Trigger updating same table sql server Xxl video sex
We will create an inventory table, an audit table and triggers for inserting, updating, and deleting of inventory data.In our trigger, we will get all the Inventory transaction and store all the history information in an audit table.Before the update, we can see the actual data of both Inventory and audit tables.Now we are going to update Item No ‘I001’ for date ‘20161205’ and for Inventory Seq no=3 with quantity as 120 now we can see the inserted original quantity is 40 from above result.But for audit table we can see only one records inserted with result as quantity as 110 which is the sum of the quantity of all In transactions less the sum of all Out.Now we can do few more insert tests with insert stock in and stock out quantity with the different date for the same item.Additional Read about GO operator: SQL SERVER – Explanation SQL Command GOReference: Pinal Dave (https://blog.sqlauthority.com) Pinal Dave is a SQL Server Performance Tuning Expert and an independent consultant.He has authored 11 SQL Server database books, 23 Pluralsight courses and has written over 4700 articles on the database technology on his blog at a https://blog.
In the resulting quantity, we have an actual result of stock quantity after Stock in and Stock out.
I searched and noticed that it was used in the name of the Stored Procedure.
I finally came up with second method which worked fine.2) Change the batch separator.
The example illustrates the kind of logical processing that can be created within the auditing layer itself Step 1 Create Inventory Database: First, we will create an inventory database for our Inventory table, audit table and auditing Trigger for Insert/Update and delete.
We have now created our tables for Inventory Management and auditing.
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Audit tables will have all the same columns of the audited table columns, in our example, along with who made the changes (user), when the change was made (date of transaction insert/update and delete), what data changed and the before and after views of changed data.