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diff --git a/Documentation/filesystems/xfs-delayed-logging-design.txt b/Documentation/filesystems/xfs-delayed-logging-design.txt new file mode 100644 index 00000000000..96d0df28bed --- /dev/null +++ b/Documentation/filesystems/xfs-delayed-logging-design.txt @@ -0,0 +1,811 @@ +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 |