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Fixes generated by 'codespell' and manually reviewed. Signed-off-by: Lucas De Marchi <lucas.demarchi@profusion.mobi>
794 lines
40 KiB
Plaintext
794 lines
40 KiB
Plaintext
XFS Delayed Logging Design
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--------------------------
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Introduction to Re-logging in XFS
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---------------------------------
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XFS logging is a combination of logical and physical logging. Some objects,
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such as inodes and dquots, are logged in logical format where the details
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logged are made up of the changes to in-core structures rather than on-disk
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structures. Other objects - typically buffers - have their physical changes
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logged. The reason for these differences is to reduce the amount of log space
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required for objects that are frequently logged. Some parts of inodes are more
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frequently logged than others, and inodes are typically more frequently logged
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than any other object (except maybe the superblock buffer) so keeping the
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amount of metadata logged low is of prime importance.
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The reason that this is such a concern is that XFS allows multiple separate
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modifications to a single object to be carried in the log at any given time.
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This allows the log to avoid needing to flush each change to disk before
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recording a new change to the object. XFS does this via a method called
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"re-logging". Conceptually, this is quite simple - all it requires is that any
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new change to the object is recorded with a *new copy* of all the existing
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changes in the new transaction that is written to the log.
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That is, if we have a sequence of changes A through to F, and the object was
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written to disk after change D, we would see in the log the following series
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of transactions, their contents and the log sequence number (LSN) of the
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transaction:
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Transaction Contents LSN
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A A X
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B A+B X+n
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C A+B+C X+n+m
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D A+B+C+D X+n+m+o
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<object written to disk>
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E E Y (> X+n+m+o)
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F E+F Yٍ+p
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In other words, each time an object is relogged, the new transaction contains
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the aggregation of all the previous changes currently held only in the log.
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This relogging technique also allows objects to be moved forward in the log so
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that an object being relogged does not prevent the tail of the log from ever
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moving forward. This can be seen in the table above by the changing
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(increasing) LSN of each subsequent transaction - the LSN is effectively a
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direct encoding of the location in the log of the transaction.
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This relogging is also used to implement long-running, multiple-commit
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transactions. These transaction are known as rolling transactions, and require
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a special log reservation known as a permanent transaction reservation. A
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typical example of a rolling transaction is the removal of extents from an
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inode which can only be done at a rate of two extents per transaction because
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of reservation size limitations. Hence a rolling extent removal transaction
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keeps relogging the inode and btree buffers as they get modified in each
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removal operation. This keeps them moving forward in the log as the operation
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progresses, ensuring that current operation never gets blocked by itself if the
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log wraps around.
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Hence it can be seen that the relogging operation is fundamental to the correct
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working of the XFS journalling subsystem. From the above description, most
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people should be able to see why the XFS metadata operations writes so much to
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the log - repeated operations to the same objects write the same changes to
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the log over and over again. Worse is the fact that objects tend to get
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dirtier as they get relogged, so each subsequent transaction is writing more
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metadata into the log.
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Another feature of the XFS transaction subsystem is that most transactions are
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asynchronous. That is, they don't commit to disk until either a log buffer is
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filled (a log buffer can hold multiple transactions) or a synchronous operation
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forces the log buffers holding the transactions to disk. This means that XFS is
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doing aggregation of transactions in memory - batching them, if you like - to
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minimise the impact of the log IO on transaction throughput.
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The limitation on asynchronous transaction throughput is the number and size of
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log buffers made available by the log manager. By default there are 8 log
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buffers available and the size of each is 32kB - the size can be increased up
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to 256kB by use of a mount option.
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Effectively, this gives us the maximum bound of outstanding metadata changes
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that can be made to the filesystem at any point in time - if all the log
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buffers are full and under IO, then no more transactions can be committed until
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the current batch completes. It is now common for a single current CPU core to
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be to able to issue enough transactions to keep the log buffers full and under
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IO permanently. Hence the XFS journalling subsystem can be considered to be IO
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bound.
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Delayed Logging: Concepts
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-------------------------
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The key thing to note about the asynchronous logging combined with the
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relogging technique XFS uses is that we can be relogging changed objects
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multiple times before they are committed to disk in the log buffers. If we
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return to the previous relogging example, it is entirely possible that
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transactions A through D are committed to disk in the same log buffer.
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That is, a single log buffer may contain multiple copies of the same object,
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but only one of those copies needs to be there - the last one "D", as it
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contains all the changes from the previous changes. In other words, we have one
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necessary copy in the log buffer, and three stale copies that are simply
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wasting space. When we are doing repeated operations on the same set of
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objects, these "stale objects" can be over 90% of the space used in the log
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buffers. It is clear that reducing the number of stale objects written to the
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log would greatly reduce the amount of metadata we write to the log, and this
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is the fundamental goal of delayed logging.
