SymetryML Projects REST API

SymetryML Projects Life-Cycle

SymetryML project are different than classical machine learning or other data science projects in the way data is ingested and in how machine learning models are created. Normally one would create a machine learning model by specifying some file(s) or data structure containing the data description - number of rows, input attributes, target(s) for models. This step can be highly memory intensive if the data to be processed is large.

SymetryML is different. There is no limitation on the number of rows that can be processed and the number of rows do not impact the memory requirement to build a model. Updating a project with some data and building a machine learning model based on a project are 2 separates operations:

• When updating a project - that is learning or forgetting some data - internally some representation of the data is being updated. This update is usually quite fast. This internal representation can be queried in real time using the Exploration API.

• When building a model, the internal representation is used to extract values needed by each of the different machine learning models supported by SymetryML. This makes model building very quick, usually under a few milli-seconds. If another model is needed perhaps with different inputs and/or target(s), one just needs to issue a request to build another model and no re-scanning of the data is needed. Models are built based on the current state of a project. If a project was updated with some data, a rebuild of the model might be needed so that the models use the latest data available in the project.

SymetryML Project Type

New with SymetryML version 5.0 are “Federated” project types. The following table describes the difference between these project types and when to use them. For more details on Federated Project please consult this section.

Project Type	Description
cpu or dynamic	- Project update (learn/forget) done on CPU. - Project stored on CPU memory. - Use this type of project if you have categorical attributes or fewer than 50-100 attributes.
gpu	- Project update (learn/forget) done on GPU. - Project stored on GPU memory. - Use this type of project if you have data with more than 100 - 200 attributes.
multi gpu	- Project update (learn/forget) done on multiple GPUs. - Project stored on multiple GPUs memory. - Use this type of project if you have dense data with more than 1000 attributes and you have multiple GPUs available. Please note that you cannot directly use category with a GPU project type. Such data needs to be one hot encoded before pushing it into a SymetryML GPU project. - Multi GPU project are stored in the local file system. Where they are saved depends on the following SymetryML configuration parameters (Consult the Section on SymetryML configuration in the Installation Guide for details) sml.mgpubet.persistence.dir sml.mgpubet.persistence.suffix sml.mgpubet.persistence.file-ext
Sequence	SymetryML needs to perform some additional logic for these type of models to be built. Use the sequence project type so that you can build such models on your data. See the section About Sequence Projects for more details.
Partitioned	Use this type of project if you need to use LDA model with multi-class classifier or if you need to build a QDA model. When creating such projects one needs to specify the attribute that will be used to partition the project. This attribute needs to be of type String and usually should be the target for building your LDA or QDA models.
Federated Project	Federated Project allows multiple SymetryML projects to form a federation that leverage each individual project so that they all work together as if they were one single project. That is from the perspective of each individual project they can all build the same models or compute the same exploration metrics and all of this is accomplished without sharing any data. For more information please consult the Federated Project Section.
Fusion Project	Fusion Project allows to handle data coming from a stream with very high throughput. Please consult the section on Fusion Project for details

SymetryML Projects and Random Forest

New With SymetryML 5.2 is a powerful Online Random Forest model. In order to use it, some configuration is needed when creating your project:

• Specify the target / dependent column

• Specify the type of random forest (currently only classifier is available, soon regressor random forest will also be available)

• Various Hyper parameters. Please see the RF Models for details about the additional configuration available.

SymetryML Projects and Kaplan Meier

Kaplan Meier(KM) is a survival model which can estimate a survival function from lifetime data. Unlike most SymetryML models, KM cannot be built after a project has learned a dataset. Instead, the user must specify the following parameters when creating a project.

• Specify the time column.

• Specify the event column.

• Specify the group column.

• Please see the KM Models for details about the additional configuration available.

Clustering

New with SymetryML version 5.4 is an online version of KMeans clustering. The clustering algorithm is controlled by a few parameters that need to be specified when creating a project. Please consult the Cluster Models for details on the additional configuration to enable KMeans clustering on your project.

Partitioned Projects

New with SymetryML 4.2 is the ability to create Partitioned Projects. Partitioned project allows you to build Multi-Class LDA models as well as QDA models. When creating such projects one must specify which attributes will be the targets for these models. This parameter is called the partition column. This parameter is mandatory. Please refer to this section for a sample REST request / response.

