chore: import upstream snapshot with attribution
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This commit is contained in:
@@ -0,0 +1,264 @@
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||||
import { db } from '@sim/db'
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||||
import { createLogger } from '@sim/logger'
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||||
import { and, inArray, isNotNull, lt, sql } from 'drizzle-orm'
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import type { PgColumn, PgTable } from 'drizzle-orm/pg-core'
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const logger = createLogger('BatchDelete')
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export const DEFAULT_BATCH_SIZE = 2000
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/** 50 × 2000 = 100K row cap per cleanup run; drains long-tail tenants in days, not weeks. */
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export const DEFAULT_MAX_BATCHES_PER_TABLE = 50
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/**
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* Split workspaceIds into this-sized groups before running SELECT/DELETE. Large
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* IN lists combined with `started_at < X` force Postgres to probe every
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* workspace range in the composite index, which blows the 90s statement timeout
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* at the scale of the full free tier.
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*/
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export const DEFAULT_WORKSPACE_CHUNK_SIZE = 50
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/** Bounds FK cascade trigger queue (per-statement in-memory) and bind-parameter count. */
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export const DEFAULT_DELETE_CHUNK_SIZE = 1000
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export function chunkArray<T>(arr: T[], size: number): T[][] {
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const out: T[][] = []
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for (let i = 0; i < arr.length; i += size) out.push(arr.slice(i, i + size))
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return out
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}
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export interface SelectByIdChunksOptions {
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/** Cap on rows returned across all chunks. Defaults to a full per-table cleanup budget. */
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overallLimit?: number
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chunkSize?: number
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}
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/**
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* Run a SELECT query once per ID chunk and concatenate results up to
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* `overallLimit`. Each chunk's query is passed the remaining row budget so the
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* total never exceeds the cap. Use this when you need the selected row set
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* (e.g. to drive S3 or copilot-backend cleanup alongside the DB delete).
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*
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* Works for any large ID set — workspace IDs, workflow IDs, etc. Avoids
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* sending one massive `IN (...)` list that would blow Postgres's statement
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* timeout.
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*/
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export async function selectRowsByIdChunks<T>(
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ids: string[],
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query: (chunkIds: string[], chunkLimit: number) => Promise<T[]>,
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{
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overallLimit = DEFAULT_BATCH_SIZE * DEFAULT_MAX_BATCHES_PER_TABLE,
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chunkSize = DEFAULT_WORKSPACE_CHUNK_SIZE,
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}: SelectByIdChunksOptions = {}
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): Promise<T[]> {
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if (ids.length === 0) return []
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const rows: T[] = []
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for (const chunkIds of chunkArray(ids, chunkSize)) {
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if (rows.length >= overallLimit) break
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const remaining = overallLimit - rows.length
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const chunkRows = await query(chunkIds, remaining)
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rows.push(...chunkRows)
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}
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return rows
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}
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export interface TableCleanupResult {
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table: string
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deleted: number
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failed: number
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}
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export interface ChunkedBatchDeleteOptions<TRow extends { id: string }> {
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tableDef: PgTable
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workspaceIds: string[]
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tableName: string
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/** SELECT eligible rows for one workspace chunk. The result must include `id`. */
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selectChunk: (chunkIds: string[], limit: number) => Promise<TRow[]>
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/** Runs between SELECT and DELETE; receives the just-selected rows. */
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onBatch?: (rows: TRow[]) => Promise<void>
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batchSize?: number
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/** Max batches per workspace chunk. */
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maxBatches?: number
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/**
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* Hard cap on rows processed (deleted + failed) across all chunks per call.
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* Defaults to `DEFAULT_BATCH_SIZE * DEFAULT_MAX_BATCHES_PER_TABLE`. Cron
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* runs frequently enough to catch up the backlog over multiple invocations.
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*/
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totalRowLimit?: number
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workspaceChunkSize?: number
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}
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/**
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* Inner loop primitive for cleanup jobs.
