integreat/docs/2026-08-15-sales-summary-rollout-plan.md

Sales-summary balancing — rollout plan

Steps to execute, in order. Every step is either reversible or verifiable before the next one begins. The one behaviour change that alters a client's books is behind a per-client feature flag that is off by default, so merging and deploying this branch changes nothing on its own.

Measured on a restored copy of production (backup point 209608347), 210 clients over 2026-05-10 → 2026-08-07, with the duplicate client records left active exactly as they will be in production: 1,191 client-days out of balance / $70,276.50 → 122 days / $2,379.45, of which only 32 are above ten cents. 1,069 days came into balance, none broke, and no already-balanced day had a figure altered.

Of the $2,379.45 left, just $648.84 across 3 days is on the twenty shared-location records. The other 119 days and $1,730.61 belong to ordinary clients and have not moved across any run of this analysis.

Getting the shared records there needs step 5 — a historical backfill from Square. Without it they carry 423 days and $18,508.39, because re-keying stops the two records fighting but does not give each its own copy of the refunds.

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Before you start

Flag introduced	summary-service-charges — off by default
Migration to run once	auto-ap.jobs.rekey-square-external-ids/migrate-all!
Expected migration runtime	~38 minutes for 19M orders on a warm cache
Nothing here touches	invoices, payments, the ledger, or any client without the flag set

Client configuration is left exactly as it is. Ten Square locations are configured against two client records each, and both stay active. The re-key is what resolves them: once every record carries its owner in its key, each client's import resolves only its own records and the two records keep independent, stable histories. No "which record survives" decision is needed, and nothing is deactivated.

The consequence to be aware of: each Square payment, refund, payout and shift at a shared location becomes two entities, one per client record — by design. That is the stable end state, not a duplicate to clean up. If any report or export aggregates across client records, one restaurant's takings would be counted twice at that layer. Nothing in this work changes that either way.

The only window of risk is between deploying and finishing the migration, while legacy keys still exist for a client to resolve. Steps 2–6 exist to make that window effectively zero.

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Step 1 — Guard remove-voided-orders

Do this before the migration, not after. :sales-order/charges is :db/isComponent true, so retracting an order cascades into its payments. Until step 4 finishes there are still payments with two parent orders, and deleting one client's voided order can take the other client's payment with it.

Either leave remove-voided-orders switched off until step 4 verifies clean, or change it to detach a payment that has more than one parent rather than delete it. Detaching is worth doing regardless — it makes the safety a property of the deletion rather than of the migration having been run first.

See docs/2026-08-15-remove-voided-orders-risk.md.

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Step 2 — Pause the Square importer

This is what makes the deploy safe, and it is easy to skip. Steps 2 through 6 should be one maintenance action, not separate days' work.

While legacy keys exist, square.core3/existing-id falls back to them — and at a shared location that is the one code path that can reach across client records. Running the migration with imports paused means no client is resolving keys while the keys are being rewritten, so the window closes entirely rather than merely narrowing.

The migration itself takes about 38 minutes for all 19M orders, so the pause is short — and if you need it shorter, see step 6: you can resume imports before it finishes.

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Step 3 — Deploy the code

Deploy the branch. The flag is absent from every client, so:

• tips are calculated exactly as they are today,
• no Service Charges line is written.

The only changes that take effect immediately are the safe ones: imbalance logging, the dirty-summary scan bounded to one client (1,321 ms → 5.6 ms per client), the schema-ordering fix, and the importer's new client-scoped keys.

The importer reads both key schemes, so the deploy does not depend on the migration having finished. Two protections cover the interval before it does: imports are paused (step 2), and existing-id refuses to resolve a record that already belongs to a different client. Do not remove the legacy lookup yet — see step 10.

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Step 4 — Run the migration

Run it immediately after the deploy, while imports are still paused.

