The default method by which SQLite implements atomic commit and rollback is a rollback journal. Beginning with version 3.7.0, a new "Write-Ahead Log" option (hereafter referred to as "WAL") is available.
There are advantages and disadvantages to using WAL instead of a rollback journal. Advantages include:
But there are also disadvantages:
The traditional rollback journal works by writing a copy of the original unchanged database content into a separate rollback journal file and then writing changes directly into the database file. In the event of a crash or ROLLBACK, the original content contained in the rollback journal is played back into the database file to revert the database file to its original state. The COMMIT occurs when the rollback journal is deleted.
The WAL approach inverts this. The original content is preserved in the database file and the changes are appended into a separate WAL file. A COMMIT occurs when a special record indicating a commit is appended to the WAL. Thus a COMMIT can happen without ever writing to the original database, which allows readers to continue operating from the original unaltered database while changes are simultaneously being committed into the WAL. Multiple transactions can be appended to the end of a single WAL file.
Of course, one wants to eventually transfer all the transactions that are appended in the WAL file back into the original database. Moving the WAL file transactions back into the database is called a "checkpoint".
Another way to think about the difference between rollback and write-ahead log is that in the rollback-journal approach, there are two primitive operations, reading and writing, whereas with a write-ahead log there are now three primitive operations: reading, writing, and checkpointing.
By default, SQLite does a checkpoint automatically when the WAL file reaches a threshold size of 1000 pages. (The SQLITE_DEFAULT_WAL_AUTOCHECKPOINT compile-time option can be used to specify a different default.) Applications using WAL do not have to do anything in order to for these checkpoints to occur. But if they want to, applications can adjust the automatic checkpoint threshold. Or they can turn off the automatic checkpoints and run checkpoints during idle moments or in a separate thread or process.
When a read operation begins on a WAL-mode database, it first remembers the location of the last valid commit record in the WAL. Call this point the "end mark". 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. But for any particular reader, the end mark is unchanged for the duration of the transaction, thus ensuring that a single read transaction only sees the database content as it existed at a single point in time.
When a reader needs a page of content, it first checks the WAL to see if that page appears there, and if so it pulls in the last copy of the page that occurs in the WAL prior to the reader's end mark. If no copy of the page exists in the WAL prior to the reader's end mark, then the page is read from the original database file. Readers can exist in separate processes, so to avoid forcing every reader to scan the entire WAL looking for pages (the WAL file can grow to multiple megabytes, depending on how often checkpoints are run), a data structure called the "wal-index" is maintained in shared memory which helps readers locate pages in the WAL quickly and with a minimum of I/O. 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. This is why the write-ahead log implementation will not work on a network filesystem.
Writers merely append new content to the end of the WAL file. Because writers do nothing that would interfere with the actions of readers, writers and readers can run at the same time. However, since there is only one WAL file, there can only be one writer at a time.
A checkpoint operation takes content from the WAL file and transfers it back into the original database file. A checkpoint can run concurrently with readers, however the checkpoint must stop when it reaches a page in the WAL that is past the end mark of any current reader. The checkpoint has to stop at that point because otherwise it might overwrite part of the database file that the reader is actively using. The checkpoint remembers (in the wal-index) how far it got and will resume transferring content from the WAL to the database from where it left off on the next invocation.
Thus a long-running read transaction can prevent a checkpointer from making progress. But presumably every read transactions will eventually end and the checkpointer will be able to continue.
Whenever a write operation occurs, the writer checks how much progress the checkpointer has made, and if the entire WAL has been transferred into the database and synced and if no readers are making use of the WAL, then the writer will rewind the WAL back to the beginning and start putting new transactions at the beginning of the WAL. This mechanism prevents a WAL file from growing without bound.
Write transactions are very fast since they only involve writing the content once (versus twice for rollback-journal transactions) and because the writes are all sequential. Further, syncing the content to the disk is not required, as long as the application is willing to sacrifice durability following a power loss or hard reboot. (Writers sync the WAL on every transaction commit if PRAGMA synchronous is set to FULL but omit this sync if PRAGMA synchronous is set to NORMAL.)