Sequence Projects

With the release of SymetryML Version 4.1 came the ability to use Markov Chains and Hidden Markov Model. To build such models, you create a sequence SymetryML Project and specify its order. Order defines your ngrams that will be learned and the level of you ngrams will be a given value in a dataframe. For Markov chains, specify a categorical attribute for the input of your model. For the Hidden Markov Model, the observed state can be categorical or continuous, but the hidden must be categorical.

For the sequence project, SymetryML interprets the dataframe data structure differently:

• If a Dataframe to be processed has only 1 attribute, it will be assumed that each line represent a token or level of a sequence.

• If a DataFrame to be processed has more than 1 column, it will be assumed that each line represent a sequence to learned.

For more information on ngrams, order, and level, see https://en.wikipedia.org/wiki/N-gram.

Federated Projects

New with version 5.0 of SymetryML is the capabilities to allows multiple SymetryML projects - possibly on different sites / geographical locations / different business units - to synchronize with each other in order to leverage each others data without sharing the actual data. This functionality is called Federated Learning. A federated project act exactly the same as any other project in terms of how you build model or explore the data. The only difference is how you create them. For more details about the lifecycle of federated project please consult the Federated Learning API.

Data Filtering

It's possible to filter data as it is consumed by a SymetryML project. In order to filter out some tuple one needs to pass a string containing a comma separated list of predicates that all need to be true for a row / tuple to be processed, otherwise it will be ignored.

Example of such string:

sml_project_predicate_row_filter:Iris_setosa==1;sepal_width_b2==1

The following table list the available binary boolean operator that can be used in any individual predicates.

Boolean Operator	Description	Notes
==	Equals	Works on both Strings and Numbers
>=	Greater or Equals	Only works with Numbers
<=	Smaller or Equals	Only works with Numbers
!=	Not Equal	Works on both Strings and Numbers
>	Greater	Only works with Numbers
<	Smaller	Only works with Numbers

Create New SymetryML project

This API function call create a SymetryML project.

URL

POST /symetry/rest/{cid}/projects?pid={new-project-id} [body=KSVSMap]

Create New SymetryML project Body

The body of the request consist of a key/value map. It is optional and depends on the type of project. Please refer to the following table that describes mandatory parameters for the different type of projects. Also refer to KSVSMap for detail on the request body json data structure.

Optional Project Parameters	Type	Description
sml_project_autosave	boolean	Default is true. This parameter controls whether or not a project is automatically saved after new data is pushed into it. The default behavior is true. If false is used, it is important to invoke the Save endpoint to persist the project in order to not lose information between server restart.
sml_project_learn_merge	boolean	Default is false. This parameter is used whenever a project learns new data, see Update for details. This configuration allows to commit new data to a project only if the whole DataFrame was processed without an error. Whenever new data is pushed to a SymetryML project the following happens: 1. A new temporary project is created 2. The new temporary project is updated with the the data. 3. If no problem is encountered the temporary project is merged with the main project. 4. This allows a commit all or nothing approach to processing data.
sml_project_predicate_row_filter	String	Default is empty. This parameter allows to filter data as it is consumed by the project. Please consult the 'Row Filtering' section for more details.

The following table list mandatory parameters for sequence, partitioned and multi-gpus projects:

Project Type	Mandatory Parameters	Description
Sequence	sml_project_order	specify the sequence order (ngram)
Partitioned	partitionSplit	specify which attribute / column to use to split the partition
Multi GPU	mgpu_num	Number of GPUs to use

Create Project Query Parameters

Parameter	Required/Optional	Description
pid	Required	Name of the new SymetryML project.
Type	Optional	The type of the project. Please see Project Types table for details.
persist	Optional	Whether to persist or not a project. Valid values are * true * false
enableHistogram	Optional	Enable histogram for continuous and binary attributes in this project.

Project Types

Project Type	Descriptions
cpu	CPU based project, this is the default value
gpu	GPU based project
sequence	Sequence project, see About Sequence Projects
partition	Partitioned project, see About Partitioned Projects
mgpuf	Multi-GPU project using 32 bits float
mgpud	Multi-GPU project using 64 bits float - aka double

HTTP Responses

HTTP Status Code	HTTP Status Message	Description
201	CREATED	Success. {"statusCode":"CREATED","statusString":" + SYMETRYML Created with id:r1","values":{}}
409	CONFLICT	SymetryML project already exists. {"statusCode":"CONFLICT","statusString":" + Customer [c1] already have SYMETRYML with id[r1], ","values":{}}

