# WARNING ABOUT GENERATED CODE
#
# This file is generated. See the contributing guide for more information:
# https://github.com/aws/aws-sdk-ruby/blob/master/CONTRIBUTING.md
#
# WARNING ABOUT GENERATED CODE
require 'seahorse/client/plugins/content_length.rb'
require 'aws-sdk-core/plugins/credentials_configuration.rb'
require 'aws-sdk-core/plugins/logging.rb'
require 'aws-sdk-core/plugins/param_converter.rb'
require 'aws-sdk-core/plugins/param_validator.rb'
require 'aws-sdk-core/plugins/user_agent.rb'
require 'aws-sdk-core/plugins/helpful_socket_errors.rb'
require 'aws-sdk-core/plugins/retry_errors.rb'
require 'aws-sdk-core/plugins/global_configuration.rb'
require 'aws-sdk-core/plugins/regional_endpoint.rb'
require 'aws-sdk-core/plugins/endpoint_discovery.rb'
require 'aws-sdk-core/plugins/endpoint_pattern.rb'
require 'aws-sdk-core/plugins/response_paging.rb'
require 'aws-sdk-core/plugins/stub_responses.rb'
require 'aws-sdk-core/plugins/idempotency_token.rb'
require 'aws-sdk-core/plugins/jsonvalue_converter.rb'
require 'aws-sdk-core/plugins/client_metrics_plugin.rb'
require 'aws-sdk-core/plugins/client_metrics_send_plugin.rb'
require 'aws-sdk-core/plugins/transfer_encoding.rb'
require 'aws-sdk-core/plugins/signature_v4.rb'
require 'aws-sdk-core/plugins/protocols/json_rpc.rb'
Aws::Plugins::GlobalConfiguration.add_identifier(:forecastservice)
module Aws::ForecastService
class Client < Seahorse::Client::Base
include Aws::ClientStubs
@identifier = :forecastservice
set_api(ClientApi::API)
add_plugin(Seahorse::Client::Plugins::ContentLength)
add_plugin(Aws::Plugins::CredentialsConfiguration)
add_plugin(Aws::Plugins::Logging)
add_plugin(Aws::Plugins::ParamConverter)
add_plugin(Aws::Plugins::ParamValidator)
add_plugin(Aws::Plugins::UserAgent)
add_plugin(Aws::Plugins::HelpfulSocketErrors)
add_plugin(Aws::Plugins::RetryErrors)
add_plugin(Aws::Plugins::GlobalConfiguration)
add_plugin(Aws::Plugins::RegionalEndpoint)
add_plugin(Aws::Plugins::EndpointDiscovery)
add_plugin(Aws::Plugins::EndpointPattern)
add_plugin(Aws::Plugins::ResponsePaging)
add_plugin(Aws::Plugins::StubResponses)
add_plugin(Aws::Plugins::IdempotencyToken)
add_plugin(Aws::Plugins::JsonvalueConverter)
add_plugin(Aws::Plugins::ClientMetricsPlugin)
add_plugin(Aws::Plugins::ClientMetricsSendPlugin)
add_plugin(Aws::Plugins::TransferEncoding)
add_plugin(Aws::Plugins::SignatureV4)
add_plugin(Aws::Plugins::Protocols::JsonRpc)
# @overload initialize(options)
# @param [Hash] options
# @option options [required, Aws::CredentialProvider] :credentials
# Your AWS credentials. This can be an instance of any one of the
# following classes:
#
# * `Aws::Credentials` - Used for configuring static, non-refreshing
# credentials.
#
# * `Aws::InstanceProfileCredentials` - Used for loading credentials
# from an EC2 IMDS on an EC2 instance.
#
# * `Aws::SharedCredentials` - Used for loading credentials from a
# shared file, such as `~/.aws/config`.
#
# * `Aws::AssumeRoleCredentials` - Used when you need to assume a role.
#
# When `:credentials` are not configured directly, the following
# locations will be searched for credentials:
#
# * `Aws.config[:credentials]`
# * The `:access_key_id`, `:secret_access_key`, and `:session_token` options.
# * ENV['AWS_ACCESS_KEY_ID'], ENV['AWS_SECRET_ACCESS_KEY']
# * `~/.aws/credentials`
# * `~/.aws/config`
# * EC2 IMDS instance profile - When used by default, the timeouts are
# very aggressive. Construct and pass an instance of
# `Aws::InstanceProfileCredentails` to enable retries and extended
# timeouts.
#
# @option options [required, String] :region
# The AWS region to connect to. The configured `:region` is
# used to determine the service `:endpoint`. When not passed,
# a default `:region` is search for in the following locations:
#
# * `Aws.config[:region]`
# * `ENV['AWS_REGION']`
# * `ENV['AMAZON_REGION']`
# * `ENV['AWS_DEFAULT_REGION']`
# * `~/.aws/credentials`
# * `~/.aws/config`
#
# @option options [String] :access_key_id
#
# @option options [Boolean] :active_endpoint_cache (false)
# When set to `true`, a thread polling for endpoints will be running in
# the background every 60 secs (default). Defaults to `false`.
#
# @option options [Boolean] :client_side_monitoring (false)
# When `true`, client-side metrics will be collected for all API requests from
# this client.
#
# @option options [String] :client_side_monitoring_client_id ("")
# Allows you to provide an identifier for this client which will be attached to
# all generated client side metrics. Defaults to an empty string.
#
# @option options [String] :client_side_monitoring_host ("127.0.0.1")
# Allows you to specify the DNS hostname or IPv4 or IPv6 address that the client
# side monitoring agent is running on, where client metrics will be published via UDP.
#
# @option options [Integer] :client_side_monitoring_port (31000)
# Required for publishing client metrics. The port that the client side monitoring
# agent is running on, where client metrics will be published via UDP.
#
# @option options [Aws::ClientSideMonitoring::Publisher] :client_side_monitoring_publisher (Aws::ClientSideMonitoring::Publisher)
# Allows you to provide a custom client-side monitoring publisher class. By default,
# will use the Client Side Monitoring Agent Publisher.
#
# @option options [Boolean] :convert_params (true)
# When `true`, an attempt is made to coerce request parameters into
# the required types.
#
# @option options [Boolean] :disable_host_prefix_injection (false)
# Set to true to disable SDK automatically adding host prefix
# to default service endpoint when available.
#
# @option options [String] :endpoint
# The client endpoint is normally constructed from the `:region`
# option. You should only configure an `:endpoint` when connecting
# to test endpoints. This should be avalid HTTP(S) URI.
#
# @option options [Integer] :endpoint_cache_max_entries (1000)
# Used for the maximum size limit of the LRU cache storing endpoints data
# for endpoint discovery enabled operations. Defaults to 1000.
#
# @option options [Integer] :endpoint_cache_max_threads (10)
# Used for the maximum threads in use for polling endpoints to be cached, defaults to 10.
#
# @option options [Integer] :endpoint_cache_poll_interval (60)
# When :endpoint_discovery and :active_endpoint_cache is enabled,
# Use this option to config the time interval in seconds for making
# requests fetching endpoints information. Defaults to 60 sec.
#
# @option options [Boolean] :endpoint_discovery (false)
# When set to `true`, endpoint discovery will be enabled for operations when available. Defaults to `false`.
#
# @option options [Aws::Log::Formatter] :log_formatter (Aws::Log::Formatter.default)
# The log formatter.
#
# @option options [Symbol] :log_level (:info)
# The log level to send messages to the `:logger` at.
#
# @option options [Logger] :logger
# The Logger instance to send log messages to. If this option
# is not set, logging will be disabled.
#
# @option options [String] :profile ("default")
# Used when loading credentials from the shared credentials file
# at HOME/.aws/credentials. When not specified, 'default' is used.
#
# @option options [Float] :retry_base_delay (0.3)
# The base delay in seconds used by the default backoff function.
#
# @option options [Symbol] :retry_jitter (:none)
# A delay randomiser function used by the default backoff function. Some predefined functions can be referenced by name - :none, :equal, :full, otherwise a Proc that takes and returns a number.
