maria-developers team mailing list archive

[Kristian Nielsen <knielsen@xxxxxxxxxxxxxxx>]

andrei.elkin@xxxxxxxxxx writes:

> Your comments, thoughts and critical notes are most welcome!

Thanks for the interesting idea and detailed description, Andrei! I have
written some initial comments inline, below:

> entering the binlog group (ordered) commit module. They can end up
> into binlog as A,B or B,A, and regardless of that (Gtid actually) order
> also be acknowledged to the user in either way.
>
> The latter fact infers that slave does not have to commit the group
> sub-transaction/branches in the GTID order. It could be done in any
> order including no order at all like to do so as one epoch commit.

However, MariaDB GTID requires that transactions be binlogged in the same
order on the slave as on the master. Otherwise it is not possible to move a
lower-level GTID slave from one master to the other, as the slave position
only includes a single GTID in MariaDB.

> conservative scheduler offers a decent parallelization method still suffering from 
> the aforementioned uneven branch's sizes and inter-thread
> communications caused by ordering. The optimistic scheduler remedies to some level
> but not fully (an optimistically executed group may be unbalanced too)
> and even conceding some risk of performance degradation (rollback is costly).

Jean François Gagné's comprehensive benchmarking of parallel replication
actually has some very interesting data on this. He ran a real Booking.com
workload with literally thousands of worker threads and had a huge rollback
ratio (I remember it as up around 40%), and still saw speedup and good
scalabitily. Apparently rollback isn't necessarily so costly; maybe because
replication servers often have spare cores idling anyway, and because the
aborted transaction acts as a pre-fetcher, improving I/O parallelism.

But the fact that thousands of threads still improved speed suggests exactly
that there was a problem of uneven transaction size - a few large
transactions spread far apart, so lots of transaction lookahead was needed.
I do not know if those transactions were single large queries or contained
many individual statements, but in the latter case this is exactly what this
idea could help with!

> There is an idea reminiscent to pipelining to handle the epoch (the
> master binlog group) as a single transaction but in parallel. That is
> to execute its statements by multiple workers, this time scheduling
> them fairly, and "atomically" commit their works.

So this is a very interesting idea. Once the transactions are recorded in
the binlog, we have a serial stream of statements that will reproduce the
original data on the master. And they will do this regardless of if we
remove some of the COMMITs/BEGINs - or if we add some. (I wonder if there
are any exceptions to this, I can't think of any off the top of my head).
So instead of trying to parallelise transactions, just do all the individual
statements in parallel, disregarding transaction boundaries (with some
restrictions to ensure consistency, as you describe below).

I wonder how much this will benefit real-life workloads. There seems to be a
lot of potential. For some workloads it will not help - if most transactions
are single-statement, or if the multi-statement transactions have
dependencies between the statements. But that doesn't seem likely to be the
typical scenario.

But why tie this to the master binlog group? It seems to fit perfectly to
the optimistic parallel replication mode, where different transactions are
run in parallel speculatively, and any conflicts are detected and resolved.
In fact, it seems the exact same mechanism will work to detect conflicts
between the more fine-grained per-statement parallelisation.

The conservative parallle replication I consider obsolete. It causes a lot
of hassle for the user to try to get good-sized group commits on the master
to ensure parallel replication opportunities on the slave. And it doesn't
even ensure consistency; there are corner cases (in InnoDB and elsewhere)
that can cause conflicts to appear anyway on the slave, so the
rollback+retry mechanism is needed anyway for conservative, just like for
optimistic.

> To the fairness part, workers get assigned by a statement at a time
> from the epoch transaction(sub-transaction BEGIN, COMMIT removed).
> Say 'E' an epoch consists of 's' of sub-transaction
>
>   E := { T_1, T_2, ... T_s }
>
> For each m from 1 to s sub-transactions T_m gets scheduled to some worker
>
>          W_1   W_2 ... W_k
>
>           |     |       |
>           V     V       V
>       
> T_m :=  { e_1, e_2, ... e_l }
>
>   Hereinafter I use the TeX math notation, '^' - a superscript attached to
>   the event to designate its parent transaction sequence number (Gtid
>   seq_no), '_' - a subscript to enumerate an object within its
>   compound object.
>
> e_i stands for T-ransation's statements, W_t:s are workers.
> Effectively the epoch breaks into modified branches executed by
> workers on one to one basic:
>
>    E := { T'_1, T'_2, ... T'_k }
>
> here 'k' is the number of workers engaged, T' indicates the modified
> transaction.
> The branches are executed until they are ready to prepare which event
> is triggered by scheduling of the last statement of the last original
> sub-transaction.
>
> It's clear that sizes of the modified branches are even this time.

