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+XFS Delayed Logging Design
+--------------------------
+
+Introduction to Re-logging in XFS
+---------------------------------
+
+XFS logging is a combination of logical and physical logging. Some objects,
+such as inodes and dquots, are logged in logical format where the details
+logged are made up of the changes to in-core structures rather than on-disk
+structures. Other objects - typically buffers - have their physical changes
+logged. The reason for these differences is to reduce the amount of log space
+required for objects that are frequently logged. Some parts of inodes are more
+frequently logged than others, and inodes are typically more frequently logged
+than any other object (except maybe the superblock buffer) so keeping the
+amount of metadata logged low is of prime importance.
+
+The reason that this is such a concern is that XFS allows multiple separate
+modifications to a single object to be carried in the log at any given time.
+This allows the log to avoid needing to flush each change to disk before
+recording a new change to the object. XFS does this via a method called
+"re-logging". Conceptually, this is quite simple - all it requires is that any
+new change to the object is recorded with a *new copy* of all the existing
+changes in the new transaction that is written to the log.
+
+That is, if we have a sequence of changes A through to F, and the object was
+written to disk after change D, we would see in the log the following series
+of transactions, their contents and the log sequence number (LSN) of the
+transaction:
+
+	Transaction		Contents	LSN
+	   A			   A		   X
+	   B			  A+B		  X+n
+	   C			 A+B+C		 X+n+m
+	   D			A+B+C+D		X+n+m+o
+	    <object written to disk>
+	   E			   E		   Y (> X+n+m+o)
+	   F			  E+F		  Yٍ+p
+
+In other words, each time an object is relogged, the new transaction contains
+the aggregation of all the previous changes currently held only in the log.
+
+This relogging technique also allows objects to be moved forward in the log so
+that an object being relogged does not prevent the tail of the log from ever
+moving forward.  This can be seen in the table above by the changing
+(increasing) LSN of each subsquent transaction - the LSN is effectively a
+direct encoding of the location in the log of the transaction.
+
+This relogging is also used to implement long-running, multiple-commit
+transactions.  These transaction are known as rolling transactions, and require
+a special log reservation known as a permanent transaction reservation. A
+typical example of a rolling transaction is the removal of extents from an
+inode which can only be done at a rate of two extents per transaction because
+of reservation size limitations. Hence a rolling extent removal transaction
+keeps relogging the inode and btree buffers as they get modified in each
+removal operation. This keeps them moving forward in the log as the operation
+progresses, ensuring that current operation never gets blocked by itself if the
+log wraps around.
+
+Hence it can be seen that the relogging operation is fundamental to the correct
+working of the XFS journalling subsystem. From the above description, most
+people should be able to see why the XFS metadata operations writes so much to
+the log - repeated operations to the same objects write the same changes to
+the log over and over again. Worse is the fact that objects tend to get
+dirtier as they get relogged, so each subsequent transaction is writing more
+metadata into the log.
+
+Another feature of the XFS transaction subsystem is that most transactions are
+asynchronous. That is, they don't commit to disk until either a log buffer is
+filled (a log buffer can hold multiple transactions) or a synchronous operation
+forces the log buffers holding the transactions to disk. This means that XFS is
+doing aggregation of transactions in memory - batching them, if you like - to
+minimise the impact of the log IO on transaction throughput.
+
+The limitation on asynchronous transaction throughput is the number and size of
+log buffers made available by the log manager. By default there are 8 log
+buffers available and the size of each is 32kB - the size can be increased up
+to 256kB by use of a mount option.
+
+Effectively, this gives us the maximum bound of outstanding metadata changes
+that can be made to the filesystem at any point in time - if all the log
+buffers are full and under IO, then no more transactions can be committed until
+the current batch completes. It is now common for a single current CPU core to
+be to able to issue enough transactions to keep the log buffers full and under
+IO permanently. Hence the XFS journalling subsystem can be considered to be IO
+bound.
+
+Delayed Logging: Concepts
+-------------------------
+
+The key thing to note about the asynchronous logging combined with the
+relogging technique XFS uses is that we can be relogging changed objects
+multiple times before they are committed to disk in the log buffers. If we
+return to the previous relogging example, it is entirely possible that
+transactions A through D are committed to disk in the same log buffer.
