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In the examples below each trigger is modifying a different table, by looking at what is being modified you can see some common applications of when different trigger types are used. The following is an Oracle syntax example of a row level trigger that is called AFTER an update FOR EACH ROW affected.
In relational databases, the log trigger or history trigger is a mechanism for automatic recording of information about changes inserting or/and updating or/and deleting rows in a database table. It is a particular technique for change data capturing , and in data warehousing for dealing with slowly changing dimensions .
For optimistic locking each row has an independent version number, typically a sequential counter. This allows a process to atomically update a row and increment its counter only if another process has not incremented the counter. But CDC cannot use row-level versions to find all changes unless it knows the original "starting" version of every row.
You also specify the timing point, which determines whether the trigger fires before or after the triggering statement runs and whether it fires for each row that the triggering statement affects. If the trigger is created on a table or view, then the triggering event is composed of DML statements, and the trigger is called a DML trigger.
This is analogous to a record level lock and is normally the highest degree of locking granularity in a database management system. In a SQL database, a record is typically called a "row". The introduction of granular (subset) locks creates the possibility for a situation called deadlock .
The Start date/time of the second row is equal to the End date/time of the previous row. The null End_Date in row two indicates the current tuple version. A standardized surrogate high date (e.g. 9999-12-31) may instead be used as an end date, so that the field can be included in an index, and so that null-value substitution is not required ...
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Over time, the attributes of a given row in a dimension table may change. For example, the shipping address for a company may change. Kimball refers to this phenomenon as slowly changing dimension. Strategies for dealing with this kind of change are divided into three categories: Type one: Simply overwrite the old value(s).