HTTP Response Entity

None

Sample Request/Response CPU/GPU Projects

POST url="http://charm:8080/symetry/rest/c1/projects?pid=testIris

{"statusCode":"CREATED","statusString":"Project Created with id:testIris","values":{}}

Sample Request/Response Partitioned Projects

Request:
POST url=http://charm:8080/symetry/rest/c1/projects?pid=irisMeta&type=partition&persist=true

Request Body:
{"partitionSplit":"class"}

Response:
{"statusCode":"CREATED","statusString":"Project Created with id:irisMeta","values":{}}

Sample Request/Response Sequence Projects

Request:
POST url=http://charm:8080/symetry/rest/c1/projects?pid=activityMC&type=sequence

Request Body:
{"sml_project_order":"1"}

Response:
{"statusCode":"CREATED","statusString":"Project Created with id:activityMC","values":{}}

Sample Request/Response Hash-trick Projects

Request:
POST url=http://charm:8080/symetry/rest/c1/projects?pid=CRITEO&type=cpu

Request Body:
{"sml_project_hashtrick_binsize":"1024"}

Response:
{"statusCode":"CREATED","statusString":"Project Created with id:CRITEO","values":{}}

Saving a SymetryML Project

This REST endpoint save a Project into the underlying persistence database - e.g. Redis. This is needed for project that do not use the autosave functionality - see Create New Symetry Project for details.

URL

GET /symetry/rest/{cid}/projects/{pid}/save

HTTP Responses

HTTP Status Code	HTTP Status Message	Description
200	OK	Success.
400	BAD REQUEST	SymetryML project does not exist. {"statusCode":"BAD_REQUEST","statusString":"Cannot Find SYMETRYML id[r5] for Customer id [c1]","values":{}

Freezing a SymetryML Project

This REST endpoint freeze a Symetry Project, that is it block it from being able to be updated. Pushing data to a frozen project will raise an Exception and the data will not be processed.

URL

GET /symetry/rest/{cid}/projects/{pid}/freeze

HTTP Responses

HTTP Status Code	HTTP Status Message	Description
200	OK	Success.
400	BAD REQUEST	SymetryML project does not exist. {"statusCode":"BAD_REQUEST","statusString":"Cannot Find SYMETRYML id[r5] for Customer id [c1]","values":{}

Unfreezing a SymetryML Project

This REST endpoint does the reverse of Freeze Project. If the project was not frozen it does nothing.

URL

GET /symetry/rest/{cid}/projects/{pid}/unfreeze

HTTP Responses

HTTP Status Code	HTTP Status Message	Description
200	OK	Success.
400	BAD REQUEST	SymetryML project does not exist. {"statusCode":"BAD_REQUEST","statusString":"Cannot Find SYMETRYML id[r5] for Customer id [c1]","values":{}

Rename a SymetryML project

This API function call renames a SymetryML project.

URL

GET /symetry/rest/{cid}/projects/{pid}/rename?newName={newname}

Query Parameters

Parameter	Required/Optional	Description
rename	Required	New name for the SymetryML project.

HTTP Responses

HTTP Status Code	HTTP Status Message	Description
201	CREATED	Success. {"statusCode":"CREATED","statusString": + "SYMETRYML Created with id:r1","values":{}}
409	CONFLICT	A SymetryML project by the specified new name already exists. {"statusCode":"CONFLICT","statusString":"Customer [c1] already have SYMETRYML with id[r1], ","values":{}}

HTTP Response Entity

None

Assign an Encoder to a SymetryML Project

This API function call assigns an encoder to a SymetryML project.

URL

GET /symetry/rest/{cid}/projects/{pid}/encoderAssign?encoderName={encname}

Query Parameters

Parameter	Required/Optional	Description
encodername	Required	Encoder name to use for this SymetryML project.

HTTP Responses

HTTP Status Code	HTTP Status Message	Description
200	OK	Success.

HTTP Response Entity

None

Delete a SymetryML project

This API function call deletes a SymetryML project from your repository.

URL

DELETE /symetry/{cid}/projects/{pid}

HTTP Responses

HTTP Status Code	HTTP Status Message	Description
200	OK	Success. {"statusCode":"OK","statusString":"deleted Project with id[r1] from Customer[c1] store","values":{}}
400	BAD REQUEST	User does not have the SymetryML project. {"statusCode":"BAD_REQUEST","statusString":" + Customer[c1] does not have Project with id[r1], ","values":{}}

HTTP Response Entity

None

List SymetryML projects

This API function call retrieves a list of SymetryML IDs that were created by a given user. The response contains a string list containing the names of all the projects that belong to the user who made the request. The format of the response is described in section Appendix A.