+
+That is, a single log buffer may contain multiple copies of the same object,
+but only one of those copies needs to be there - the last one "D", as it
+contains all the changes from the previous changes. In other words, we have one
+necessary copy in the log buffer, and three stale copies that are simply
+wasting space. When we are doing repeated operations on the same set of
+objects, these "stale objects" can be over 90% of the space used in the log
+buffers. It is clear that reducing the number of stale objects written to the
+log would greatly reduce the amount of metadata we write to the log, and this
+is the fundamental goal of delayed logging.
+
+From a conceptual point of view, XFS is already doing relogging in memory (where
+memory == log buffer), only it is doing it extremely inefficiently. It is using
+logical to physical formatting to do the relogging because there is no
+infrastructure to keep track of logical changes in memory prior to physically
+formatting the changes in a transaction to the log buffer. Hence we cannot avoid
+accumulating stale objects in the log buffers.
+
+Delayed logging is the name we've given to keeping and tracking transactional
+changes to objects in memory outside the log buffer infrastructure. Because of
+the relogging concept fundamental to the XFS journalling subsystem, this is
+actually relatively easy to do - all the changes to logged items are already
+tracked in the current infrastructure. The big problem is how to accumulate
+them and get them to the log in a consistent, recoverable manner.
+Describing the problems and how they have been solved is the focus of this
+document.
+
+One of the key changes that delayed logging makes to the operation of the
+journalling subsystem is that it disassociates the amount of outstanding
+metadata changes from the size and number of log buffers available. In other
+words, instead of there only being a maximum of 2MB of transaction changes not
+written to the log at any point in time, there may be a much greater amount
+being accumulated in memory. Hence the potential for loss of metadata on a
+crash is much greater than for the existing logging mechanism.
+
+It should be noted that this does not change the guarantee that log recovery
+will result in a consistent filesystem. What it does mean is that as far as the
+recovered filesystem is concerned, there may be many thousands of transactions
+that simply did not occur as a result of the crash. This makes it even more
+important that applications that care about their data use fsync() where they
+need to ensure application level data integrity is maintained.
+
+It should be noted that delayed logging is not an innovative new concept that
+warrants rigorous proofs to determine whether it is correct or not. The method
+of accumulating changes in memory for some period before writing them to the
+log is used effectively in many filesystems including ext3 and ext4. Hence
+no time is spent in this document trying to convince the reader that the
+concept is sound. Instead it is simply considered a "solved problem" and as
+such implementing it in XFS is purely an exercise in software engineering.
+
+The fundamental requirements for delayed logging in XFS are simple:
+
+	1. Reduce the amount of metadata written to the log by at least
+	   an order of magnitude.
+	2. Supply sufficient statistics to validate Requirement #1.
+	3. Supply sufficient new tracing infrastructure to be able to debug
+	   problems with the new code.
+	4. No on-disk format change (metadata or log format).
+	5. Enable and disable with a mount option.
+	6. No performance regressions for synchronous transaction workloads.
+
+Delayed Logging: Design
+-----------------------
+
+Storing Changes
+
+The problem with accumulating changes at a logical level (i.e. just using the
+existing log item dirty region tracking) is that when it comes to writing the
+changes to the log buffers, we need to ensure that the object we are formatting
+is not changing while we do this. This requires locking the object to prevent
+concurrent modification. Hence flushing the logical changes to the log would
+require us to lock every object, format them, and then unlock them again.
+
+This introduces lots of scope for deadlocks with transactions that are already
+running. For example, a transaction has object A locked and modified, but needs
+the delayed logging tracking lock to commit the transaction. However, the
+flushing thread has the delayed logging tracking lock already held, and is
+trying to get the lock on object A to flush it to the log buffer. This appears
+to be an unsolvable deadlock condition, and it was solving this problem that
+was the barrier to implementing delayed logging for so long.
+
+The solution is relatively simple - it just took a long time to recognise it.
+Put simply, the current logging code formats the changes to each item into an
+vector array that points to the changed regions in the item. The log write code
+simply copies the memory these vectors point to into the log buffer during
+transaction commit while the item is locked in the transaction. Instead of
+using the log buffer as the destination of the formatting code, we can use an
+allocated memory buffer big enough to fit the formatted vector.
+
+If we then copy the vector into the memory buffer and rewrite the vector to
+point to the memory buffer rather than the object itself, we now have a copy of
+the changes in a format that is compatible with the log buffer writing code.
+that does not require us to lock the item to access. This formatting and
+rewriting can all be done while the object is locked during transaction commit,
+resulting in a vector that is transactionally consistent and can be accessed
+without needing to lock the owning item.