(require '[auto-ap.jobs.rekey-square-external-ids :as rk])

;; read-only first — no two entities may want the same key. `plan` does NOT return a
;; :collisions key; you have to hand its :new-keys to `collisions` yourself.
(rk/collisions (:new-keys (rk/plan (d/db conn) :charge/external-id rk/charge-prefix)))
;; => []   (anything else: stop, do not migrate)

;; then the whole thing
(rk/migrate-all! 2000)

migrate-all! runs this same check itself, on every attribute including charges, and throws rather than transacting if it finds one. Running it by hand first just means finding out before the 38-minute walk rather than partway through it.

Runs in about thirty-eight minutes over 19M orders. It is idempotent and resumable — a record that already carries the right name is skipped, so it can be stopped and re-run without consequence.

It is also ordered so that stopping early is survivable. Refunds, payouts and cash-drawer shifts go first — a quarter of a million records, seconds of work — so an interruption cannot catch them half done. The long part then walks orders a month at a time, from the current month backwards, logging ::month-complete as each finishes:

::month-complete :month "2026-08" :rekeyed 118203 :cloned 2244
::month-complete :month "2026-07" :rekeyed 241887 :cloned 4611
...

That ordering is the recovery plan. If it dies, everything from the last logged month forward is fully scoped — and that recent window is what the importer actually reads — so you can resume imports against a partially migrated database and finish the older tail later. Walking oldest first would have spent the first several hours on 2019 data no import will touch, leaving exactly the wrong end done.

If you do resume imports mid-migration, the ownership guard in existing-id is what keeps the unmigrated tail safe: a client cannot resolve onto another client's legacy-keyed record.

If it appears to crawl, the cause is almost certainly garbage collection in the process driving it, not the transactor. That misdiagnosis cost two days of projected runtime during this work. Free retained memory in the REPL and re-measure before changing anything about the database.

Verify. Two checks, doing two different jobs — run both.

(a) Completeness, across everything. plan must report nothing left to do, for all four attributes:

(dissoc (rk/plan (d/db conn) :charge/external-id rk/charge-prefix) :new-keys)
;; => {:total 17045933 :to-migrate 0 :already-scoped 17045933 :unscopable 0}

Read :to-migrate 0 and :unscopable 0. This is the authoritative signal, and it covers all 17M charges.

unscoped-report is useful colour but is not the gate: its :no-owner column never reaches zero for charges, because ~283k payout stubs carry no :charge/client of their own and it classifies by attribute rather than by resolving ownership. Judge completeness by plan.

(b) The safety gate for the cascade — no payment may answer to two orders, or re-enabling remove-voided-orders in step 9 can delete a payment another order still needs. Check every order in the last year, with no sampling:

(let [db   (d/db conn)
      cs   (map first (d/q '[:find ?c :where [?c :client/code _]] db))
      year (java.util.Date. (- (.getTime (java.util.Date.)) (long (* 365 86400000))))]
  (rk/charges-with-multiple-parents
    db (map first (iol-ion.query/scan-sales-orders db cs year nil))))
;; => 0

On the restored copy that is 5,158,470 orders — 27% of the table — via the :sales-order/client+date index. A year is chosen deliberately: remove-voided-orders only ever deletes orders Square reports as voided, which are recent, so that is where the destructive risk lives. Completeness across all of history is check (a)'s job, not this one.

Do not sample this with (take n (rk/all-order-ids db)). all-order-ids streams :aevt, which is ascending entity id, so a take returns the oldest orders — on the restored copy the first 400,000 are all from 2019–2021, before any of the contention this gate looks for. It would report a confident zero having inspected none of the relevant data.

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Step 5 — Backfill the shared-location clients from Square

Skip this and the ten duplicated restaurants stay badly out of balance. It is the difference between 122 client-days out of balance and 542.

Sales orders have always been keyed by client, so both records of a pair built their own order history. Refunds, payouts and cash-drawer shifts were not, so only ONE record holds each of them. Re-keying freezes that ownership; it does not even it out. The record left without them shows returns from its own orders and no refunds against them — NGBK held 158,535 orders and five refunds — and is out of balance by exactly what its twin is holding.

