putdataframeanalytics

Documentation

Overview

Instantiates a data frame analytics job.

Index

• Variables
• type NewPutDataFrameAnalytics
  • func NewPutDataFrameAnalyticsFunc(tp elastictransport.Interface) NewPutDataFrameAnalytics
• type PutDataFrameAnalytics
  • func New(tp elastictransport.Interface) *PutDataFrameAnalytics
  • func (r PutDataFrameAnalytics) Do(ctx context.Context) (*Response, error)
  • func (r *PutDataFrameAnalytics) Header(key, value string) *PutDataFrameAnalytics
  • func (r *PutDataFrameAnalytics) HttpRequest(ctx context.Context) (*http.Request, error)
  • func (r *PutDataFrameAnalytics) Id(v string) *PutDataFrameAnalytics
  • func (r PutDataFrameAnalytics) Perform(ctx context.Context) (*http.Response, error)
  • func (r *PutDataFrameAnalytics) Raw(raw io.Reader) *PutDataFrameAnalytics
  • func (r *PutDataFrameAnalytics) Request(req *Request) *PutDataFrameAnalytics
• type Request
  • func NewRequest() *Request
  • func (r *Request) FromJSON(data string) (*Request, error)
• type Response
  • func NewResponse() *Response

Variables

var ErrBuildPath = errors.New("cannot build path, check for missing path parameters")

ErrBuildPath is returned in case of missing parameters within the build of the request.

Types

type NewPutDataFrameAnalytics

type NewPutDataFrameAnalytics func(id string) *PutDataFrameAnalytics

NewPutDataFrameAnalytics type alias for index.

func NewPutDataFrameAnalyticsFunc

func NewPutDataFrameAnalyticsFunc(tp elastictransport.Interface) NewPutDataFrameAnalytics

NewPutDataFrameAnalyticsFunc returns a new instance of PutDataFrameAnalytics with the provided transport. Used in the index of the library this allows to retrieve every apis in once place.

type PutDataFrameAnalytics

type PutDataFrameAnalytics struct {
	// contains filtered or unexported fields
}

func New

func New(tp elastictransport.Interface) *PutDataFrameAnalytics

Instantiates a data frame analytics job.

https://www.elastic.co/guide/en/elasticsearch/reference/{branch}/put-dfanalytics.html

func (PutDataFrameAnalytics) Do

func (r PutDataFrameAnalytics) Do(ctx context.Context) (*Response, error)

Do runs the request through the transport, handle the response and returns a putdataframeanalytics.Response

func (*PutDataFrameAnalytics) Header

func (r *PutDataFrameAnalytics) Header(key, value string) *PutDataFrameAnalytics

Header set a key, value pair in the PutDataFrameAnalytics headers map.

func (*PutDataFrameAnalytics) HttpRequest

func (r *PutDataFrameAnalytics) HttpRequest(ctx context.Context) (*http.Request, error)

HttpRequest returns the http.Request object built from the given parameters.

func (*PutDataFrameAnalytics) Id

func (r *PutDataFrameAnalytics) Id(v string) *PutDataFrameAnalytics

Id Identifier for the data frame analytics job. This identifier can contain lowercase alphanumeric characters (a-z and 0-9), hyphens, and underscores. It must start and end with alphanumeric characters. API Name: id

func (PutDataFrameAnalytics) Perform

func (r PutDataFrameAnalytics) Perform(ctx context.Context) (*http.Response, error)

Perform runs the http.Request through the provided transport and returns an http.Response.

func (*PutDataFrameAnalytics) Raw

func (r *PutDataFrameAnalytics) Raw(raw io.Reader) *PutDataFrameAnalytics

Raw takes a json payload as input which is then passed to the http.Request If specified Raw takes precedence on Request method.

func (*PutDataFrameAnalytics) Request

func (r *PutDataFrameAnalytics) Request(req *Request) *PutDataFrameAnalytics

Request allows to set the request property with the appropriate payload.