#
# @see https://www.awsarchitectureblog.com/2015/03/backoff.html
#
# @option options [Integer] :retry_limit (3)
# The maximum number of times to retry failed requests. Only
# ~ 500 level server errors and certain ~ 400 level client errors
# are retried. Generally, these are throttling errors, data
# checksum errors, networking errors, timeout errors and auth
# errors from expired credentials.
#
# @option options [Integer] :retry_max_delay (0)
# The maximum number of seconds to delay between retries (0 for no limit) used by the default backoff function.
#
# @option options [String] :secret_access_key
#
# @option options [String] :session_token
#
# @option options [Boolean] :simple_json (false)
# Disables request parameter conversion, validation, and formatting.
# Also disable response data type conversions. This option is useful
# when you want to ensure the highest level of performance by
# avoiding overhead of walking request parameters and response data
# structures.
#
# When `:simple_json` is enabled, the request parameters hash must
# be formatted exactly as the DynamoDB API expects.
#
# @option options [Boolean] :stub_responses (false)
# Causes the client to return stubbed responses. By default
# fake responses are generated and returned. You can specify
# the response data to return or errors to raise by calling
# {ClientStubs#stub_responses}. See {ClientStubs} for more information.
#
# ** Please note ** When response stubbing is enabled, no HTTP
# requests are made, and retries are disabled.
#
# @option options [Boolean] :validate_params (true)
# When `true`, request parameters are validated before
# sending the request.
#
# @option options [URI::HTTP,String] :http_proxy A proxy to send
# requests through. Formatted like 'http://proxy.com:123'.
#
# @option options [Float] :http_open_timeout (15) The number of
# seconds to wait when opening a HTTP session before rasing a
# `Timeout::Error`.
#
# @option options [Integer] :http_read_timeout (60) The default
# number of seconds to wait for response data. This value can
# safely be set
# per-request on the session yeidled by {#session_for}.
#
# @option options [Float] :http_idle_timeout (5) The number of
# seconds a connection is allowed to sit idble before it is
# considered stale. Stale connections are closed and removed
# from the pool before making a request.
#
# @option options [Float] :http_continue_timeout (1) The number of
# seconds to wait for a 100-continue response before sending the
# request body. This option has no effect unless the request has
# "Expect" header set to "100-continue". Defaults to `nil` which
# disables this behaviour. This value can safely be set per
# request on the session yeidled by {#session_for}.
#
# @option options [Boolean] :http_wire_trace (false) When `true`,
# HTTP debug output will be sent to the `:logger`.
#
# @option options [Boolean] :ssl_verify_peer (true) When `true`,
# SSL peer certificates are verified when establishing a
# connection.
#
# @option options [String] :ssl_ca_bundle Full path to the SSL
# certificate authority bundle file that should be used when
# verifying peer certificates. If you do not pass
# `:ssl_ca_bundle` or `:ssl_ca_directory` the the system default
# will be used if available.
#
# @option options [String] :ssl_ca_directory Full path of the
# directory that contains the unbundled SSL certificate
# authority files for verifying peer certificates. If you do
# not pass `:ssl_ca_bundle` or `:ssl_ca_directory` the the
# system default will be used if available.
#
def initialize(*args)
super
end
# @!group API Operations
# Creates an Amazon Forecast dataset. The information about the dataset
# that you provide helps Forecast understand how to consume the data for
# model training. This includes the following:
#
# * DataFrequency - How frequently your historical
# time-series data is collected.
#
# * Domain and DatasetType -
# Each dataset has an associated dataset domain and a type within the
# domain. Amazon Forecast provides a list of predefined domains and
# types within each domain. For each unique dataset domain and type
# within the domain, Amazon Forecast requires your data to include a
# minimum set of predefined fields.
#
# * Schema - A schema specifies the fields in the
# dataset, including the field name and data type.
#
# After creating a dataset, you import your training data into it and
# add the dataset to a dataset group. You use the dataset group to
# create a predictor. For more information, see
# howitworks-datasets-groups.
#
# To get a list of all your datasets, use the ListDatasets operation.
#
# For example Forecast datasets, see the [Amazon Forecast Sample GitHub
# repository][1].
#
# The `Status` of a dataset must be `ACTIVE` before you can import
# training data. Use the DescribeDataset operation to get the status.
#
#
#
#
#
# [1]: https://github.com/aws-samples/amazon-forecast-samples/tree/master/data
#
# @option params [required, String] :dataset_name
# A name for the dataset.
#
# @option params [required, String] :domain
# The domain associated with the dataset. When you add a dataset to a
# dataset group, this value and the value specified for the `Domain`
# parameter of the CreateDatasetGroup operation must match.
#
# The `Domain` and `DatasetType` that you choose determine the fields
# that must be present in the training data that you import to the
# dataset. For example, if you choose the `RETAIL` domain and
# `TARGET_TIME_SERIES` as the `DatasetType`, Amazon Forecast requires
# `item_id`, `timestamp`, and `demand` fields to be present in your
# data. For more information, see howitworks-datasets-groups.
#
# @option params [required, String] :dataset_type
# The dataset type. Valid values depend on the chosen `Domain`.
#
# @option params [String] :data_frequency
# The frequency of data collection. This parameter is required for
# RELATED\_TIME\_SERIES datasets.
#
# Valid intervals are Y (Year), M (Month), W (Week), D (Day), H (Hour),
# 30min (30 minutes), 15min (15 minutes), 10min (10 minutes), 5min (5
# minutes), and 1min (1 minute). For example, "D" indicates every day
# and "15min" indicates every 15 minutes.
#
# @option params [required, Types::Schema] :schema
# The schema for the dataset. The schema attributes and their order must
# match the fields in your data. The dataset `Domain` and `DatasetType`
# that you choose determine the minimum required fields in your training
# data. For information about the required fields for a specific dataset
# domain and type, see howitworks-domains-ds-types.
#
# @option params [Types::EncryptionConfig] :encryption_config
# An AWS Key Management Service (KMS) key and the AWS Identity and
# Access Management (IAM) role that Amazon Forecast can assume to access
# the key.
#
# @return [Types::CreateDatasetResponse] Returns a {Seahorse::Client::Response response} object which responds to the following methods:
#
# * {Types::CreateDatasetResponse#dataset_arn #dataset_arn} => String
#
# @example Request syntax with placeholder values
#
# resp = client.create_dataset({
# dataset_name: "Name", # required
# domain: "RETAIL", # required, accepts RETAIL, CUSTOM, INVENTORY_PLANNING, EC2_CAPACITY, WORK_FORCE, WEB_TRAFFIC, METRICS
# dataset_type: "TARGET_TIME_SERIES", # required, accepts TARGET_TIME_SERIES, RELATED_TIME_SERIES, ITEM_METADATA
# data_frequency: "Frequency",
# schema: { # required
# attributes: [
# {
# attribute_name: "Name",
# attribute_type: "string", # accepts string, integer, float, timestamp
# },
# ],
# },
# encryption_config: {
# role_arn: "Arn", # required
# kms_key_arn: "KMSKeyArn", # required
# },
# })
#
# @example Response structure
#
# resp.dataset_arn #=> String
#
# @see http://docs.aws.amazon.com/goto/WebAPI/forecast-2018-06-26/CreateDataset AWS API Documentation
#
# @overload create_dataset(params = {})
# @param [Hash] params ({})
def create_dataset(params = {}, options = {})
req = build_request(:create_dataset, params)
req.send_request(options)
end
# Creates a dataset group, which holds a collection of related datasets.
# You can add datasets to the dataset group when you create the dataset
# group, or later by using the UpdateDatasetGroup operation.
#
# After creating a dataset group and adding datasets, you use the
# dataset group when you create a predictor. For more information, see
# howitworks-datasets-groups.
#
# To get a list of all your datasets groups, use the ListDatasetGroups
# operation.
#
# The `Status` of a dataset group must be `ACTIVE` before you can create
# use the dataset group to create a predictor. To get the status, use
# the DescribeDatasetGroup operation.
#
#
#
# @option params [required, String] :dataset_group_name
# A name for the dataset group.
#
# @option params [required, String] :domain
# The domain associated with the dataset group. When you add a dataset
# to a dataset group, this value and the value specified for the
# `Domain` parameter of the CreateDataset operation must match.
#
# The `Domain` and `DatasetType` that you choose determine the fields
# that must be present in training data that you import to a dataset.
# For example, if you choose the `RETAIL` domain and
# `TARGET_TIME_SERIES` as the `DatasetType`, Amazon Forecast requires
# that `item_id`, `timestamp`, and `demand` fields are present in your
# data. For more information, see howitworks-datasets-groups.
#
# @option params [Array] :dataset_arns
# An array of Amazon Resource Names (ARNs) of the datasets that you want
# to include in the dataset group.
#
# @return [Types::CreateDatasetGroupResponse] Returns a {Seahorse::Client::Response response} object which responds to the following methods:
#
# * {Types::CreateDatasetGroupResponse#dataset_group_arn #dataset_group_arn} => String
#
# @example Request syntax with placeholder values
#
# resp = client.create_dataset_group({
# dataset_group_name: "Name", # required
# domain: "RETAIL", # required, accepts RETAIL, CUSTOM, INVENTORY_PLANNING, EC2_CAPACITY, WORK_FORCE, WEB_TRAFFIC, METRICS
# dataset_arns: ["Arn"],
# })
#
# @example Response structure
#
# resp.dataset_group_arn #=> String
#
# @see http://docs.aws.amazon.com/goto/WebAPI/forecast-2018-06-26/CreateDatasetGroup AWS API Documentation
#
# @overload create_dataset_group(params = {})
# @param [Hash] params ({})
def create_dataset_group(params = {}, options = {})
req = build_request(:create_dataset_group, params)
req.send_request(options)
