mirror of
https://github.com/VictoriaMetrics/VictoriaMetrics.git
synced 2024-12-15 08:23:34 +01:00
348 lines
10 KiB
Go
348 lines
10 KiB
Go
package opentsdb
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import (
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"bytes"
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"encoding/json"
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"fmt"
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"io/ioutil"
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"log"
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"net/http"
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"strings"
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"time"
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)
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// Retention objects contain meta data about what to query for our run
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type Retention struct {
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/*
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OpenTSDB has two levels of aggregation,
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First, we aggregate any un-mentioned tags into the last result
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Second, we aggregate into buckets over time
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To simulate this with config, we have
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FirstOrder (e.g. sum/avg/max/etc.)
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SecondOrder (e.g. sum/avg/max/etc.)
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AggTime (e.g. 1m/10m/1d/etc.)
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This will build into m=<FirstOrder>:<AggTime>-<SecondOrder>-none:
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Or an example: m=sum:1m-avg-none
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*/
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FirstOrder string
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SecondOrder string
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AggTime string
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// The actual ranges will will attempt to query (as offsets from now)
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QueryRanges []TimeRange
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}
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// RetentionMeta objects exist to pass smaller subsets (only one retention range) of a full Retention object around
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type RetentionMeta struct {
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FirstOrder string
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SecondOrder string
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AggTime string
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}
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// Client object holds general config about how queries should be performed
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type Client struct {
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Addr string
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// The meta query limit for series returned
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Limit int
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Retentions []Retention
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Filters []string
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Normalize bool
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}
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// Config contains fields required
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// for Client configuration
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type Config struct {
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Addr string
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Limit int
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Offset int64
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HardTS int64
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Retentions []string
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Filters []string
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Normalize bool
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MsecsTime bool
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}
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// TimeRange contains data about time ranges to query
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type TimeRange struct {
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Start int64
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End int64
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}
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// MetaResults contains return data from search series lookup queries
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type MetaResults struct {
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Type string `json:"type"`
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Results []Meta `json:"results"`
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//metric string
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//tags interface{}
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//limit int
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//time int
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//startIndex int
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//totalResults int
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}
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// Meta A meta object about a metric
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// only contain the tags/etc. and no data
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type Meta struct {
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//tsuid string
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Metric string `json:"metric"`
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Tags map[string]string `json:"tags"`
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}
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// Metric holds the time series data
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type Metric struct {
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Metric string
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Tags map[string]string
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Timestamps []int64
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Values []float64
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}
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// ExpressionOutput contains results from actual data queries
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type ExpressionOutput struct {
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Outputs []qoObj `json:"outputs"`
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Query interface{} `json:"query"`
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}
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// QoObj contains actual timeseries data from the returned data query
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type qoObj struct {
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ID string `json:"id"`
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Alias string `json:"alias"`
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Dps [][]float64 `json:"dps"`
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//dpsMeta interface{}
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//meta interface{}
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}
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// Expression objects format our data queries
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/*
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All of the following structs are to build a OpenTSDB expression object
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*/
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type Expression struct {
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Time timeObj `json:"time"`
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Filters []filterObj `json:"filters"`