On the other hand, read performance deteriorates as the WAL file grows in size since each reader must check the WAL file for the content and the time needed to check the WAL file is proportional to the size of the WAL file. The wal-index helps find content in the WAL file much faster, but performance still falls off with increasing WAL file size. Hence, to maintain good read performance it is important to keep the WAL file size down by running checkpoints at regular intervals.
Checkpointing does require sync operations in order to avoid the possibility of database corruption following a power loss or hard reboot. The WAL must be synced to persistent storage prior to moving content from the WAL into the database and the database file must by synced prior to resetting the WAL. Checkpoint also requires more seeking. 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. These factors combine to make checkpoints slower than write transactions.
The default strategy is to allow successive write transactions to grow the WAL until the WAL becomes about 1000 pages in size, then to run a checkpoint operation for each subsequent COMMIT until the WAL is reset to be smaller than 1000 pages. By default, the checkpoint will be run automatically by the same thread that does the COMMIT that pushes the WAL over its size limit. This has the effect of causing most COMMIT operations to be very fast but an occasional COMMIT (those that trigger a checkpoint) to be much slower. If that effect is undesirable, then the application can disable automatic checkpointing and run the periodic checkpoints in a separate thread, or separate process. (Links to commands and interfaces to accomplish this are shown below.)
Note that with PRAGMA synchronous set to NORMAL, the checkpoint is the only operation to issue an I/O barrier or sync operation (fsync() on unix or FlushFileBuffers() on windows). If an application therefore runs checkpoint in a separate thread or process, the main thread or process that is doing database queries and updates will never block on a sync operation. This helps to prevent "latch-up" in applications running on a busy disk drive. The downside to this configuration is that transactions are no longer durable and might rollback following a power failure or hard reset.
Notice too that there is a tradeoff between average read performance and average write performance. To maximize the read performance, one wants to keep the WAL as small as possible and hence run checkpoints frequently, perhaps as often as every COMMIT. To maximize write performance, one wants to amortize the cost of each checkpoint over as many writes as possible, meaning that one wants to run checkpoints infrequently and let the WAL grow as large as possible before each checkpoint. The decision of how often to run checkpoints may therefore vary from one application to another depending on the relative read and write performance requirements of the application. The default strategy is to run a checkpoint once the WAL reaches 1000 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.
An SQLite database connection defaults to journal_mode=DELETE. To convert to WAL mode, use the following pragma:
The journal_mode pragma returns a string which is the new journal mode. On success, the pragma will return the string "wal". If the conversion to WAL could not be completed (for example, if the VFS does not support the necessary shared-memory primitives) then the journaling mode will be unchanged and the string returned from the primitive will be the prior journaling mode (for example "delete").
By default, SQLite will automatically checkpoint whenever a COMMIT occurs that causes the WAL file to be 1000 pages or more in size, or when the last database connection on a database file closes. The default configuration is intended to work well for most applications. But programs that want more control can force a checkpoint using the wal_checkpoint pragma or by calling the sqlite3_wal_checkpoint() C interface. The automatic checkpoint threshold can be changed or automatic checkpointing can be completely disabled using the wal_autocheckpoint pragma or by calling the sqlite3_wal_autocheckpoint() C interface. A program can also use sqlite3_wal_hook() to register a callback to be invoked whenever any transaction commits to the WAL. This callback can then invoke sqlite3_wal_checkpoint() or sqlite3_wal_checkpoint_v2() based on whatever criteria it thinks is appropriate. (The automatic checkpoint mechanism is implemented as a simple wrapper around sqlite3_wal_hook().)
An application can initiate a checkpoint using any writable database connection on the database simply by invoking sqlite3_wal_checkpoint() or sqlite3_wal_checkpoint_v2(). There are three subtypes of checkpoints that vary in their aggressiveness: PASSIVE, FULL, and RESTART. The default checkpoint style is PASSIVE, which does as much work as it can without interfering with other database connections, and which might not run to completion if there are concurrent readers or writers. All checkpoints initiated by sqlite3_wal_checkpoint() and by the automatic checkpoint mechanism are PASSIVE. FULL and RESTART checkpoints try harder to run the checkpoint to completion and can only be initiated by a call to sqlite3_wal_checkpoint_v2(). See the sqlite3_wal_checkpoint_v2() documentation for additional information on FULL and RESET checkpoints.