end
# Imports your training data to an Amazon Forecast dataset. You provide
# the location of your training data in an Amazon Simple Storage Service
# (Amazon S3) bucket and the Amazon Resource Name (ARN) of the dataset
# that you want to import the data to.
#
# You must specify a DataSource object that includes an AWS Identity and
# Access Management (IAM) role that Amazon Forecast can assume to access
# the data. For more information, see aws-forecast-iam-roles.
#
# The training data must be in CSV format. The delimiter must be a comma
# (,).
#
# You can specify the path to a specific CSV file, the S3 bucket, or to
# a folder in the S3 bucket. For the latter two cases, Amazon Forecast
# imports all files up to the limit of 10,000 files.
#
# To get a list of all your dataset import jobs, filtered by specified
# criteria, use the ListDatasetImportJobs operation.
#
# @option params [required, String] :dataset_import_job_name
# The name for the dataset import job. We recommend including the
# current timestamp in the name, for example, `20190721DatasetImport`.
# This can help you avoid getting a `ResourceAlreadyExistsException`
# exception.
#
# @option params [required, String] :dataset_arn
# The Amazon Resource Name (ARN) of the Amazon Forecast dataset that you
# want to import data to.
#
# @option params [required, Types::DataSource] :data_source
# The location of the training data to import and an AWS Identity and
# Access Management (IAM) role that Amazon Forecast can assume to access
# the data. The training data must be stored in an Amazon S3 bucket.
#
# If encryption is used, `DataSource` must include an AWS Key Management
# Service (KMS) key and the IAM role must allow Amazon Forecast
# permission to access the key. The KMS key and IAM role must match
# those specified in the `EncryptionConfig` parameter of the
# CreateDataset operation.
#
# @option params [String] :timestamp_format
# The format of timestamps in the dataset. The format that you specify
# depends on the `DataFrequency` specified when the dataset was created.
# The following formats are supported
#
# * "yyyy-MM-dd"
#
# For the following data frequencies: Y, M, W, and D
#
# * "yyyy-MM-dd HH:mm:ss"
#
# For the following data frequencies: H, 30min, 15min, and 1min; and
# optionally, for: Y, M, W, and D
#
# If the format isn't specified, Amazon Forecast expects the format to
# be "yyyy-MM-dd HH:mm:ss".
#
# @return [Types::CreateDatasetImportJobResponse] Returns a {Seahorse::Client::Response response} object which responds to the following methods:
#
# * {Types::CreateDatasetImportJobResponse#dataset_import_job_arn #dataset_import_job_arn} => String
#
# @example Request syntax with placeholder values
#
# resp = client.create_dataset_import_job({
# dataset_import_job_name: "Name", # required
# dataset_arn: "Arn", # required
# data_source: { # required
# s3_config: { # required
# path: "S3Path", # required
# role_arn: "Arn", # required
# kms_key_arn: "KMSKeyArn",
# },
# },
# timestamp_format: "TimestampFormat",
# })
#
# @example Response structure
#
# resp.dataset_import_job_arn #=> String
#
# @see http://docs.aws.amazon.com/goto/WebAPI/forecast-2018-06-26/CreateDatasetImportJob AWS API Documentation
#
# @overload create_dataset_import_job(params = {})
# @param [Hash] params ({})
def create_dataset_import_job(params = {}, options = {})
req = build_request(:create_dataset_import_job, params)
req.send_request(options)
end
# Creates a forecast for each item in the `TARGET_TIME_SERIES` dataset
# that was used to train the predictor. This is known as inference. To
# retrieve the forecast for a single item at low latency, use the
# operation. To export the complete forecast into your Amazon Simple
# Storage Service (Amazon S3) bucket, use the CreateForecastExportJob
# operation.
#
# The range of the forecast is determined by the `ForecastHorizon`
# value, which you specify in the CreatePredictor request, multiplied by
# the `DataFrequency` value, which you specify in the CreateDataset
# request. When you query a forecast, you can request a specific date
# range within the forecast.
#
# To get a list of all your forecasts, use the ListForecasts operation.
#
# The forecasts generated by Amazon Forecast are in the same time zone
# as the dataset that was used to create the predictor.
#
#
#
# For more information, see howitworks-forecast.
#
# The `Status` of the forecast must be `ACTIVE` before you can query or
# export the forecast. Use the DescribeForecast operation to get the
# status.
#
#
#
# @option params [required, String] :forecast_name
# A name for the forecast.
#
# @option params [required, String] :predictor_arn
# The Amazon Resource Name (ARN) of the predictor to use to generate the
# forecast.
#
# @option params [Array] :forecast_types
# The quantiles at which probabilistic forecasts are generated. You can
# specify up to 5 quantiles per forecast. Accepted values include `0.01
# to 0.99` (increments of .01 only) and `mean`. The mean forecast is
# different from the median (0.50) when the distribution is not
# symmetric (e.g. Beta, Negative Binomial). The default value is
# `["0.1", "0.5", "0.9"]`.
#
# @return [Types::CreateForecastResponse] Returns a {Seahorse::Client::Response response} object which responds to the following methods:
#
# * {Types::CreateForecastResponse#forecast_arn #forecast_arn} => String
#
# @example Request syntax with placeholder values
#
# resp = client.create_forecast({
# forecast_name: "Name", # required
# predictor_arn: "Arn", # required
# forecast_types: ["ForecastType"],
# })
#
# @example Response structure
#
# resp.forecast_arn #=> String
#
# @see http://docs.aws.amazon.com/goto/WebAPI/forecast-2018-06-26/CreateForecast AWS API Documentation
#
# @overload create_forecast(params = {})
# @param [Hash] params ({})
def create_forecast(params = {}, options = {})
req = build_request(:create_forecast, params)
req.send_request(options)
end
# Exports a forecast created by the CreateForecast operation to your
# Amazon Simple Storage Service (Amazon S3) bucket. The forecast file
# name will match the following conventions:
#
# <ForecastExportJobName>\_<ExportTimestamp>\_<PageNumber>
#
# where the <ExportTimestamp> component is in Java
# SimpleDateFormat (yyyy-MM-ddTHH-mm-ssZ).
#
# You must specify a DataDestination object that includes an AWS
# Identity and Access Management (IAM) role that Amazon Forecast can
# assume to access the Amazon S3 bucket. For more information, see
# aws-forecast-iam-roles.
#
# For more information, see howitworks-forecast.
#
# To get a list of all your forecast export jobs, use the
# ListForecastExportJobs operation.
#
# The `Status` of the forecast export job must be `ACTIVE` before you
# can access the forecast in your Amazon S3 bucket. To get the status,
# use the DescribeForecastExportJob operation.
#
#
#
# @option params [required, String] :forecast_export_job_name
# The name for the forecast export job.
#
# @option params [required, String] :forecast_arn
# The Amazon Resource Name (ARN) of the forecast that you want to
# export.
#
# @option params [required, Types::DataDestination] :destination
# The location where you want to save the forecast and an AWS Identity
# and Access Management (IAM) role that Amazon Forecast can assume to
# access the location. The forecast must be exported to an Amazon S3
# bucket.
#
# If encryption is used, `Destination` must include an AWS Key
# Management Service (KMS) key. The IAM role must allow Amazon Forecast
# permission to access the key.
#
# @return [Types::CreateForecastExportJobResponse] Returns a {Seahorse::Client::Response response} object which responds to the following methods:
#
# * {Types::CreateForecastExportJobResponse#forecast_export_job_arn #forecast_export_job_arn} => String
#
# @example Request syntax with placeholder values
#
# resp = client.create_forecast_export_job({
# forecast_export_job_name: "Name", # required
# forecast_arn: "Arn", # required
# destination: { # required
# s3_config: { # required
# path: "S3Path", # required
# role_arn: "Arn", # required
# kms_key_arn: "KMSKeyArn",
# },
# },
# })
#
# @example Response structure
#
# resp.forecast_export_job_arn #=> String
#
# @see http://docs.aws.amazon.com/goto/WebAPI/forecast-2018-06-26/CreateForecastExportJob AWS API Documentation
#
# @overload create_forecast_export_job(params = {})
# @param [Hash] params ({})
def create_forecast_export_job(params = {}, options = {})
req = build_request(:create_forecast_export_job, params)
req.send_request(options)