+
+Hence we avoid the need to lock items when we need to flush outstanding
+asynchronous transactions to the log. The differences between the existing
+formatting method and the delayed logging formatting can be seen in the
+diagram below.
+
+Current format log vector:
+
+Object    +---------------------------------------------+
+Vector 1      +----+
+Vector 2                    +----+
+Vector 3                                   +----------+
+
+After formatting:
+
+Log Buffer    +-V1-+-V2-+----V3----+
+
+Delayed logging vector:
+
+Object    +---------------------------------------------+
+Vector 1      +----+
+Vector 2                    +----+
+Vector 3                                   +----------+
+
+After formatting:
+
+Memory Buffer +-V1-+-V2-+----V3----+
+Vector 1      +----+
+Vector 2           +----+
+Vector 3                +----------+
+
+The memory buffer and associated vector need to be passed as a single object,
+but still need to be associated with the parent object so if the object is
+relogged we can replace the current memory buffer with a new memory buffer that
+contains the latest changes.
+
+The reason for keeping the vector around after we've formatted the memory
+buffer is to support splitting vectors across log buffer boundaries correctly.
+If we don't keep the vector around, we do not know where the region boundaries
+are in the item, so we'd need a new encapsulation method for regions in the log
+buffer writing (i.e. double encapsulation). This would be an on-disk format
+change and as such is not desirable.  It also means we'd have to write the log
+region headers in the formatting stage, which is problematic as there is per
+region state that needs to be placed into the headers during the log write.
+
+Hence we need to keep the vector, but by attaching the memory buffer to it and
+rewriting the vector addresses to point at the memory buffer we end up with a
+self-describing object that can be passed to the log buffer write code to be
+handled in exactly the same manner as the existing log vectors are handled.
+Hence we avoid needing a new on-disk format to handle items that have been
+relogged in memory.
+
+
+Tracking Changes
+
+Now that we can record transactional changes in memory in a form that allows
+them to be used without limitations, we need to be able to track and accumulate
+them so that they can be written to the log at some later point in time.  The
+log item is the natural place to store this vector and buffer, and also makes sense
+to be the object that is used to track committed objects as it will always
+exist once the object has been included in a transaction.
+
+The log item is already used to track the log items that have been written to
+the log but not yet written to disk. Such log items are considered "active"
+and as such are stored in the Active Item List (AIL) which is a LSN-ordered
+double linked list. Items are inserted into this list during log buffer IO
+completion, after which they are unpinned and can be written to disk. An object
+that is in the AIL can be relogged, which causes the object to be pinned again
+and then moved forward in the AIL when the log buffer IO completes for that
+transaction.
+
+Essentially, this shows that an item that is in the AIL can still be modified
+and relogged, so any tracking must be separate to the AIL infrastructure. As
+such, we cannot reuse the AIL list pointers for tracking committed items, nor
+can we store state in any field that is protected by the AIL lock. Hence the
+committed item tracking needs it's own locks, lists and state fields in the log
+item.
+
+Similar to the AIL, tracking of committed items is done through a new list
+called the Committed Item List (CIL).  The list tracks log items that have been
+committed and have formatted memory buffers attached to them. It tracks objects
+in transaction commit order, so when an object is relogged it is removed from
+it's place in the list and re-inserted at the tail. This is entirely arbitrary
+and done to make it easy for debugging - the last items in the list are the
+ones that are most recently modified. Ordering of the CIL is not necessary for
+transactional integrity (as discussed in the next section) so the ordering is
+done for convenience/sanity of the developers.
+
+
+Delayed Logging: Checkpoints
+
+When we have a log synchronisation event, commonly known as a "log force",
+all the items in the CIL must be written into the log via the log buffers.
+We need to write these items in the order that they exist in the CIL, and they
+need to be written as an atomic transaction. The need for all the objects to be
+written as an atomic transaction comes from the requirements of relogging and
+log replay - all the changes in all the objects in a given transaction must
+either be completely replayed during log recovery, or not replayed at all. If
+a transaction is not replayed because it is not complete in the log, then
+no later transactions should be replayed, either.
+
+To fulfill this requirement, we need to write the entire CIL in a single log
+transaction. Fortunately, the XFS log code has no fixed limit on the size of a
+transaction, nor does the log replay code. The only fundamental limit is that
+the transaction cannot be larger than just under half the size of the log.  The
+reason for this limit is that to find the head and tail of the log, there must
+be at least one complete transaction in the log at any given time. If a
+transaction is larger than half the log, then there is the possibility that a
+crash during the write of a such a transaction could partially overwrite the
+only complete previous transaction in the log. This will result in a recovery
+failure and an inconsistent filesystem and hence we must enforce the maximum
+size of a checkpoint to be slightly less than a half the log.
