#[non_exhaustive]
pub struct CreateDataSourceFromRedshiftInputBuilder { /* private fields */ }
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impl CreateDataSourceFromRedshiftInputBuilder

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pub fn data_source_id(self, input: impl Into<String>) -> Self

A user-supplied ID that uniquely identifies the DataSource.

This field is required.
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pub fn set_data_source_id(self, input: Option<String>) -> Self

A user-supplied ID that uniquely identifies the DataSource.

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pub fn get_data_source_id(&self) -> &Option<String>

A user-supplied ID that uniquely identifies the DataSource.

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pub fn data_source_name(self, input: impl Into<String>) -> Self

A user-supplied name or description of the DataSource.

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pub fn set_data_source_name(self, input: Option<String>) -> Self

A user-supplied name or description of the DataSource.

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pub fn get_data_source_name(&self) -> &Option<String>

A user-supplied name or description of the DataSource.

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pub fn data_spec(self, input: RedshiftDataSpec) -> Self

The data specification of an Amazon Redshift DataSource:

  • DatabaseInformation -

    • DatabaseName - The name of the Amazon Redshift database.

    • ClusterIdentifier - The unique ID for the Amazon Redshift cluster.

  • DatabaseCredentials - The AWS Identity and Access Management (IAM) credentials that are used to connect to the Amazon Redshift database.

  • SelectSqlQuery - The query that is used to retrieve the observation data for the Datasource.

  • S3StagingLocation - The Amazon Simple Storage Service (Amazon S3) location for staging Amazon Redshift data. The data retrieved from Amazon Redshift using the SelectSqlQuery query is stored in this location.

  • DataSchemaUri - The Amazon S3 location of the DataSchema.

  • DataSchema - A JSON string representing the schema. This is not required if DataSchemaUri is specified.

  • DataRearrangement - A JSON string that represents the splitting and rearrangement requirements for the DataSource.

    Sample - "{\"splitting\":{\"percentBegin\":10,\"percentEnd\":60}}"

This field is required.
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pub fn set_data_spec(self, input: Option<RedshiftDataSpec>) -> Self

The data specification of an Amazon Redshift DataSource:

  • DatabaseInformation -

    • DatabaseName - The name of the Amazon Redshift database.

    • ClusterIdentifier - The unique ID for the Amazon Redshift cluster.

  • DatabaseCredentials - The AWS Identity and Access Management (IAM) credentials that are used to connect to the Amazon Redshift database.

  • SelectSqlQuery - The query that is used to retrieve the observation data for the Datasource.

  • S3StagingLocation - The Amazon Simple Storage Service (Amazon S3) location for staging Amazon Redshift data. The data retrieved from Amazon Redshift using the SelectSqlQuery query is stored in this location.

  • DataSchemaUri - The Amazon S3 location of the DataSchema.

  • DataSchema - A JSON string representing the schema. This is not required if DataSchemaUri is specified.

  • DataRearrangement - A JSON string that represents the splitting and rearrangement requirements for the DataSource.

    Sample - "{\"splitting\":{\"percentBegin\":10,\"percentEnd\":60}}"

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pub fn get_data_spec(&self) -> &Option<RedshiftDataSpec>

The data specification of an Amazon Redshift DataSource:

  • DatabaseInformation -

    • DatabaseName - The name of the Amazon Redshift database.

    • ClusterIdentifier - The unique ID for the Amazon Redshift cluster.

  • DatabaseCredentials - The AWS Identity and Access Management (IAM) credentials that are used to connect to the Amazon Redshift database.

  • SelectSqlQuery - The query that is used to retrieve the observation data for the Datasource.

  • S3StagingLocation - The Amazon Simple Storage Service (Amazon S3) location for staging Amazon Redshift data. The data retrieved from Amazon Redshift using the SelectSqlQuery query is stored in this location.

  • DataSchemaUri - The Amazon S3 location of the DataSchema.

  • DataSchema - A JSON string representing the schema. This is not required if DataSchemaUri is specified.

  • DataRearrangement - A JSON string that represents the splitting and rearrangement requirements for the DataSource.

    Sample - "{\"splitting\":{\"percentBegin\":10,\"percentEnd\":60}}"

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pub fn role_arn(self, input: impl Into<String>) -> Self

A fully specified role Amazon Resource Name (ARN). Amazon ML assumes the role on behalf of the user to create the following:

  • A security group to allow Amazon ML to execute the SelectSqlQuery query on an Amazon Redshift cluster

  • An Amazon S3 bucket policy to grant Amazon ML read/write permissions on the S3StagingLocation

This field is required.
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pub fn set_role_arn(self, input: Option<String>) -> Self

A fully specified role Amazon Resource Name (ARN). Amazon ML assumes the role on behalf of the user to create the following:

  • A security group to allow Amazon ML to execute the SelectSqlQuery query on an Amazon Redshift cluster

  • An Amazon S3 bucket policy to grant Amazon ML read/write permissions on the S3StagingLocation

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pub fn get_role_arn(&self) -> &Option<String>

A fully specified role Amazon Resource Name (ARN). Amazon ML assumes the role on behalf of the user to create the following:

  • A security group to allow Amazon ML to execute the SelectSqlQuery query on an Amazon Redshift cluster

  • An Amazon S3 bucket policy to grant Amazon ML read/write permissions on the S3StagingLocation

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pub fn compute_statistics(self, input: bool) -> Self

The compute statistics for a DataSource. The statistics are generated from the observation data referenced by a DataSource. Amazon ML uses the statistics internally during MLModel training. This parameter must be set to true if the DataSource needs to be used for MLModel training.

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pub fn set_compute_statistics(self, input: Option<bool>) -> Self

The compute statistics for a DataSource. The statistics are generated from the observation data referenced by a DataSource. Amazon ML uses the statistics internally during MLModel training. This parameter must be set to true if the DataSource needs to be used for MLModel training.

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pub fn get_compute_statistics(&self) -> &Option<bool>

The compute statistics for a DataSource. The statistics are generated from the observation data referenced by a DataSource. Amazon ML uses the statistics internally during MLModel training. This parameter must be set to true if the DataSource needs to be used for MLModel training.

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pub fn build(self) -> Result<CreateDataSourceFromRedshiftInput, BuildError>

Consumes the builder and constructs a CreateDataSourceFromRedshiftInput.

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impl CreateDataSourceFromRedshiftInputBuilder

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pub async fn send_with( self, client: &Client ) -> Result<CreateDataSourceFromRedshiftOutput, SdkError<CreateDataSourceFromRedshiftError, HttpResponse>>

Sends a request with this input using the given client.

Trait Implementations§

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impl Clone for CreateDataSourceFromRedshiftInputBuilder

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fn clone(&self) -> CreateDataSourceFromRedshiftInputBuilder

Returns a copy of the value. Read more
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fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source. Read more
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impl Debug for CreateDataSourceFromRedshiftInputBuilder

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fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter. Read more
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impl Default for CreateDataSourceFromRedshiftInputBuilder

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fn default() -> CreateDataSourceFromRedshiftInputBuilder

Returns the “default value” for a type. Read more
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impl PartialEq for CreateDataSourceFromRedshiftInputBuilder

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fn eq(&self, other: &CreateDataSourceFromRedshiftInputBuilder) -> bool

This method tests for self and other values to be equal, and is used by ==.
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fn ne(&self, other: &Rhs) -> bool

This method tests for !=. The default implementation is almost always sufficient, and should not be overridden without very good reason.
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impl StructuralPartialEq for CreateDataSourceFromRedshiftInputBuilder

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