DBA Table Modifications – Oracle EBS SQL Report
Oracle E-Business Suite SQL report from the Enginatics Library powered by Blitz Report™.
Overview
If table monitoring is activated, dba_tab_modifications shows the number of rows modified since the last time a table was analyzed.
Report Parameters
Changes per Day From, Last Analyzed within x Days
Oracle EBS Tables Used
dba_tab_modifications, dba_tables
Report Categories
Related Reports
Blitz Report VPD Policy Setup, FND Audit Setup, DBA Object Access Privileges, DBA Table Columns, DBA Blitz Report ORDS Configuration, DBA ORDS Configuration Validation, FND Lookup Search, DBA AWR Active Session History, DBA SGA Active Session History
Running This SQL Without Blitz Report
Some Oracle EBS SQL reports in this library require functions from the utility package xxen_util. Install it before running the SQL directly against your Oracle EBS database.
Download & Import Options
| Resource | Link |
|---|---|
| Excel Example Output | DBA Table Modifications 14-Oct-2021 105513.xlsx |
| Blitz Report™ XML Import | DBA_Table_Modifications.xml |
| Full SQL on Enginatics | www.enginatics.com/reports/dba-table-modifications/ |
Case Study & Technical Analysis
Abstract
The DBA Table Modifications report leverages the database’s internal monitoring mechanism to track data manipulation language (DML) activity. It queries DBA_TAB_MODIFICATIONS, which records the approximate number of INSERT, UPDATE, and DELETE operations performed on a table since the last time optimizer statistics were gathered. This report is essential for understanding data volatility and tuning statistics gathering strategies.
Technical Analysis
Core Metrics
- Inserts/Updates/Deletes: The raw count of row changes.
- Timestamp: The time of the last analysis vs. the timestamp of the modification data.
- Truncated: A flag indicating if the table was truncated (which resets the high water mark but might not trigger a stats update immediately).
Key View
DBA_TAB_MODIFICATIONS: This view is populated by the database kernel in memory and flushed to disk periodically (or manually viaDBMS_STATS.FLUSH_DATABASE_MONITORING_INFO).
Operational Use Cases
- Stale Statistics: Identifying tables that have changed significantly (e.g., >10% of rows) but haven’t been analyzed, leading to poor execution plans.
- Batch Verification: Confirming that a nightly load job actually processed data.
- Volatility Profiling: Distinguishing between static lookup tables and high-churn transaction tables.
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