+
+Apart from this size requirement, a checkpoint transaction looks no different
+to any other transaction - it contains a transaction header, a series of
+formatted log items and a commit record at the tail. From a recovery
+perspective, the checkpoint transaction is also no different - just a lot
+bigger with a lot more items in it. The worst case effect of this is that we
+might need to tune the recovery transaction object hash size.
+
+Because the checkpoint is just another transaction and all the changes to log
+items are stored as log vectors, we can use the existing log buffer writing
+code to write the changes into the log. To do this efficiently, we need to
+minimise the time we hold the CIL locked while writing the checkpoint
+transaction. The current log write code enables us to do this easily with the
+way it separates the writing of the transaction contents (the log vectors) from
+the transaction commit record, but tracking this requires us to have a
+per-checkpoint context that travels through the log write process through to
+checkpoint completion.
+
+Hence a checkpoint has a context that tracks the state of the current
+checkpoint from initiation to checkpoint completion. A new context is initiated
+at the same time a checkpoint transaction is started. That is, when we remove
+all the current items from the CIL during a checkpoint operation, we move all
+those changes into the current checkpoint context. We then initialise a new
+context and attach that to the CIL for aggregation of new transactions.
+
+This allows us to unlock the CIL immediately after transfer of all the
+committed items and effectively allow new transactions to be issued while we
+are formatting the checkpoint into the log. It also allows concurrent
+checkpoints to be written into the log buffers in the case of log force heavy
+workloads, just like the existing transaction commit code does. This, however,
+requires that we strictly order the commit records in the log so that
+checkpoint sequence order is maintained during log replay.
+
+To ensure that we can be writing an item into a checkpoint transaction at
+the same time another transaction modifies the item and inserts the log item
+into the new CIL, then checkpoint transaction commit code cannot use log items
+to store the list of log vectors that need to be written into the transaction.
+Hence log vectors need to be able to be chained together to allow them to be
+detatched from the log items. That is, when the CIL is flushed the memory
+buffer and log vector attached to each log item needs to be attached to the
+checkpoint context so that the log item can be released. In diagrammatic form,
+the CIL would look like this before the flush:
+
+	CIL Head
+	   |
+	   V
+	Log Item <-> log vector 1	-> memory buffer
+	   |				-> vector array
+	   V
+	Log Item <-> log vector 2	-> memory buffer
+	   |				-> vector array
+	   V
+	......
+	   |
+	   V
+	Log Item <-> log vector N-1	-> memory buffer
+	   |				-> vector array
+	   V
+	Log Item <-> log vector N	-> memory buffer
+					-> vector array
+
+And after the flush the CIL head is empty, and the checkpoint context log
+vector list would look like:
+
+	Checkpoint Context
+	   |
+	   V
+	log vector 1	-> memory buffer
+	   |		-> vector array
+	   |		-> Log Item
+	   V
+	log vector 2	-> memory buffer
+	   |		-> vector array
+	   |		-> Log Item
+	   V
+	......
+	   |
+	   V
+	log vector N-1	-> memory buffer
+	   |		-> vector array
+	   |		-> Log Item
+	   V
+	log vector N	-> memory buffer
+			-> vector array
+			-> Log Item
+
+Once this transfer is done, the CIL can be unlocked and new transactions can
+start, while the checkpoint flush code works over the log vector chain to
+commit the checkpoint.
+
+Once the checkpoint is written into the log buffers, the checkpoint context is
+attached to the log buffer that the commit record was written to along with a
+completion callback. Log IO completion will call that callback, which can then
+run transaction committed processing for the log items (i.e. insert into AIL
+and unpin) in the log vector chain and then free the log vector chain and
+checkpoint context.
+
+Discussion Point: I am uncertain as to whether the log item is the most
+efficient way to track vectors, even though it seems like the natural way to do
+it. The fact that we walk the log items (in the CIL) just to chain the log
+vectors and break the link between the log item and the log vector means that
+we take a cache line hit for the log item list modification, then another for
+the log vector chaining. If we track by the log vectors, then we only need to
+break the link between the log item and the log vector, which means we should
+dirty only the log item cachelines. Normally I wouldn't be concerned about one
+vs two dirty cachelines except for the fact I've seen upwards of 80,000 log
+vectors in one checkpoint transaction. I'd guess this is a "measure and
+compare" situation that can be done after a working and reviewed implementation
+is in the dev tree....
