Struct DataSource

pub struct DataSource {

    pub compute_statistics: Option<bool>,
    pub compute_time: Option<i64>,
    pub created_at: Option<f64>,
    pub created_by_iam_user: Option<String>,
    pub data_location_s3: Option<String>,
    pub data_rearrangement: Option<String>,
    pub data_size_in_bytes: Option<i64>,
    pub data_source_id: Option<String>,
    pub finished_at: Option<f64>,
    pub last_updated_at: Option<f64>,
    pub message: Option<String>,
    pub name: Option<String>,
    pub number_of_files: Option<i64>,
    pub rds_metadata: Option<RDSMetadata>,
    pub redshift_metadata: Option<RedshiftMetadata>,
    pub role_arn: Option<String>,
    pub started_at: Option<f64>,
    pub status: Option<String>,
}

Represents the output of the GetDataSource operation.

The content consists of the detailed metadata and data file information and the current status of the DataSource.

Fields

compute_statistics: Option<bool>

The parameter is true if statistics need to be generated from the observation data.

compute_time: Option<i64>

created_at: Option<f64>

The time that the DataSource was created. The time is expressed in epoch time.

created_by_iam_user: Option<String>

The AWS user account from which the DataSource was created. The account type can be either an AWS root account or an AWS Identity and Access Management (IAM) user account.

data_location_s3: Option<String>

The location and name of the data in Amazon Simple Storage Service (Amazon S3) that is used by a DataSource.

data_rearrangement: Option<String>

A JSON string that represents the splitting and rearrangement requirement used when this DataSource was created.

data_size_in_bytes: Option<i64>

The total number of observations contained in the data files that the DataSource references.

data_source_id: Option<String>

The ID that is assigned to the DataSource during creation.

finished_at: Option<f64>

last_updated_at: Option<f64>

The time of the most recent edit to the BatchPrediction. The time is expressed in epoch time.

message: Option<String>

A description of the most recent details about creating the DataSource.

name: Option<String>

A user-supplied name or description of the DataSource.

number_of_files: Option<i64>

The number of data files referenced by the DataSource.

rds_metadata: Option<RDSMetadata>

redshift_metadata: Option<RedshiftMetadata>

role_arn: Option<String>

started_at: Option<f64>

status: Option<String>

The current status of the DataSource. This element can have one of the following values:

• PENDING - Amazon Machine Learning (Amazon ML) submitted a request to create a DataSource.
• INPROGRESS - The creation process is underway.
• FAILED - The request to create a DataSource did not run to completion. It is not usable.
• COMPLETED - The creation process completed successfully.
• DELETED - The DataSource is marked as deleted. It is not usable.

Trait Implementations

impl Clone for DataSource

fn clone(&self) -> DataSource

Returns a copy of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for DataSource

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

Formats the value using the given formatter.

impl Default for DataSource

fn default() -> DataSource

Returns the “default value” for a type.

impl<'de> Deserialize<'de> for DataSource

fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error>

where __D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer.

impl PartialEq for DataSource

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

Tests for self and other values to be equal, and is used by ==.

fn ne(&self, other: &Rhs) -> bool

Tests for !=. The default implementation is almost always sufficient, and should not be overridden without very good reason.

impl StructuralPartialEq for DataSource