Write ahead logging explained further
However, compile-time and run-time options exist that can disable or defer this automatic checkpoint. Like the undo log, the changes are idempotent so repeated calls are fine.
Write ahead log implementation
There is a lot more information in Database Systems: The Complete Book which the above is a blatant plagarism of. However, if a database has many concurrent overlapping readers and there is always at least one active reader, then no checkpoints will be able to complete and hence the WAL file will grow without bound. By archiving the WAL data we can support reverting to any time instant covered by the available WAL data: we simply install a prior physical backup of the database, and replay the WAL log just as far as the desired time. Because writers do nothing that would interfere with the actions of readers, writers and readers can run at the same time. But presumably every read transaction will eventually end and the checkpointer will be able to continue. Checkpoint also requires more seeking. Modern file systems typically use a variant of WAL for at least file system metadata called journaling. But it is possible to get SQLite into a state where the WAL file will grow without bound, causing excess disk space usage and slow queries speeds. The checkpointer makes an effort to do as many sequential page writes to the database as it can the pages are transferred from WAL to database in ascending order but even then there will typically be many seek operations interspersed among the page writes. Usually both redo and undo information is stored in the log. Both Chrome and Firefox open their database files in exclusive locking mode, so attempts to read Chrome or Firefox databases while the applications are running will run into this problem, for example. We write-ahead. The wal-index greatly improves the performance of readers, but the use of shared memory means that all readers must exist on the same machine. Nonzero values indicate the time and disk space threshold to trigger archived WAL deletion. In the event of a failure, write ahead logs can be used to completely recover the data in the memtable, which is necessary to restore the database to the original state.
The problem with that approach is that processes with a different root directory changed via chroot will see different files and hence use different shared memory areas, leading to database corruption.
Because the WAL can be growing and adding new commit records while various readers connect to the database, each reader can potentially have its own end mark.
With the undo log in place, how do we recovery from failure?
If there's no size limit, users may need to keep really old WALs when the infrequently-updated column families hasn't flushed for a while.
The default strategy is to run a checkpoint once the WAL reaches pages and this strategy seems to work well in test applications on workstations, but other strategies might work better on different platforms or for different workloads.
What's more, the physical backup doesn't have to be an instantaneous snapshot of the database state — if it is made over some period of time, then replaying the WAL log for that period will fix any internal inconsistencies.
In a system using WAL, all modifications are written to a log before they are applied.
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