+
+Delayed Logging: Checkpoint Sequencing
+
+One of the key aspects of the XFS transaction subsystem is that it tags
+committed transactions with the log sequence number of the transaction commit.
+This allows transactions to be issued asynchronously even though there may be
+future operations that cannot be completed until that transaction is fully
+committed to the log. In the rare case that a dependent operation occurs (e.g.
+re-using a freed metadata extent for a data extent), a special, optimised log
+force can be issued to force the dependent transaction to disk immediately.
+
+To do this, transactions need to record the LSN of the commit record of the
+transaction. This LSN comes directly from the log buffer the transaction is
+written into. While this works just fine for the existing transaction
+mechanism, it does not work for delayed logging because transactions are not
+written directly into the log buffers. Hence some other method of sequencing
+transactions is required.
+
+As discussed in the checkpoint section, delayed logging uses per-checkpoint
+contexts, and as such it is simple to assign a sequence number to each
+checkpoint. Because the switching of checkpoint contexts must be done
+atomically, it is simple to ensure that each new context has a monotonically
+increasing sequence number assigned to it without the need for an external
+atomic counter - we can just take the current context sequence number and add
+one to it for the new context.
+
+Then, instead of assigning a log buffer LSN to the transaction commit LSN
+during the commit, we can assign the current checkpoint sequence. This allows
+operations that track transactions that have not yet completed know what
+checkpoint sequence needs to be committed before they can continue. As a
+result, the code that forces the log to a specific LSN now needs to ensure that
+the log forces to a specific checkpoint.
+
+To ensure that we can do this, we need to track all the checkpoint contexts
+that are currently committing to the log. When we flush a checkpoint, the
+context gets added to a "committing" list which can be searched. When a
+checkpoint commit completes, it is removed from the committing list. Because
+the checkpoint context records the LSN of the commit record for the checkpoint,
+we can also wait on the log buffer that contains the commit record, thereby
+using the existing log force mechanisms to execute synchronous forces.
+
+It should be noted that the synchronous forces may need to be extended with
+mitigation algorithms similar to the current log buffer code to allow
+aggregation of multiple synchronous transactions if there are already
+synchronous transactions being flushed. Investigation of the performance of the
+current design is needed before making any decisions here.
+
+The main concern with log forces is to ensure that all the previous checkpoints
+are also committed to disk before the one we need to wait for. Therefore we
+need to check that all the prior contexts in the committing list are also
+complete before waiting on the one we need to complete. We do this
+synchronisation in the log force code so that we don't need to wait anywhere
+else for such serialisation - it only matters when we do a log force.
+
+The only remaining complexity is that a log force now also has to handle the
+case where the forcing sequence number is the same as the current context. That
+is, we need to flush the CIL and potentially wait for it to complete. This is a
+simple addition to the existing log forcing code to check the sequence numbers
+and push if required. Indeed, placing the current sequence checkpoint flush in
+the log force code enables the current mechanism for issuing synchronous
+transactions to remain untouched (i.e. commit an asynchronous transaction, then
+force the log at the LSN of that transaction) and so the higher level code
+behaves the same regardless of whether delayed logging is being used or not.
+
+Delayed Logging: Checkpoint Log Space Accounting
+
+The big issue for a checkpoint transaction is the log space reservation for the
+transaction. We don't know how big a checkpoint transaction is going to be
+ahead of time, nor how many log buffers it will take to write out, nor the
+number of split log vector regions are going to be used. We can track the
+amount of log space required as we add items to the commit item list, but we
+still need to reserve the space in the log for the checkpoint.
+
+A typical transaction reserves enough space in the log for the worst case space
+usage of the transaction. The reservation accounts for log record headers,
+transaction and region headers, headers for split regions, buffer tail padding,
+etc. as well as the actual space for all the changed metadata in the
+transaction. While some of this is fixed overhead, much of it is dependent on
+the size of the transaction and the number of regions being logged (the number
+of log vectors in the transaction).