end
# Creates an Amazon Forecast predictor.
#
# In the request, you provide a dataset group and either specify an
# algorithm or let Amazon Forecast choose the algorithm for you using
# AutoML. If you specify an algorithm, you also can override
# algorithm-specific hyperparameters.
#
# Amazon Forecast uses the chosen algorithm to train a model using the
# latest version of the datasets in the specified dataset group. The
# result is called a predictor. You then generate a forecast using the
# CreateForecast operation.
#
# After training a model, the `CreatePredictor` operation also evaluates
# it. To see the evaluation metrics, use the GetAccuracyMetrics
# operation. Always review the evaluation metrics before deciding to use
# the predictor to generate a forecast.
#
# Optionally, you can specify a featurization configuration to fill and
# aggregate the data fields in the `TARGET_TIME_SERIES` dataset to
# improve model training. For more information, see FeaturizationConfig.
#
# For RELATED\_TIME\_SERIES datasets, `CreatePredictor` verifies that
# the `DataFrequency` specified when the dataset was created matches the
# `ForecastFrequency`. TARGET\_TIME\_SERIES datasets don't have this
# restriction. Amazon Forecast also verifies the delimiter and timestamp
# format. For more information, see howitworks-datasets-groups.
#
# **AutoML**
#
# If you want Amazon Forecast to evaluate each algorithm and choose the
# one that minimizes the `objective function`, set `PerformAutoML` to
# `true`. The `objective function` is defined as the mean of the
# weighted p10, p50, and p90 quantile losses. For more information, see
# EvaluationResult.
#
# When AutoML is enabled, the following properties are disallowed:
#
# * `AlgorithmArn`
#
# * `HPOConfig`
#
# * `PerformHPO`
#
# * `TrainingParameters`
#
# To get a list of all of your predictors, use the ListPredictors
# operation.
#
# Before you can use the predictor to create a forecast, the `Status` of
# the predictor must be `ACTIVE`, signifying that training has
# completed. To get the status, use the DescribePredictor operation.
#
#
#
# @option params [required, String] :predictor_name
# A name for the predictor.
#
# @option params [String] :algorithm_arn
# The Amazon Resource Name (ARN) of the algorithm to use for model
# training. Required if `PerformAutoML` is not set to `true`.
#
# **Supported algorithms:**
#
# * `arn:aws:forecast:::algorithm/ARIMA`
#
# * `arn:aws:forecast:::algorithm/Deep_AR_Plus`
#
# Supports hyperparameter optimization (HPO)
#
# * `arn:aws:forecast:::algorithm/ETS`
#
# * `arn:aws:forecast:::algorithm/NPTS`
#
# * `arn:aws:forecast:::algorithm/Prophet`
#
# @option params [required, Integer] :forecast_horizon
# Specifies the number of time-steps that the model is trained to
# predict. The forecast horizon is also called the prediction length.
#
# For example, if you configure a dataset for daily data collection
# (using the `DataFrequency` parameter of the CreateDataset operation)
# and set the forecast horizon to 10, the model returns predictions for
# 10 days.
#
# The maximum forecast horizon is the lesser of 500 time-steps or 1/3 of
# the TARGET\_TIME\_SERIES dataset length.
#
# @option params [Boolean] :perform_auto_ml
# Whether to perform AutoML. When Amazon Forecast performs AutoML, it
# evaluates the algorithms it provides and chooses the best algorithm
# and configuration for your training dataset.
#
# The default value is `false`. In this case, you are required to
# specify an algorithm.
#
# Set `PerformAutoML` to `true` to have Amazon Forecast perform AutoML.
# This is a good option if you aren't sure which algorithm is suitable
# for your training data. In this case, `PerformHPO` must be false.
#
# @option params [Boolean] :perform_hpo
# Whether to perform hyperparameter optimization (HPO). HPO finds
# optimal hyperparameter values for your training data. The process of
# performing HPO is known as running a hyperparameter tuning job.
#
# The default value is `false`. In this case, Amazon Forecast uses
# default hyperparameter values from the chosen algorithm.
#
# To override the default values, set `PerformHPO` to `true` and,
# optionally, supply the HyperParameterTuningJobConfig object. The
# tuning job specifies a metric to optimize, which hyperparameters
# participate in tuning, and the valid range for each tunable
# hyperparameter. In this case, you are required to specify an algorithm
# and `PerformAutoML` must be false.
#
# The following algorithm supports HPO:
#
# * DeepAR+
#
# ^
#
# @option params [Hash] :training_parameters
# The hyperparameters to override for model training. The
# hyperparameters that you can override are listed in the individual
# algorithms. For the list of supported algorithms, see
# aws-forecast-choosing-recipes.
#
# @option params [Types::EvaluationParameters] :evaluation_parameters
# Used to override the default evaluation parameters of the specified
# algorithm. Amazon Forecast evaluates a predictor by splitting a
# dataset into training data and testing data. The evaluation parameters
# define how to perform the split and the number of iterations.
#
# @option params [Types::HyperParameterTuningJobConfig] :hpo_config
# Provides hyperparameter override values for the algorithm. If you
# don't provide this parameter, Amazon Forecast uses default values.
# The individual algorithms specify which hyperparameters support
# hyperparameter optimization (HPO). For more information, see
# aws-forecast-choosing-recipes.
#
# If you included the `HPOConfig` object, you must set `PerformHPO` to
# true.
#
# @option params [required, Types::InputDataConfig] :input_data_config
# Describes the dataset group that contains the data to use to train the
# predictor.
#
# @option params [required, Types::FeaturizationConfig] :featurization_config
# The featurization configuration.
#
# @option params [Types::EncryptionConfig] :encryption_config
# An AWS Key Management Service (KMS) key and the AWS Identity and
# Access Management (IAM) role that Amazon Forecast can assume to access
# the key.
#
# @return [Types::CreatePredictorResponse] Returns a {Seahorse::Client::Response response} object which responds to the following methods:
#
# * {Types::CreatePredictorResponse#predictor_arn #predictor_arn} => String
#
# @example Request syntax with placeholder values
#
# resp = client.create_predictor({
# predictor_name: "Name", # required
# algorithm_arn: "Arn",
# forecast_horizon: 1, # required
# perform_auto_ml: false,
# perform_hpo: false,
# training_parameters: {
# "ParameterKey" => "ParameterValue",
# },
# evaluation_parameters: {
# number_of_backtest_windows: 1,
# back_test_window_offset: 1,
# },
# hpo_config: {
# parameter_ranges: {
# categorical_parameter_ranges: [
# {
# name: "Name", # required
# values: ["Value"], # required
# },
# ],
# continuous_parameter_ranges: [
# {
# name: "Name", # required
# max_value: 1.0, # required
# min_value: 1.0, # required
# scaling_type: "Auto", # accepts Auto, Linear, Logarithmic, ReverseLogarithmic
# },
# ],
# integer_parameter_ranges: [
# {
# name: "Name", # required
# max_value: 1, # required
# min_value: 1, # required
# scaling_type: "Auto", # accepts Auto, Linear, Logarithmic, ReverseLogarithmic
# },
# ],
# },
# },
# input_data_config: { # required
# dataset_group_arn: "Arn", # required
# supplementary_features: [
# {
# name: "Name", # required
# value: "Value", # required
# },
# ],
# },
# featurization_config: { # required
# forecast_frequency: "Frequency", # required
# forecast_dimensions: ["Name"],
# featurizations: [
# {
# attribute_name: "Name", # required
# featurization_pipeline: [
# {
# featurization_method_name: "filling", # required, accepts filling
# featurization_method_parameters: {
# "ParameterKey" => "ParameterValue",
# },
# },
# ],
# },
# ],
# },
# encryption_config: {
# role_arn: "Arn", # required
# kms_key_arn: "KMSKeyArn", # required
# },
# })
#
# @example Response structure
#
# resp.predictor_arn #=> String
#
# @see http://docs.aws.amazon.com/goto/WebAPI/forecast-2018-06-26/CreatePredictor AWS API Documentation
#
# @overload create_predictor(params = {})
# @param [Hash] params ({})
def create_predictor(params = {}, options = {})
req = build_request(:create_predictor, params)
req.send_request(options)
end
# Deletes an Amazon Forecast dataset that was created using the
# CreateDataset operation. You can only delete datasets that have a
# status of `ACTIVE` or `CREATE_FAILED`. To get the status use the
# DescribeDataset operation.
#
# @option params [required, String] :dataset_arn
# The Amazon Resource Name (ARN) of the dataset to delete.
#
# @return [Struct] Returns an empty {Seahorse::Client::Response response}.
#
# @example Request syntax with placeholder values
#
# resp = client.delete_dataset({
# dataset_arn: "Arn", # required
# })
#
# @see http://docs.aws.amazon.com/goto/WebAPI/forecast-2018-06-26/DeleteDataset AWS API Documentation
#
# @overload delete_dataset(params = {})
# @param [Hash] params ({})
def delete_dataset(params = {}, options = {})
req = build_request(:delete_dataset, params)
req.send_request(options)
end
# Deletes a dataset group created using the CreateDatasetGroup
# operation. You can only delete dataset groups that have a status of
# `ACTIVE`, `CREATE_FAILED`, or `UPDATE_FAILED`. To get the status, use
# the DescribeDatasetGroup operation.
#
# This operation deletes only the dataset group, not the datasets in the
# group.
#
# @option params [required, String] :dataset_group_arn
# The Amazon Resource Name (ARN) of the dataset group to delete.
#
# @return [Struct] Returns an empty {Seahorse::Client::Response response}.
#
# @example Request syntax with placeholder values
#
# resp = client.delete_dataset_group({
# dataset_group_arn: "Arn", # required
# })
#
# @see http://docs.aws.amazon.com/goto/WebAPI/forecast-2018-06-26/DeleteDatasetGroup AWS API Documentation
#
# @overload delete_dataset_group(params = {})
# @param [Hash] params ({})
def delete_dataset_group(params = {}, options = {})
req = build_request(:delete_dataset_group, params)
req.send_request(options)
end
# Deletes a dataset import job created using the CreateDatasetImportJob
# operation. You can delete only dataset import jobs that have a status
# of `ACTIVE` or `CREATE_FAILED`. To get the status, use the
# DescribeDatasetImportJob operation.
#
# @option params [required, String] :dataset_import_job_arn
# The Amazon Resource Name (ARN) of the dataset import job to delete.
#
# @return [Struct] Returns an empty {Seahorse::Client::Response response}.
#
# @example Request syntax with placeholder values
#
# resp = client.delete_dataset_import_job({
# dataset_import_job_arn: "Arn", # required
# })
#
# @see http://docs.aws.amazon.com/goto/WebAPI/forecast-2018-06-26/DeleteDatasetImportJob AWS API Documentation
#
# @overload delete_dataset_import_job(params = {})
# @param [Hash] params ({})
def delete_dataset_import_job(params = {}, options = {})
req = build_request(:delete_dataset_import_job, params)
req.send_request(options)
end
# Deletes a forecast created using the CreateForecast operation. You can
# delete only forecasts that have a status of `ACTIVE` or
# `CREATE_FAILED`. To get the status, use the DescribeForecast
# operation.
#
# You can't delete a forecast while it is being exported. After a
# forecast is deleted, you can no longer query the forecast.
#
# @option params [required, String] :forecast_arn
# The Amazon Resource Name (ARN) of the forecast to delete.
#
# @return [Struct] Returns an empty {Seahorse::Client::Response response}.
#
# @example Request syntax with placeholder values
#
# resp = client.delete_forecast({
# forecast_arn: "Arn", # required
# })
#
# @see http://docs.aws.amazon.com/goto/WebAPI/forecast-2018-06-26/DeleteForecast AWS API Documentation
#
# @overload delete_forecast(params = {})
# @param [Hash] params ({})
def delete_forecast(params = {}, options = {})
req = build_request(:delete_forecast, params)
req.send_request(options)
end
# Deletes a forecast export job created using the
# CreateForecastExportJob operation. You can delete only export jobs
# that have a status of `ACTIVE` or `CREATE_FAILED`. To get the status,
# use the DescribeForecastExportJob operation.
#
# @option params [required, String] :forecast_export_job_arn
# The Amazon Resource Name (ARN) of the forecast export job to delete.
#
# @return [Struct] Returns an empty {Seahorse::Client::Response response}.
#
# @example Request syntax with placeholder values
#
# resp = client.delete_forecast_export_job({
# forecast_export_job_arn: "Arn", # required
# })
#
# @see http://docs.aws.amazon.com/goto/WebAPI/forecast-2018-06-26/DeleteForecastExportJob AWS API Documentation
#
# @overload delete_forecast_export_job(params = {})
# @param [Hash] params ({})
def delete_forecast_export_job(params = {}, options = {})
req = build_request(:delete_forecast_export_job, params)
req.send_request(options)
end
# Deletes a predictor created using the CreatePredictor operation. You
# can delete only predictor that have a status of `ACTIVE` or
# `CREATE_FAILED`. To get the status, use the DescribePredictor
# operation.
#
# @option params [required, String] :predictor_arn
# The Amazon Resource Name (ARN) of the predictor to delete.
#
# @return [Struct] Returns an empty {Seahorse::Client::Response response}.
#
# @example Request syntax with placeholder values
#
# resp = client.delete_predictor({
# predictor_arn: "Arn", # required
# })
#
# @see http://docs.aws.amazon.com/goto/WebAPI/forecast-2018-06-26/DeletePredictor AWS API Documentation
#
# @overload delete_predictor(params = {})
# @param [Hash] params ({})
def delete_predictor(params = {}, options = {})
req = build_request(:delete_predictor, params)
req.send_request(options)
