VictoriaMetrics/app/vmctl/opentsdb/opentsdb.go
John Seekins a9d76b06a7
Improve documentation on OpenTSDB migration tool and fix a bug with hard offsets (#1198)
* add more documentation on OpenTSDB migration explaining what chunking means
* more clarification of OpenTSDB aggregations
* break out what a retention string becomes
* add more docs around retention strings
* add example of running program and fix mistake in how hard offsets are handled
* fix formatting
2021-04-10 13:24:18 +01:00

349 lines
10 KiB
Go

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