+
+An example of the differences would be logging directory changes versus logging
+inode changes. If you modify lots of inode cores (e.g. chmod -R g+w *), then
+there are lots of transactions that only contain an inode core and an inode log
+format structure. That is, two vectors totaling roughly 150 bytes. If we modify
+10,000 inodes, we have about 1.5MB of metadata to write in 20,000 vectors. Each
+vector is 12 bytes, so the total to be logged is approximately 1.75MB. In
+comparison, if we are logging full directory buffers, they are typically 4KB
+each, so we in 1.5MB of directory buffers we'd have roughly 400 buffers and a
+buffer format structure for each buffer - roughly 800 vectors or 1.51MB total
+space.  From this, it should be obvious that a static log space reservation is
+not particularly flexible and is difficult to select the "optimal value" for
+all workloads.
+
+Further, if we are going to use a static reservation, which bit of the entire
+reservation does it cover? We account for space used by the transaction
+reservation by tracking the space currently used by the object in the CIL and
+then calculating the increase or decrease in space used as the object is
+relogged. This allows for a checkpoint reservation to only have to account for
+log buffer metadata used such as log header records.
+
+However, even using a static reservation for just the log metadata is
+problematic. Typically log record headers use at least 16KB of log space per
+1MB of log space consumed (512 bytes per 32k) and the reservation needs to be
+large enough to handle arbitrary sized checkpoint transactions. This
+reservation needs to be made before the checkpoint is started, and we need to
+be able to reserve the space without sleeping.  For a 8MB checkpoint, we need a
+reservation of around 150KB, which is a non-trivial amount of space.
+
+A static reservation needs to manipulate the log grant counters - we can take a
+permanent reservation on the space, but we still need to make sure we refresh
+the write reservation (the actual space available to the transaction) after
+every checkpoint transaction completion. Unfortunately, if this space is not
+available when required, then the regrant code will sleep waiting for it.
+
+The problem with this is that it can lead to deadlocks as we may need to commit
+checkpoints to be able to free up log space (refer back to the description of
+rolling transactions for an example of this).  Hence we *must* always have
+space available in the log if we are to use static reservations, and that is
+very difficult and complex to arrange. It is possible to do, but there is a
+simpler way.
+
+The simpler way of doing this is tracking the entire log space used by the
+items in the CIL and using this to dynamically calculate the amount of log
+space required by the log metadata. If this log metadata space changes as a
+result of a transaction commit inserting a new memory buffer into the CIL, then
+the difference in space required is removed from the transaction that causes
+the change. Transactions at this level will *always* have enough space
+available in their reservation for this as they have already reserved the
+maximal amount of log metadata space they require, and such a delta reservation
+will always be less than or equal to the maximal amount in the reservation.
+
+Hence we can grow the checkpoint transaction reservation dynamically as items
+are added to the CIL and avoid the need for reserving and regranting log space
+up front. This avoids deadlocks and removes a blocking point from the
+checkpoint flush code.
+
+As mentioned early, transactions can't grow to more than half the size of the
+log. Hence as part of the reservation growing, we need to also check the size
+of the reservation against the maximum allowed transaction size. If we reach
+the maximum threshold, we need to push the CIL to the log. This is effectively
+a "background flush" and is done on demand. This is identical to
+a CIL push triggered by a log force, only that there is no waiting for the
+checkpoint commit to complete. This background push is checked and executed by
+transaction commit code.
+
+If the transaction subsystem goes idle while we still have items in the CIL,
+they will be flushed by the periodic log force issued by the xfssyncd. This log
+force will push the CIL to disk, and if the transaction subsystem stays idle,
+allow the idle log to be covered (effectively marked clean) in exactly the same
+manner that is done for the existing logging method. A discussion point is
+whether this log force needs to be done more frequently than the current rate
+which is once every 30s.
+
+
+Delayed Logging: Log Item Pinning
+
+Currently log items are pinned during transaction commit while the items are
+still locked. This happens just after the items are formatted, though it could
+be done any time before the items are unlocked. The result of this mechanism is
+that items get pinned once for every transaction that is committed to the log
+buffers. Hence items that are relogged in the log buffers will have a pin count
+for every outstanding transaction they were dirtied in. When each of these
+transactions is completed, they will unpin the item once. As a result, the item
+only becomes unpinned when all the transactions complete and there are no
+pending transactions. Thus the pinning and unpinning of a log item is symmetric
+as there is a 1:1 relationship with transaction commit and log item completion.
+
+For delayed logging, however, we have an assymetric transaction commit to
+completion relationship. Every time an object is relogged in the CIL it goes
+through the commit process without a corresponding completion being registered.
+That is, we now have a many-to-one relationship between transaction commit and
+log item completion. The result of this is that pinning and unpinning of the
+log items becomes unbalanced if we retain the "pin on transaction commit, unpin
+on transaction completion" model.
