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In SQL, the TRUNCATE TABLE statement is a data manipulation language (DML) [1] operation that deletes all rows of a table without causing a triggered action. The result of this operation quickly removes all data from a table , typically bypassing a number of integrity enforcing mechanisms.
The DROP statement is distinct from the DELETE and TRUNCATE statements, in that DELETE and TRUNCATE do not remove the table itself. For example, a DELETE statement might delete some (or all) data from a table while leaving the table itself in the database, whereas a DROP statement removes the entire table from the database.
Transaction log - DELETE needs to read records, check constraints, update block, update indexes, and generate redo / undo. All of this takes time, hence it takes time much longer than with TRUNCATE; reduces performance during execution - each record in the table is locked for deletion; DELETE uses more transaction space than the TRUNCATE statement
SQL statements are used to perform tasks such as insert data to a database, delete or update data in a database, or retrieve data from a database. Though database systems use SQL, they also have their own additional proprietary extensions that are usually only used on their system.
In SQL, the data manipulation language comprises the SQL-data change statements, [3] which modify stored data but not the schema or database objects. Manipulation of persistent database objects, e.g., tables or stored procedures, via the SQL schema statements, [3] rather than the data stored within them, is considered to be part of a separate data definition language (DDL).
undoNextLSN: This field contains the LSN of the next log record that is to be undone for transaction that wrote the last Update Log. Commit Record notes a decision to commit a transaction. Abort Record notes a decision to abort and hence roll back a transaction. Checkpoint Record notes that a checkpoint has been made. These are used to speed up ...
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 .
Cascading aborts occur when one transaction's abort causes another transaction to abort because it read and relied on the first transaction's changes to an object. A dirty read occurs when a transaction reads data from uncommitted write in another transaction. [9] The following examples are the same as the ones in the discussion on recoverable: