| 1 | import * as GCP from "alchemy/GCP"; |
| 2 | import * as Clock from "effect/Clock"; |
| 3 | import * as Effect from "effect/Effect"; |
| 4 | import { |
| 5 | Orders, |
| 6 | Reports, |
| 7 | summaryKey, |
| 8 | type DailySummary, |
| 9 | type RegionTotal, |
| 10 | } from "./resources.ts"; |
| 11 | |
| 12 | const DAY_MS = 24 * 60 * 60 * 1000; |
| 13 | |
| 14 | /** |
| 15 | * The nightly batch: roll the last 24 hours of orders up into one JSON |
| 16 | * summary in Cloud Storage. |
| 17 | * |
| 18 | * A Cloud Run Job runs to completion and exits, so nothing is billed |
| 19 | * between runs. It is started by Cloud Scheduler every night and by the |
| 20 | * admin route in {@link ../Admin.ts} on demand; both paths create a new |
| 21 | * execution through the Cloud Run Admin API. |
| 22 | * |
| 23 | * Re-running is safe: a run for the same day overwrites that day's |
| 24 | * object with a fresh aggregate. |
| 25 | */ |
| 26 | export default class Summarize extends GCP.Run.Job<Summarize>()( |
| 27 | "Summarize", |
| 28 | { |
| 29 | main: import.meta.url, |
| 30 | // A failed summary is retried once, then the execution fails and the |
| 31 | // next trigger tries again. |
| 32 | maxRetries: 1, |
| 33 | timeout: "300s", |
| 34 | }, |
| 35 | Effect.gen(function* () { |
| 36 | const table = yield* Orders; |
| 37 | const orders = yield* GCP.BigQuery.ReadTable(table); |
| 38 | const reports = yield* GCP.Storage.WriteBucket(Reports); |
| 39 | // The table id is bound at deploy time and read inside `run`. |
| 40 | const tableId = yield* table.tableId; |
| 41 | |
| 42 | return { |
| 43 | run: Effect.gen(function* () { |
| 44 | const to = new Date(yield* Clock.currentTimeMillis); |
| 45 | const from = new Date(to.getTime() - DAY_MS); |
| 46 | // Cloud Run names each execution in the task's environment. |
| 47 | const execution = yield* Effect.sync( |
| 48 | () => process.env.CLOUD_RUN_EXECUTION ?? null, |
| 49 | ); |
| 50 | |
| 51 | // Unqualified table names resolve against the table's dataset. |
| 52 | const rows = yield* orders.query( |
| 53 | `SELECT region, COUNT(*) AS orders, SUM(amountCents) AS revenueCents |
| 54 | FROM \`${yield* tableId}\` |
| 55 | WHERE occurredAt >= TIMESTAMP(@from) AND occurredAt < TIMESTAMP(@to) |
| 56 | GROUP BY region |
| 57 | ORDER BY region`, |
| 58 | { from: from.toISOString(), to: to.toISOString() }, |
| 59 | ); |
| 60 | |
| 61 | const regions: RegionTotal[] = rows.map((row) => ({ |
| 62 | region: String(row.region), |
| 63 | orders: Number(row.orders), |
| 64 | revenueCents: Number(row.revenueCents ?? 0), |
| 65 | })); |
| 66 | |
| 67 | const summary: DailySummary = { |
| 68 | from: from.toISOString(), |
| 69 | to: to.toISOString(), |
| 70 | execution, |
| 71 | orders: regions.reduce((n, r) => n + r.orders, 0), |
| 72 | revenueCents: regions.reduce((n, r) => n + r.revenueCents, 0), |
| 73 | regions, |
| 74 | }; |
| 75 | |
| 76 | const key = summaryKey(to); |
| 77 | yield* reports.put(key, JSON.stringify(summary, null, 2), { |
| 78 | contentType: "application/json", |
| 79 | }); |
| 80 | yield* Effect.log( |
| 81 | `summarize: ${summary.orders} order(s) in ${regions.length} region(s) -> ${key}`, |
| 82 | ); |
| 83 | }).pipe(Effect.orDie), |
| 84 | }; |
| 85 | }).pipe( |
| 86 | Effect.provide([GCP.BigQuery.ReadTableHttp, GCP.Storage.WriteBucketHttp]), |
| 87 | ), |
| 88 | ) {} |