Unlike the other journaling modes, PRAGMA journal_mode=WAL is persistent. If a process sets WAL mode, then closes and reopens the database, the database will come back in WAL mode. In contrast, if a process sets (for example) PRAGMA journal_mode=TRUNCATE and then closes and reopens the database will come back up in the default rollback mode of DELETE rather than the previous TRUNCATE setting.
The persistence of WAL mode means that applications can be converted to using SQLite in WAL mode without making any changes to the application itself. One has merely to run "PRAGMA journal_mode=WAL;" on the database file(s) using the command-line shell or other utility, then restart the application.
The WAL journal mode will be set on all connections to the same database file if it is set on any one connection.
No SQLite database (regardless of whether or not it is WAL mode) is readable if it is located on read-only media and it requires recovery. So, for example, if an application crashes and leaves an SQLite database with a hot journal, that database cannot be opened unless the opening process has write privilege on the database file, the directory containing the database file, and the hot journal. This is because the incomplete transaction left over from the crash must be rolled back prior to reading the database and that rollback cannot occur without write permission on all files and the directory containing them.
A database in WAL mode cannot generally be opened from read-only media because even ordinary reads in WAL mode require recovery-like operations.
An efficient implementation of the WAL read algorithm requires that there exist a hash table in shared memory over the content of the WAL file. This hash table is called the wal-index. The wal-index is in shared memory, and so technically it does not have to have a name in the host computer filesystem. Custom VFS implementations are free to implement shared memory in any way they see fit, but the default unix and windows drivers that come built-in with SQLite implement shared memory using mmapped files named using the suffix "-shm" and located in the same directory as the database file. The wal-index must be rebuilt upon first access, even by readers, and so in order to open the WAL database, write access is required on the "-shm" shared memory file if the file exists, or else write access is required on the directory containing the database so that the wal-index can be created if it does not already exist. This does not preclude custom VFS implementations that implement shared memory differently from being able to access read-only WAL databases, but it does prevent the default unix and windows backends from accessing WAL databases on read-only media.
Hence, SQLite databases should always be converted to PRAGMA journal_mode=DELETE prior to being transferred to read-only media.
Also, if multiple processes are to access a WAL mode database, then all processes should run under user or group IDs that give them write access to the database files, the WAL file, the shared memory -shm file, and the containing directory.
In normal cases, new content is appended to the WAL file until the WAL file accumulates about 1000 pages (and is thus about 4MB in size) at which point a checkpoint is automatically run and the WAL file is recycled. The checkpoint does not normally truncate the WAL file (unless the journal_size_limit pragma is set). Instead, it merely causes SQLite to start overwriting the WAL file from the beginning. This is done because it is normally faster to overwrite an existing file than to append. When the last connection to a database closes, that connection does one last checkpoint and then deletes the WAL and its associated shared-memory file, to clean up the disk.
So in the vast majority of cases, applications need not worry about the WAL file at all. SQLite will automatically take care of it. 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 following bullets enumerate some of the ways that this can happen and how to avoid them.
Disabling the automatic checkpoint mechanism. In its default configuration, SQLite will checkpoint the WAL file at the conclusion of any transaction when the WAL file is more than 1000 pages long. However, compile-time and run-time options exist that can disable or defer this automatic checkpoint. If an application disables the automatic checkpoint, then there is nothing to prevent the WAL file from growing excessively.
Checkpoint starvation. A checkpoint is only able to run to completion, and reset the WAL file, if there are no other database connections using the WAL file. If another connection has a read transaction open, then the checkpoint cannot reset the WAL file because doing so might delete content out from under the reader. The checkpoint will do as much work as it can without upsetting the reader, but it cannot run to completion. The checkpoint will start up again where it left off after the next write transaction. This repeats until some checkpoint is able to complete.
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.
This scenario can be avoided by ensuring that there are "reader gaps": times when no processes are reading from the database and that checkpoints are attempted during those times. In applications with many concurrent readers, one might also consider running manual checkpoints with the SQLITE_CHECKPOINT_RESTART or SQLITE_CHECKPOINT_TRUNCATE option which will ensure that the checkpoint runs to completion before returning. The disadvantage of using SQLITE_CHECKPOINT_RESTART and SQLITE_CHECKPOINT_TRUNCATE is that readers might block while the checkpoint is running.
