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Parameter selection
The
ParameterSelection field in a study specifies which parameters of the system should be tuned while running the optimization study.In case this selection is not specified, all parameters are considered.
A parameter selection can either assume the value of
all to indicate that all the available parameters of the system of the study should be tuned, or can assume the value of a list with items of the shape like the one below:Field | Type | Value restriction | Is required | Default value | Description |
|---|---|---|---|---|---|
name | string | should match the following syntax: component_name.parameter_namewhere component_name is an existing component, where parameter_name is an existing parameter that is associated with the component-type of the component component_name | TRUE | The name of the parameter to be tuned including the name of the component it refers to | |
domain | array of numbers | should be of size 2, contain either all integers or real numbers(do not omit the "."), be set only if the parameter has a domain of type integer or real,and be compatible with the domain defined in the component-type the component_name refers to | FALSE | A custom domain for the parameter to be used only for the study | |
categories | array of string | should be set only if the parameter has a domain of type categorical, and be compatible with the domain defined in the component-type the component_name refers to. | FALSE | A custom set of categories for the parameter to be used only for the study. |
Notice that, by default, every parameter specified in the parameters selection of a study is applied. This can be modified, by leveraging the Parameter rendering options.
The following fragment is an example:
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parametersSelection:
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- name: jvm.jvm_gcType
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- name: jvm.jvm_maxG1NewSizePercent
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domain: [10, 90]
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- name: webserver.aws_ec2_instance_size
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categories: ["large", "x.large", "2x.large"]
Last modified 4mo ago