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Metrics []metricObj `json:"metrics"`
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// this just needs to be an empty object, so the value doesn't matter
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Expressions []int `json:"expressions"`
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Outputs []outputObj `json:"outputs"`
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}
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type timeObj struct {
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Start int64 `json:"start"`
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End int64 `json:"end"`
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Aggregator string `json:"aggregator"`
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Downsampler dSObj `json:"downsampler"`
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}
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type dSObj struct {
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Interval string `json:"interval"`
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Aggregator string `json:"aggregator"`
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FillPolicy fillObj `json:"fillPolicy"`
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}
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type fillObj struct {
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// we'll always hard-code to NaN here, so we don't need value
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Policy string `json:"policy"`
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}
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type filterObj struct {
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Tags []tagObj `json:"tags"`
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ID string `json:"id"`
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}
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type tagObj struct {
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Type string `json:"type"`
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Tagk string `json:"tagk"`
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Filter string `json:"filter"`
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GroupBy bool `json:"groupBy"`
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}
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type metricObj struct {
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ID string `json:"id"`
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Metric string `json:"metric"`
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Filter string `json:"filter"`
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FillPolicy fillObj `json:"fillPolicy"`
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}
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type outputObj struct {
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ID string `json:"id"`
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Alias string `json:"alias"`
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}
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/* End expression object structs */
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var (
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exprOutput = outputObj{ID: "a", Alias: "query"}
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exprFillPolicy = fillObj{Policy: "nan"}
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)
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// FindMetrics discovers all metrics that OpenTSDB knows about (given a filter)
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// e.g. /api/suggest?type=metrics&q=system&max=100000
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func (c Client) FindMetrics(q string) ([]string, error) {
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resp, err := http.Get(q)
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if err != nil {
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return nil, fmt.Errorf("failed to send GET request to %q: %s", q, err)
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}
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if resp.StatusCode != 200 {
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return nil, fmt.Errorf("Bad return from OpenTSDB: %q: %v", resp.StatusCode, resp)
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}
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defer func() { _ = resp.Body.Close() }()
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body, err := ioutil.ReadAll(resp.Body)
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if err != nil {
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return nil, fmt.Errorf("could not retrieve metric data from %q: %s", q, err)
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}
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var metriclist []string
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err = json.Unmarshal(body, &metriclist)
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if err != nil {
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return nil, fmt.Errorf("failed to read response from %q: %s", q, err)
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}
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return metriclist, nil
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}
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// FindSeries discovers all series associated with a metric
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// e.g. /api/search/lookup?m=system.load5&limit=1000000
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func (c Client) FindSeries(metric string) ([]Meta, error) {
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q := fmt.Sprintf("%s/api/search/lookup?m=%s&limit=%d", c.Addr, metric, c.Limit)
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resp, err := http.Get(q)
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if err != nil {
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return nil, fmt.Errorf("failed to set GET request to %q: %s", q, err)
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}
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if resp.StatusCode != 200 {
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return nil, fmt.Errorf("Bad return from OpenTSDB: %q: %v", resp.StatusCode, resp)
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}
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defer func() { _ = resp.Body.Close() }()
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body, err := ioutil.ReadAll(resp.Body)
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if err != nil {
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return nil, fmt.Errorf("could not retrieve series data from %q: %s", q, err)
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}
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var results MetaResults
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err = json.Unmarshal(body, &results)
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if err != nil {
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return nil, fmt.Errorf("failed to read response from %q: %s", q, err)
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}
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return results.Results, nil
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}
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// GetData actually retrieves data for a series at a specified time range
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func (c Client) GetData(series Meta, rt RetentionMeta, start int64, end int64) (Metric, error) {
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/*
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Here we build the actual exp query we'll send to OpenTSDB
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This is comprised of a number of different settings. We hard-code
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a few to simplify the JSON object creation.
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There are examples queries available, so not too much detail here...