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*
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* For each workspace chunk: SELECT a batch of eligible rows → run optional
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* `onBatch` hook (e.g. to delete S3 files) → DELETE those rows by ID. Repeats
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* until exhausted or `maxBatches` is hit, then moves to the next chunk. Stops
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* the whole call once `totalRowLimit` rows have been processed.
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*
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* Workspace IDs are chunked before the SELECT — see
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* `DEFAULT_WORKSPACE_CHUNK_SIZE` for why.
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*/
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export async function chunkedBatchDelete<TRow extends { id: string }>({
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tableDef,
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workspaceIds,
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tableName,
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selectChunk,
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onBatch,
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batchSize = DEFAULT_BATCH_SIZE,
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maxBatches = DEFAULT_MAX_BATCHES_PER_TABLE,
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totalRowLimit = DEFAULT_BATCH_SIZE * DEFAULT_MAX_BATCHES_PER_TABLE,
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workspaceChunkSize = DEFAULT_WORKSPACE_CHUNK_SIZE,
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}: ChunkedBatchDeleteOptions<TRow>): Promise<TableCleanupResult> {
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const result: TableCleanupResult = { table: tableName, deleted: 0, failed: 0 }
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if (workspaceIds.length === 0) {
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logger.info(`[${tableName}] Skipped — no workspaces in scope`)
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return result
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}
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const chunks = chunkArray(workspaceIds, workspaceChunkSize)
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let stoppedEarly = false
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let attempted = 0
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for (const [chunkIdx, chunkIds] of chunks.entries()) {
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if (attempted >= totalRowLimit) {
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stoppedEarly = true
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break
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}
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let batchesProcessed = 0
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let hasMore = true
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while (hasMore && batchesProcessed < maxBatches && attempted < totalRowLimit) {
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let rows: TRow[] = []
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try {
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const remainingLimit = totalRowLimit - attempted
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const effectiveBatchSize = Math.min(batchSize, remainingLimit)
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if (effectiveBatchSize <= 0) {
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hasMore = false
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break
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}
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rows = await selectChunk(chunkIds, effectiveBatchSize)
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if (rows.length === 0) {
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hasMore = false
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break
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}
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attempted += rows.length
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if (onBatch) await onBatch(rows)
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const ids = rows.map((r) => r.id)
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const deleted = await db
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.delete(tableDef)
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.where(inArray(sql`id`, ids))
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.returning({ id: sql`id` })
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result.deleted += deleted.length
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result.failed += rows.length - deleted.length
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hasMore = rows.length === effectiveBatchSize && attempted < totalRowLimit
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batchesProcessed++
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} catch (error) {
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// Count rows we tried to delete; SELECT-stage errors leave rows=[].
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result.failed += rows.length
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logger.error(
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`[${tableName}] Batch failed (chunk ${chunkIdx + 1}/${chunks.length}, ${rows.length} rows):`,
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{ error }
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)
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hasMore = false
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}
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}
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}
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logger.info(
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`[${tableName}] Complete: ${result.deleted} deleted, ${result.failed} failed across ${chunks.length} chunks${stoppedEarly ? ' (row-limit reached, remaining chunks deferred to next run)' : ''}`
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)
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return result
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}
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export interface BatchDeleteOptions {
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tableDef: PgTable
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workspaceIdCol: PgColumn
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timestampCol: PgColumn
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workspaceIds: string[]
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retentionDate: Date
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tableName: string
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/** When true, also requires `timestampCol IS NOT NULL` (soft-delete semantics). */
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requireTimestampNotNull?: boolean
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batchSize?: number
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maxBatches?: number
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workspaceChunkSize?: number
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}
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/**
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* Convenience wrapper around `chunkedBatchDelete` for the common case: delete
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* rows where `workspaceId IN (...) AND timestamp < retentionDate`. Use this
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* when there's no per-row side effect (e.g. no S3 files to clean up alongside).
