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323 lines
11 KiB
323 lines
11 KiB
package logql
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import (
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"context"
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"hash/fnv"
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"strings"
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"time"
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"github.com/dustin/go-humanize"
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"github.com/go-kit/log"
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"github.com/go-kit/log/level"
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"github.com/prometheus/client_golang/prometheus"
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"github.com/prometheus/client_golang/prometheus/promauto"
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promql_parser "github.com/prometheus/prometheus/promql/parser"
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"github.com/grafana/loki/pkg/logql/syntax"
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"github.com/grafana/loki/pkg/logqlmodel"
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logql_stats "github.com/grafana/loki/pkg/logqlmodel/stats"
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"github.com/grafana/loki/pkg/usagestats"
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"github.com/grafana/loki/pkg/util/httpreq"
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util_log "github.com/grafana/loki/pkg/util/log"
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)
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const (
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QueryTypeMetric = "metric"
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QueryTypeFilter = "filter"
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QueryTypeLimited = "limited"
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QueryTypeLabels = "labels"
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QueryTypeSeries = "series"
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latencyTypeSlow = "slow"
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latencyTypeFast = "fast"
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slowQueryThresholdSecond = float64(10)
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)
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var (
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bytesPerSecond = promauto.NewHistogramVec(prometheus.HistogramOpts{
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Namespace: "loki",
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Name: "logql_querystats_bytes_processed_per_seconds",
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Help: "Distribution of bytes processed per second for LogQL queries.",
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// 50MB 100MB 200MB 400MB 600MB 800MB 1GB 2GB 3GB 4GB 5GB 6GB 7GB 8GB 9GB 10GB 15GB 20GB 30GB, 40GB 50GB 60GB
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Buckets: []float64{50 * 1e6, 100 * 1e6, 400 * 1e6, 600 * 1e6, 800 * 1e6, 1 * 1e9, 2 * 1e9, 3 * 1e9, 4 * 1e9, 5 * 1e9, 6 * 1e9, 7 * 1e9, 8 * 1e9, 9 * 1e9, 10 * 1e9, 15 * 1e9, 20 * 1e9, 30 * 1e9, 40 * 1e9, 50 * 1e9, 60 * 1e9},
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}, []string{"status_code", "type", "range", "latency_type"})
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execLatency = promauto.NewHistogramVec(prometheus.HistogramOpts{
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Namespace: "loki",
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Name: "logql_querystats_latency_seconds",
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Help: "Distribution of latency for LogQL queries.",
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// 0.25 0.5 1 2 4 8 16 32 64 128
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Buckets: prometheus.ExponentialBuckets(0.250, 2, 10),
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}, []string{"status_code", "type", "range"})
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chunkDownloadLatency = promauto.NewHistogramVec(prometheus.HistogramOpts{
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Namespace: "loki",
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Name: "logql_querystats_chunk_download_latency_seconds",
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Help: "Distribution of chunk downloads latency for LogQL queries.",
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// 0.25 0.5 1 2 4 8 16 32 64 128
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Buckets: prometheus.ExponentialBuckets(0.250, 2, 10),
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}, []string{"status_code", "type", "range"})
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duplicatesTotal = promauto.NewCounter(prometheus.CounterOpts{
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Namespace: "loki",
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Name: "logql_querystats_duplicates_total",
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Help: "Total count of duplicates found while executing LogQL queries.",
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})
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chunkDownloadedTotal = promauto.NewCounterVec(prometheus.CounterOpts{
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Namespace: "loki",
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Name: "logql_querystats_downloaded_chunk_total",
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Help: "Total count of chunks downloaded found while executing LogQL queries.",
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}, []string{"status_code", "type", "range"})
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ingesterLineTotal = promauto.NewCounter(prometheus.CounterOpts{
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Namespace: "loki",
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Name: "logql_querystats_ingester_sent_lines_total",
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Help: "Total count of lines sent from ingesters while executing LogQL queries.",
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})
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bytePerSecondMetricUsage = usagestats.NewStatistics("query_metric_bytes_per_second")
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bytePerSecondLogUsage = usagestats.NewStatistics("query_log_bytes_per_second")
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linePerSecondMetricUsage = usagestats.NewStatistics("query_metric_lines_per_second")
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linePerSecondLogUsage = usagestats.NewStatistics("query_log_lines_per_second")
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)
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func RecordRangeAndInstantQueryMetrics(
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ctx context.Context,
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log log.Logger,
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p Params,
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status string,
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stats logql_stats.Result,
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result promql_parser.Value,
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) {
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var (
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logger = util_log.WithContext(ctx, log)
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rt = string(GetRangeType(p))
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latencyType = latencyTypeFast
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returnedLines = 0
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)
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queryType, err := QueryType(p.Query())
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if err != nil {
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level.Warn(logger).Log("msg", "error parsing query type", "err", err)
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}
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// Tag throughput metric by latency type based on a threshold.
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// Latency below the threshold is fast, above is slow.
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if stats.Summary.ExecTime > slowQueryThresholdSecond {
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latencyType = latencyTypeSlow
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}
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if result != nil && result.Type() == logqlmodel.ValueTypeStreams {
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returnedLines = int(result.(logqlmodel.Streams).Lines())
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}
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queryTags, _ := ctx.Value(httpreq.QueryTagsHTTPHeader).(string) // it's ok to be empty.
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logValues := make([]interface{}, 0, 30)
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logValues = append(logValues, []interface{}{
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"latency", latencyType, // this can be used to filter log lines.
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"query", p.Query(),
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"query_hash", HashedQuery(p.Query()),
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"query_type", queryType,
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"range_type", rt,
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"length", p.End().Sub(p.Start()),
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"start_delta", time.Since(p.Start()),
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"end_delta", time.Since(p.End()),
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"step", p.Step(),
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"duration", logql_stats.ConvertSecondsToNanoseconds(stats.Summary.ExecTime),
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"status", status,
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"limit", p.Limit(),
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"returned_lines", returnedLines,
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"throughput", strings.Replace(humanize.Bytes(uint64(stats.Summary.BytesProcessedPerSecond)), " ", "", 1),
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"total_bytes", strings.Replace(humanize.Bytes(uint64(stats.Summary.TotalBytesProcessed)), " ", "", 1),
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"total_entries", stats.Summary.TotalEntriesReturned,
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"store_chunks_download_time", stats.ChunksDownloadTime(),
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"queue_time", logql_stats.ConvertSecondsToNanoseconds(stats.Summary.QueueTime),
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"subqueries", stats.Summary.Subqueries,
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"cache_chunk_req", stats.Caches.Chunk.EntriesRequested,
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"cache_chunk_hit", stats.Caches.Chunk.EntriesFound,
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"cache_chunk_bytes_stored", stats.Caches.Chunk.BytesSent,
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"cache_chunk_bytes_fetched", stats.Caches.Chunk.BytesReceived,
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"cache_chunk_download_time", stats.Caches.Chunk.CacheDownloadTime(),
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"cache_index_req", stats.Caches.Index.EntriesRequested,
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"cache_index_hit", stats.Caches.Index.EntriesFound,
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"cache_index_download_time", stats.Caches.Index.CacheDownloadTime(),
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"cache_result_req", stats.Caches.Result.EntriesRequested,
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"cache_result_hit", stats.Caches.Result.EntriesFound,
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"cache_result_download_time", stats.Caches.Result.CacheDownloadTime(),
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}...)
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logValues = append(logValues, tagsToKeyValues(queryTags)...)
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level.Info(logger).Log(
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logValues...,
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)
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bytesPerSecond.WithLabelValues(status, queryType, rt, latencyType).
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Observe(float64(stats.Summary.BytesProcessedPerSecond))
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execLatency.WithLabelValues(status, queryType, rt).
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Observe(stats.Summary.ExecTime)
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chunkDownloadLatency.WithLabelValues(status, queryType, rt).
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Observe(stats.ChunksDownloadTime().Seconds())
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duplicatesTotal.Add(float64(stats.TotalDuplicates()))
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chunkDownloadedTotal.WithLabelValues(status, queryType, rt).
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Add(float64(stats.TotalChunksDownloaded()))
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ingesterLineTotal.Add(float64(stats.Ingester.TotalLinesSent))
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recordUsageStats(queryType, stats)
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}
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func HashedQuery(query string) uint32 {
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h := fnv.New32()
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_, _ = h.Write([]byte(query))
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return h.Sum32()
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}
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func RecordLabelQueryMetrics(
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ctx context.Context,
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log log.Logger,
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start, end time.Time,
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label, status string,
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stats logql_stats.Result,
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) {
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var (
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logger = util_log.WithContext(ctx, log)
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latencyType = latencyTypeFast
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queryType = QueryTypeLabels
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)
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// Tag throughput metric by latency type based on a threshold.
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// Latency below the threshold is fast, above is slow.
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if stats.Summary.ExecTime > slowQueryThresholdSecond {
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latencyType = latencyTypeSlow
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}
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level.Info(logger).Log(
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"latency", latencyType,
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"query_type", queryType,
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"length", end.Sub(start),
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"duration", time.Duration(int64(stats.Summary.ExecTime*float64(time.Second))),
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"status", status,
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"label", label,
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"throughput", strings.Replace(humanize.Bytes(uint64(stats.Summary.BytesProcessedPerSecond)), " ", "", 1),
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"total_bytes", strings.Replace(humanize.Bytes(uint64(stats.Summary.TotalBytesProcessed)), " ", "", 1),
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"total_entries", stats.Summary.TotalEntriesReturned,
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)
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bytesPerSecond.WithLabelValues(status, queryType, "", latencyType).
