySex",
  "Offset": 0,
  "Size": 100,
  "IsFullPage": true,
  "Filter": [{
      "Name": "dim0",
      "Op": "IN",
      "Values": ["L", "H"]
    }, {
      "Name": "dim1",
      "Op": "BETWEEN",
      "Values": ["F", "all"]
    }
  ],
  "OrderBy": [{
      "IndexOne": 2,
      "IsDesc": true
    }, {
      "IndexOne": 3,
      "IsDesc": true
    }
  ],
  "IsSubId": true,
  "SubId": 2,
  "ValueName": "acc2",
  "IsAccum": true,
  "IsAllAccum": true
}

Name       - (required) output table name
Offset     - (optional) zero-based start row to select output table values
Size       - (optional) max row count to select output table values, if size <= 0 then all rows selected
IsFullPage - (optional) if true then always return non-empty last page of data
Filter     - (optional) conditions to filter dimension enum id's
OrderBy    - (optional) list of columns indexes (one based) to order by
IsSubId    - (optional) if true then select only single sub-value, default: all sub-values
SubId      - (optional) sub-value id to select if IsSubId is true
ValueName  - (optional) if not empty then only that value selected (ex.: "acc2"), default: all values
IsAccum    - (optional) if true then select accumulators
IsAllAccum - (optional) if true then select from "all accumulators" view else from accumulators table

Filter conditions joined by AND and can have following operations:

=       - enum equal to:          AgeGroup = "20-30"
!=      - enum not equal to:      AgeGroup <> "20-30"
>       - enum greater than:      AgeGroup > "20-30"
>=      - enum greater or equal:  AgeGroup >= "20-30"
<       - enum less than:         AgeGroup < "20-30"
<=      - enum less or equal:     AgeGroup <= "20-30"
IN      - enum is in the list of: AgeGroup IN ("20-30", "30-40", "40+")
BETWEEN - between min and max:    AgeGroup BETWEEN "30-40" AND "all"
IN_AUTO - automatically choose most suitable: = or != or IN or BETWEEN

Keep in mind: dimension enums are always ordered by id's, not by code and result of filter Sex < "M" may not be Sex = "F".

Order by specified by one-based column(s) index(es) in result. Columns always contain enum id's, not enum codes and therefore result ordered by id's

In case of output table expressions columns are:

  SELECT expr_id, dim0, dim1, ..., expr_value FROM valueTable ORDER BY 1, 2,...

In case of output table accumulators columns are:

  SELECT acc_id, sub_id, dim0, dim1, ..., acc_value FROM accumulatorTable ORDER BY 1, 2,...

In case of "all accumulators" columns are:

  SELECT sub_id, dim0, dim1, ..., acc0, acc1,... FROM allAccumulatorsView ORDER BY 1, 2,...

JSON response:

{
  Layout: {
    Offset:     actual first row number of the page data (zero-base),
    Size:       actual data page row count,
    IsLastPage: true if this is last page of data
  },
  Page: [....page of data...]
}

Example 1:

JSON body:

{
  "Name": "salarySex",
  "Filter": [],
  "OrderBy": []
}

Result:

{"Layout":{"Offset":0,"Size":36,"IsFullPage":false,"IsLastPage":true}
,"Page":[{"Dims":["L","M"],"Value":50,"IsNull":false,"ExprId":0}
,{"Dims":["L","F"],"Value":60,"IsNull":false,"ExprId":0}
,{"Dims":["L","all"],"Value":1,"IsNull":false,"ExprId":0}
,{"Dims":["M","M"],"Value":51.599999999999994,"IsNull":false,"ExprId":0}
,{"Dims":["M","F"],"Value":62,"IsNull":false,"ExprId":0}
,{"Dims":["M","all"],"Value":2,"IsNull":false,"ExprId":0}
,{"Dims":["H","M"],"Value":53.2,"IsNull":false,"ExprId":0}
,{"Dims":["H","F"],"Value":64,"IsNull":false,"ExprId":0}
,{"Dims":["H","all"],"Value":3,"IsNull":false,"ExprId":0}
,{"Dims":["L","M"],"Value":1,"IsNull":false,"ExprId":1}
,{"Dims":["L","F"],"Value":2,"IsNull":false,"ExprId":1}
,{"Dims":["L","all"],"Value":801,"IsNull":false,"ExprId":1}
,{"Dims":["M","M"],"Value":3,"IsNull":false,"ExprId":1}
,{"Dims":["M","F"],"Value":4,"IsNull":false,"ExprId":1}
,{"Dims":["M","all"],"Value":803,"IsNull":false,"ExprId":1}
,{"Dims":["H","M"],"Value":4,"IsNull":false,"ExprId":1}
,{"Dims":["H","F"],"Value":5,"IsNull":false,"ExprId":1}
,{"Dims":["H","all"],"Value":804,"IsNull":false,"ExprId":1}
,{"Dims":["L","M"],"Value":50,"IsNull":false,"ExprId":2}
,{"Dims":["L","F"],"Value":60,"IsNull":false,"ExprId":2}
,{"Dims":["L","all"],"Value":1,"IsNull":false,"ExprId":2}
,{"Dims":["M","M"],"Value":51.599999999999994,"IsNull":false,"ExprId":2}
,{"Dims":["M","F"],"Value":62,"IsNull":false,"ExprId":2}
,{"Dims":["M","all"],"Value":2,"IsNull":false,"ExprId":2}
,{"Dims":["H","M"],"Value":53.2,"IsNull":false,"ExprId":2}
,{"Dims":["H","F"],"Value":64,"IsNull":false,"ExprId":2}
,{"Dims":["H","all"],"Value":3,"IsNull":false,"ExprId":2}
,{"Dims":["L","M"],"Value":50,"IsNull":false,"ExprId":3}
,{"Dims":["L","F"],"Value":120,"IsNull":false,"ExprId":3}
,{"Dims":["L","all"],"Value":801,"IsNull":false,"ExprId":3}
,{"Dims":["M","M"],"Value":154.79999999999998,"IsNull":false,"ExprId":3}
,{"Dims":["M","F"],"Value":248,"IsNull":false,"ExprId":3}
,{"Dims":["M","all"],"Value":1606,"IsNull":false,"ExprId":3}
,{"Dims":["H","M"],"Value":212.8,"IsNull":false,"ExprId":3}
,{"Dims":["H","F"],"Value":320,"IsNull":false,"ExprId":3}
,{"Dims":["H","all"],"Value":2412,"IsNull":false,"ExprId":3}
]}