Well... each worker has exactly one statement at a time, but each statement
can be very different in execution cost. But more even than
transaction-based scheduling, certainly.

> The last statement worker coordinates 2pc.
>
> Thinking more technically workers can consume/pull from
> the current epoch presented as a queue which is pushed into
> by statement producer.
>
> Here is a possible state of the queue when m:th statement of T_n is
> about to be pushed:
>
> e^n_k ->
>
>
>  [ e^n_m-1, ..., e^n_2, e^n_1;    ...;       e^1_l1, ... e^1_2, e^1_1 ]
>
>    ...----- T_n ------------| T_n-1,...T_2   |---------- T_1 ---------| 
>
> A pull by consumer at this point would return e^1_1.

How do you imagine integrating this in the current parallel replication
scheduling algorithm?

In the current algorithm, the producer (the SQL thread) assigns work to
worker threads in a round-robin way. There is a lot of care taken to
minimise contention on a single global queue-lock or similar, and I think
that is an important reason why Jean François' tests were able to scale so
well to many thousand worker threads.

I wonder if the existing scheduling could not be used directly for this idea
also - but it needs to be extended of course to schedule individual
statements rather than whole transactions, with some way to let worker
threads coordinate transaction start/end between them.

What are your thoughts on this?

> Very likely that by the epoch prepare event *all* the branches have been already
> ready for prepare().

Hm, any particular reason you think so? I would imagine the opposite, that
individual statements will be scheduled quickly, and it will be quite random
in which order they happen to become ready in?

> This pipelining parallelization method can work for the single "large"
> transaction in the binlog group and also could drag into the
> parallelizable input transactions from later groups if we additionally
> create master side dependency tracking (think of mysql logical
> timestamp method).
> Also notice that the optimisitic scheduler is orthogonal to this
> method so the two can be combined.
>
> Consistency concern
> -------------------
>
> The epoch parallel execution (scheduling) must respect
> intra-transaction statement dependencies (e.g FIFO execution order of
> operations over the same object [record, table]). There is no
> inter-transaction dependencies, at least in theory.

In fact, there do exist such inter-transaction dependencies in a number of
corner cases, at least if we want to enforce the same commit order on slave
as on master, which is required for MariaDB GTID. But that is already
handled in current code, by detecting the dependency inside the storage
engine (the thd_rpl_deadlock_check() mechanism).

I wonder if the exact same thd_rpl_deadlock_check() mechanism would not work
as well for this per-statement scheduling idea? It would be interesting to
see a proof-of-concept based on this...

> The notion of a leader, the two-phase-commits leader, remains roughly
> the same as in the existing conservative scheduler. This time more
> than initiating commits of the epoch branches it also takes care to
> advance the slave gtid execution status accordingly.
> It could be implemented as the very last statement of its own T' branch.

Hm, right, interesting, agree that this seems a good fit.
In fact, if the existing mechanism can be slightly extended, maybe it can
already do much of what is needed to ensure consistency. Eg. suppose we have
3 original transactions each with two statements:

  e^1_1 e^1_2 e^2_1 e^2_2 e^3_1 e^3_2

Suppose the first 3 of these are ready to commit at some point:

  e^1_1 e^1_2 e^2_1

The leader can check that it doesn't try to commit only part of an original
transaction. In this case it sees that e^2_1 is missing e_2_2, and it can
commit only the first part and leave the partial transaction for a following
group commit:

  e^2_1

This way, we already ensure that a crash will not leave us with an
inconsistent storage engine state on the slave. Because we never commit part
of an original master transaction - all parts of it are always
group-committed together. Seems promising, though that code is also heavily
optimised for scalability, so will require some case.

Hm, one case needs to be handled though - when there are more statements in
one original master transaction, than there are worker threads - otherwise
we end up with a deadlock.

> It's clear that causal dependencies of an user write and a read (to
> find the effect of that write) can be tracked by WAIT_FOR_GTID() as
> currently.
>
> A plain two-phase commit does admit possibility to catch on slave combinations
> of the old (pre-epoch) and new version (post-epoch) or some objects of
> the same transaction if the user hits with non-locking SELECT in a
> "tiny" time window between commit():s of two branches
> like in the following example.
>
> Let t1,t2 some tables and the binlog group consists of just one
> transaction
>
>      T_1 := { update(t1), update(t2) }
>
> Let on slave it's modified into two parallel ones:
>
>    T'_1 := { update(t1) } || T'2 := { update(t2) }
>
> After both respond OK to 2pc prepare() and then the leader initiates
> commit() where could be 4 possible result sets to the contemporary SELECT
>
>    SET @@session.tx_isolation='REPEATABLE-READ';
>    SELECT * from t1 as t_1, t2 as t_2;
>    => ...