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From a conceptual point of view, XFS is already doing relogging in memory (where
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memory == log buffer), only it is doing it extremely inefficiently. It is using
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logical to physical formatting to do the relogging because there is no
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infrastructure to keep track of logical changes in memory prior to physically
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formatting the changes in a transaction to the log buffer. Hence we cannot avoid
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accumulating stale objects in the log buffers.
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Delayed logging is the name we've given to keeping and tracking transactional
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changes to objects in memory outside the log buffer infrastructure. Because of
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the relogging concept fundamental to the XFS journalling subsystem, this is
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actually relatively easy to do - all the changes to logged items are already
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tracked in the current infrastructure. The big problem is how to accumulate
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them and get them to the log in a consistent, recoverable manner.
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Describing the problems and how they have been solved is the focus of this
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document.
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One of the key changes that delayed logging makes to the operation of the
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journalling subsystem is that it disassociates the amount of outstanding
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metadata changes from the size and number of log buffers available. In other
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words, instead of there only being a maximum of 2MB of transaction changes not
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written to the log at any point in time, there may be a much greater amount
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being accumulated in memory. Hence the potential for loss of metadata on a
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crash is much greater than for the existing logging mechanism.
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It should be noted that this does not change the guarantee that log recovery
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will result in a consistent filesystem. What it does mean is that as far as the
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recovered filesystem is concerned, there may be many thousands of transactions
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that simply did not occur as a result of the crash. This makes it even more
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important that applications that care about their data use fsync() where they
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need to ensure application level data integrity is maintained.
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It should be noted that delayed logging is not an innovative new concept that
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warrants rigorous proofs to determine whether it is correct or not. The method
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of accumulating changes in memory for some period before writing them to the
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log is used effectively in many filesystems including ext3 and ext4. Hence
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no time is spent in this document trying to convince the reader that the
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concept is sound. Instead it is simply considered a "solved problem" and as
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such implementing it in XFS is purely an exercise in software engineering.
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The fundamental requirements for delayed logging in XFS are simple:
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1. Reduce the amount of metadata written to the log by at least
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an order of magnitude.
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2. Supply sufficient statistics to validate Requirement #1.
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3. Supply sufficient new tracing infrastructure to be able to debug
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problems with the new code.
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4. No on-disk format change (metadata or log format).
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5. Enable and disable with a mount option.
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6. No performance regressions for synchronous transaction workloads.
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Delayed Logging: Design
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-----------------------
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Storing Changes
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The problem with accumulating changes at a logical level (i.e. just using the
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existing log item dirty region tracking) is that when it comes to writing the
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changes to the log buffers, we need to ensure that the object we are formatting
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is not changing while we do this. This requires locking the object to prevent
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concurrent modification. Hence flushing the logical changes to the log would
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require us to lock every object, format them, and then unlock them again.
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This introduces lots of scope for deadlocks with transactions that are already
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running. For example, a transaction has object A locked and modified, but needs
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the delayed logging tracking lock to commit the transaction. However, the
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flushing thread has the delayed logging tracking lock already held, and is
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trying to get the lock on object A to flush it to the log buffer. This appears
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to be an unsolvable deadlock condition, and it was solving this problem that
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was the barrier to implementing delayed logging for so long.
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The solution is relatively simple - it just took a long time to recognise it.
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Put simply, the current logging code formats the changes to each item into an
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vector array that points to the changed regions in the item. The log write code
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simply copies the memory these vectors point to into the log buffer during
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transaction commit while the item is locked in the transaction. Instead of
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using the log buffer as the destination of the formatting code, we can use an
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allocated memory buffer big enough to fit the formatted vector.
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If we then copy the vector into the memory buffer and rewrite the vector to
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point to the memory buffer rather than the object itself, we now have a copy of
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the changes in a format that is compatible with the log buffer writing code.
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that does not require us to lock the item to access. This formatting and
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rewriting can all be done while the object is locked during transaction commit,
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resulting in a vector that is transactionally consistent and can be accessed
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without needing to lock the owning item.
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Hence we avoid the need to lock items when we need to flush outstanding
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asynchronous transactions to the log. The differences between the existing
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formatting method and the delayed logging formatting can be seen in the
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diagram below.
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Current format log vector:
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Object +---------------------------------------------+
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Vector 1 +----+
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Vector 2 +----+
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Vector 3 +----------+
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After formatting:
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Log Buffer +-V1-+-V2-+----V3----+
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Delayed logging vector:
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Object +---------------------------------------------+
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Vector 1 +----+
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Vector 2 +----+
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Vector 3 +----------+
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After formatting:
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Memory Buffer +-V1-+-V2-+----V3----+
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Vector 1 +----+
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Vector 2 +----+
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Vector 3 +----------+
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The memory buffer and associated vector need to be passed as a single object,
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but still need to be associated with the parent object so if the object is
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relogged we can replace the current memory buffer with a new memory buffer that
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contains the latest changes.
