SymetryML Documentation
Predictions

Predict using data source

Schedules an asynchronous prediction job reading from the `indsname` data source and either writing to the `outdsname` data source, or (if `outdsname` is omitted) returning results as an inline `DataFrame` via job status. `indsname`, `outdsname`, and `impute` are the only query parameters the server reads. An unknown **input** data source name fails synchronously with a raw, unhandled `NullPointerException` reported as `500`. An unknown **output** data source name does not fail synchronously at all — the job is still accepted (`202`) and only fails asynchronously, visible via job status.

POST
/{user}/projects/{project}/dss/predict/{model}

Schedules an asynchronous prediction job reading from the indsname data source and either writing to the outdsname data source, or (if outdsname is omitted) returning results as an inline DataFrame via job status. indsname, outdsname, and impute are the only query parameters the server reads.

An unknown input data source name fails synchronously with a raw, unhandled NullPointerException reported as 500. An unknown output data source name does not fail synchronously at all — the job is still accepted (202) and only fails asynchronously, visible via job status.

Authorization

SymetryMLAuth
AuthorizationBearer <token>

HMAC-SHA256 signature-based authentication: requests are signed with your secret key and sent with the Customer-ID, Sym-date, Authorization, Content-MD5 and sym-version headers. See SymetryML REST API Security for the signature algorithm and a complete example.

In: header

Path Parameters

user*string

User/Customer identifier

project*string

Project identifier

model*string

Model identifier

Query Parameters

indsname*string

Input data source name

outdsname?string

Output data source name for prediction results. If omitted, results are returned inline as a DataFrame via job status instead of being written to a data source.

impute?boolean

Enable data imputation for missing values

Defaultfalse

Response Body

application/json

application/json

application/json

curl -X POST "https://example.com/c1/projects/nbra_prj_iris/dss/predict/nbra_prj_iris_build_1?indsname=nbra_dspredictin&outdsname=nbra_dspredictout"
{  "statusCode": 200,  "statusString": "Job is finished",  "values": {    "dataframe": {      "attributeNames": [        "resZ_Result",        "res_Result",        "normZ_Result",        "resU_Result",        "sepal_length",        "sepal_width",        "petal_length",        "petal_width"      ],      "data": [        [          "-7.30448447562378",          "0",          "0.49244735211790924",          "0",          "4.3",          "3",          "1.1",          "0.1"        ],        [          "-6.977202102359432",          "1",          "0.5039865396670957",          "0",          "4.8",          "3",          "1.4",          "0.1"        ],        [          "-7.122806687213056",          "0",          "0.49885266630871783",          "0",          "4.9",          "3.1",          "1.5",          "0.1"        ]      ]    }  }}
{  "statusCode": 202,  "statusString": "Job Created",  "values": {}}

{  "statusCode": 500,  "statusString": "Generic Exception [java.lang.NullPointerException: Cannot invoke \"com.rtlm.json.DSInfo.equals(Object)\" because \"inputInfo\" is null]",  "values": {}}

Delete prediction results DELETE

Deletes a previously-saved input→output prediction pairing recorded against this model.

Learn then predict (or predict then learn) in one call POST

Combines a learn (DEM update) and a prediction in a single request against a large inline `DataFrame`. `{model}` accepts a comma-separated list of model ids to run in one call, not just a single model. The response is the input `DataFrame` filtered down to the columns named in `keepColumns` plus each model's derived result/score columns (`{model}::...`). Every failure is reported as **400** with the raw Java exception `toString()` as the message — there is no separate 500 path, unlike `Predict`/`DSPredict`. An unknown project, for example, surfaces this way as a bare `NullPointerException` with no further detail.