end
# Describes an Amazon Forecast dataset created using the CreateDataset
# operation.
#
# In addition to listing the parameters specified in the `CreateDataset`
# request, this operation includes the following dataset properties:
#
# * `CreationTime`
#
# * `LastModificationTime`
#
# * `Status`
#
# @option params [required, String] :dataset_arn
# The Amazon Resource Name (ARN) of the dataset.
#
# @return [Types::DescribeDatasetResponse] Returns a {Seahorse::Client::Response response} object which responds to the following methods:
#
# * {Types::DescribeDatasetResponse#dataset_arn #dataset_arn} => String
# * {Types::DescribeDatasetResponse#dataset_name #dataset_name} => String
# * {Types::DescribeDatasetResponse#domain #domain} => String
# * {Types::DescribeDatasetResponse#dataset_type #dataset_type} => String
# * {Types::DescribeDatasetResponse#data_frequency #data_frequency} => String
# * {Types::DescribeDatasetResponse#schema #schema} => Types::Schema
# * {Types::DescribeDatasetResponse#encryption_config #encryption_config} => Types::EncryptionConfig
# * {Types::DescribeDatasetResponse#status #status} => String
# * {Types::DescribeDatasetResponse#creation_time #creation_time} => Time
# * {Types::DescribeDatasetResponse#last_modification_time #last_modification_time} => Time
#
# @example Request syntax with placeholder values
#
# resp = client.describe_dataset({
# dataset_arn: "Arn", # required
# })
#
# @example Response structure
#
# resp.dataset_arn #=> String
# resp.dataset_name #=> String
# resp.domain #=> String, one of "RETAIL", "CUSTOM", "INVENTORY_PLANNING", "EC2_CAPACITY", "WORK_FORCE", "WEB_TRAFFIC", "METRICS"
# resp.dataset_type #=> String, one of "TARGET_TIME_SERIES", "RELATED_TIME_SERIES", "ITEM_METADATA"
# resp.data_frequency #=> String
# resp.schema.attributes #=> Array
# resp.schema.attributes[0].attribute_name #=> String
# resp.schema.attributes[0].attribute_type #=> String, one of "string", "integer", "float", "timestamp"
# resp.encryption_config.role_arn #=> String
# resp.encryption_config.kms_key_arn #=> String
# resp.status #=> String
# resp.creation_time #=> Time
# resp.last_modification_time #=> Time
#
# @see http://docs.aws.amazon.com/goto/WebAPI/forecast-2018-06-26/DescribeDataset AWS API Documentation
#
# @overload describe_dataset(params = {})
# @param [Hash] params ({})
def describe_dataset(params = {}, options = {})
req = build_request(:describe_dataset, params)
req.send_request(options)
end
# Describes a dataset group created using the CreateDatasetGroup
# operation.
#
# In addition to listing the parameters provided in the
# `CreateDatasetGroup` request, this operation includes the following
# properties:
#
# * `DatasetArns` - The datasets belonging to the group.
#
# * `CreationTime`
#
# * `LastModificationTime`
#
# * `Status`
#
# @option params [required, String] :dataset_group_arn
# The Amazon Resource Name (ARN) of the dataset group.
#
# @return [Types::DescribeDatasetGroupResponse] Returns a {Seahorse::Client::Response response} object which responds to the following methods:
#
# * {Types::DescribeDatasetGroupResponse#dataset_group_name #dataset_group_name} => String
# * {Types::DescribeDatasetGroupResponse#dataset_group_arn #dataset_group_arn} => String
# * {Types::DescribeDatasetGroupResponse#dataset_arns #dataset_arns} => Array<String>
# * {Types::DescribeDatasetGroupResponse#domain #domain} => String
# * {Types::DescribeDatasetGroupResponse#status #status} => String
# * {Types::DescribeDatasetGroupResponse#creation_time #creation_time} => Time
# * {Types::DescribeDatasetGroupResponse#last_modification_time #last_modification_time} => Time
#
# @example Request syntax with placeholder values
#
# resp = client.describe_dataset_group({
# dataset_group_arn: "Arn", # required
# })
#
# @example Response structure
#
# resp.dataset_group_name #=> String
# resp.dataset_group_arn #=> String
# resp.dataset_arns #=> Array
# resp.dataset_arns[0] #=> String
# resp.domain #=> String, one of "RETAIL", "CUSTOM", "INVENTORY_PLANNING", "EC2_CAPACITY", "WORK_FORCE", "WEB_TRAFFIC", "METRICS"
# resp.status #=> String
# resp.creation_time #=> Time
# resp.last_modification_time #=> Time
#
# @see http://docs.aws.amazon.com/goto/WebAPI/forecast-2018-06-26/DescribeDatasetGroup AWS API Documentation
#
# @overload describe_dataset_group(params = {})
# @param [Hash] params ({})
def describe_dataset_group(params = {}, options = {})
req = build_request(:describe_dataset_group, params)
req.send_request(options)
end
# Describes a dataset import job created using the
# CreateDatasetImportJob operation.
#
# In addition to listing the parameters provided in the
# `CreateDatasetImportJob` request, this operation includes the
# following properties:
#
# * `CreationTime`
#
# * `LastModificationTime`
#
# * `DataSize`
#
# * `FieldStatistics`
#
# * `Status`
#
# * `Message` - If an error occurred, information about the error.
#
# @option params [required, String] :dataset_import_job_arn
# The Amazon Resource Name (ARN) of the dataset import job.
#
# @return [Types::DescribeDatasetImportJobResponse] Returns a {Seahorse::Client::Response response} object which responds to the following methods:
#
# * {Types::DescribeDatasetImportJobResponse#dataset_import_job_name #dataset_import_job_name} => String
# * {Types::DescribeDatasetImportJobResponse#dataset_import_job_arn #dataset_import_job_arn} => String
# * {Types::DescribeDatasetImportJobResponse#dataset_arn #dataset_arn} => String
# * {Types::DescribeDatasetImportJobResponse#timestamp_format #timestamp_format} => String
# * {Types::DescribeDatasetImportJobResponse#data_source #data_source} => Types::DataSource
# * {Types::DescribeDatasetImportJobResponse#field_statistics #field_statistics} => Hash<String,Types::Statistics>
# * {Types::DescribeDatasetImportJobResponse#data_size #data_size} => Float
# * {Types::DescribeDatasetImportJobResponse#status #status} => String
# * {Types::DescribeDatasetImportJobResponse#message #message} => String
# * {Types::DescribeDatasetImportJobResponse#creation_time #creation_time} => Time
# * {Types::DescribeDatasetImportJobResponse#last_modification_time #last_modification_time} => Time
#
# @example Request syntax with placeholder values
#
# resp = client.describe_dataset_import_job({
# dataset_import_job_arn: "Arn", # required
# })
#
# @example Response structure
#
# resp.dataset_import_job_name #=> String
# resp.dataset_import_job_arn #=> String
# resp.dataset_arn #=> String
# resp.timestamp_format #=> String
# resp.data_source.s3_config.path #=> String
# resp.data_source.s3_config.role_arn #=> String
# resp.data_source.s3_config.kms_key_arn #=> String
# resp.field_statistics #=> Hash
# resp.field_statistics["String"].count #=> Integer
# resp.field_statistics["String"].count_distinct #=> Integer
# resp.field_statistics["String"].count_null #=> Integer
# resp.field_statistics["String"].count_nan #=> Integer
# resp.field_statistics["String"].min #=> String
# resp.field_statistics["String"].max #=> String
# resp.field_statistics["String"].avg #=> Float
# resp.field_statistics["String"].stddev #=> Float
# resp.data_size #=> Float
# resp.status #=> String
# resp.message #=> String
# resp.creation_time #=> Time
# resp.last_modification_time #=> Time
#
# @see http://docs.aws.amazon.com/goto/WebAPI/forecast-2018-06-26/DescribeDatasetImportJob AWS API Documentation
#
# @overload describe_dataset_import_job(params = {})
# @param [Hash] params ({})
def describe_dataset_import_job(params = {}, options = {})
req = build_request(:describe_dataset_import_job, params)
req.send_request(options)
end
# Describes a forecast created using the CreateForecast operation.
#
# In addition to listing the properties provided in the `CreateForecast`
# request, this operation lists the following properties:
#
# * `DatasetGroupArn` - The dataset group that provided the training
# data.
#
# * `CreationTime`
#
# * `LastModificationTime`
#
# * `Status`
#
# * `Message` - If an error occurred, information about the error.
#
# @option params [required, String] :forecast_arn
# The Amazon Resource Name (ARN) of the forecast.
#
# @return [Types::DescribeForecastResponse] Returns a {Seahorse::Client::Response response} object which responds to the following methods:
#
# * {Types::DescribeForecastResponse#forecast_arn #forecast_arn} => String
# * {Types::DescribeForecastResponse#forecast_name #forecast_name} => String
# * {Types::DescribeForecastResponse#forecast_types #forecast_types} => Array<String>
# * {Types::DescribeForecastResponse#predictor_arn #predictor_arn} => String
# * {Types::DescribeForecastResponse#dataset_group_arn #dataset_group_arn} => String
# * {Types::DescribeForecastResponse#status #status} => String
# * {Types::DescribeForecastResponse#message #message} => String
# * {Types::DescribeForecastResponse#creation_time #creation_time} => Time
# * {Types::DescribeForecastResponse#last_modification_time #last_modification_time} => Time
#
# @example Request syntax with placeholder values
#
# resp = client.describe_forecast({
# forecast_arn: "Arn", # required
# })
#
# @example Response structure
#
# resp.forecast_arn #=> String
# resp.forecast_name #=> String
# resp.forecast_types #=> Array
# resp.forecast_types[0] #=> String
# resp.predictor_arn #=> String
# resp.dataset_group_arn #=> String
# resp.status #=> String
# resp.message #=> String
# resp.creation_time #=> Time
# resp.last_modification_time #=> Time
#
# @see http://docs.aws.amazon.com/goto/WebAPI/forecast-2018-06-26/DescribeForecast AWS API Documentation
#
# @overload describe_forecast(params = {})
# @param [Hash] params ({})
def describe_forecast(params = {}, options = {})
req = build_request(:describe_forecast, params)
req.send_request(options)
