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Overview
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Overview

APPS.CSP_USAGE_HISTORIES_V1 is a supplementary view in the Oracle E-Business Suite Applications (APPS) schema, registered under FND Design Data as CSP.CSP_USAGE_HISTORIES_V1. It is classified as a "supplementary view used to simplify forms coding" — a pattern Oracle employs to wrap complex form-block queries behind a stable, single-object name. The view exposes usage history data at the intersection of inventory items, organizations, subinventories, hierarchy nodes, and time periods, and it is a component of the CSP (Spares/Customer Service Procurement or field service-related) module family. In Oracle EBS 12.1.1 and 12.2.2 the object retains a VALID status, and its structure and column list are consistent across both releases.

The view's principal purpose is reporting and integration around demand and consumption. It aggregates usage, sales order, and forecast quantities into a single, period-aligned record, making it practical for downstream analytics, replenishment planning, and service parts forecasting. Oracle's own documentation explicitly cautions that the view is intended for forms coding and is not recommended for direct querying or data alteration, since its definition may change substantially in subsequent minor or major releases.

Underlying Base Objects

The view is defined over a single documented base object: CSP_USAGE_HISTORIES, exposed as a synonym within the APPS schema. The dependency metadata records no other base tables, and the view is not referenced by any database object, confirming it is a terminal, read-oriented construct rather than a dependency for further database logic.

Because the view is derived from CSP_USAGE_HISTORIES, all column semantics, data types, and precision originate in that underlying table. Any change to the base table's structure or content directly affects results returned through the view, which reinforces the caution against treating the view as a stable public interface.

Key Columns

The view exposes eleven columns spanning temporal, organizational, item, and quantitative dimensions:

  • PERIOD_START_DATE (DATE) — the opening date of the reporting period to which each usage record belongs.
  • PERIOD_TYPE (VARCHAR2(30)) — the granularity or category of the period (for example weekly, monthly, or another defined classification).
  • INVENTORY_ITEM_ID (NUMBER(35)) — the unique identifier of the inventory item.
  • ORGANIZATION_ID (NUMBER(35)) — the inventory organization context for the record.
  • PARTS_LOOP_ID (NUMBER(35)) — an internal grouping identifier used to associate related item records.
  • SUBINVENTORY_CODE (VARCHAR2(30)) — the subinventory name where the activity occurred.
  • HIERARCHY_NODE_ID (NUMBER(35)) — the identifier of the hierarchy node, supporting roll-up reporting.
  • USAGE_QUANTITY (NUMBER) — the quantity consumed in the period.
  • SO_QUANTITY (NUMBER) — the sales order quantity, representing demand captured from sales order transactions.
  • FORECAST_QUANTITY (NUMBER) — the forecasted quantity for the period.
  • TOTAL (NUMBER) — the combined usage plus sales order quantity.

Common Use Cases and Queries

Typical use cases include period-over-period consumption analysis, reconciliation of actual usage against sales orders and forecasts, and demand aggregation by subinventory or hierarchy node. A basic query returning usage and sales order quantities for a specific item and organization is shown below.

SELECT PERIOD_START_DATE, PERIOD_TYPE, INVENTORY_ITEM_ID, ORGANIZATION_ID, SUBINVENTORY_CODE, USAGE_QUANTITY, SO_QUANTITY, FORECAST_QUANTITY, TOTAL
FROM APPS.CSP_USAGE_HISTORIES_V1
WHERE INVENTORY_ITEM_ID = :item_id
AND ORGANIZATION_ID = :org_id
ORDER BY PERIOD_START_DATE;

For trend analysis, analysts group by period and aggregate the quantities: SELECT PERIOD_START_DATE, PERIOD_TYPE, SUM(USAGE_QUANTITY) USAGE, SUM(SO_QUANTITY) SALES_ORDERS, SUM(TOTAL) COMBINED FROM APPS.CSP_USAGE_HISTORIES_V1 WHERE ORGANIZATION_ID = :org_id GROUP BY PERIOD_START_DATE, PERIOD_TYPE ORDER BY PERIOD_START_DATE. Because the underlying metadata warns that direct querying is not recommended, consumers should evaluate whether the base CSP_USAGE_HISTORIES table or a supported reporting interface is more appropriate for production integrations.