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*/
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export async function batchDeleteByWorkspaceAndTimestamp({
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tableDef,
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workspaceIdCol,
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timestampCol,
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workspaceIds,
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retentionDate,
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tableName,
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requireTimestampNotNull = false,
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...rest
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}: BatchDeleteOptions): Promise<TableCleanupResult> {
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return chunkedBatchDelete({
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tableDef,
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workspaceIds,
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tableName,
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selectChunk: (chunkIds, limit) => {
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const predicates = [inArray(workspaceIdCol, chunkIds), lt(timestampCol, retentionDate)]
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if (requireTimestampNotNull) predicates.push(isNotNull(timestampCol))
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return db
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.select({ id: sql<string>`id` })
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.from(tableDef)
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.where(and(...predicates))
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.limit(limit)
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},
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...rest,
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})
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}
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/**
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* Delete by explicit ID list, chunked so each statement is its own transaction.
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* Partial progress survives chunk-level failures.
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*/
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export async function deleteRowsById(
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tableDef: PgTable,
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idCol: PgColumn,
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ids: string[],
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tableName: string,
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chunkSize: number = DEFAULT_DELETE_CHUNK_SIZE
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): Promise<TableCleanupResult> {
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const result: TableCleanupResult = { table: tableName, deleted: 0, failed: 0 }
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if (ids.length === 0) return result
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const chunks = chunkArray(ids, chunkSize)
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for (const [chunkIdx, chunkIds] of chunks.entries()) {
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try {
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const deleted = await db
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.delete(tableDef)
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.where(inArray(idCol, chunkIds))
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.returning({ id: idCol })
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result.deleted += deleted.length
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} catch (error) {
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// Upper bound: Postgres rolls back the chunk on error, so actual deletes = 0,
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// but we can't tell which IDs in the chunk would have matched. The next cron
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// run picks up whatever's still expired, so this only inflates the metric.
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result.failed += chunkIds.length
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logger.error(
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`[${tableName}] Delete chunk ${chunkIdx + 1}/${chunks.length} failed (up to ${chunkIds.length} rows):`,
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{ error }
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)
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}
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}
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logger.info(
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`[${tableName}] Deleted ${result.deleted} rows across ${chunks.length} chunk(s)${result.failed > 0 ? `, ${result.failed} failed` : ''}`
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)
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return result
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}
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@@ -0,0 +1,215 @@
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import { db } from '@sim/db'
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import { copilotMessages, workspaceFiles } from '@sim/db/schema'
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import { createLogger } from '@sim/logger'
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import { and, inArray, isNull } from 'drizzle-orm'
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import { chunkArray } from '@/lib/cleanup/batch-delete'
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import { SIM_AGENT_API_URL } from '@/lib/copilot/constants'
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import { env } from '@/lib/core/config/env'
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import type { StorageContext } from '@/lib/uploads'
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import { isUsingCloudStorage, StorageService } from '@/lib/uploads'
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const logger = createLogger('ChatCleanup')
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const COPILOT_CLEANUP_BATCH_SIZE = 1000
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/** Bounds how many chats' `copilot_messages` rows are scanned per query. */
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const CHAT_FILE_COLLECT_CHUNK_SIZE = 500
|
||||
|
||||
/**
|
||||
* Only storage in these contexts is tied to chat/task lifecycle. Workspace
|
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* files, execution logs, knowledge bases, profile pictures, etc. are owned by
|
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* other subsystems and must never be touched by chat cleanup — even if a row
|
||||
* somehow ends up with `chatId` set through a future flow.