URL

GET /symetry/rest/{cid}/projects/list

HTTP Responses

HTTP Status Code	HTTP Status Message	Description
200	OK	Success.

HTTP Response Entity

HTTP Response Entity	Example
StringList	{"statusCode":"OK","statusString":"OK","values":{"stringList":{"values":["r1","r11","r2","r3"]}}}

Sample JSON Response

Request:
GET url="http://charm:8080/symetry/rest/c1/projects/list

Response:
{"statusCode":"OK","statusString":"OK","values":{"stringList":{"values":["irisTest","anotherProject"]}}}

SymetryML Project Unload

In order to save memory on the server, it’s possible to unload a project from memory. Note that if you do that with a project that is not persisted then the project cannot be restored.

URL

GET /symetry/rest/{cid}/projects/{pid}/unload

HTTP Responses

HTTP Status Code	HTTP Status Message	Description
200	OK	Success.

SymetryML Project Merge

It’s possible to merge 2 SymetryML projects together using the following rest endpoint.

URL

GET /symetry/rest/{cid}/projects/{pid}/merge?otherProjectName={otherProject}

Query Parameters

Parameter	Required/Optional	Description
otherProject	Required	Name of the other SymetryML project to use for the merging. At the end of this operation otherProject will be merge into pid. That is otherProject will stay the same while pid will be updated with the content of otherProject.

HTTP Responses

HTTP Status Code	HTTP Status Message	Description
200	OK	Success.

SymetryML Project Information About One Project

This REST API function call retrieves information about a single SymetryML project. The following information about a particular SymetryML project is returned as part of the ProjectInfo JSON response.

Field	Description
modelsList	List of models
modelTypeList	List of model types
dsList	List of data source names
encoderName	Encoder name if the SymetryML project use an encoder
attributeNames	List of attributes names
attributeIndexes	List of attributes index
attributeTypes	List of attributes type. For example: - ([C] = continuous - [B] = binary - [S] = string - [L] = list - [X] = ignore
pid	Name of this object
hash	Internal use only
isDirty	Internal use only. This field is deprecated.
creationDate	Date this project was created.
lastModificationDate	Last time data was added / learned on this project.
modelAssessment	Internal use. List of assessments from SymetryML Web application
modelPredictions	Internal use. List of predictions from SymetryML Web application
categorySeparator	Internal use.
loaded	Specifies if a project is loaded in memory or not
persisted	Specifies if a project is persisted or not
streams	List of streams that belong to that project
partitionColumn	For Partitioned Projects, this is the column to use to partition the project
autoSave	Whether or not this project is autosaved.
type	The type of this project
histogramEnabled	Whether or not this project has histogram enabled.
fusionCellInfoList	For Fusion projects, this contain the information about the fusion cells. Please see FusionCellInfoList.
params	A map containing various key / values. See Table Below

Project Params

Params Key	Description
fusion_fetch_error	Error string from the last time a fusion project fetched data from its cells.
sml_project_is_freeze	Describe if this project is in the frozen state, that it is not possible for it to process new incoming data.
automl_project_is_automl	Specify that this project use AutoML
automl_setup_done	When using AutoML, this boolean key indicates that the auto ml 'warm up' is complete.
sml_project_power_column	Needed for power transformation model. Consult Model API for details.
sml_project_power_min	Needed for power transformation model. Consult Model API for details.
sml_project_power_max	Needed for power transformation model. Consult Model API for details.
sml_project_power_steps	Needed for power transformation model. Consult Model API for details.
fed_pulsing	If a Federated Project is pulsing or not
fed_has_error	If a Federated Project has error or not
fed_is_admin	If a Federated Project is the admin of the federation it is a member.

URL

GET /symetry/rest/{cid}/projects/{pid}/info

HTTP Responses

HTTP Status Code	HTTP Status Message	Description
200	OK	Success.
400	BAD REQUEST	SymetryML project does not exist. {"statusCode":"BAD_REQUEST","statusString":"Cannot Find SYMETRYML id[r5] for Customer id [c1]","values":{}

HTTP Response Entity

HTTP Response Entity	Description
ProjectInfo	See the example below.

