To effectively design and implement recovery mechanisms, a DBMS must anticipate and classify the different types of failures it might encounter. Each type of failure presents unique challenges and requires specific recovery strategies. We can broadly categorize failures based on their scope and impact:

A transaction failure occurs when a single, executing transaction cannot complete its operations successfully and must be terminated or rolled back. These failures are typically localized to one or a few transactions, and the database system is generally still operational.

• Logical Errors: These are errors within the transaction logic itself.
• Example: A transaction attempts to divide by zero, tries to insert a duplicate key into a unique index, or violates an integrity constraint (e.g., trying to set a negative balance). The DBMS detects these violations and typically aborts the transaction.
• Internal Database Errors: These are errors detected by the DBMS during transaction execution.
• Example: A deadlock occurs (two or more transactions are waiting indefinitely for each other to release locks), or an invalid memory access happens within the DBMS itself. The system detects these and typically aborts one or more transactions to resolve the issue.
• User-Initiated Abort: A user or application program explicitly requests the termination of a transaction.
• Example: A user decides to cancel a complex operation, or an application detects an error in user input and rolls back the current transaction.

When a transaction fails, the DBMS must ensure that the database is restored to the state it was in before the failed transaction began. This property is known as atomicity.

A system crash (also known as a soft crash or a "failure of the system") refers to the failure of the entire DBMS software or the operating system, or a power failure that affects volatile storage (main memory). In such scenarios, the contents of main memory (buffers, CPU registers, process stacks) are lost, but the contents of non-volatile storage (disks) are generally preserved.

• Software Errors:
• Example: A bug in the DBMS code, an operating system error, or an application bug that causes the DBMS process to terminate abnormally.
• Hardware Errors (Volatile Storage):
• Example: A power outage that wipes out the contents of RAM (main memory) where active transactions, cached data, and transaction logs might reside. This is distinct from disk failures where non-volatile storage is compromised.

Upon recovery from a system crash, the DBMS must ensure two critical aspects:
1. Atomicity: All transactions that were active (uncommitted) at the time of the crash must be undone (rolled back) to their initial state, as if they never occurred.
2. Durability: All transactions that committed before the crash must have their changes permanently reflected in the database on disk, even if those changes were only in memory buffers at the time of the crash. This is why a transaction is not truly "committed" until its log records are safely written to stable storage.

A disk failure (also known as a hard crash or a media failure) is the most serious type of failure. It involves the loss of non-volatile storage, where the database files and potentially the transaction logs are permanently damaged or become unreadable. This could be due to a head crash, controller failure, or unrecoverable bad blocks on the disk.

• Example: A hard disk drive physically breaks down, making all data stored on it inaccessible.

Recovery from a disk failure is more complex because the primary copy of the database data (and potentially logs) is lost. This requires restoring the database from a backup copy and then applying subsequent changes using a surviving log, if available. This process is often called media recovery.

Understanding these failure types is the first step in appreciating the sophisticated recovery mechanisms employed by a DBMS to maintain the ACID properties (Atomicity, Consistency, Isolation, Durability) of transactions and the overall integrity of the database.