Refactor scrape() to break out the major components.
This puts us on the road to dropping the bash tests and doing it all in Go.
This commit is contained in:
Will Rouesnel
parent
53ad0efbbb
commit
a95fad8d1e
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@ -10,13 +10,14 @@ import (
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"os"
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"strconv"
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"time"
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"regexp"
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"errors"
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"gopkg.in/yaml.v2"
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_ "github.com/lib/pq"
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"github.com/prometheus/client_golang/prometheus"
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"github.com/prometheus/common/log"
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"regexp"
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)
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var Version string = "0.0.1"
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@ -589,6 +590,119 @@ func newDesc(subsystem, name, help string) *prometheus.Desc {
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)
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}
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// Query the SHOW variables from the query map
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// TODO: make this more functional
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func (e *Exporter) queryShowVariables(ch chan<- prometheus.Metric, db *sql.DB) {
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log.Debugln("Querying SHOW variables")
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for _, mapping := range e.variableMap {
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for columnName, columnMapping := range mapping.columnMappings {
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// Check for a discard request on this value
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if columnMapping.discard {
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continue
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}
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// Use SHOW to get the value
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row := db.QueryRow(fmt.Sprintf("SHOW %s;", columnName))
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var val interface{}
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err := row.Scan(&val)
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if err != nil {
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log.Errorln("Error scanning runtime variable:", columnName, err)
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continue
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}
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fval, ok := columnMapping.conversion(val)
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if !ok {
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e.error.Set(1)
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log.Errorln("Unexpected error parsing column: ", namespace, columnName, val)
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continue
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}
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ch <- prometheus.MustNewConstMetric(columnMapping.desc, columnMapping.vtype, fval)
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}
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}
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}
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func queryNamespaceMapping(ch chan<- prometheus.Metric, db *sql.DB, namespace string, mapping MetricMapNamespace) error {
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query, er := queryOverrides[namespace]
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if er == false {
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query = fmt.Sprintf("SELECT * FROM %s;", namespace)
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}
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// Don't fail on a bad scrape of one metric
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rows, err := db.Query(query)
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if err != nil {
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return errors.New(fmt.Sprintln("Error running query on database: ", namespace, err))
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}
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defer rows.Close()
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var columnNames []string
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columnNames, err = rows.Columns()
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if err != nil {
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return errors.New(fmt.Sprintln("Error retrieving column list for: ", namespace, err))
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}
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// Make a lookup map for the column indices
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var columnIdx = make(map[string]int, len(columnNames))
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for i, n := range columnNames {
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columnIdx[n] = i
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}
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var columnData = make([]interface{}, len(columnNames))
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var scanArgs = make([]interface{}, len(columnNames))
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for i := range columnData {
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scanArgs[i] = &columnData[i]
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}
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for rows.Next() {
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err = rows.Scan(scanArgs...)
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if err != nil {
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return errors.New(fmt.Sprintln("Error retrieving rows:", namespace, err))
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}
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// Get the label values for this row
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var labels = make([]string, len(mapping.labels))
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for idx, columnName := range mapping.labels {
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labels[idx], _ = dbToString(columnData[columnIdx[columnName]])
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}
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// Loop over column names, and match to scan data. Unknown columns
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// will be filled with an untyped metric number *if* they can be
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// converted to float64s. NULLs are allowed and treated as NaN.
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for idx, columnName := range columnNames {
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if metricMapping, ok := mapping.columnMappings[columnName]; ok {
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// Is this a metricy metric?
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if metricMapping.discard {
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continue
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}
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value, ok := dbToFloat64(columnData[idx])
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if !ok {
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log.Errorln("Unexpected error parsing column: ", namespace, columnName, columnData[idx])
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continue
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}
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// Generate the metric
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ch <- prometheus.MustNewConstMetric(metricMapping.desc, metricMapping.vtype, value, labels...)
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} else {
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// Unknown metric. Report as untyped if scan to float64 works, else note an error too.
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desc := prometheus.NewDesc(fmt.Sprintf("%s_%s", namespace, columnName), fmt.Sprintf("Unknown metric from %s", namespace), nil, nil)
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// Its not an error to fail here, since the values are
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// unexpected anyway.
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value, ok := dbToFloat64(columnData[idx])
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if !ok {
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log.Warnln("Unparseable column type - discarding: ", namespace, columnName, err)
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continue
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}
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ch <- prometheus.MustNewConstMetric(desc, prometheus.UntypedValue, value, labels...)
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}
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}
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}
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return nil
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}
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func (e *Exporter) scrape(ch chan<- prometheus.Metric) {
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defer func(begun time.Time) {
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e.duration.Set(time.Since(begun).Seconds())
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@ -619,124 +733,16 @@ func (e *Exporter) scrape(ch chan<- prometheus.Metric) {
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versionDesc := prometheus.NewDesc(fmt.Sprintf("%s_%s", namespace, staticLabelName), "Version string as reported by postgres", []string{"version", "short_version"}, nil)
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ch <- prometheus.MustNewConstMetric(versionDesc, prometheus.UntypedValue, 1, versionString, shortVersion)
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log.Debugln("Querying SHOW variables")
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for _, mapping := range e.variableMap {
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for columnName, columnMapping := range mapping.columnMappings {
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// Check for a discard request on this value
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if columnMapping.discard {
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continue
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}
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// Use SHOW to get the value
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row := db.QueryRow(fmt.Sprintf("SHOW %s;", columnName))
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var val interface{}
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err := row.Scan(&val)
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if err != nil {
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log.Errorln("Error scanning runtime variable:", columnName, err)
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continue
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}
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fval, ok := columnMapping.conversion(val)
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if !ok {
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e.error.Set(1)
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log.Errorln("Unexpected error parsing column: ", namespace, columnName, val)
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continue
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}
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ch <- prometheus.MustNewConstMetric(columnMapping.desc, columnMapping.vtype, fval)
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}
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}
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// Handle querying the show variables
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e.queryShowVariables(ch, db)
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for namespace, mapping := range e.metricMap {
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log.Debugln("Querying namespace: ", namespace)
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func() {
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query, er := queryOverrides[namespace]
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if er == false {
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query = fmt.Sprintf("SELECT * FROM %s;", namespace)
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}
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// Don't fail on a bad scrape of one metric
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rows, err := db.Query(query)
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if err != nil {
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log.Infoln("Error running query on database: ", namespace, err)
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e.error.Set(1)
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return
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}
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defer rows.Close()
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var columnNames []string
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columnNames, err = rows.Columns()
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if err != nil {
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log.Infoln("Error retrieving column list for: ", namespace, err)
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e.error.Set(1)
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return
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}
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// Make a lookup map for the column indices
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var columnIdx = make(map[string]int, len(columnNames))
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for i, n := range columnNames {
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columnIdx[n] = i
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}
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var columnData = make([]interface{}, len(columnNames))
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var scanArgs = make([]interface{}, len(columnNames))
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for i := range columnData {
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scanArgs[i] = &columnData[i]
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}
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for rows.Next() {
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err = rows.Scan(scanArgs...)
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if err != nil {
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log.Infoln("Error retrieving rows:", namespace, err)
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e.error.Set(1)
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return
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}
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// Get the label values for this row
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var labels = make([]string, len(mapping.labels))
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for idx, columnName := range mapping.labels {
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labels[idx], _ = dbToString(columnData[columnIdx[columnName]])
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}
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// Loop over column names, and match to scan data. Unknown columns
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// will be filled with an untyped metric number *if* they can be
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// converted to float64s. NULLs are allowed and treated as NaN.
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for idx, columnName := range columnNames {
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if metricMapping, ok := mapping.columnMappings[columnName]; ok {
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// Is this a metricy metric?
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if metricMapping.discard {
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continue
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}
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value, ok := dbToFloat64(columnData[idx])
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if !ok {
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e.error.Set(1)
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log.Errorln("Unexpected error parsing column: ", namespace, columnName, columnData[idx])
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continue
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}
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// Generate the metric
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ch <- prometheus.MustNewConstMetric(metricMapping.desc, metricMapping.vtype, value, labels...)
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} else {
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// Unknown metric. Report as untyped if scan to float64 works, else note an error too.
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desc := prometheus.NewDesc(fmt.Sprintf("%s_%s", namespace, columnName), fmt.Sprintf("Unknown metric from %s", namespace), nil, nil)
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// Its not an error to fail here, since the values are
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// unexpected anyway.
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value, ok := dbToFloat64(columnData[idx])
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if !ok {
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log.Warnln("Unparseable column type - discarding: ", namespace, columnName, err)
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continue
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}
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ch <- prometheus.MustNewConstMetric(desc, prometheus.UntypedValue, value, labels...)
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}
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}
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}
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}()
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err = queryNamespaceMapping(ch, db, namespace, mapping)
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if err != nil {
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log.Infoln(err)
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e.error.Set(1)
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}
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}
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}
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