|
||||
*/
|
||||
const CHAT_SCOPED_CONTEXTS = ['copilot', 'mothership'] as const satisfies readonly StorageContext[]
|
||||
type ChatScopedContext = (typeof CHAT_SCOPED_CONTEXTS)[number]
|
||||
|
||||
interface FileRef {
|
||||
key: string
|
||||
context: ChatScopedContext
|
||||
}
|
||||
|
||||
/**
|
||||
* Collect all file storage keys for the given chat IDs from two sources:
|
||||
* 1. workspaceFiles rows with chatId FK (chat-scoped contexts only)
|
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* 2. fileAttachments[].key inside each copilot_messages.content
|
||||
*/
|
||||
export async function collectChatFiles(chatIds: string[]): Promise<FileRef[]> {
|
||||
const files: FileRef[] = []
|
||||
if (chatIds.length === 0) return files
|
||||
|
||||
const seen = new Set<string>()
|
||||
|
||||
for (const chunk of chunkArray(chatIds, CHAT_FILE_COLLECT_CHUNK_SIZE)) {
|
||||
const [linkedFiles, messageRows] = await Promise.all([
|
||||
db
|
||||
.select({ key: workspaceFiles.key, context: workspaceFiles.context })
|
||||
.from(workspaceFiles)
|
||||
.where(
|
||||
and(
|
||||
inArray(workspaceFiles.chatId, chunk),
|
||||
isNull(workspaceFiles.deletedAt),
|
||||
inArray(workspaceFiles.context, [...CHAT_SCOPED_CONTEXTS])
|
||||
)
|
||||
),
|
||||
// Scan every message row for the chat (no deleted_at filter): this is a
|
||||
// deletion path collecting blob keys, so attachments on any row count.
|
||||
db
|
||||
.select({ content: copilotMessages.content })
|
||||
.from(copilotMessages)
|
||||
.where(inArray(copilotMessages.chatId, chunk)),
|
||||
])
|
||||
|
||||
for (const f of linkedFiles) {
|
||||
if (!seen.has(f.key)) {
|
||||
seen.add(f.key)
|
||||
files.push({ key: f.key, context: f.context as ChatScopedContext })
|
||||
}
|
||||
}
|
||||
|
||||
for (const row of messageRows) {
|
||||
const msg = row.content
|
||||
if (!msg || typeof msg !== 'object') continue
|
||||
const attachments = (msg as Record<string, unknown>).fileAttachments
|
||||
if (!Array.isArray(attachments)) continue
|
||||
for (const attachment of attachments) {
|
||||
if (
|
||||
attachment &&
|
||||
typeof attachment === 'object' &&
|
||||
(attachment as Record<string, unknown>).key
|
||||
) {
|
||||
const key = (attachment as Record<string, unknown>).key as string
|
||||
if (!seen.has(key)) {
|
||||
seen.add(key)
|
||||
files.push({ key, context: 'copilot' })
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
return files
|
||||
}
|
||||
|
||||
/** Groups files by storage context so each context can use one batch DELETE call. */
|
||||
export async function deleteStorageFiles(
|
||||
files: FileRef[],
|
||||
label: string
|
||||
): Promise<{ filesDeleted: number; filesFailed: number }> {
|
||||
const stats = { filesDeleted: 0, filesFailed: 0 }
|
||||
if (files.length === 0 || !isUsingCloudStorage()) return stats
|
||||
|
||||
const keysByContext = new Map<ChatScopedContext, string[]>()
|
||||
for (const file of files) {
|
||||
const bucket = keysByContext.get(file.context)
|
||||
if (bucket) bucket.push(file.key)
|
||||
else keysByContext.set(file.context, [file.key])
|
||||
}
|
||||
|
||||
for (const [context, keys] of keysByContext) {
|
||||
const result = await StorageService.deleteFiles(keys, context)
|
||||
stats.filesDeleted += result.deleted
|
||||
stats.filesFailed += result.failed.length
|
||||
for (const { key, error } of result.failed) {
|
||||
logger.error(`[${label}] Failed to delete storage file ${key} (context: ${context}):`, {
|
||||
error,
|
||||
})
|
||||
}
|
||||
}
|
||||
|
||||
return stats
|
||||
}
|
||||
|
||||
/**
|
||||
* Call the copilot backend to delete chat data (memory_files, checkpoints, task_chains, etc.)
|
||||
* Chunked at 1000 per request.
