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EBS Reference

AR_PAYMENT_SCHEDULES_ALL

Schema: ARtransactionOU-striped (ORG_ID)

The open-receivables engine — one row per transaction installment AND one row per receipt, carrying original and remaining amounts, due date, and closure state; what aging, DSO, and collections analytics read

Identity
Module: FinancialsOperating-unit striped (ORG_ID)
Grain note

Transactions AND receipts both write rows here, with opposite signs (debits positive, credits and receipts negative), and split terms produce several installments per transaction — filter CLASS before aging AR

Notes

CLASS separates the row kinds (invoice, credit memo, receipt…) per the data dictionary's own enumeration; STATUS moves OP to CL when the remaining amount reaches zero. Open AR is the STORED remaining amount — the deliberate contrast with the quantity side, where open is always arithmetic.

What the badges mean
Schema: INV
Schema: the Oracle product schema that owns the table (INV, ONT, WSH, PO, BOM, WIP, MRP, MSC, AR, AP, GL, HR, APPLSYS) — tells you which product family the object belongs to, not who can query it.
master
Data class: what the table holds — master data, transaction documents, control/configuration, interface/staging, or an APPS-schema view.

Structural facts — how the table is partitioned, not a trap by itself

OU-striped (ORG_ID)
Rows are scoped to an operating unit. A landed extract carries every operating unit’s rows — filter or join on ORG_ID, and don’t confuse it with ORGANIZATION_ID (see the quirks guide).
Per inventory org
Rows are scoped to an inventory organization (plant or warehouse) via ORGANIZATION_ID — a different partition from OU-striped tables (see the quirks guide).
Language-striped
The table carries a LANGUAGE column (a _TL translation table or FND_LOOKUP_VALUES) — one row per language. Filter to one LANGUAGE or a join multiplies rows (see the quirks guide).

Join & extract hazards — verify before you rely on this

View
This is an APPS-schema convenience view, not a physical table. Extract the base tables it joins instead — views can be slow at scale and aren't guaranteed stable across patches.
In field listings, the Key chip marks a primary-key field.

Fields

18 fields · 1 key

18 fields.

Table fields: position, field name, description, data type, and flags. 18 fields.
#FieldDescriptionTypeFlags
1PAYMENT_SCHEDULE_IDSurrogate key of the schedule rowNUMBER
Primary-key field
2ORG_IDOperating unitNUMBER
3CUSTOMER_TRX_IDThe transaction — populated on transaction rows, NULL on receipt rowsNUMBER
4CASH_RECEIPT_IDThe receipt — populated on receipt rowsNUMBER
5CUSTOMER_IDThe customer accountNUMBER
6CUSTOMER_SITE_USE_IDThe bill-to site useNUMBER
7CLASSRow kind — INV, DM, GUAR, CM, DEP, CB, PMT, BR (per the data dictionary's enumeration); PMT rows are receiptsVARCHAR2
8STATUSOP while open, CL once the remaining amount reaches zeroVARCHAR2
9DUE_DATEWhen the installment falls due — the aging dateDATE
The table's primary analysis date — a real DATE column, no conversion needed
10TRX_DATEThe transaction date, denormalizedDATE
11TRX_NUMBERThe document number, denormalizedVARCHAR2
12AMOUNT_DUE_ORIGINALOriginal amount — debits positive, credits and receipts NEGATIVE (the sign convention)NUMBER
13AMOUNT_DUE_REMAININGThe open amount — stored, not arithmetic; what aging sumsNUMBER
14AMOUNT_APPLIEDAmount applied to dateNUMBER
15TERMS_SEQUENCE_NUMBERThe installment number — split terms produce several rows per transactionNUMBER
16INVOICE_CURRENCY_CODECurrency of the amountsVARCHAR2
17GL_DATEThe accounting dateDATE
18ACTUAL_DATE_CLOSEDWhen the row actually closedDATE

Field provenance: hand-curated. 1 key field.

Boilerplate SQL

Starting point for reading AR_PAYMENT_SCHEDULES_ALL on Databricks — real DATE columns need no conversion, and the org anchor is already in place. The optional LAST_UPDATE_DATE watermark is included. Set your Unity Catalog location, schema, and org values below; they’re substituted into the SQL and the copy button.

