Jason Kulatunga
3 years ago
parent
f60636a6aa
commit
0a9d364aea
@ -0,0 +1,163 @@
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package database
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import (
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"context"
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"fmt"
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"github.com/analogj/scrutiny/webapp/backend/pkg/models/collector"
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"github.com/analogj/scrutiny/webapp/backend/pkg/models/measurements"
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influxdb2 "github.com/influxdata/influxdb-client-go/v2"
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"strings"
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)
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////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
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// SMART
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////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
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func (sr *scrutinyRepository) SaveSmartAttributes(ctx context.Context, wwn string, collectorSmartData collector.SmartInfo) (measurements.Smart, error) {
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deviceSmartData := measurements.Smart{}
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err := deviceSmartData.FromCollectorSmartInfo(wwn, collectorSmartData)
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if err != nil {
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sr.logger.Errorln("Could not process SMART metrics", err)
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return measurements.Smart{}, err
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}
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tags, fields := deviceSmartData.Flatten()
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p := influxdb2.NewPoint("smart",
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tags,
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fields,
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deviceSmartData.Date)
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// write point immediately
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return deviceSmartData, sr.influxWriteApi.WritePoint(ctx, p)
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}
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func (sr *scrutinyRepository) GetSmartAttributeHistory(ctx context.Context, wwn string, durationKey string, attributes []string) ([]measurements.Smart, error) {
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// Get SMartResults from InfluxDB
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fmt.Println("GetDeviceDetails from INFLUXDB")
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//TODO: change the filter startrange to a real number.
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// Get parser flux query result
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//appConfig.GetString("web.influxdb.bucket")
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queryStr := sr.aggregateSmartAttributesQuery(wwn, durationKey)
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smartResults := []measurements.Smart{}
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result, err := sr.influxQueryApi.Query(ctx, queryStr)
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if err == nil {
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fmt.Println("GetDeviceDetails NO EROR")
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// Use Next() to iterate over query result lines
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for result.Next() {
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fmt.Println("GetDeviceDetails NEXT")
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// Observe when there is new grouping key producing new table
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if result.TableChanged() {
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//fmt.Printf("table: %s\n", result.TableMetadata().String())
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}
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fmt.Printf("DECODINIG TABLE VALUES: %v", result.Record().Values())
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smartData, err := measurements.NewSmartFromInfluxDB(result.Record().Values())
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if err != nil {
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return nil, err
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}
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smartResults = append(smartResults, *smartData)
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}
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if result.Err() != nil {
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fmt.Printf("Query error: %s\n", result.Err().Error())
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}
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} else {
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return nil, err
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}
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return smartResults, nil
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//if err := device.SquashHistory(); err != nil {
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// logger.Errorln("An error occurred while squashing device history", err)
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// c.JSON(http.StatusInternalServerError, gin.H{"success": false})
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// return
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//}
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//
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//if err := device.ApplyMetadataRules(); err != nil {
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// logger.Errorln("An error occurred while applying scrutiny thresholds & rules", err)
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// c.JSON(http.StatusInternalServerError, gin.H{"success": false})
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// return
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//}
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}
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////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
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// Helper Methods
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////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
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func (sr *scrutinyRepository) aggregateSmartAttributesQuery(wwn string, durationKey string) string {
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/*
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import "influxdata/influxdb/schema"
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weekData = from(bucket: "metrics")
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|> range(start: -1w, stop: now())
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|> filter(fn: (r) => r["_measurement"] == "smart" )
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|> filter(fn: (r) => r["device_wwn"] == "%s" )
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|> aggregateWindow(every: 1h, fn: mean, createEmpty: false)
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|> group(columns: ["device_wwn"])
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|> toInt()
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monthData = from(bucket: "metrics_weekly")
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|> range(start: -1mo, stop: now())
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|> filter(fn: (r) => r["_measurement"] == "smart" )
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|> filter(fn: (r) => r["device_wwn"] == "%s" )
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|> aggregateWindow(every: 1h, fn: mean, createEmpty: false)
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|> group(columns: ["device_wwn"])
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|> toInt()
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union(tables: [weekData, monthData])
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|> group(columns: ["device_wwn"])
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|> sort(columns: ["_time"], desc: false)
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|> schema.fieldsAsCols()
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*/
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partialQueryStr := []string{
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`import "influxdata/influxdb/schema"`,
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}
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nestedDurationKeys := sr.lookupNestedDurationKeys(durationKey)
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subQueryNames := []string{}
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for _, nestedDurationKey := range nestedDurationKeys {
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bucketName := sr.lookupBucketName(nestedDurationKey)
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durationRange := sr.lookupDuration(nestedDurationKey)
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subQueryNames = append(subQueryNames, fmt.Sprintf(`%sData`, nestedDurationKey))
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partialQueryStr = append(partialQueryStr, []string{
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fmt.Sprintf(`%sData = from(bucket: "%s")`, nestedDurationKey, bucketName),
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fmt.Sprintf(`|> range(start: %s, stop: %s)`, durationRange[0], durationRange[1]),
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`|> filter(fn: (r) => r["_measurement"] == "smart" )`,
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fmt.Sprintf(`|> filter(fn: (r) => r["device_wwn"] == "%s" )`, wwn),
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`|> aggregateWindow(every: 1h, fn: last, createEmpty: false)`,
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`|> group(columns: ["device_wwn"])`,
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`|> toInt()`,
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"",
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}...)
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}
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if len(subQueryNames) == 1 {
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//there's only one bucket being queried, no need to union, just aggregate the dataset and return
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partialQueryStr = append(partialQueryStr, []string{
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subQueryNames[0],
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"|> schema.fieldsAsCols()",
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"|> yield()",
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}...)
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} else {
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partialQueryStr = append(partialQueryStr, []string{
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fmt.Sprintf("union(tables: [%s])", strings.Join(subQueryNames, ", ")),
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`|> group(columns: ["device_wwn"])`,
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`|> sort(columns: ["_time"], desc: false)`,
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"|> schema.fieldsAsCols()",
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}...)
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}
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return strings.Join(partialQueryStr, "\n")
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}
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