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*/
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expr := Expression{}
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expr.Outputs = []outputObj{exprOutput}
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expr.Metrics = append(expr.Metrics, metricObj{ID: "a", Metric: series.Metric,
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Filter: "f1", FillPolicy: exprFillPolicy})
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expr.Time = timeObj{Start: start, End: end, Aggregator: rt.FirstOrder,
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Downsampler: dSObj{Interval: rt.AggTime,
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Aggregator: rt.SecondOrder,
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FillPolicy: exprFillPolicy}}
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var TagList []tagObj
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for k, v := range series.Tags {
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/*
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every tag should be a literal_or because that's the closest to a full "==" that
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this endpoint allows for
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*/
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TagList = append(TagList, tagObj{Type: "literal_or", Tagk: k,
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Filter: v, GroupBy: true})
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}
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expr.Filters = append(expr.Filters, filterObj{ID: "f1", Tags: TagList})
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// "expressions" is required in the query object or we get a 5xx, so force it to exist
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expr.Expressions = make([]int, 0)
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inputData, err := json.Marshal(expr)
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if err != nil {
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return Metric{}, fmt.Errorf("failed to marshal query JSON %s", err)
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}
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q := fmt.Sprintf("%s/api/query/exp", c.Addr)
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resp, err := http.Post(q, "application/json", bytes.NewBuffer(inputData))
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if err != nil {
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return Metric{}, fmt.Errorf("failed to send GET request to %q: %s", q, err)
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}
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if resp.StatusCode != 200 {
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return Metric{}, fmt.Errorf("Bad return from OpenTSDB: %q: %v", resp.StatusCode, resp)
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}
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defer func() { _ = resp.Body.Close() }()
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body, err := ioutil.ReadAll(resp.Body)
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if err != nil {
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return Metric{}, fmt.Errorf("could not retrieve series data from %q: %s", q, err)
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}
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var output ExpressionOutput
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err = json.Unmarshal(body, &output)
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if err != nil {
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return Metric{}, fmt.Errorf("failed to unmarshal response from %q: %s", q, err)
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}
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if len(output.Outputs) < 1 {
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// no results returned...return an empty object without error
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return Metric{}, nil
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}
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data := Metric{}
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data.Metric = series.Metric
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data.Tags = series.Tags
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/*
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We evaluate data for correctness before formatting the actual values
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to skip a little bit of time if the series has invalid formatting
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First step is to enforce Prometheus' data model
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*/
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data, err = modifyData(data, c.Normalize)
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if err != nil {
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return Metric{}, fmt.Errorf("invalid series data from %q: %s", q, err)
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}
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/*
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Convert data from OpenTSDB's output format ([[ts,val],[ts,val]...])
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to VictoriaMetrics format: {"timestamps": [ts,ts,ts...], "values": [val,val,val...]}
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The nasty part here is that because an object in each array
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can be a float64, we have to initially cast _all_ objects that way
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then convert the timestamp back to something reasonable.
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*/
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for _, tsobj := range output.Outputs[0].Dps {
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data.Timestamps = append(data.Timestamps, int64(tsobj[0]))
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data.Values = append(data.Values, tsobj[1])
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}
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return data, nil
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}
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// NewClient creates and returns OpenTSDB client
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// configured with passed Config
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func NewClient(cfg Config) (*Client, error) {
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var retentions []Retention
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offsetPrint := int64(time.Now().Unix())
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if cfg.MsecsTime {
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// 1000000 == Nanoseconds -> Milliseconds difference
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offsetPrint = int64(time.Now().UnixNano() / 1000000)
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}
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if cfg.HardTS > 0 {
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/*
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"Hard" offsets are specific timestamps, rather than
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a relative number of days. To use them effectively
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we should subtract them from our default offset (Now)
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*/
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offsetPrint = offsetPrint - cfg.HardTS
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} else if cfg.Offset > 0 {
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/*
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Our "offset" is the number of days we should step
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back before starting to scan for data
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*/
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if cfg.MsecsTime {
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offsetPrint = offsetPrint - (cfg.Offset * 24 * 60 * 60 * 1000)
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} else {
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offsetPrint = offsetPrint - (cfg.Offset * 24 * 60 * 60)
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}
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}
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log.Println(fmt.Sprintf("Will collect data starting at TS %v", offsetPrint))
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for _, r := range cfg.Retentions {
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ret, err := convertRetention(r, offsetPrint, cfg.MsecsTime)
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if err != nil {
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return &Client{}, fmt.Errorf("Couldn't parse retention %q :: %v", r, err)
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}
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retentions = append(retentions, ret)
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}
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client := &Client{
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Addr: strings.Trim(cfg.Addr, "/"),
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Retentions: retentions,
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Limit: cfg.Limit,
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Filters: cfg.Filters,
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Normalize: cfg.Normalize,
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}
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return client, nil
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}
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