Rather than manufacture copies, ask Square again. Client-scoped keys mean each record now creates its own copy of whatever it reads, so replaying the window makes the two histories converge:

(require '[auto-ap.square.core3 :as sq])
(require '[clj-time.core :as t])

@(apply sq/backfill-history
        (t/date-time 2026 5 10) (t/date-time 2026 8 9)
        ["NGBK" "NGBR" "NGCD" "NGCC" "NGVG" "NGVC" "NGEZ" "NGJS" "NGDG" "NGDU"
         "NGDV" "NGDS" "NGWC" "NGWN" "NGHY" "NGHA" "NGDA" "NGDL" "NGCL" "NGCT"])

Verify — every pair should hold matching order and refund counts in the window:

;; per pair, per side: window orders and window refunds. The two sides should agree.

Measured on the restored copy: all ten pairs matched afterwards, and the shared records went from 423 days and $18,508.39 out of balance to 3 days and $648.84.

Budget an overnight run. This took 5.9 hours for ninety days across the twenty records. Every Square call in the process shares one 25-requests-per-second throttle, refunds and shifts cost one API call per record, and backfill-history imports three clients at a time — raise its s/buffer if you need it faster. Neither the database nor the transactor is the limit; reads measured at 32 µs.

It must run after the migration. Run before, and it imports against legacy keys and leaves more to migrate.

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Step 6 — Resume the Square importer

Normally: once step 4's two checks read clean and step 5's backfill has finished. The maintenance window ends here.

If the migration did not finish, you do not have to wait for it. Resume imports once the ::month-complete log covers the window your importer reads — the last 75 days for payouts and cash-drawer shifts, and whatever range the order import is configured for. Then re-run migrate-all! afterwards to walk the remaining older months; it will skip everything already done. Run the step 4 checks again once it does finish.

The first cycle after resuming is the one to watch. Compare these against the same counts taken immediately before the deploy — growth should be ordinary daily volume:

(count (d/datoms (d/db conn) :aevt :sales-refund/external-id))
(count (d/datoms (d/db conn) :aevt :expected-deposit/external-id))
(count (d/datoms (d/db conn) :aevt :cash-drawer-shift/external-id))
(count (d/datoms (d/db conn) :aevt :charge/external-id))

A near-doubling of any of them means records are being created rather than matched — stop and roll back the deploy. Charges are included deliberately: they are the one that doubles a client's takings rather than merely duplicating a row.

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Step 7 — Recompute summaries, flags still off

(require '[auto-ap.jobs.sales-summaries :as ss])
(ss/refresh-sales-summaries 90)

This is the pass that banks the deduplication. Capture the result before going further — you will need it as the baseline for step 8, and it cannot be reconstructed afterwards:

(require '[auto-ap.tools.compare-sales-summaries :as cmp])   ; test/dev classpath
(def before (cmp/summaries-in (d/db conn) start end))
(spit "before.edn" (pr-str before))

Do not use d/as-of to compare summary amounts. :ledger-mapped/amount, ledger-side and account are :db/noHistory, so past values are discarded. A summary that has since been recomputed reads back through as-of with its amounts absent, which looks like a legitimate balanced day. Capture live, before and after, and diff the captures.

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Step 8 — Turn the flag on, a few restaurants at a time

Needs accounting sign-off first: summary-service-charges posts to 49000 Service Income, chosen so the work could be measured. It affects reporting, never whether a day balances.

@(d/transact conn [{:db/id [:client/code "NGxx"]
                    :client/feature-flags ["summary-service-charges"]}])
(ss/refresh-sales-summaries 90)

Start with two or three restaurants, confirm, then widen.

Verify against the capture from step 7:

(def after (cmp/summaries-in (d/db conn) start end))
(cmp/compare-window ...)   ; both arguments live database values, never as-of

The two numbers that matter — both were zero across all 18,900 client-days in testing:

• :balanced->unbalanced must be 0
• previously-balanced days whose lines changed must be 0

If either is non-zero, retract the flag for the affected clients and re-run step 7. The flag is the rollback: removing it restores today's behaviour exactly.

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Step 9 — Re-enable remove-voided-orders

Safe once step 4's gate reads zero. Keep the detach-rather-than-delete guard from step 1.