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The reason for keeping the vector around after we've formatted the memory
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buffer is to support splitting vectors across log buffer boundaries correctly.
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If we don't keep the vector around, we do not know where the region boundaries
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are in the item, so we'd need a new encapsulation method for regions in the log
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buffer writing (i.e. double encapsulation). This would be an on-disk format
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change and as such is not desirable. It also means we'd have to write the log
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region headers in the formatting stage, which is problematic as there is per
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region state that needs to be placed into the headers during the log write.
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Hence we need to keep the vector, but by attaching the memory buffer to it and
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rewriting the vector addresses to point at the memory buffer we end up with a
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self-describing object that can be passed to the log buffer write code to be
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handled in exactly the same manner as the existing log vectors are handled.
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Hence we avoid needing a new on-disk format to handle items that have been
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relogged in memory.
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Tracking Changes
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Now that we can record transactional changes in memory in a form that allows
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them to be used without limitations, we need to be able to track and accumulate
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them so that they can be written to the log at some later point in time. The
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log item is the natural place to store this vector and buffer, and also makes sense
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to be the object that is used to track committed objects as it will always
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exist once the object has been included in a transaction.
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The log item is already used to track the log items that have been written to
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the log but not yet written to disk. Such log items are considered "active"
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and as such are stored in the Active Item List (AIL) which is a LSN-ordered
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double linked list. Items are inserted into this list during log buffer IO
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completion, after which they are unpinned and can be written to disk. An object
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that is in the AIL can be relogged, which causes the object to be pinned again
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and then moved forward in the AIL when the log buffer IO completes for that
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transaction.
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Essentially, this shows that an item that is in the AIL can still be modified
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and relogged, so any tracking must be separate to the AIL infrastructure. As
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such, we cannot reuse the AIL list pointers for tracking committed items, nor
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can we store state in any field that is protected by the AIL lock. Hence the
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committed item tracking needs it's own locks, lists and state fields in the log
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item.
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Similar to the AIL, tracking of committed items is done through a new list
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called the Committed Item List (CIL). The list tracks log items that have been
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committed and have formatted memory buffers attached to them. It tracks objects
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in transaction commit order, so when an object is relogged it is removed from
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it's place in the list and re-inserted at the tail. This is entirely arbitrary
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and done to make it easy for debugging - the last items in the list are the
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ones that are most recently modified. Ordering of the CIL is not necessary for
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transactional integrity (as discussed in the next section) so the ordering is
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done for convenience/sanity of the developers.
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Delayed Logging: Checkpoints
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When we have a log synchronisation event, commonly known as a "log force",
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all the items in the CIL must be written into the log via the log buffers.
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We need to write these items in the order that they exist in the CIL, and they
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need to be written as an atomic transaction. The need for all the objects to be
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written as an atomic transaction comes from the requirements of relogging and
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log replay - all the changes in all the objects in a given transaction must
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either be completely replayed during log recovery, or not replayed at all. If
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a transaction is not replayed because it is not complete in the log, then
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no later transactions should be replayed, either.
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To fulfill this requirement, we need to write the entire CIL in a single log
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transaction. Fortunately, the XFS log code has no fixed limit on the size of a
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transaction, nor does the log replay code. The only fundamental limit is that
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the transaction cannot be larger than just under half the size of the log. The
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reason for this limit is that to find the head and tail of the log, there must
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be at least one complete transaction in the log at any given time. If a
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transaction is larger than half the log, then there is the possibility that a
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crash during the write of a such a transaction could partially overwrite the
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only complete previous transaction in the log. This will result in a recovery
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failure and an inconsistent filesystem and hence we must enforce the maximum
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size of a checkpoint to be slightly less than a half the log.
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Apart from this size requirement, a checkpoint transaction looks no different
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to any other transaction - it contains a transaction header, a series of
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formatted log items and a commit record at the tail. From a recovery
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perspective, the checkpoint transaction is also no different - just a lot
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bigger with a lot more items in it. The worst case effect of this is that we
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might need to tune the recovery transaction object hash size.
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Because the checkpoint is just another transaction and all the changes to log
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items are stored as log vectors, we can use the existing log buffer writing
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code to write the changes into the log. To do this efficiently, we need to
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minimise the time we hold the CIL locked while writing the checkpoint
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transaction. The current log write code enables us to do this easily with the
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way it separates the writing of the transaction contents (the log vectors) from
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the transaction commit record, but tracking this requires us to have a
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per-checkpoint context that travels through the log write process through to
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checkpoint completion.