Sample Request/Response

Request:
GET url="http://charm:8080/symetry/rest/c1/projects/irisTest/info"

Response:
{"statusCode":"OK","statusString":"OK","values":{"smlInfo":{"modelsList":["ldaReduced","svmModel"],"modelTypeList":["lda","lsvm"],"attributeNames":["sepal_length","sepal_width","petal_length","petal_width","sepal_lengt_b1","sepal_lengt_b2","sepal_width_b1","sepal_width_b2","petal_length_b1","petal_length_b2","petal_width_b1","petal_width_b2","Iris_setosa","Iris_versicolor","Iris_virginica"],"attributeIndexes":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14],"attributeTypes":["C","C","C","C","B","B","B","B","B","B","B","B","B","B","B"],"pid":"irisTest","attributeStates":["u","u","u","u","u","u","u","u","u","u","u","u","u","u","u"],"hash":-1,"isDirty":true}}}

SymetryML Project Information About All Projects

This REST API function call returns information about all SymetryML projects that were created previously by a given user. To conserve memory usage, minimal information about each SymetryML project loads into server memory. If more information is required, it is loaded "lazily and transparently" by the server. For more information about the response format, see the ProjectInfoList.

This API function is asynchronous. If it succeeds, it returns a 202 response, along with a Location header that specifies the job URL. For more information about asynchronous REST calls, see the section "Asynchronous Learning."

URL

GET /symetry/rest/{cid}/projects/info

Query Parameters

Parameter	Required / Optional	Description
async	Optional	If set to true then the ProjectInfo request will be done asynchronously and the result will be fetched using the Job API.

HTTP Responses

HTTP Status Code	HTTP Status Message	Description
202	ACCEPTED	Success. Includes an HTTP Location header specifying the location of the job ID that was created to handle the request. For example: {"statusCode":"ACCEPTED","statusString":"Job Created","values":{}}

After a Restore job completes, it returns the following information:

HTTP Status Code	HTTP Status Message	Description
200	OK	Response entity is a ProjectInfoList JSON data structure. For each SymetryML project ID restored, the entity contains its ID as well as the ID of models that belong to it.
202	ACCEPTED	Job is not finished. Includes a JobInfo entity. For more information, see SymetryML Job.

HTTP Response Entity

None

Sample Request/Response

Request
GET url="http://charm:8080/symetry/rest/c1/projects/info"

Response Header:
Location: http://charm:8080/symetry/rest/c1/jobs/4

Response:
{"statusCode":"ACCEPTED","statusString":"Job Created","values":{}}

Job Request:
GET url="http://charm:8080/symetry/rest/c1/jobs/4

Job Response:
{"statusCode":"OK","statusString":"Job is finished","values":{"smlInfoList":{"values":[{"modelsList":[],"modelTypeList":[],"attributeNames":[],"attributeIndexes":[],"attributeTypes":[],"pid":"anotherProject","attributeStates":[],"hash":-1,"isDirty":true},{"modelsList":["ldaReduced","svmModel"],"modelTypeList":["lda","lsvm"],"attributeNames":["sepal_length","sepal_width","petal_length","petal_width","sepal_lengt_b1","sepal_lengt_b2","sepal_width_b1","sepal_width_b2","petal_length_b1","petal_length_b2","petal_width_b1","petal_width_b2","Iris_setosa","Iris_versicolor","Iris_virginica"],"attributeIndexes":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14],"attributeTypes":["C","C","C","C","B","B","B","B","B","B","B","B","B","B","B"],"pid":"irisTest","attributeStates":["u","u","u","u","u","u","u","u","u","u","u","u","u","u","u"],"hash":-1,"isDirty":true}]},"ac":"z3SMHWgE8cqIHJUtBDV8Fg\u003d\u003d","Options":{"gpuEnabled":0}}

Exporting and Importing SymetryML Project Rest API

Export / Import functionality enables the user to export projects and then re-import them. Projects are encoded into a Base 64 string so that they can easily be transmitted using various channels of communication.

Export a Project

Export a model into a Base 64 string.

URL

GET /symetry/rest/{cid}/projects/{pid}/export

HTTP Responses

HTTP Status Code	HTTP Status Message	Description
200	OK	Success.

HTTP Response Entity

HTTP Response Entity	Example
String	A Base64 representation of the project.

Import a Project

Import a model into a project.