+
+To keep pin/unpin symmetry, the algorithm needs to change to a "pin on
+insertion into the CIL, unpin on checkpoint completion". In other words, the
+pinning and unpinning becomes symmetric around a checkpoint context. We have to
+pin the object the first time it is inserted into the CIL - if it is already in
+the CIL during a transaction commit, then we do not pin it again. Because there
+can be multiple outstanding checkpoint contexts, we can still see elevated pin
+counts, but as each checkpoint completes the pin count will retain the correct
+value according to it's context.
+
+Just to make matters more slightly more complex, this checkpoint level context
+for the pin count means that the pinning of an item must take place under the
+CIL commit/flush lock. If we pin the object outside this lock, we cannot
+guarantee which context the pin count is associated with. This is because of
+the fact pinning the item is dependent on whether the item is present in the
+current CIL or not. If we don't pin the CIL first before we check and pin the
+object, we have a race with CIL being flushed between the check and the pin
+(or not pinning, as the case may be). Hence we must hold the CIL flush/commit
+lock to guarantee that we pin the items correctly.
+
+Delayed Logging: Concurrent Scalability
+
+A fundamental requirement for the CIL is that accesses through transaction
+commits must scale to many concurrent commits. The current transaction commit
+code does not break down even when there are transactions coming from 2048
+processors at once. The current transaction code does not go any faster than if
+there was only one CPU using it, but it does not slow down either.
+
+As a result, the delayed logging transaction commit code needs to be designed
+for concurrency from the ground up. It is obvious that there are serialisation
+points in the design - the three important ones are:
+
+	1. Locking out new transaction commits while flushing the CIL
+	2. Adding items to the CIL and updating item space accounting
+	3. Checkpoint commit ordering
+
+Looking at the transaction commit and CIL flushing interactions, it is clear
+that we have a many-to-one interaction here. That is, the only restriction on
+the number of concurrent transactions that can be trying to commit at once is
+the amount of space available in the log for their reservations. The practical
+limit here is in the order of several hundred concurrent transactions for a
+128MB log, which means that it is generally one per CPU in a machine.
+
+The amount of time a transaction commit needs to hold out a flush is a
+relatively long period of time - the pinning of log items needs to be done
+while we are holding out a CIL flush, so at the moment that means it is held
+across the formatting of the objects into memory buffers (i.e. while memcpy()s
+are in progress). Ultimately a two pass algorithm where the formatting is done
+separately to the pinning of objects could be used to reduce the hold time of
+the transaction commit side.
+
+Because of the number of potential transaction commit side holders, the lock
+really needs to be a sleeping lock - if the CIL flush takes the lock, we do not
+want every other CPU in the machine spinning on the CIL lock. Given that
+flushing the CIL could involve walking a list of tens of thousands of log
+items, it will get held for a significant time and so spin contention is a
+significant concern. Preventing lots of CPUs spinning doing nothing is the
+main reason for choosing a sleeping lock even though nothing in either the
+transaction commit or CIL flush side sleeps with the lock held.
+
+It should also be noted that CIL flushing is also a relatively rare operation
+compared to transaction commit for asynchronous transaction workloads - only
+time will tell if using a read-write semaphore for exclusion will limit
+transaction commit concurrency due to cache line bouncing of the lock on the
+read side.
+
+The second serialisation point is on the transaction commit side where items
+are inserted into the CIL. Because transactions can enter this code
+concurrently, the CIL needs to be protected separately from the above
+commit/flush exclusion. It also needs to be an exclusive lock but it is only
+held for a very short time and so a spin lock is appropriate here. It is
+possible that this lock will become a contention point, but given the short
+hold time once per transaction I think that contention is unlikely.
+
+The final serialisation point is the checkpoint commit record ordering code
+that is run as part of the checkpoint commit and log force sequencing. The code
+path that triggers a CIL flush (i.e. whatever triggers the log force) will enter
+an ordering loop after writing all the log vectors into the log buffers but
+before writing the commit record. This loop walks the list of committing
+checkpoints and needs to block waiting for checkpoints to complete their commit
+record write. As a result it needs a lock and a wait variable. Log force
+sequencing also requires the same lock, list walk, and blocking mechanism to
+ensure completion of checkpoints.