|
||||
*/
|
||||
export async function cleanupCopilotBackend(
|
||||
chatIds: string[],
|
||||
label: string
|
||||
): Promise<{ deleted: number; failed: number }> {
|
||||
const stats = { deleted: 0, failed: 0 }
|
||||
|
||||
if (chatIds.length === 0 || !env.COPILOT_API_KEY) {
|
||||
if (!env.COPILOT_API_KEY) {
|
||||
logger.warn(`[${label}] COPILOT_API_KEY not set, skipping copilot backend cleanup`)
|
||||
}
|
||||
return stats
|
||||
}
|
||||
|
||||
for (let i = 0; i < chatIds.length; i += COPILOT_CLEANUP_BATCH_SIZE) {
|
||||
const chunk = chatIds.slice(i, i + COPILOT_CLEANUP_BATCH_SIZE)
|
||||
try {
|
||||
const response = await fetch(`${SIM_AGENT_API_URL}/api/tasks/cleanup`, {
|
||||
method: 'POST',
|
||||
headers: {
|
||||
'Content-Type': 'application/json',
|
||||
'x-api-key': env.COPILOT_API_KEY,
|
||||
},
|
||||
body: JSON.stringify({ chatIds: chunk }),
|
||||
})
|
||||
|
||||
if (!response.ok) {
|
||||
const errorBody = await response.text().catch(() => '')
|
||||
logger.error(`[${label}] Copilot backend cleanup failed: ${response.status}`, {
|
||||
errorBody,
|
||||
chatCount: chunk.length,
|
||||
})
|
||||
stats.failed += chunk.length
|
||||
continue
|
||||
}
|
||||
|
||||
const result = await response.json()
|
||||
stats.deleted += result.deleted ?? 0
|
||||
logger.info(
|
||||
`[${label}] Copilot backend cleanup: ${result.deleted} chats deleted (batch ${Math.floor(i / COPILOT_CLEANUP_BATCH_SIZE) + 1})`
|
||||
)
|
||||
} catch (error) {
|
||||
stats.failed += chunk.length
|
||||
logger.error(`[${label}] Copilot backend cleanup request failed:`, { error })
|
||||
}
|
||||
}
|
||||
|
||||
return stats
|
||||
}
|
||||
|
||||
/**
|
||||
* Full chat cleanup: collect file refs, then (after DB deletion by caller)
|
||||
* call copilot backend and delete storage files.
|
||||
*
|
||||
* Usage:
|
||||
* const cleanup = await prepareChatCleanup(chatIds, label)
|
||||
* // ... delete DB rows ...
|
||||
* await cleanup.execute()
|
||||
*/
|
||||
export async function prepareChatCleanup(
|
||||
chatIds: string[],
|
||||
label: string
|
||||
): Promise<{ execute: () => Promise<void> }> {
|
||||
// Collect file refs BEFORE DB deletion (keys + context are lost after cascade)
|
||||
const files = await collectChatFiles(chatIds)
|
||||
if (files.length > 0) {
|
||||
logger.info(`[${label}] Collected ${files.length} files for cleanup`, {
|
||||
files: files.map((f) => ({ key: f.key, context: f.context })),
|
||||
})
|
||||
}
|
||||
|
||||
return {
|
||||
execute: async () => {
|
||||
// Call copilot backend
|
||||
if (chatIds.length > 0) {
|
||||
const copilotResult = await cleanupCopilotBackend(chatIds, label)
|
||||
logger.info(
|
||||
`[${label}] Copilot backend: ${copilotResult.deleted} deleted, ${copilotResult.failed} failed`
|
||||
)
|
||||
}
|
||||
|
||||
// Delete storage files with correct context per file
|
||||
if (files.length > 0) {
|
||||
const fileStats = await deleteStorageFiles(files, label)
|
||||
logger.info(
|
||||
`[${label}] Storage cleanup: ${fileStats.filesDeleted} deleted, ${fileStats.filesFailed} failed`
|
||||
)
|
||||
}
|
||||
},
|
||||
}
|
||||
}
|
||||
Reference in New Issue
Block a user