type Request

type Request struct {

	// AllowLazyStart Specifies whether this job can start when there is insufficient machine
	// learning node capacity for it to be immediately assigned to a node. If
	// set to `false` and a machine learning node with capacity to run the job
	// cannot be immediately found, the API returns an error. If set to `true`,
	// the API does not return an error; the job waits in the `starting` state
	// until sufficient machine learning node capacity is available. This
	// behavior is also affected by the cluster-wide
	// `xpack.ml.max_lazy_ml_nodes` setting.
	AllowLazyStart *bool `json:"allow_lazy_start,omitempty"`
	// Analysis The analysis configuration, which contains the information necessary to
	// perform one of the following types of analysis: classification, outlier
	// detection, or regression.
	Analysis types.DataframeAnalysisContainer `json:"analysis"`
	// AnalyzedFields Specifies `includes` and/or `excludes` patterns to select which fields
	// will be included in the analysis. The patterns specified in `excludes`
	// are applied last, therefore `excludes` takes precedence. In other words,
	// if the same field is specified in both `includes` and `excludes`, then
	// the field will not be included in the analysis. If `analyzed_fields` is
	// not set, only the relevant fields will be included. For example, all the
	// numeric fields for outlier detection.
	// The supported fields vary for each type of analysis. Outlier detection
	// requires numeric or `boolean` data to analyze. The algorithms don’t
	// support missing values therefore fields that have data types other than
	// numeric or boolean are ignored. Documents where included fields contain
	// missing values, null values, or an array are also ignored. Therefore the
	// `dest` index may contain documents that don’t have an outlier score.
	// Regression supports fields that are numeric, `boolean`, `text`,
	// `keyword`, and `ip` data types. It is also tolerant of missing values.
	// Fields that are supported are included in the analysis, other fields are
	// ignored. Documents where included fields contain an array with two or
	// more values are also ignored. Documents in the `dest` index that don’t
	// contain a results field are not included in the regression analysis.
	// Classification supports fields that are numeric, `boolean`, `text`,
	// `keyword`, and `ip` data types. It is also tolerant of missing values.
	// Fields that are supported are included in the analysis, other fields are
	// ignored. Documents where included fields contain an array with two or
	// more values are also ignored. Documents in the `dest` index that don’t
	// contain a results field are not included in the classification analysis.
	// Classification analysis can be improved by mapping ordinal variable
	// values to a single number. For example, in case of age ranges, you can
	// model the values as `0-14 = 0`, `15-24 = 1`, `25-34 = 2`, and so on.
	AnalyzedFields *types.DataframeAnalysisAnalyzedFields `json:"analyzed_fields,omitempty"`
	// Description A description of the job.
	Description *string `json:"description,omitempty"`
	// Dest The destination configuration.
	Dest    types.DataframeAnalyticsDestination `json:"dest"`
	Headers map[string][]string                 `json:"headers,omitempty"`
	// MaxNumThreads The maximum number of threads to be used by the analysis. Using more
	// threads may decrease the time necessary to complete the analysis at the
	// cost of using more CPU. Note that the process may use additional threads
	// for operational functionality other than the analysis itself.
	MaxNumThreads *int `json:"max_num_threads,omitempty"`
	// ModelMemoryLimit The approximate maximum amount of memory resources that are permitted for
	// analytical processing. If your `elasticsearch.yml` file contains an
	// `xpack.ml.max_model_memory_limit` setting, an error occurs when you try
	// to create data frame analytics jobs that have `model_memory_limit` values
	// greater than that setting.
	ModelMemoryLimit *string `json:"model_memory_limit,omitempty"`
	// Source The configuration of how to source the analysis data.
	Source  types.DataframeAnalyticsSource `json:"source"`
	Version *string                        `json:"version,omitempty"`
}

Request holds the request body struct for the package putdataframeanalytics

https://github.com/elastic/elasticsearch-specification/blob/1ad7fe36297b3a8e187b2259dedaf68a47bc236e/specification/ml/put_data_frame_analytics/MlPutDataFrameAnalyticsRequest.ts#L30-L139

func NewRequest

func NewRequest() *Request

NewRequest returns a Request

func (*Request) FromJSON

func (r *Request) FromJSON(data string) (*Request, error)

FromJSON allows to load an arbitrary json into the request structure

type Response

type Response struct {
	AllowLazyStart   bool                                   `json:"allow_lazy_start"`
	Analysis         types.DataframeAnalysisContainer       `json:"analysis"`
	AnalyzedFields   *types.DataframeAnalysisAnalyzedFields `json:"analyzed_fields,omitempty"`
	Authorization    *types.DataframeAnalyticsAuthorization `json:"authorization,omitempty"`
	CreateTime       int64                                  `json:"create_time"`
	Description      *string                                `json:"description,omitempty"`
	Dest             types.DataframeAnalyticsDestination    `json:"dest"`
	Id               string                                 `json:"id"`
	MaxNumThreads    int                                    `json:"max_num_threads"`
	ModelMemoryLimit string                                 `json:"model_memory_limit"`
	Source           types.DataframeAnalyticsSource         `json:"source"`
	Version          string                                 `json:"version"`
}

func NewResponse

func NewResponse() *Response

NewResponse returns a Response