end
# Describes a forecast export job created using the
# CreateForecastExportJob operation.
#
# In addition to listing the properties provided by the user in the
# `CreateForecastExportJob` request, this operation lists the following
# properties:
#
# * `CreationTime`
#
# * `LastModificationTime`
#
# * `Status`
#
# * `Message` - If an error occurred, information about the error.
#
# @option params [required, String] :forecast_export_job_arn
# The Amazon Resource Name (ARN) of the forecast export job.
#
# @return [Types::DescribeForecastExportJobResponse] Returns a {Seahorse::Client::Response response} object which responds to the following methods:
#
# * {Types::DescribeForecastExportJobResponse#forecast_export_job_arn #forecast_export_job_arn} => String
# * {Types::DescribeForecastExportJobResponse#forecast_export_job_name #forecast_export_job_name} => String
# * {Types::DescribeForecastExportJobResponse#forecast_arn #forecast_arn} => String
# * {Types::DescribeForecastExportJobResponse#destination #destination} => Types::DataDestination
# * {Types::DescribeForecastExportJobResponse#message #message} => String
# * {Types::DescribeForecastExportJobResponse#status #status} => String
# * {Types::DescribeForecastExportJobResponse#creation_time #creation_time} => Time
# * {Types::DescribeForecastExportJobResponse#last_modification_time #last_modification_time} => Time
#
# @example Request syntax with placeholder values
#
# resp = client.describe_forecast_export_job({
# forecast_export_job_arn: "Arn", # required
# })
#
# @example Response structure
#
# resp.forecast_export_job_arn #=> String
# resp.forecast_export_job_name #=> String
# resp.forecast_arn #=> String
# resp.destination.s3_config.path #=> String
# resp.destination.s3_config.role_arn #=> String
# resp.destination.s3_config.kms_key_arn #=> String
# resp.message #=> String
# resp.status #=> String
# resp.creation_time #=> Time
# resp.last_modification_time #=> Time
#
# @see http://docs.aws.amazon.com/goto/WebAPI/forecast-2018-06-26/DescribeForecastExportJob AWS API Documentation
#
# @overload describe_forecast_export_job(params = {})
# @param [Hash] params ({})
def describe_forecast_export_job(params = {}, options = {})
req = build_request(:describe_forecast_export_job, params)
req.send_request(options)
end
# Describes a predictor created using the CreatePredictor operation.
#
# In addition to listing the properties provided in the
# `CreatePredictor` request, this operation lists the following
# properties:
#
# * `DatasetImportJobArns` - The dataset import jobs used to import
# training data.
#
# * `AutoMLAlgorithmArns` - If AutoML is performed, the algorithms that
# were evaluated.
#
# * `CreationTime`
#
# * `LastModificationTime`
#
# * `Status`
#
# * `Message` - If an error occurred, information about the error.
#
# @option params [required, String] :predictor_arn
# The Amazon Resource Name (ARN) of the predictor that you want
# information about.
#
# @return [Types::DescribePredictorResponse] Returns a {Seahorse::Client::Response response} object which responds to the following methods:
#
# * {Types::DescribePredictorResponse#predictor_arn #predictor_arn} => String
# * {Types::DescribePredictorResponse#predictor_name #predictor_name} => String
# * {Types::DescribePredictorResponse#algorithm_arn #algorithm_arn} => String
# * {Types::DescribePredictorResponse#forecast_horizon #forecast_horizon} => Integer
# * {Types::DescribePredictorResponse#perform_auto_ml #perform_auto_ml} => Boolean
# * {Types::DescribePredictorResponse#perform_hpo #perform_hpo} => Boolean
# * {Types::DescribePredictorResponse#training_parameters #training_parameters} => Hash<String,String>
# * {Types::DescribePredictorResponse#evaluation_parameters #evaluation_parameters} => Types::EvaluationParameters
# * {Types::DescribePredictorResponse#hpo_config #hpo_config} => Types::HyperParameterTuningJobConfig
# * {Types::DescribePredictorResponse#input_data_config #input_data_config} => Types::InputDataConfig
# * {Types::DescribePredictorResponse#featurization_config #featurization_config} => Types::FeaturizationConfig
# * {Types::DescribePredictorResponse#encryption_config #encryption_config} => Types::EncryptionConfig
# * {Types::DescribePredictorResponse#predictor_execution_details #predictor_execution_details} => Types::PredictorExecutionDetails
# * {Types::DescribePredictorResponse#dataset_import_job_arns #dataset_import_job_arns} => Array<String>
# * {Types::DescribePredictorResponse#auto_ml_algorithm_arns #auto_ml_algorithm_arns} => Array<String>
# * {Types::DescribePredictorResponse#status #status} => String
# * {Types::DescribePredictorResponse#message #message} => String
# * {Types::DescribePredictorResponse#creation_time #creation_time} => Time
# * {Types::DescribePredictorResponse#last_modification_time #last_modification_time} => Time
#
# @example Request syntax with placeholder values
#
# resp = client.describe_predictor({
# predictor_arn: "Arn", # required
# })
#
# @example Response structure
#
# resp.predictor_arn #=> String
# resp.predictor_name #=> String
# resp.algorithm_arn #=> String
# resp.forecast_horizon #=> Integer
# resp.perform_auto_ml #=> Boolean
# resp.perform_hpo #=> Boolean
# resp.training_parameters #=> Hash
# resp.training_parameters["ParameterKey"] #=> String
# resp.evaluation_parameters.number_of_backtest_windows #=> Integer
# resp.evaluation_parameters.back_test_window_offset #=> Integer
# resp.hpo_config.parameter_ranges.categorical_parameter_ranges #=> Array
# resp.hpo_config.parameter_ranges.categorical_parameter_ranges[0].name #=> String
# resp.hpo_config.parameter_ranges.categorical_parameter_ranges[0].values #=> Array
# resp.hpo_config.parameter_ranges.categorical_parameter_ranges[0].values[0] #=> String
# resp.hpo_config.parameter_ranges.continuous_parameter_ranges #=> Array
# resp.hpo_config.parameter_ranges.continuous_parameter_ranges[0].name #=> String
# resp.hpo_config.parameter_ranges.continuous_parameter_ranges[0].max_value #=> Float
# resp.hpo_config.parameter_ranges.continuous_parameter_ranges[0].min_value #=> Float
# resp.hpo_config.parameter_ranges.continuous_parameter_ranges[0].scaling_type #=> String, one of "Auto", "Linear", "Logarithmic", "ReverseLogarithmic"
# resp.hpo_config.parameter_ranges.integer_parameter_ranges #=> Array
# resp.hpo_config.parameter_ranges.integer_parameter_ranges[0].name #=> String
# resp.hpo_config.parameter_ranges.integer_parameter_ranges[0].max_value #=> Integer
# resp.hpo_config.parameter_ranges.integer_parameter_ranges[0].min_value #=> Integer
# resp.hpo_config.parameter_ranges.integer_parameter_ranges[0].scaling_type #=> String, one of "Auto", "Linear", "Logarithmic", "ReverseLogarithmic"
# resp.input_data_config.dataset_group_arn #=> String
# resp.input_data_config.supplementary_features #=> Array
# resp.input_data_config.supplementary_features[0].name #=> String
# resp.input_data_config.supplementary_features[0].value #=> String
# resp.featurization_config.forecast_frequency #=> String
# resp.featurization_config.forecast_dimensions #=> Array
# resp.featurization_config.forecast_dimensions[0] #=> String
# resp.featurization_config.featurizations #=> Array
# resp.featurization_config.featurizations[0].attribute_name #=> String
# resp.featurization_config.featurizations[0].featurization_pipeline #=> Array
# resp.featurization_config.featurizations[0].featurization_pipeline[0].featurization_method_name #=> String, one of "filling"
# resp.featurization_config.featurizations[0].featurization_pipeline[0].featurization_method_parameters #=> Hash
# resp.featurization_config.featurizations[0].featurization_pipeline[0].featurization_method_parameters["ParameterKey"] #=> String
# resp.encryption_config.role_arn #=> String
# resp.encryption_config.kms_key_arn #=> String
# resp.predictor_execution_details.predictor_executions #=> Array
# resp.predictor_execution_details.predictor_executions[0].algorithm_arn #=> String
# resp.predictor_execution_details.predictor_executions[0].test_windows #=> Array
# resp.predictor_execution_details.predictor_executions[0].test_windows[0].test_window_start #=> Time
# resp.predictor_execution_details.predictor_executions[0].test_windows[0].test_window_end #=> Time
# resp.predictor_execution_details.predictor_executions[0].test_windows[0].status #=> String
# resp.predictor_execution_details.predictor_executions[0].test_windows[0].message #=> String
# resp.dataset_import_job_arns #=> Array
# resp.dataset_import_job_arns[0] #=> String
# resp.auto_ml_algorithm_arns #=> Array
# resp.auto_ml_algorithm_arns[0] #=> String
# resp.status #=> String
# resp.message #=> String
# resp.creation_time #=> Time
# resp.last_modification_time #=> Time
#
# @see http://docs.aws.amazon.com/goto/WebAPI/forecast-2018-06-26/DescribePredictor AWS API Documentation
#
# @overload describe_predictor(params = {})
# @param [Hash] params ({})
def describe_predictor(params = {}, options = {})
req = build_request(:describe_predictor, params)
req.send_request(options)