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Observe(float64(stats.Summary.BytesProcessedPerSecond))
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execLatency.WithLabelValues(status, queryType, "").
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Observe(stats.Summary.ExecTime)
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chunkDownloadLatency.WithLabelValues(status, queryType, "").
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Observe(stats.ChunksDownloadTime().Seconds())
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duplicatesTotal.Add(float64(stats.TotalDuplicates()))
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chunkDownloadedTotal.WithLabelValues(status, queryType, "").
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Add(float64(stats.TotalChunksDownloaded()))
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ingesterLineTotal.Add(float64(stats.Ingester.TotalLinesSent))
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}
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func PrintMatches(matches []string) string {
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// not using comma (,) as separator as matcher may already have comma (e.g: `{a="b", c="d"}`)
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return strings.Join(matches, ":")
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}
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func RecordSeriesQueryMetrics(
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ctx context.Context,
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log log.Logger,
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start, end time.Time,
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match []string,
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status string,
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stats logql_stats.Result,
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) {
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var (
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logger = util_log.WithContext(ctx, log)
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latencyType = latencyTypeFast
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queryType = QueryTypeSeries
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)
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// Tag throughput metric by latency type based on a threshold.
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// Latency below the threshold is fast, above is slow.
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if stats.Summary.ExecTime > slowQueryThresholdSecond {
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latencyType = latencyTypeSlow
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}
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// we also log queries, useful for troubleshooting slow queries.
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level.Info(logger).Log(
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"latency", latencyType,
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"query_type", queryType,
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"length", end.Sub(start),
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"duration", time.Duration(int64(stats.Summary.ExecTime*float64(time.Second))),
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"status", status,
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"match", PrintMatches(match),
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"throughput", strings.Replace(humanize.Bytes(uint64(stats.Summary.BytesProcessedPerSecond)), " ", "", 1),
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"total_bytes", strings.Replace(humanize.Bytes(uint64(stats.Summary.TotalBytesProcessed)), " ", "", 1),
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"total_entries", stats.Summary.TotalEntriesReturned,
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)
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bytesPerSecond.WithLabelValues(status, queryType, "", latencyType).
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Observe(float64(stats.Summary.BytesProcessedPerSecond))
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execLatency.WithLabelValues(status, queryType, "").
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Observe(stats.Summary.ExecTime)
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chunkDownloadLatency.WithLabelValues(status, queryType, "").
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Observe(stats.ChunksDownloadTime().Seconds())
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duplicatesTotal.Add(float64(stats.TotalDuplicates()))
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chunkDownloadedTotal.WithLabelValues(status, queryType, "").
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Add(float64(stats.TotalChunksDownloaded()))
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ingesterLineTotal.Add(float64(stats.Ingester.TotalLinesSent))
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}
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func recordUsageStats(queryType string, stats logql_stats.Result) {
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if queryType == QueryTypeMetric {
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bytePerSecondMetricUsage.Record(float64(stats.Summary.BytesProcessedPerSecond))
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linePerSecondMetricUsage.Record(float64(stats.Summary.LinesProcessedPerSecond))
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} else {
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bytePerSecondLogUsage.Record(float64(stats.Summary.BytesProcessedPerSecond))
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linePerSecondLogUsage.Record(float64(stats.Summary.LinesProcessedPerSecond))
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}
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}
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func QueryType(query string) (string, error) {
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expr, err := syntax.ParseExpr(query)
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if err != nil {
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return "", err
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}
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switch e := expr.(type) {
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case syntax.SampleExpr:
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return QueryTypeMetric, nil
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case syntax.LogSelectorExpr:
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if e.HasFilter() {
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return QueryTypeFilter, nil
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}
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return QueryTypeLimited, nil
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default:
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return "", nil
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}
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}
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// tagsToKeyValues converts QueryTags to form that is easy to log.
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// e.g: `Source=foo,Feature=beta` -> []interface{}{"source", "foo", "feature", "beta"}
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// so that we could log nicely!
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// If queryTags is not in canonical form then its completely ignored (e.g: `key1=value1,key2=value`)
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func tagsToKeyValues(queryTags string) []interface{} {
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toks := strings.FieldsFunc(queryTags, func(r rune) bool {
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return r == ','
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})
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vals := make([]string, 0)
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for _, tok := range toks {
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val := strings.FieldsFunc(tok, func(r rune) bool {
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return r == '='
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})
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if len(val) != 2 {
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continue
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}
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vals = append(vals, val...)
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}
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res := make([]interface{}, 0, len(vals))
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for _, val := range vals {
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res = append(res, strings.ToLower(val))
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}
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return res
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}
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