Documentation
¶
Overview ¶
Instantiates a data frame analytics job.
Index ¶
- Variables
- type NewPutDataFrameAnalytics
- type 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
- type Response
Constants ¶
This section is empty.
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.
Functions ¶
This section is empty.
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 ¶
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 ¶
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
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"`
}