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Hence a checkpoint has a context that tracks the state of the current
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checkpoint from initiation to checkpoint completion. A new context is initiated
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at the same time a checkpoint transaction is started. That is, when we remove
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all the current items from the CIL during a checkpoint operation, we move all
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those changes into the current checkpoint context. We then initialise a new
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context and attach that to the CIL for aggregation of new transactions.
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This allows us to unlock the CIL immediately after transfer of all the
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committed items and effectively allow new transactions to be issued while we
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are formatting the checkpoint into the log. It also allows concurrent
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checkpoints to be written into the log buffers in the case of log force heavy
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workloads, just like the existing transaction commit code does. This, however,
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requires that we strictly order the commit records in the log so that
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checkpoint sequence order is maintained during log replay.
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To ensure that we can be writing an item into a checkpoint transaction at
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the same time another transaction modifies the item and inserts the log item
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into the new CIL, then checkpoint transaction commit code cannot use log items
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to store the list of log vectors that need to be written into the transaction.
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Hence log vectors need to be able to be chained together to allow them to be
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detached from the log items. That is, when the CIL is flushed the memory
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buffer and log vector attached to each log item needs to be attached to the
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checkpoint context so that the log item can be released. In diagrammatic form,
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the CIL would look like this before the flush:
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CIL Head
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V
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Log Item <-> log vector 1 -> memory buffer
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| -> vector array
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V
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Log Item <-> log vector 2 -> memory buffer
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| -> vector array
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V
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......
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V
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Log Item <-> log vector N-1 -> memory buffer
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| -> vector array
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V
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Log Item <-> log vector N -> memory buffer
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-> vector array
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And after the flush the CIL head is empty, and the checkpoint context log
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vector list would look like:
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Checkpoint Context
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V
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log vector 1 -> memory buffer
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| -> vector array
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| -> Log Item
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V
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log vector 2 -> memory buffer
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| -> vector array
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| -> Log Item
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V
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......
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V
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log vector N-1 -> memory buffer
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| -> vector array
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| -> Log Item
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V
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log vector N -> memory buffer
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-> vector array
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-> Log Item
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Once this transfer is done, the CIL can be unlocked and new transactions can
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start, while the checkpoint flush code works over the log vector chain to
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commit the checkpoint.
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Once the checkpoint is written into the log buffers, the checkpoint context is
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attached to the log buffer that the commit record was written to along with a
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completion callback. Log IO completion will call that callback, which can then
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run transaction committed processing for the log items (i.e. insert into AIL
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and unpin) in the log vector chain and then free the log vector chain and
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checkpoint context.
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Discussion Point: I am uncertain as to whether the log item is the most
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efficient way to track vectors, even though it seems like the natural way to do
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it. The fact that we walk the log items (in the CIL) just to chain the log
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vectors and break the link between the log item and the log vector means that
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we take a cache line hit for the log item list modification, then another for
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the log vector chaining. If we track by the log vectors, then we only need to
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break the link between the log item and the log vector, which means we should
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dirty only the log item cachelines. Normally I wouldn't be concerned about one
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vs two dirty cachelines except for the fact I've seen upwards of 80,000 log
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vectors in one checkpoint transaction. I'd guess this is a "measure and
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compare" situation that can be done after a working and reviewed implementation
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is in the dev tree....
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Delayed Logging: Checkpoint Sequencing
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One of the key aspects of the XFS transaction subsystem is that it tags
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committed transactions with the log sequence number of the transaction commit.
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This allows transactions to be issued asynchronously even though there may be
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future operations that cannot be completed until that transaction is fully
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committed to the log. In the rare case that a dependent operation occurs (e.g.
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re-using a freed metadata extent for a data extent), a special, optimised log
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force can be issued to force the dependent transaction to disk immediately.
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To do this, transactions need to record the LSN of the commit record of the
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transaction. This LSN comes directly from the log buffer the transaction is
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written into. While this works just fine for the existing transaction
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mechanism, it does not work for delayed logging because transactions are not
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written directly into the log buffers. Hence some other method of sequencing
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transactions is required.
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As discussed in the checkpoint section, delayed logging uses per-checkpoint
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contexts, and as such it is simple to assign a sequence number to each
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checkpoint. Because the switching of checkpoint contexts must be done
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atomically, it is simple to ensure that each new context has a monotonically
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increasing sequence number assigned to it without the need for an external
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atomic counter - we can just take the current context sequence number and add
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one to it for the new context.
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Then, instead of assigning a log buffer LSN to the transaction commit LSN
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during the commit, we can assign the current checkpoint sequence. This allows
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operations that track transactions that have not yet completed know what
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checkpoint sequence needs to be committed before they can continue. As a
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|
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 asymmetric 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
|
|
committing 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.
|