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Step 10 — Remove the legacy key lookup

Schedule this; do not leave it open-ended. Both client records at a shared location stay active permanently, so the legacy fallback in square.core3/existing-id is the one code path that can ever reach across them. Deleting it is what turns the guarantee from conventional into structural.

Once plan reports :to-migrate 0 and has stayed there through several import cycles, drop the legacy branch of existing-id — and with it owned-by-other-client?, which exists only to make that branch safe while it lives. After this, two clients on one location are structurally incapable of resolving onto each other's records, and no ordering discipline is required to keep it that way.

Until it is done, the protection is the guard plus the maintenance window, both of which depend on people doing the right thing. That is the reason not to let this drift.

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Step 11 — Deal with the refunds that have no sales behind them

The most important item in this document, and the only one that is not just execution.

171 of the 542 remaining days are a record carrying refunds on a day it recorded no sales at all. 140 of those fall before that client's first ever order. Nine records are affected, holding 660 refunds worth $15,237.02 dated before their own first order:

Client	First order	Refunds before it	Value
NGDL	2026-07-29	96	$2,751.50
NGWN	2026-07-30	95	$2,218.61
NGDU	2026-08-02	94	$2,188.44
NG4S	2026-05-29	79	$2,180.08
NGPS	2026-05-26	81	$2,167.60
NGCT	2026-08-01	98	$1,789.49
NGVC	2026-08-02	95	$1,594.17
NGDS	2026-01-14	22	$347.13

They did not make those refunds. The database's own ownership history shows a $35.35 refund dated 26 February belonging to NGDG that day and taken over by NGDU on 12 August, with others flipping between the two several times a day across 12–15 August. Unscoped refund keys meant whichever import ran last took ownership — fault 1, seen from the other end. Steps 1 and 4 stop it recurring; they do not undo it.

Note NG4S and NGPS are not among the ten shared locations, so this is wider than the duplicate records.

Two ways to close it, and the business has to pick:

1. Import the missing sales. Correct if these records are meant to have their own books. Their refunds are real and the matching orders exist in Square.
2. Move the refunds to the record that has the sales. Correct if the record is a duplicate that should never have had books of its own.

Before either, check whether the surviving record already holds the same Square refund — within the ninety-day window all 192 orphans did, but outside it payouts and shifts have no counterpart at all, so a blanket delete would destroy the only copy of some records.

;; per client: refunds dated before that client's own first order
(let [first-order (->> (d/q '[:find [?d ...] :in $ ?c
                              :where [?o :sales-order/client ?c] [?o :sales-order/date ?d]]
                            (d/db conn) [:client/code "NGDU"])
                       (reduce (fn [a b] (if (.before a b) a b))))]
  (->> (d/q '[:find [(pull ?r [:sales-refund/date :sales-refund/total]) ...] :in $ ?c
              :where [?r :sales-refund/client ?c]]
            (d/db conn) [:client/code "NGDU"])
       (filter #(.before (:sales-refund/date %) first-order))
       count))

Until this is resolved those days stay out of balance, on purpose. A summary change to close them was written and measured — it works, closes 171 days and $5,795.18, and breaks nothing — and it was removed, because an unbalanced day is the only visible signal that a restaurant's sales are not being imported. A test asserts the day stays unbalanced so nobody closes it without reading this.

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What this will not fix

The 371 real trading days still out of balance, $14,443.82 — of which $13,940.86 is on the twenty shared-location records, where the two books disagree about who owns what. For every other client it is 103 days and $502.96. Named causes: the NGBR/NGBK tender gap ($6,358.99 of tender against $6,059.57 of order totals on one day), the ezCater fee question, and unexplained clusters on NGMV and NGEB.

Plus 16 days / $1,227.65 where a processing fee lands on a day with no trading — the same shape as step 11 but from the payout side, so it needs the payout modelled rather than a rule in the summary.

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Two operational findings, unrelated to the summaries

• The production backup had not written a restore point since 2025-03-10 — about seventeen months — although data files were still uploading daily. Worth an alert on restore-point age.
• The database server is sized for a much smaller dataset: a 2 GB cache against 27 GB of data. Worth checking what production is set to.