Search Results ar_xml_so_info_v




Overview
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Overview

AR_XML_SO_INFO_V is a public synonym exposed by the APPS schema in Oracle E-Business Suite Receivables (AR). It is a lightweight, purpose-built view that surfaces sales order reference information for customer transaction lines, together with five extensible user columns populated at query time by PL/SQL functions. The view exists to support XML-based outbound documents generated by Receivables — most notably invoice and credit memo extracts — where the trading partner or downstream system requires the originating sales order context alongside each transaction line.

Unlike a conventional reporting view that materializes stored columns, AR_XML_SO_INFO_V combines two static business columns from the transaction line with five dynamically computed expression columns. This design allows implementations to substitute their own business logic — for example, pulling a contract number, a project reference, or a drop-ship identifier — without altering the view definition itself. The status of the object is documented as VALID in ETRM, confirming that it compiles cleanly in both 12.1.1 and 12.2.2 reference environments.

Underlying Base Objects

The view is defined over two documented dependencies. The primary source object is RA_CUSTOMER_TRX_LINES, accessed through its APPS synonym, which supplies the transaction line grain and the sales order attributes. Every row returned by the view corresponds to exactly one customer transaction line that has a non-null SALES_ORDER value; lines without an associated sales order are filtered out by the WHERE clause and never appear.

The second dependency is the AR_XML_VIEW_FUNCTIONS package. Five functions in this package — SO_FUNCTION1 through SO_FUNCTION5 — are invoked once per row and exposed as USER1 through USER5. Because these are PL/SQL calls embedded in a SQL statement, the view carries the usual performance characteristics of function-based row-level expressions: each function executes for every qualifying row unless the optimizer is able to cache or short-circuit the result.

Key Columns

  • CUSTOMER_TRX_LINE_ID — Primary identifier of the customer transaction line. Joins directly to RA_CUSTOMER_TRX_LINES.CUSTOMER_TRX_LINE_ID and is the anchor for linking back to the invoice or credit memo header.
  • SALES_ORDER — Sales order number from the originating order management transaction. Not null is enforced by the view predicate.
  • SALES_ORDER_REVISION — Revision indicator for the sales order, useful where orders are amended after booking.
  • SALES_ORDER_DATE — Booking or order date carried through from the order line.
  • SALES_ORDER_LINE — Line number within the sales order, enabling line-level reconciliation between order and invoice.
  • USER1 – USER5 — Extensible descriptors computed by AR_XML_VIEW_FUNCTIONS. These carry implementation-defined values returned by SO_FUNCTION1 through SO_FUNCTION5, typically requiring both CUSTOMER_TRX_ID and CUSTOMER_TRX_LINE_ID, and are intended for custom XML document attributes rather than standard reporting.

Common Use Cases and Queries

The principal use case is the Receivables XML invoice extract, where the publishing program needs order reference data per invoice line without joining to the full order management schema. A typical reconciliation query joins the view back to the transaction line and header:

  • Listing all invoice lines tied to a given sales order, including revision and line number, for order-to-cash analysis.
  • Retrieving the five user attributes for a specific transaction line during XML document generation or partner-specific remittance formatting.
  • Auditing which invoiced lines carry sales order references versus those that do not.

Sample query:

  • SELECT v.customer_trx_line_id, v.sales_order, v.sales_order_revision, v.sales_order_date, v.sales_order_line, v.user1, v.user2 FROM ar_xml_so_info_v v WHERE v.sales_order = :p_order;

Because the USER columns invoke PL/SQL, queries that do not require them should select only the five base columns to avoid unnecessary function execution and improve response time on high-volume extracts.