URL

POST /symetry/rest/{cid}/projects/{pid}/import?persist= [body=string]

Parameter	Required/Optional	Description
persist	Optional	Whether or not to persist that project

Request Body

The body is a Base 64 string from a project that was exported first with the [Project Export] functionality.

HTTP Responses

HTTP Status Code	HTTP Status Message	Description
200	OK	Success.

Real Time Streaming of Data into SymetryML Projects

SymetryML projects support streaming data. The streaming capabilities are encompassed in 2 major functionalities:

1. Using the Learn or Forget by providing a DataFrame as the request body.

2. Using the Stream API to create stream data source that automatically push streaming data into your SymetryML project. Use this API to manage connections to streaming server solution such as Apache Kafka.

The following sub-sections will describe the learn and forget streaming API.

Asynchronous Learning

Both the learn and forget methods can be invoked synchronously or asynchronously. The default method is synchronous. To run the task asynchronously, add async=true as a query parameter to your REST invocation. When invoked, the response is 202 ACCEPTED and you can use the Job Status API to determine when a learning job is finished. For more information, see Data Source API.

Usually, there is no need to run learn and forget tasks asynchronously unless your data has a large number of attributes that, depending on your hardware, can take more or less time to be executed. As a rule of thumb, data with fewer than 100 attributes can be learned and forgotten safely using synchronous execution. However, your experiences might be different. Therefore, if your data has a large number of attributes, we recommend that you perform testing to determine whether the asynchronous or synchronous method will work better for you.

Note

Addition of new attributes is handled by the incremental update automatically, as described in the next section.

Learn New Data (Incremental Update)

This API function call learns new data. The body of the request should contain a DataFrame JSON data structure. For information about this JSON data structure, see the DataFrame. For information about the async parameter, see Asynchronous Learning.

URL

POST /symetry/rest/{cid}/projects/{pid}/learn [?async=true]* [body = DataFrame]

Query Parameters

Parameter	Required/Optional	Description
async	Optional	Performs the operation asynchronously. We recommend using true for this parameter if your data is wider than 100 attributes. Default: false

HTTP Responses

HTTP Status Code	HTTP Status Message	Description
200	OK	Success. {"statusCode":"OK","statusString":"OK","values":{}}
202	Accepted	If async == true, the server accepted the request.
400	BAD REQUEST	SymetryML project cannot be found. {"statusCode":"BAD_REQUEST","statusString":" + Cannot Find SYMETRYML id[r2] for Customer id [c1]","values":{}}

HTTP Response Entity

None

Sample Request/Response

Request:
POST url="http://charm:8080/symetry/rest/c1/projects/irisTest/learn?async=false"

Body:
{"attributeNames":["sepal_length","sepal_width","petal_length","petal_width","sepal_lengt_b1","sepal_lengt_b2","sepal_width_b1","sepal_width_b2","petal_length_b1","petal_length_b2","petal_width_b1","petal_width_b2","Iris_setosa","Iris_versicolor","Iris_virginica"],"data":[["4.3","3","1.1","0.1","1","0","0","1","1","0","1","0","1","0","0"],["4.8","3","1.4","0.1","1","0","0","1","1","0","1","0","1","0","0"],["4.9","3.1","1.5","0.1","1","0","0","1","1","0","1","0","1","0","0"]],"attributeTypes":["C","C","C","C","B","B","B","B","B","B","B","B","B","B","B"]}

Response:
{"statusCode":"OK","statusString":"OK","values":{}}

Forgetting Data (Decremental Update)

This API function call allows users to forget data. The body of the request should contain a DataFrame JSON data structure. For information about this JSON data structure, see DataFrame. For information about the async parameter, see Asynchronous Learning.

URL

POST /symetry/rest/{cid}/projects/{pid}/forget [?async=true]* [body=DataFrame]

Query Parameters

Parameter	Required/Optional	Description
async	Optional	Performs the operation asynchronously. We recommend using true for this parameter if your data is wider than 100 attributes. Default: false

HTTP Responses

HTTP Status Code	HTTP Status Message	Description
200	OK	Success. {"statusCode":"OK","statusString":"OK"," + values":{}}
400	BAD REQUEST	If SymetryML project cannot be found: {"statusCode":"BAD_REQUEST","statusString":" + Cannot Find SYMETRYML id[r2] for Customer id [c1]","values":{}}

HTTP Response Entity

None

Sample Request/Response

See the sample in the previous section.