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In computer science, write-ahead logging (WAL) is a family of techniques for providing atomicity and durability (two of the ACID properties) in database systems. [1]A write ahead log is an append-only auxiliary disk-resident structure used for crash and transaction recovery.
Write-ahead logging: Any change to an object is first recorded in the log, and the log must be written to stable storage before changes to the object are written to disk. Repeating history during Redo: On restart after a crash, ARIES retraces the actions of a database before the crash and brings the system back to the exact state that it was in ...
In particular, the logging mechanism is called write-ahead log (WAL) and allows durability by buffering changes to the disk before they are synchronized from the main memory. In this way, by reconstruction from the log file, all committed transactions are resilient to system-level failures, because they can be redone.
Physically, a log is a file listing changes to the database, stored in a stable storage format. If, after a start, the database is found in an inconsistent state or not been shut down properly, the database management system reviews the database logs for uncommitted transactions and rolls back the changes made by these transactions ...
there is stable storage at each node with a write-ahead log, no node crashes forever, the data in the write-ahead log is never lost or corrupted in a crash, and; any two nodes can communicate with each other. The last assumption is not too restrictive, as network communication can typically be rerouted.
In write ahead logging, durability is guaranteed by writing the prospective change to a persistent log before changing the database. That allows the database to return to a consistent state in the event of a crash. In shadowing, updates are applied to a partial copy of the database, and the new copy is activated when the transaction commits.
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Such tuning involves writing data in a sequential manner as opposed to as a series of separate random access requests. This optimization reduces seek time in hard-disk drives (HDDs) and latency in solid-state drives (SSDs). Diagram illustrating compaction of data in a log-structured merge tree. Most LSM trees used in practice employ multiple ...