Very large write transactions. A checkpoint can only complete when no other transactions are running, which means the WAL file cannot be reset in the middle of a write transaction. So a large change to a large database might result in a large WAL file. The WAL file will be checkpointed once the write transaction completes (assuming there are no other readers blocking it) but in the meantime, the file can grow very big.
As of SQLite version 3.11.0, the WAL file for a single transaction should be proportional in size to the transaction itself. Pages that are changed by the transaction should only be written into the WAL file once. However, with older versions of SQLite, the same page might be written into the WAL file multiple times if the transaction grows larger than the page cache.
The wal-index is implemented using an ordinary file that is mmapped for robustness. Early (pre-release) implementations of WAL mode stored the wal-index in volatile shared-memory, such as files created in /dev/shm on Linux or /tmp on other unix systems. 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. Other methods for creating nameless shared memory blocks are not portable across the various flavors of unix. And we could not find any method to create nameless shared memory blocks on windows. The only way we have found to guarantee that all processes accessing the same database file use the same shared memory is to create the shared memory by mmapping a file in the same directory as the database itself.
Using an ordinary disk file to provide shared memory has the disadvantage that it might actually do unnecessary disk I/O by writing the shared memory to disk. However, the developers do not think this is a major concern since the wal-index rarely exceeds 32 KiB in size and is never synced. Furthermore, the wal-index backing file is deleted when the last database connection disconnects, which often prevents any real disk I/O from ever happening.
Specialized applications for which the default implementation of shared memory is unacceptable can devise alternative methods via a custom VFS. For example, if it is known that a particular database will only be accessed by threads within a single process, the wal-index can be implemented using heap memory instead of true shared memory.
Beginning in SQLite version 3.7.4, WAL databases can be created, read, and written even if shared memory is unavailable as long as the locking_mode is set to EXCLUSIVE before the first attempted access. In other words, a process can interact with a WAL database without using shared memory if that process is guaranteed to be the only process accessing the database. This feature allows WAL databases to be created, read, and written by legacy VFSes that lack the "version 2" shared-memory methods xShmMap, xShmLock, xShmBarrier, and xShmUnmap on the sqlite3_io_methods object.
If EXCLUSIVE locking mode is set prior to the first WAL-mode database access, then SQLite never attempts to call any of the shared-memory methods and hence no shared-memory wal-index is ever created. In that case, the database connection remains in EXCLUSIVE mode as long as the journal mode is WAL; attempts to change the locking mode using "PRAGMA locking_mode=NORMAL;" are no-ops. The only way to change out of EXCLUSIVE locking mode is to first change out of WAL journal mode.
If NORMAL locking mode is in effect for the first WAL-mode database access, then the shared-memory wal-index is created. This means that the underlying VFS must support the "version 2" shared-memory. If the VFS does not support shared-memory methods, then the attempt to open a database that is already in WAL mode, or the attempt convert a database into WAL mode, will fail. As long as exactly one connection is using a shared-memory wal-index, the locking mode can be changed freely between NORMAL and EXCLUSIVE. It is only when the shared-memory wal-index is omitted, when the locking mode is EXCLUSIVE prior to the first WAL-mode database access, that the locking mode is stuck in EXCLUSIVE.
The database file format is unchanged for WAL mode. However, the WAL file and the wal-index are new concepts and so older versions of SQLite will not know how to recover a crashed SQLite database that was operating in WAL mode when the crash occurred. To prevent older versions of SQLite (prior to version 3.7.0, 2010-07-22) from trying to recover a WAL-mode database (and making matters worse) the database file format version numbers (bytes 18 and 19 in the database header) are increased from 1 to 2 in WAL mode. Thus, if an older version of SQLite attempts to connect to an SQLite database that is operating in WAL mode, it will report an error along the lines of "file is encrypted or is not a database".
One can explicitly change out of WAL mode using a pragma such as this:
Deliberately changing out of WAL mode changes the database file format version numbers back to 1 so that older versions of SQLite can once again access the database file.