Algorithm for Recovery and Isolation Exploiting Semantics (ARIES)

introduction to ARIES

1. ARIES
The ARIES (Algorithms for Recovery and Isolation Exploiting Semantics) algorithm is a
highly influential method used in the field of database recovery. Developed by IBM's C. Mohan
in 1992, it has become a foundation for the recovery mechanisms in many modern database
systems. The ARIES algorithm is complex but highly effective, designed to ensure the integrity
and consistency of databases through its robust recovery processes and support for concurrent
transactions.
Key Features of ARIES:
1. Write-Ahead Logging (WAL):
o ARIES uses WAL to ensure that no data modifications are written to the
database before the corresponding log records are safely stored. This helps in
maintaining data integrity in case of a crash.
2. Fine-Grained Locking:
o It employs fine-grained locking which allows more concurrent operations on
the database, reducing bottlenecks and improving overall system performance.
3. Partial Redo and Undo:
o ARIES can perform partial redo operations, where only the necessary parts of
transactions are redone, and partial undo operations, where only the necessary
parts of transactions are undone, making the recovery process more efficient.
4. Repeatable History:
o During recovery, ARIES reconstructs a transaction history that is guaranteed to
be consistent with the original execution order, ensuring repeatable history
property.
5. Support for Various Types of Failures:
o ARIES is designed to handle different types of system failures, including
transaction failures, system crashes, and media failures.
Functionality and Operations:
1. Logging:
o Every database operation is logged with enough information (redo and undo
information) to either repeat the operation or reverse it.
2. Concurrency Control:
o ARIES uses locking protocols that ensure isolation among concurrent
transactions, adhering to the ACID properties of database systems.
3. Checkpointing:
o Checkpoints are used to reduce the amount of work during recovery by
periodically saving the state of the system (transaction table, dirty page table).
Recovery Process:
The recovery process in ARIES is divided into three main phases:
1. Analysis Phase:
o This phase starts at the last checkpoint and scans the log forward to identify the
transactions that were active and the dirty pages at the time of the crash. It
determines the starting points for the redo and undo phases.

2. 2. Redo Phase:
o The redo phase processes from the earliest log record of a dirty page identified
during the analysis phase to the end of the log. This phase ensures that all
committed changes are reflected in the database, even if they were only in
volatile memory at the time of the crash.
3. Undo Phase:
o This phase rolls back all updates made by transactions that were active at the
time of the crash, using the log records linked in reverse order by each
transaction. The undo phase continues until all such transactions are fully rolled
back to maintain the database consistency.
Phases Detailed:
 Analysis:
o Builds a list of transactions that need to be redone or undone.
o Determines the earliest log sequence number (LSN) from which the redo should
start.
 Redo:
o Applies all redo information from the log to ensure all committed data is
correctly reflected in the database.
o Starts from the earliest LSN identified in the analysis phase and moves forward,
applying redo steps to the affected pages.
 Undo:
o Rolls back transactions that were not complete at the time of the crash.
o Uses a Last-in-First-out (LIFO) strategy by following the chain of log records
in reverse order.
The design and execution of the ARIES algorithm make it one of the most reliable and efficient
recovery mechanisms in database management, ensuring robustness and integrity even in the
face of system failures.
Data Structures:
Log Records
Purpose: To record every modification to the database, enabling both undo and redo
operations during recovery.
Components:
 LSN (Log Sequence Number): A unique identifier for each log entry, establishing an
order.
 Previous LSN: Link to the previous log entry of the same transaction.
 Transaction ID: Identifier of the transaction responsible for the log entry.
 Type: Type of log entry (e.g., update, commit, abort).
 Data: Contains redo and undo information necessary for recovery processes.
 Page ID: Identifier of the page affected by the log entry (for entries involving page
modifications).
Dirty Page Table (DPT)

3. Purpose: To track pages that have been modified during current transactions but not yet
written back to disk.
Components:
 Page ID: Identifier of a modified (dirty) page.
 RecLSN: The Log Sequence Number of the first log record that modified the page.
This marks the point from which a redo operation must be applied during recovery.
Transaction Table
Purpose: To monitor the current state and activities of transactions, particularly useful in
crash recovery scenarios.
Components:
 Transaction ID: Identifier of a transaction.
 State: Current state of the transaction (e.g., active, committing, aborted).
 Last LSN: Log Sequence Number of the last log record written by this transaction,
useful during the undo process.
 Undo Next LSN: Pointer to the next log record to process during the undo phase.
Buffers
Purpose: To temporarily store copies of disk pages that are in active use by transactions,
facilitating quick access and manipulation.
Checkpoints
Purpose: To reduce recovery time by periodically saving a consistent state of the system,
including the Dirty Page Table and Transaction Table.
Components:
 Checkpoint LSN: The Log Sequence Number at which the checkpoint was recorded.
 Active Transactions: List of transactions active at the checkpoint time.
 Dirty Page Table: Snapshot of the Dirty Page Table at the checkpoint.
These data structures are integral to implementing the ARIES algorithm effectively, ensuring
that a database can be quickly and accurately restored to a consistent state following a system
crash.