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https://github.com/jcreek/CosmicClash.git
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5453e19761
Each ten-second queue heartbeat mints a fresh idempotency key and permanently inserts a row. Published outbox rows and expired/revoked sessions were never purged either -- the maintenance role performed lifecycle reconciliation only. At 10,000 queued players heartbeats alone add roughly 60,000 durable rows per minute, so table and index growth, vacuum pressure, backup size and recovery time were all unbounded on a service intended to scale horizontally. Add retention windows chosen to exceed every retry and recovery horizon that could still consult the row -- deleting an idempotency key early would turn a client replay into a second real mutation, so this is a correctness bound, not just a housekeeping one. Dead-lettered outbox rows are kept longest, being the record of events never delivered. Deletes run in bounded SKIP LOCKED batches so a purge never blocks live traffic, never holds a long transaction, and concurrent maintenance replicas do not contend. Indexes back each predicate so a pass cannot degrade into a sequential scan of the table it is bounding. The maintenance role reports rows purged, the backlog past its window (deletion lag), and any dead-lettered events. Also make the migration-rollback test derive its step counts instead of hardcoding them: adding a migration silently shifted the fixed counts so the failure surfaced as an unrelated "0006 rollback did not drop matches.allocation_id".
134 lines
4.7 KiB
Go
134 lines
4.7 KiB
Go
package store
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import (
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"context"
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"database/sql"
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"fmt"
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"time"
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)
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// Retention windows. Each must comfortably exceed every retry and recovery
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// horizon that could still consult the row, because deleting one early changes
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// behaviour rather than merely reclaiming space:
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//
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// - An idempotency key must outlive any client retry of the same mutation;
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// deleting it early turns a replay into a second real mutation. The client
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// heartbeats every 10s and abandons a ticket far sooner than this.
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// - A published outbox row is only kept for operator forensics; delivery has
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// already happened, and the dispatcher never re-reads a published row.
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// - A session row past expiry can no longer authenticate, so retaining it
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// buys nothing beyond a short audit tail.
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const (
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IdempotencyKeyRetention = 24 * time.Hour
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PublishedOutboxRetention = 72 * time.Hour
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ExpiredSessionRetention = 24 * time.Hour
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// DeadLetteredOutboxRetention is deliberately the longest: those rows are
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// the record of events that were never delivered, and an operator needs
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// time to notice and investigate them.
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DeadLetteredOutboxRetention = 30 * 24 * time.Hour
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)
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// Deletes are batched and use SKIP LOCKED so a purge never blocks live
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// traffic, never holds a long transaction, and multiple maintenance replicas
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// can run concurrently without contending on the same rows.
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const (
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PurgeIdempotencyKeysSQL = `DELETE FROM idempotency_keys
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WHERE (scope, idempotency_key) IN (
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SELECT scope, idempotency_key FROM idempotency_keys
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WHERE created_at < $1
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ORDER BY created_at
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LIMIT $2
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FOR UPDATE SKIP LOCKED
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)`
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PurgePublishedOutboxSQL = `DELETE FROM outbox
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WHERE event_id IN (
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SELECT event_id FROM outbox
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WHERE published_at IS NOT NULL AND published_at < $1
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ORDER BY published_at
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LIMIT $2
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FOR UPDATE SKIP LOCKED
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)`
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PurgeDeadLetteredOutboxSQL = `DELETE FROM outbox
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WHERE event_id IN (
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SELECT event_id FROM outbox
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WHERE dead_lettered_at IS NOT NULL AND dead_lettered_at < $1
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ORDER BY dead_lettered_at
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LIMIT $2
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FOR UPDATE SKIP LOCKED
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)`
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PurgeExpiredSessionsSQL = `DELETE FROM sessions
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WHERE session_id IN (
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SELECT session_id FROM sessions
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WHERE expires_at < $1
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ORDER BY expires_at
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LIMIT $2
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FOR UPDATE SKIP LOCKED
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)`
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)
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// RetentionReport is the per-pass result. Callers expose these as metrics so
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// deletion lag is observable: if a count stays pinned at the batch size, the
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// purge is not keeping up with insert volume.
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type RetentionReport struct {
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IdempotencyKeys int64
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PublishedOutbox int64
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DeadLetteredOutbox int64
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ExpiredSessions int64
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}
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func (r RetentionReport) Total() int64 {
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return r.IdempotencyKeys + r.PublishedOutbox + r.DeadLetteredOutbox + r.ExpiredSessions
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}
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// PurgeExpiredRecords removes one bounded batch from each retained table. It
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// returns partial progress alongside an error so a failure in one table does
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// not hide the work already done in another.
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func PurgeExpiredRecords(ctx context.Context, db *sql.DB, now time.Time, batch int) (RetentionReport, error) {
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var report RetentionReport
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if db == nil || now.IsZero() || batch < 1 || batch > 10000 {
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return report, fmt.Errorf("invalid retention arguments")
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}
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steps := []struct {
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query string
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cutoff time.Time
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into *int64
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}{
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{PurgeIdempotencyKeysSQL, now.Add(-IdempotencyKeyRetention), &report.IdempotencyKeys},
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{PurgePublishedOutboxSQL, now.Add(-PublishedOutboxRetention), &report.PublishedOutbox},
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{PurgeDeadLetteredOutboxSQL, now.Add(-DeadLetteredOutboxRetention), &report.DeadLetteredOutbox},
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{PurgeExpiredSessionsSQL, now.Add(-ExpiredSessionRetention), &report.ExpiredSessions},
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}
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for _, step := range steps {
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result, err := db.ExecContext(ctx, step.query, step.cutoff, batch)
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if err != nil {
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return report, err
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}
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deleted, err := result.RowsAffected()
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if err != nil {
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return report, err
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}
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*step.into = deleted
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}
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return report, nil
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}
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// RetentionBacklog counts rows already past their retention window. This is
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// the deletion-lag metric: a number that keeps climbing means the purge
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// interval or batch size is too small for current volume.
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func RetentionBacklog(ctx context.Context, db *sql.DB, now time.Time) (int64, error) {
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if db == nil || now.IsZero() {
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return 0, fmt.Errorf("invalid retention backlog arguments")
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}
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const query = `SELECT
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(SELECT count(*) FROM idempotency_keys WHERE created_at < $1)
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+ (SELECT count(*) FROM outbox WHERE published_at IS NOT NULL AND published_at < $2)
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+ (SELECT count(*) FROM sessions WHERE expires_at < $3)`
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var backlog int64
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err := db.QueryRowContext(ctx, query,
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now.Add(-IdempotencyKeyRetention),
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now.Add(-PublishedOutboxRetention),
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now.Add(-ExpiredSessionRetention),
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).Scan(&backlog)
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return backlog, err
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}
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