tbphp
d79180fda2
* feat(subscriptions): refine credential trend insights * fix(classic): accept health identity fields (#682) * fix(ui): standardize English unit abbreviations (#683) * feat(subscriptions): refine credential trend insights * fix(subscriptions): address trend review findings
98 lines
3.8 KiB
Go
98 lines
3.8 KiB
Go
package requestlog
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import (
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"fmt"
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"gorm.io/gorm"
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"gpt-load/internal/platform/epochms"
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)
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// ResolveUsageTimeBucket 根据精确时间跨度选择趋势桶，不依赖前端快捷范围。
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func ResolveUsageTimeBucket(fromMS, toMS int64) (UsageGranularity, int64, error) {
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const maxSafeMilliseconds int64 = 1<<53 - 1
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if fromMS < 0 || toMS <= fromMS || toMS > maxSafeMilliseconds {
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return "", 0, fmt.Errorf("query usage: invalid or unsafe time range")
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}
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spanMS := toMS - fromMS
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hour, day := epochms.MillisecondsPerHour, epochms.MillisecondsPerDay
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switch {
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case spanMS <= 6*hour:
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return UsageGranularityMinute, UsageFiveMinuteBucketMS, nil
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case spanMS <= day:
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return UsageGranularityHour, hour, nil
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case spanMS <= 3*day:
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return UsageGranularityHour, 3 * hour, nil
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case spanMS <= 7*day:
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return UsageGranularityHour, 6 * hour, nil
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case spanMS <= 15*day:
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return UsageGranularityHour, 12 * hour, nil
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default:
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// 向上取整时不先加除数，超长区间仍保持安全整数运算。
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return UsageGranularityDay, ((spanMS-1)/(30*day) + 1) * day, nil
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}
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}
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// usageWindowScope 先按时间拆分来源，再合并行集供总览、趋势和分布使用。
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// 数据缺失不会改变分段，也不会把首尾小时的整桶统计带入精确区间。
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func usageWindowScope(db *gorm.DB, input UsageQuery, groupIDs ...uint) *gorm.DB {
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hour := epochms.MillisecondsPerHour
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if input.ToMS-input.FromMS <= hour {
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return usageRequestLogScope(db, input, groupIDs...)
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}
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fullFromMS := input.FromMS
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if remainder := fullFromMS % hour; remainder != 0 {
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fullFromMS += hour - remainder
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}
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fullToMS := input.ToMS - input.ToMS%hour
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full := input
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full.FromMS, full.ToMS = fullFromMS, fullToMS
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// 数值运算固定参数类型，避免 PostgreSQL 把 SELECT 中的独立参数推断为 text。
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parts := []any{usageStatScope(db, full, groupIDs...).Select(usageWindowColumns+", ? + 0 AS bucket_alignment_ms", hour)}
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unionSQL := "?"
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for _, boundary := range [][2]int64{{input.FromMS, fullFromMS}, {fullToMS, input.ToMS}} {
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if boundary[0] >= boundary[1] {
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continue
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}
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part := input
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part.FromMS, part.ToMS = boundary[0], boundary[1]
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parts = append(parts, usageRequestLogScope(db, part, groupIDs...).Select(usageWindowColumns+", bucket_alignment_ms"))
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unionSQL += " UNION ALL ?"
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}
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return db.Session(&gorm.Session{NewDB: true}).Table("("+unionSQL+") AS usage_rows", parts...)
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}
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func queryUsageWindowSeries(scope *gorm.DB, input UsageQuery, widthMS int64) ([]UsageSeriesPoint, error) {
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var rows []struct {
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BucketStartMS int64 `gorm:"column:series_bucket_ms"`
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UsageAggregate
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}
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// 直接按最终自然桶聚合，年度等长区间不会把每个小时传回进程再合并。
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if err := scope.Select("bucket_start_ms - bucket_start_ms % ? AS series_bucket_ms, "+usageAggregateSelect, widthMS).
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Group("series_bucket_ms").Order("series_bucket_ms ASC").
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Scan(&rows).Error; err != nil {
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return nil, fmt.Errorf("query usage window series: %w", err)
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}
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series := make([]UsageSeriesPoint, 0, len(rows))
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for _, row := range rows {
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if err := validateUsageAggregate(row.UsageAggregate); err != nil {
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return nil, fmt.Errorf("validate usage window series: %w", err)
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}
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endMS := input.ToMS
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if input.ToMS-row.BucketStartMS > widthMS {
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endMS = row.BucketStartMS + widthMS
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}
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series = append(series, UsageSeriesPoint{
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BucketStartMS: max(row.BucketStartMS, input.FromMS), BucketEndMS: endMS,
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UsageAggregate: row.UsageAggregate,
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})
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}
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return series, nil
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}
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const usageWindowColumns = `bucket_start_ms, group_id, access_key_id, model,
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request_count, success_count, failure_count,
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uncached_input_tokens, cache_read_tokens, cache_write_5m_tokens, cache_write_1h_tokens,
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cache_write_unknown_tokens, output_tokens, estimated_cost_nano_usd,
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usage_missing_count, partial_count, unpriced_request_count, pricing_partial_count`
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