end
# Provides metrics on the accuracy of the models that were trained by
# the CreatePredictor operation. Use metrics to see how well the model
# performed and to decide whether to use the predictor to generate a
# forecast. For more information, see metrics.
#
# This operation generates metrics for each backtest window that was
# evaluated. The number of backtest windows (`NumberOfBacktestWindows`)
# is specified using the EvaluationParameters object, which is
# optionally included in the `CreatePredictor` request. If
# `NumberOfBacktestWindows` isn't specified, the number defaults to
# one.
#
# The parameters of the `filling` method determine which items
# contribute to the metrics. If you want all items to contribute,
# specify `zero`. If you want only those items that have complete data
# in the range being evaluated to contribute, specify `nan`. For more
# information, see FeaturizationMethod.
#
# Before you can get accuracy metrics, the `Status` of the predictor
# must be `ACTIVE`, signifying that training has completed. To get the
# status, use the DescribePredictor operation.
#
#
#
# @option params [required, String] :predictor_arn
# The Amazon Resource Name (ARN) of the predictor to get metrics for.
#
# @return [Types::GetAccuracyMetricsResponse] Returns a {Seahorse::Client::Response response} object which responds to the following methods:
#
# * {Types::GetAccuracyMetricsResponse#predictor_evaluation_results #predictor_evaluation_results} => Array<Types::EvaluationResult>
#
# @example Request syntax with placeholder values
#
# resp = client.get_accuracy_metrics({
# predictor_arn: "Arn", # required
# })
#
# @example Response structure
#
# resp.predictor_evaluation_results #=> Array
# resp.predictor_evaluation_results[0].algorithm_arn #=> String
# resp.predictor_evaluation_results[0].test_windows #=> Array
# resp.predictor_evaluation_results[0].test_windows[0].test_window_start #=> Time
# resp.predictor_evaluation_results[0].test_windows[0].test_window_end #=> Time
# resp.predictor_evaluation_results[0].test_windows[0].item_count #=> Integer
# resp.predictor_evaluation_results[0].test_windows[0].evaluation_type #=> String, one of "SUMMARY", "COMPUTED"
# resp.predictor_evaluation_results[0].test_windows[0].metrics.rmse #=> Float
# resp.predictor_evaluation_results[0].test_windows[0].metrics.weighted_quantile_losses #=> Array
# resp.predictor_evaluation_results[0].test_windows[0].metrics.weighted_quantile_losses[0].quantile #=> Float
# resp.predictor_evaluation_results[0].test_windows[0].metrics.weighted_quantile_losses[0].loss_value #=> Float
#
# @see http://docs.aws.amazon.com/goto/WebAPI/forecast-2018-06-26/GetAccuracyMetrics AWS API Documentation
#
# @overload get_accuracy_metrics(params = {})
# @param [Hash] params ({})
def get_accuracy_metrics(params = {}, options = {})
req = build_request(:get_accuracy_metrics, params)
req.send_request(options)
end
# Returns a list of dataset groups created using the CreateDatasetGroup
# operation. For each dataset group, this operation returns a summary of
# its properties, including its Amazon Resource Name (ARN). You can
# retrieve the complete set of properties by using the dataset group ARN
# with the DescribeDatasetGroup operation.
#
# @option params [String] :next_token
# If the result of the previous request was truncated, the response
# includes a `NextToken`. To retrieve the next set of results, use the
# token in the next request. Tokens expire after 24 hours.
#
# @option params [Integer] :max_results
# The number of items to return in the response.
#
# @return [Types::ListDatasetGroupsResponse] Returns a {Seahorse::Client::Response response} object which responds to the following methods:
#
# * {Types::ListDatasetGroupsResponse#dataset_groups #dataset_groups} => Array<Types::DatasetGroupSummary>
# * {Types::ListDatasetGroupsResponse#next_token #next_token} => String
#
# @example Request syntax with placeholder values
#
# resp = client.list_dataset_groups({
# next_token: "NextToken",
# max_results: 1,
# })
#
# @example Response structure
#
# resp.dataset_groups #=> Array
# resp.dataset_groups[0].dataset_group_arn #=> String
# resp.dataset_groups[0].dataset_group_name #=> String
# resp.dataset_groups[0].creation_time #=> Time
# resp.dataset_groups[0].last_modification_time #=> Time
# resp.next_token #=> String
#
# @see http://docs.aws.amazon.com/goto/WebAPI/forecast-2018-06-26/ListDatasetGroups AWS API Documentation
#
# @overload list_dataset_groups(params = {})
# @param [Hash] params ({})
def list_dataset_groups(params = {}, options = {})
req = build_request(:list_dataset_groups, params)
req.send_request(options)
end
# Returns a list of dataset import jobs created using the
# CreateDatasetImportJob operation. For each import job, this operation
# returns a summary of its properties, including its Amazon Resource
# Name (ARN). You can retrieve the complete set of properties by using
# the ARN with the DescribeDatasetImportJob operation. You can filter
# the list by providing an array of Filter objects.
#
# @option params [String] :next_token
# If the result of the previous request was truncated, the response
# includes a `NextToken`. To retrieve the next set of results, use the
# token in the next request. Tokens expire after 24 hours.
#
# @option params [Integer] :max_results
# The number of items to return in the response.
#
# @option params [Array] :filters
# An array of filters. For each filter, you provide a condition and a
# match statement. The condition is either `IS` or `IS_NOT`, which
# specifies whether to include or exclude the datasets that match the
# statement from the list, respectively. The match statement consists of
# a key and a value.
#
# **Filter properties**
#
# * `Condition` - The condition to apply. Valid values are `IS` and
# `IS_NOT`. To include the datasets that match the statement, specify
# `IS`. To exclude matching datasets, specify `IS_NOT`.
#
# * `Key` - The name of the parameter to filter on. Valid values are
# `DatasetArn` and `Status`.
#
# * `Value` - The value to match.
#
# For example, to list all dataset import jobs whose status is ACTIVE,
# you specify the following filter:
#
# `"Filters": [ \{ "Condition": "IS", "Key": "Status", "Value": "ACTIVE"
# \} ]`
#
# @return [Types::ListDatasetImportJobsResponse] Returns a {Seahorse::Client::Response response} object which responds to the following methods:
#
# * {Types::ListDatasetImportJobsResponse#dataset_import_jobs #dataset_import_jobs} => Array<Types::DatasetImportJobSummary>
# * {Types::ListDatasetImportJobsResponse#next_token #next_token} => String
#
# @example Request syntax with placeholder values
#
# resp = client.list_dataset_import_jobs({
# next_token: "NextToken",
# max_results: 1,
# filters: [
# {
# key: "String", # required
# value: "Arn", # required
# condition: "IS", # required, accepts IS, IS_NOT
# },
# ],
# })
#
# @example Response structure
#
# resp.dataset_import_jobs #=> Array
# resp.dataset_import_jobs[0].dataset_import_job_arn #=> String
# resp.dataset_import_jobs[0].dataset_import_job_name #=> String
# resp.dataset_import_jobs[0].data_source.s3_config.path #=> String
# resp.dataset_import_jobs[0].data_source.s3_config.role_arn #=> String
# resp.dataset_import_jobs[0].data_source.s3_config.kms_key_arn #=> String
# resp.dataset_import_jobs[0].status #=> String
# resp.dataset_import_jobs[0].message #=> String
# resp.dataset_import_jobs[0].creation_time #=> Time
# resp.dataset_import_jobs[0].last_modification_time #=> Time
# resp.next_token #=> String
#
# @see http://docs.aws.amazon.com/goto/WebAPI/forecast-2018-06-26/ListDatasetImportJobs AWS API Documentation
#
# @overload list_dataset_import_jobs(params = {})
# @param [Hash] params ({})
def list_dataset_import_jobs(params = {}, options = {})
req = build_request(:list_dataset_import_jobs, params)
req.send_request(options)
end
# Returns a list of datasets created using the CreateDataset operation.
# For each dataset, a summary of its properties, including its Amazon
# Resource Name (ARN), is returned. To retrieve the complete set of
# properties, use the ARN with the DescribeDataset operation.
#
# @option params [String] :next_token
# If the result of the previous request was truncated, the response
# includes a `NextToken`. To retrieve the next set of results, use the
# token in the next request. Tokens expire after 24 hours.
#
# @option params [Integer] :max_results
# The number of items to return in the response.
#
# @return [Types::ListDatasetsResponse] Returns a {Seahorse::Client::Response response} object which responds to the following methods:
#
# * {Types::ListDatasetsResponse#datasets #datasets} => Array<Types::DatasetSummary>
# * {Types::ListDatasetsResponse#next_token #next_token} => String
#
# @example Request syntax with placeholder values
#
# resp = client.list_datasets({
# next_token: "NextToken",
# max_results: 1,
# })
#
# @example Response structure
#
# resp.datasets #=> Array
# resp.datasets[0].dataset_arn #=> String
# resp.datasets[0].dataset_name #=> String
# resp.datasets[0].dataset_type #=> String, one of "TARGET_TIME_SERIES", "RELATED_TIME_SERIES", "ITEM_METADATA"
# resp.datasets[0].domain #=> String, one of "RETAIL", "CUSTOM", "INVENTORY_PLANNING", "EC2_CAPACITY", "WORK_FORCE", "WEB_TRAFFIC", "METRICS"
# resp.datasets[0].creation_time #=> Time
# resp.datasets[0].last_modification_time #=> Time
# resp.next_token #=> String
#
# @see http://docs.aws.amazon.com/goto/WebAPI/forecast-2018-06-26/ListDatasets AWS API Documentation
#
# @overload list_datasets(params = {})
# @param [Hash] params ({})
def list_datasets(params = {}, options = {})
req = build_request(:list_datasets, params)
req.send_request(options)