Example 2:

JSON body:

{
  "Name":       "salarySex",
  "Offset":     32,
  "Size":       8,
  "IsFullPage": true,
  "Filter":     [],
  "OrderBy":    []
}

Result:

{"Layout":{"Offset":32,"Size":4,"IsFullPage":true,"IsLastPage":true}
,"Page":[{"Dims":["M","all"],"Value":1606,"IsNull":false,"ExprId":3}
,{"Dims":["H","M"],"Value":212.8,"IsNull":false,"ExprId":3}
,{"Dims":["H","F"],"Value":320,"IsNull":false,"ExprId":3}
,{"Dims":["H","all"],"Value":2412,"IsNull":false,"ExprId":3}
]}

Example 3:

JSON body:

{
  "Name": "salarySex",
  "Filter": [],
  "OrderBy": [{
      "IndexOne": 2,
      "IsDesc": true
    }, {
      "IndexOne": 3,
      "IsDesc": true
    }
  ],
  "IsAccum": true,
  "IsAllAccum": false
}

Result:

{"Layout":{"Offset":0,"Size":18,"IsFullPage":false,"IsLastPage":true}
,"Page":[{"Dims":["H","M"],"Value":53.2,"IsNull":false,"AccId":0,"SubId":0}
,{"Dims":["H","F"],"Value":64,"IsNull":false,"AccId":0,"SubId":0}
,{"Dims":["H","all"],"Value":3,"IsNull":false,"AccId":0,"SubId":0}
,{"Dims":["H","M"],"Value":4,"IsNull":false,"AccId":1,"SubId":0}
,{"Dims":["H","F"],"Value":5,"IsNull":false,"AccId":1,"SubId":0}
,{"Dims":["H","all"],"Value":804,"IsNull":false,"AccId":1,"SubId":0}
,{"Dims":["M","M"],"Value":51.599999999999994,"IsNull":false,"AccId":0,"SubId":0}
,{"Dims":["M","F"],"Value":62,"IsNull":false,"AccId":0,"SubId":0}
,{"Dims":["M","all"],"Value":2,"IsNull":false,"AccId":0,"SubId":0}
,{"Dims":["M","M"],"Value":3,"IsNull":false,"AccId":1,"SubId":0}
,{"Dims":["M","F"],"Value":4,"IsNull":false,"AccId":1,"SubId":0}
,{"Dims":["M","all"],"Value":803,"IsNull":false,"AccId":1,"SubId":0}
,{"Dims":["L","M"],"Value":50,"IsNull":false,"AccId":0,"SubId":0}
,{"Dims":["L","F"],"Value":60,"IsNull":false,"AccId":0,"SubId":0}
,{"Dims":["L","all"],"Value":1,"IsNull":false,"AccId":0,"SubId":0}
,{"Dims":["L","M"],"Value":1,"IsNull":false,"AccId":1,"SubId":0}
,{"Dims":["L","F"],"Value":2,"IsNull":false,"AccId":1,"SubId":0}
,{"Dims":["L","all"],"Value":801,"IsNull":false,"AccId":1,"SubId":0}
]}

Example 4:

There are 3 filters applied to salarySex output table accumulator acc1, sub-value id = 2:

• salary level dimension: dim0 IN ["L", "H"]
• AND sex dimension: dim1 BETWEEN ["F", "all"]
• AND values of second sub-value of accumulator acc1 > 5

JSON body:

{
  "Name": "salarySex",
  "Offset": 0,
  "Size": 100,
  "Filter": [{
      "Name": "dim0",
      "Op": "IN",
      "Values": ["L", "H"]
    }, {
      "Name": "dim1",
      "Op": "BETWEEN",
      "Values": ["F", "all"]
    }, {
      "Name": "acc1",
      "Op": ">",
      "Values": ["5"]
    }
  ],
  "OrderBy": [{
      "IndexOne": 2,
      "IsDesc": true
    }, {
      "IndexOne": 3,
      "IsDesc": true
    }
  ],
  "IsSubId": true,
  "SubId": 2,
  "ValueName": "acc1",
  "IsAccum": true,
  "IsAllAccum": false
}

Result:

{
"Page":
[
{"Dims":["H","all"],"IsNull":false,"Value":804,"AccId":1,"SubId":2}
,{"Dims":["L","all"],"IsNull":false,"Value":802,"AccId":1,"SubId":2}
],
"Layout":{"Offset":0,"Size":2,"IsLastPage":true,"IsFullPage":false}
}