Well, due to the enforced commit order, it will not be possible to see the
case where update(t2) is committed but update(t1) is not.

In fact, if the group commit is extended as suggested above (to only
group-commit the statements of an original transaction together), then I
think it is possible for the user to avoid this problem entirely using

  START TRANSACTION WITH CONSISTENT SNAPSHOT

In MariaDB, this ensures a consistent read view against 2pc transactions
(reader will always see all of the 2pc commit or none of it). And IIRC, it
works by holding the same lock (LOCK_commit_ordered) that is used by the
group commit leader. So if the user has some special case where this minor
read-inconsistency is sensitive, the START TRANSACTION WITH CONSISTENT
SNAPSHOT mechanism can be used to avoid it completely.

> While this is perhaps more than imperfect, I believe it may be
> relevant only to remote corner cases, but more importantly, we still can
> refine that doing some *adjustments* in the Engine studied briefly
> myself of what would be a sub-transaction in Innodb,
> "ideologically" endorsed  and guided by Marko Makela.
> The idea is to hold the branch's locks even after the branch commits,
> and delegate their release to the leader.
>
> Recoverability
> --------------
>
> When slave is configured to log in the binary log
> we must make sure to rollback any prepared
> epoch branches at the server recovery unless the last branch (of the
> leader) is also there, prepared.
>
> When it does not binlog the problem is that the modified branch's binlog
> images can't be just flushed one after another especially
> if the user specifies to log on the slave uniformly with the master
> that is to preserve the original sub-transaction structures and their
> boundaries.

"if the user specified" - but this is always a requirement in MariaDB,
right? Otherwise GTID order is broken?

> In such case there are several multiple option, here are some:
>
> - use relay-logged image of original sub-transactions (may be limited
>   to the  master and slave version combination though;)

I did not follow what this means - can you elaborate?

> - reconstruct original sub-transaction's binlog images. That is
>   binlog events "belonging" to an original sub-transaction will be
>   cached cooperatively by workers that took share of the
>   original sub-transaction execution.
>
>   Optionally at least the caching could be set to allow out
>   of order while the statements are parallelizable, like in the above
>   T1(t1,t2) example. Otherwise the ordering will be preserved through
>   implementing the shared cache as as a queue with an interface
>   to insert an item into the middle.

Isn't it possible to do the binlog caching locally, each worker caching just
the binlogging for its own statement? If we make sure they group-commit
together, they will be written in sequence into the binlog, so they can just
write each their part one after the other?

> - exotics like to create the slave side "merge" GTID which would
>   embed the original "commit". (The quotes here to allude to the Git's
>   way).
>
> While it's a serious subject I am leaving out mariabackup for this moment.
> I believe it will be feasible to adjust its logics to
> account as prepared only such transactions that that
> are prepared in all their branches.
>
> More about pipeline style optimization
> --------------------------------------
>
> As mentioned workers can be made self-serving to assign events for
> execution at once when become available. That must turn to think of
> producer-consumer model, potentially lock-free queues, dynamical # of
> workers to stay in balance with the receiver's pace etc.

So are you planning to implement a completely new parallel replication
scheduler, rather than build on the existing one?

> I think *eventually* we will need to assign the producer role to
> the IO (receiver) thread, and convert the current SQL (driver) thread
> into (relay-) logger (we still may have to have such logger for
> the semisync replication, the relay logger can be opted out
> otherwise).
> Here is a picture
>
> IO_thread.push()
>    |                                  +---- worker.pull()
>    V                                  V
>   e^s_i -> [  e^s_i-1, ... e^s_1 }, T_s-1, ... ]
>                                       ^
>                                       |
>                                       SQL.pull()
>
> where on the right hand side the two consumers handle
> a transaction and when both of them have done with it
> (a worker has read its last event and the logger written
> it to the relay-log) the query element becomes
> garbage-collectable.

So overall, this was an interesting idea to see! I never thought before of
doing parallelisation beyond the original transaction boundaries from the
master. But now that you have described it, it actually seems quite a
natural extension of the optimistic parallel replication, and it fits very
well with the fundamental principle in MariaDB replication of preserving
strict GTID ordering, which might work to handle much of the consistency
requirements.

It would be quite interesting to see this in practice on real workloads and
with benchmarks - I could imagine very large improvements for some
workloads. Though I suppose you shouldn't underestimate the work required to
complete something like this in production quality (the devil is in the
detail, once you get to nasty things like temporary tables and
non-transactional engines and other horrors that are part of the
MySQL/MariaDB ecosystem).

Hope this helps,

 - Kristian.