end
# Returns a list of forecast export jobs created using the
# CreateForecastExportJob operation. For each forecast export job, this
# operation returns a summary of its properties, including its Amazon
# Resource Name (ARN). To retrieve the complete set of properties, use
# the ARN with the DescribeForecastExportJob operation. You can filter
# the list using an array of Filter objects.
#
# @option params [String] :next_token
# If the result of the previous request was truncated, the response
# includes a `NextToken`. To retrieve the next set of results, use the
# token in the next request. Tokens expire after 24 hours.
#
# @option params [Integer] :max_results
# The number of items to return in the response.
#
# @option params [Array] :filters
# An array of filters. For each filter, you provide a condition and a
# match statement. The condition is either `IS` or `IS_NOT`, which
# specifies whether to include or exclude the forecast export jobs that
# match the statement from the list, respectively. The match statement
# consists of a key and a value.
#
# **Filter properties**
#
# * `Condition` - The condition to apply. Valid values are `IS` and
# `IS_NOT`. To include the forecast export jobs that match the
# statement, specify `IS`. To exclude matching forecast export jobs,
# specify `IS_NOT`.
#
# * `Key` - The name of the parameter to filter on. Valid values are
# `ForecastArn` and `Status`.
#
# * `Value` - The value to match.
#
# For example, to list all jobs that export a forecast named
# *electricityforecast*, specify the following filter:
#
# `"Filters": [ \{ "Condition": "IS", "Key": "ForecastArn", "Value":
# "arn:aws:forecast:us-west-2::forecast/electricityforecast" \}
# ]`
#
# @return [Types::ListForecastExportJobsResponse] Returns a {Seahorse::Client::Response response} object which responds to the following methods:
#
# * {Types::ListForecastExportJobsResponse#forecast_export_jobs #forecast_export_jobs} => Array<Types::ForecastExportJobSummary>
# * {Types::ListForecastExportJobsResponse#next_token #next_token} => String
#
# @example Request syntax with placeholder values
#
# resp = client.list_forecast_export_jobs({
# next_token: "NextToken",
# max_results: 1,
# filters: [
# {
# key: "String", # required
# value: "Arn", # required
# condition: "IS", # required, accepts IS, IS_NOT
# },
# ],
# })
#
# @example Response structure
#
# resp.forecast_export_jobs #=> Array
# resp.forecast_export_jobs[0].forecast_export_job_arn #=> String
# resp.forecast_export_jobs[0].forecast_export_job_name #=> String
# resp.forecast_export_jobs[0].destination.s3_config.path #=> String
# resp.forecast_export_jobs[0].destination.s3_config.role_arn #=> String
# resp.forecast_export_jobs[0].destination.s3_config.kms_key_arn #=> String
# resp.forecast_export_jobs[0].status #=> String
# resp.forecast_export_jobs[0].message #=> String
# resp.forecast_export_jobs[0].creation_time #=> Time
# resp.forecast_export_jobs[0].last_modification_time #=> Time
# resp.next_token #=> String
#
# @see http://docs.aws.amazon.com/goto/WebAPI/forecast-2018-06-26/ListForecastExportJobs AWS API Documentation
#
# @overload list_forecast_export_jobs(params = {})
# @param [Hash] params ({})
def list_forecast_export_jobs(params = {}, options = {})
req = build_request(:list_forecast_export_jobs, params)
req.send_request(options)
end
# Returns a list of forecasts created using the CreateForecast
# operation. For each forecast, this operation returns a summary of its
# properties, including its Amazon Resource Name (ARN). To retrieve the
# complete set of properties, specify the ARN with the DescribeForecast
# operation. You can filter the list using an array of Filter objects.
#
# @option params [String] :next_token
# If the result of the previous request was truncated, the response
# includes a `NextToken`. To retrieve the next set of results, use the
# token in the next request. Tokens expire after 24 hours.
#
# @option params [Integer] :max_results
# The number of items to return in the response.
#
# @option params [Array] :filters
# An array of filters. For each filter, you provide a condition and a
# match statement. The condition is either `IS` or `IS_NOT`, which
# specifies whether to include or exclude the forecasts that match the
# statement from the list, respectively. The match statement consists of
# a key and a value.
#
# **Filter properties**
#
# * `Condition` - The condition to apply. Valid values are `IS` and
# `IS_NOT`. To include the forecasts that match the statement, specify
# `IS`. To exclude matching forecasts, specify `IS_NOT`.
#
# * `Key` - The name of the parameter to filter on. Valid values are
# `DatasetGroupArn`, `PredictorArn`, and `Status`.
#
# * `Value` - The value to match.
#
# For example, to list all forecasts whose status is not ACTIVE, you
# would specify:
#
# `"Filters": [ \{ "Condition": "IS_NOT", "Key": "Status", "Value":
# "ACTIVE" \} ]`
#
# @return [Types::ListForecastsResponse] Returns a {Seahorse::Client::Response response} object which responds to the following methods:
#
# * {Types::ListForecastsResponse#forecasts #forecasts} => Array<Types::ForecastSummary>
# * {Types::ListForecastsResponse#next_token #next_token} => String
#
# @example Request syntax with placeholder values
#
# resp = client.list_forecasts({
# next_token: "NextToken",
# max_results: 1,
# filters: [
# {
# key: "String", # required
# value: "Arn", # required
# condition: "IS", # required, accepts IS, IS_NOT
# },
# ],
# })
#
# @example Response structure
#
# resp.forecasts #=> Array
# resp.forecasts[0].forecast_arn #=> String
# resp.forecasts[0].forecast_name #=> String
# resp.forecasts[0].predictor_arn #=> String
# resp.forecasts[0].dataset_group_arn #=> String
# resp.forecasts[0].status #=> String
# resp.forecasts[0].message #=> String
# resp.forecasts[0].creation_time #=> Time
# resp.forecasts[0].last_modification_time #=> Time
# resp.next_token #=> String
#
# @see http://docs.aws.amazon.com/goto/WebAPI/forecast-2018-06-26/ListForecasts AWS API Documentation
#
# @overload list_forecasts(params = {})
# @param [Hash] params ({})
def list_forecasts(params = {}, options = {})
req = build_request(:list_forecasts, params)
req.send_request(options)
end
# Returns a list of predictors created using the CreatePredictor
# operation. For each predictor, this operation returns a summary of its
# properties, including its Amazon Resource Name (ARN). You can retrieve
# the complete set of properties by using the ARN with the
# DescribePredictor operation. You can filter the list using an array of
# Filter objects.
#
# @option params [String] :next_token
# If the result of the previous request was truncated, the response
# includes a `NextToken`. To retrieve the next set of results, use the
# token in the next request. Tokens expire after 24 hours.
#
# @option params [Integer] :max_results
# The number of items to return in the response.
#
# @option params [Array] :filters
# An array of filters. For each filter, you provide a condition and a
# match statement. The condition is either `IS` or `IS_NOT`, which
# specifies whether to include or exclude the predictors that match the
# statement from the list, respectively. The match statement consists of
# a key and a value.
#
# **Filter properties**
#
# * `Condition` - The condition to apply. Valid values are `IS` and
# `IS_NOT`. To include the predictors that match the statement,
# specify `IS`. To exclude matching predictors, specify `IS_NOT`.
#
# * `Key` - The name of the parameter to filter on. Valid values are
# `DatasetGroupArn` and `Status`.
#
# * `Value` - The value to match.
#
# For example, to list all predictors whose status is ACTIVE, you would
# specify:
#
# `"Filters": [ \{ "Condition": "IS", "Key": "Status", "Value": "ACTIVE"
# \} ]`
#
# @return [Types::ListPredictorsResponse] Returns a {Seahorse::Client::Response response} object which responds to the following methods:
#
# * {Types::ListPredictorsResponse#predictors #predictors} => Array<Types::PredictorSummary>
# * {Types::ListPredictorsResponse#next_token #next_token} => String
#
# @example Request syntax with placeholder values
#
# resp = client.list_predictors({
# next_token: "NextToken",
# max_results: 1,
# filters: [
# {
# key: "String", # required
# value: "Arn", # required
# condition: "IS", # required, accepts IS, IS_NOT
# },
# ],
# })
#
# @example Response structure
#
# resp.predictors #=> Array
# resp.predictors[0].predictor_arn #=> String
# resp.predictors[0].predictor_name #=> String
# resp.predictors[0].dataset_group_arn #=> String
# resp.predictors[0].status #=> String
# resp.predictors[0].message #=> String
# resp.predictors[0].creation_time #=> Time
# resp.predictors[0].last_modification_time #=> Time
# resp.next_token #=> String
#
# @see http://docs.aws.amazon.com/goto/WebAPI/forecast-2018-06-26/ListPredictors AWS API Documentation
#
# @overload list_predictors(params = {})
# @param [Hash] params ({})
def list_predictors(params = {}, options = {})
req = build_request(:list_predictors, params)
req.send_request(options)
end
# Replaces the datasets in a dataset group with the specified datasets.
#
# The `Status` of the dataset group must be `ACTIVE` before you can use
# the dataset group to create a predictor. Use the DescribeDatasetGroup
# operation to get the status.
#
#
#
# @option params [required, String] :dataset_group_arn
# The ARN of the dataset group.
#
# @option params [required, Array] :dataset_arns
# An array of the Amazon Resource Names (ARNs) of the datasets to add to
# the dataset group.
#
# @return [Struct] Returns an empty {Seahorse::Client::Response response}.
#
# @example Request syntax with placeholder values
#
# resp = client.update_dataset_group({
# dataset_group_arn: "Arn", # required
# dataset_arns: ["Arn"], # required
# })
#
# @see http://docs.aws.amazon.com/goto/WebAPI/forecast-2018-06-26/UpdateDatasetGroup AWS API Documentation
#
# @overload update_dataset_group(params = {})
# @param [Hash] params ({})
def update_dataset_group(params = {}, options = {})
req = build_request(:update_dataset_group, params)
req.send_request(options)
end
# @!endgroup
# @param params ({})
# @api private
def build_request(operation_name, params = {})
handlers = @handlers.for(operation_name)
context = Seahorse::Client::RequestContext.new(
operation_name: operation_name,
operation: config.api.operation(operation_name),
client: self,
params: params,
config: config)
context[:gem_name] = 'aws-sdk-forecastservice'
context[:gem_version] = '1.2.0'
Seahorse::Client::Request.new(handlers, context)
end
# @api private
# @deprecated
def waiter_names
[]
end
class << self
# @api private
attr_reader :identifier
# @api private
def errors_module
Errors
end
end
end
end