+
+These two sequencing operations can use the mechanism even though the
+events they are waiting for are different. The checkpoint commit record
+sequencing needs to wait until checkpoint contexts contain a commit LSN
+(obtained through completion of a commit record write) while log force
+sequencing needs to wait until previous checkpoint contexts are removed from
+the committing list (i.e. they've completed). A simple wait variable and
+broadcast wakeups (thundering herds) has been used to implement these two
+serialisation queues. They use the same lock as the CIL, too. If we see too
+much contention on the CIL lock, or too many context switches as a result of
+the broadcast wakeups these operations can be put under a new spinlock and
+given separate wait lists to reduce lock contention and the number of processes
+woken by the wrong event.
+
+
+Lifecycle Changes
+
+The existing log item life cycle is as follows:
+
+	1. Transaction allocate
+	2. Transaction reserve
+	3. Lock item
+	4. Join item to transaction
+		If not already attached,
+			Allocate log item
+			Attach log item to owner item
+		Attach log item to transaction
+	5. Modify item
+		Record modifications in log item
+	6. Transaction commit
+		Pin item in memory
+		Format item into log buffer
+		Write commit LSN into transaction
+		Unlock item
+		Attach transaction to log buffer
+
+	<log buffer IO dispatched>
+	<log buffer IO completes>
+
+	7. Transaction completion
+		Mark log item committed
+		Insert log item into AIL
+			Write commit LSN into log item
+		Unpin log item
+	8. AIL traversal
+		Lock item
+		Mark log item clean
+		Flush item to disk
+
+	<item IO completion>
+
+	9. Log item removed from AIL
+		Moves log tail
+		Item unlocked
+
+Essentially, steps 1-6 operate independently from step 7, which is also
+independent of steps 8-9. An item can be locked in steps 1-6 or steps 8-9
+at the same time step 7 is occurring, but only steps 1-6 or 8-9 can occur
+at the same time. If the log item is in the AIL or between steps 6 and 7
+and steps 1-6 are re-entered, then the item is relogged. Only when steps 8-9
+are entered and completed is the object considered clean.
+
+With delayed logging, there are new steps inserted into the life cycle:
+
+	1. Transaction allocate
+	2. Transaction reserve
+	3. Lock item
+	4. Join item to transaction
+		If not already attached,
+			Allocate log item
+			Attach log item to owner item
+		Attach log item to transaction
+	5. Modify item
+		Record modifications in log item
+	6. Transaction commit
+		Pin item in memory if not pinned in CIL
+		Format item into log vector + buffer
+		Attach log vector and buffer to log item
+		Insert log item into CIL
+		Write CIL context sequence into transaction
+		Unlock item
+
+	<next log force>
+
+	7. CIL push
+		lock CIL flush
+		Chain log vectors and buffers together
+		Remove items from CIL
+		unlock CIL flush
+		write log vectors into log
+		sequence commit records
+		attach checkpoint context to log buffer
+
+	<log buffer IO dispatched>
+	<log buffer IO completes>
+
+	8. Checkpoint completion
+		Mark log item committed
+		Insert item into AIL
+			Write commit LSN into log item
+		Unpin log item
+	9. AIL traversal
+		Lock item
+		Mark log item clean
+		Flush item to disk
+	<item IO completion>
+	10. Log item removed from AIL
+		Moves log tail
+		Item unlocked
+
+From this, it can be seen that the only life cycle differences between the two
+logging methods are in the middle of the life cycle - they still have the same
+beginning and end and execution constraints. The only differences are in the
+commiting of the log items to the log itself and the completion processing.
+Hence delayed logging should not introduce any constraints on log item
+behaviour, allocation or freeing that don't already exist.
+
+As a result of this zero-impact "insertion" of delayed logging infrastructure
+and the design of the internal structures to avoid on disk format changes, we
+can basically switch between delayed logging and the existing mechanism with a
+mount option. Fundamentally, there is no reason why the log manager would not
+be able to swap methods automatically and transparently depending on load
+characteristics, but this should not be necessary if delayed logging works as
+designed.
+
+Roadmap:
+
+2.6.37 Remove experimental tag from mount option
+	=> should be roughly 6 months after initial merge
+	=> enough time to:
+		=> gain confidence and fix problems reported by early
+		   adopters (a.k.a. guinea pigs)
+		=> address worst performance regressions and undesired
+		   behaviours
+		=> start tuning/optimising code for parallelism
+		=> start tuning/optimising algorithms consuming
+		   excessive CPU time
+
+2.6.39 Switch default mount option to use delayed logging
+	=> should be roughly 12 months after initial merge
+	=> enough time to shake out remaining problems before next round of
+	   enterprise distro kernel rebases