Query parameters

7 parameters not filled: <catalog>, <schema>, <operating_unit_id>, <PAYMENT_SCHEDULE_ID>, <DATE_FROM>, <DATE_TO>, <watermark>

-- ============================================================
-- Table  : AR_PAYMENT_SCHEDULES_ALL — The open-receivables engine — one row per transaction installment AND one row per receipt, carrying original and remaining amounts, due date, and closure state; what aging, DSO, and collections analytics read
-- Purpose: Column-selected read of AR_PAYMENT_SCHEDULES_ALL — auto-generated from field metadata
-- Grain  : One row per operating unit (ORG_ID) + PAYMENT_SCHEDULE_ID
-- Caution: Transactions AND receipts both write rows here, with opposite signs (debits positive, credits and receipts negative), and split terms produce several installments per transaction — filter CLASS before aging AR
-- Notes  : Auto-generated skeleton for Oracle EBS R12 data landed in your lakehouse. Dates are real DATE/TIMESTAMP columns — no conversion needed. WHO audit columns omitted (see the quirks guide); the optional LAST_UPDATE_DATE watermark filter supports incremental extracts.
-- ============================================================
SELECT
  t.PAYMENT_SCHEDULE_ID AS "Surrogate key of the schedule row",
  t.ORG_ID AS "Operating unit",
  t.CUSTOMER_TRX_ID AS "The transaction — populated on transaction rows, NULL on receipt rows",
  t.CASH_RECEIPT_ID AS "The receipt — populated on receipt rows",
  t.CUSTOMER_ID AS "The customer account",
  t.CUSTOMER_SITE_USE_ID AS "The bill-to site use",
  t.CLASS AS "Row kind — INV, DM, GUAR, CM, DEP, CB, PMT, BR (per the data dictionary's enumeration); PMT rows are receipts",
  t.STATUS AS "OP while open, CL once the remaining amount reaches zero",
  t.DUE_DATE AS "When the installment falls due — the aging date",
  t.TRX_DATE AS "The transaction date, denormalized",
  t.TRX_NUMBER AS "The document number, denormalized",
  t.AMOUNT_DUE_ORIGINAL AS "Original amount — debits positive, credits and receipts NEGATIVE (the sign convention)",
  t.AMOUNT_DUE_REMAINING AS "The open amount — stored, not arithmetic; what aging sums",
  t.AMOUNT_APPLIED AS "Amount applied to date",
  t.TERMS_SEQUENCE_NUMBER AS "The installment number — split terms produce several rows per transaction",
  t.INVOICE_CURRENCY_CODE AS "Currency of the amounts",
  t.GL_DATE AS "The accounting date",
  t.ACTUAL_DATE_CLOSED AS "When the row actually closed"
FROM <catalog>.<schema>.AR_PAYMENT_SCHEDULES_ALL t
WHERE
  t.ORG_ID = <operating_unit_id>  -- operating unit (MOAC does not filter extracts)
  -- AND t.PAYMENT_SCHEDULE_ID = <PAYMENT_SCHEDULE_ID>
  -- AND t.DUE_DATE >= DATE '<DATE_FROM>'
  -- AND t.DUE_DATE <= DATE '<DATE_TO>'
  -- AND t.LAST_UPDATE_DATE >= TIMESTAMP '<watermark>'  -- WHO watermark, bulk-stamped by batch jobs; see quirks guide #who-columns
ORDER BY t.PAYMENT_SCHEDULE_ID;

Verified September 2026

Relationships

Diagram of 1-hop neighbors — join details below. FND lookup decode and translation edges are highlighted; they’re the joins newcomers most often get wrong.

Join details

  • AR_PAYMENT_SCHEDULES_ALLRA_CUSTOMER_TRX_ALLforeign key · N:1
    ON AR_PAYMENT_SCHEDULES_ALL.CUSTOMER_TRX_ID = RA_CUSTOMER_TRX_ALL.CUSTOMER_TRX_ID AND AR_PAYMENT_SCHEDULES_ALL.ORG_ID = RA_CUSTOMER_TRX_ALL.ORG_ID
  • AR_PAYMENT_SCHEDULES_ALLAR_CASH_RECEIPTS_ALLforeign key · N:1
    ON AR_PAYMENT_SCHEDULES_ALL.CASH_RECEIPT_ID = AR_CASH_RECEIPTS_ALL.CASH_RECEIPT_ID AND AR_PAYMENT_SCHEDULES_ALL.ORG_ID = AR_CASH_RECEIPTS_ALL.ORG_ID
  • AR_PAYMENT_SCHEDULES_ALLHZ_CUST_ACCOUNTSforeign key · N:1
    ON AR_PAYMENT_SCHEDULES_ALL.CUSTOMER_ID = HZ_CUST_ACCOUNTS.CUST_ACCOUNT_ID

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