Subject: Re: Using Expanded Objects other than Arrays from plpgsql

From: Michel Pelletier <[email-masked]>
Date: Sun, 20 Oct 2024 20:29:13 -0700

On Sun, Oct 20, 2024 at 10:13 AM Tom Lane <[email-masked]> wrote:

>
> I'm not sure.  It seems certain that if the object is already expanded
> (either R/W or R/O), the paths for that in plpgsql_exec_function could
> be taken regardless of its specific type.
>

> But it seems like we could get an easy win by adjusting
> plpgsql_exec_function along the lines of
>
> l. 549:
> -                    if (!var->isnull && var->datatype->typisarray)
> +                    if (!var->isnull)
>
> l. 564:
> -                        else
> +                        else if (var->datatype->typisarray)
>
> How far does that improve matters for you?
>

I tried this change and couldn't get it to work, on the next line:

if (!var->isnull)
{
    if (VARATT_IS_EXTERNAL_EXPANDED_RW(DatumGetPointer(var->value)))

var->value might not be a pointer, as it seems at least from my gdb
scratching, but say an integer.  This segfaults on non-array but
non-expandable datum.

I guess this gets back into knowing if a flat thing is expandable or not.
I'm going to spend some more time looking at it, I haven't been in this
corner of Postgres before.

Another comment that caught my eye was this one:

https://github.com/postgres/postgres/blob/master/src/pl/plpgsql/src/pl_exec.c#L8304

Not sure what the implication is there.

-Michel

---

From: Tom Lane <[email-masked]>
Date: Sun, 20 Oct 2024 23:46:44 -0400

Michel Pelletier <[email-masked]> writes:
>> ...

> scratching, but say an integer.  This segfaults on non-array but

Oh, duh --- the typisarray test serves to eliminate pass-by-value
types.  We need the same test that exec_assign_value makes,
!var->datatype->typbyval, before it's safe to apply DatumGetPointer.
So line 549 needs to be more like

-                    if (!var->isnull && var->datatype->typisarray)
+                    if (!var->isnull && !var->datatype->typbyval)

> Not sure what the implication is there.

Yeah, that's some more unfinished business.  I'm not sure if it
matters to your use-case or not.

BTW, we probably should move this thread to pgsql-hackers.

			regards, tom lane

---

From: Michel Pelletier <[email-masked]>
Date: Mon, 21 Oct 2024 10:23:33 -0700

> > On Sun, Oct 20, 2024 at 10:13 AM Tom Lane <[email-masked]> wrote:

(from thread
https://www.postgresql.org/message-id/CACxu%3DvJaKFNsYxooSnW1wEgsAO5u_v1XYBacfVJ14wgJV_PYeg%40mail.gmail.com
)

>   We need the same test that exec_assign_value makes,

And here we are, thanks for your help on this Tom.  For some thread
switching context for others, I'm writing a postgres extension that wraps
the SuiteSparse:GraphBLAS API and provides new types for sparse and dense
matrices and vectors.  It's like a combination of numpy and scipy.sparse
but for Postgres with an emphasis on graph analytics as sparse adjacency
matrices using linear algebra.

I use the expandeddatum API to flatten and expand on disk compressed
representations of these objects into "live" in-memory objects managed by
SuiteSparse.  All GraphBLAS objects are opaque handles, and my expanded
objects are essentially a box around this handle.  I use memory context
callbacks to free the handles when the memory context of the box is freed.
This works very well and I've made a lot of progress on creating a very
clean algebraic API, here are the doctests for matrices, this is all
generated from live code!

https://onesparse.github.io/OneSparse/test_matrix_header/

Doing some benchmarking I noticed that when writing some simple graph
algorithms in plpgsql, my objects were being constantly flattened and
expanded.  Posting my question above to pgsql-general Tom gave me some tips
and suggested I move the thread here.

My non-expert summary: plpgsql only optimizes for expanded objects if they
are arrays.  Non array expanded objects get flattened/expanded on every
use.  For large matrices and vectors this is very expensive.  Ideally I'd
like to expand my object, use it throughout the function, return it to
another function that may use it, and only flatten it when it goes to disk
or it's completely unavoidable.  The comment in expandeddatum.h really kind
of sells this as one of the main features:

 * An expanded object is meant to survive across multiple operations, but
 * not to be enormously long-lived; for example it might be a local variable
 * in a PL/pgSQL procedure.  So its extra bulk compared to the on-disk
format
 * is a worthwhile trade-off.

In my case it's not a question of saving bulk, the on disk representation
of a matrix is not useful at compute time, it needs to be expanded (using
GraphBLAS's serialize/deserialize API) for it to be usable for matrix
operations like matmul.  In most cases algorithms using these objects
iterate in a loop, doing various algebraic operations almost always
involving a matmul until they converge on a stable solution or they exhaust
the input elements.  Here for example is a "minimum parent BFS" that takes
a graph and a starting node, and traverses the graph breadth first,
computing a vector of every node and its minimum parent id.

CREATE OR REPLACE FUNCTION bfs(graph matrix, start_node bigint)
>     RETURNS vector LANGUAGE plpgsql AS
>     $$
>     DECLARE
>     bfs_vector vector = vector('int32');
>     next_vector vector = vector('int32');
>     BEGIN
>         bfs_vector = set_element(bfs_vector, start_node, 1);
>         WHILE sssp_vector != next_vector LOOP
>             next_vector = dup(bfs_vector);
>             bfs_vector = vxm(bfs_vector, graph, 'any_secondi_int32',
>                              w=>bfs_vector, accum=>'min_int32');
>         END LOOP;
>     RETURN bfs_vector;
>     end;
>     $$;
>

(If you're wondering "Why would anyone do it this way" it's because
SuiteSparse is optimized for parallel sparse matrix multiplication and has
a JIT compiler that can target multiple architectures, at the moment CPUs
and CUDA GPUs.  Reusing the same Linear Algebra already prevalent in graph
theory means not having to think about any low level implementation issues
and having code that is completely portable from CPU to GPU or other
accelerators).

So, I made the two small changes Tom suggested above and I have them in a
side fork here:

https://github.com/postgres/postgres/compare/master...michelp:postgres-upstream:michelp-flatless#diff-0c35024d1576c347689c7abad68abd8562a0aa5f0d2c63d6d65df4b360b0e807

Good news, my code still works, but bad news is there is still a lot of
flattening/expanding/freeing going on at multiple points in each iteration
of the algorithm.  I'll note too that:

    BEGIN
        bfs_vector = set_element(sssp_vector, start_node, 1);

I'd prefer that to not be an assignment, set_element mutates the object (I
eventually plan to support subscripting syntax like bfs_vector[start_node]
= 1)

same with:

            bfs_vector = vxm(bfs_vector, graph, 'any_secondi_int32',
                             w=>bfs_vector, accum=>'min_int32');

This matmul mutates bfs_vector, I shouldn't need to reassign it back but at
the moment it seems necessary otherwise the mutations are lost but this
costs a full flatten/expand cycle.

Short term my goal is to optimize plpgsql so that my objects stay expanded
for the life of the function.  Long term there's some "unfinished business"
to use Tom's words around the expandeddatum API.  I'm not really qualified
to speak on these issue but this is my understanding of some of them:

  - plpgsql knows how to expand arrays and is hardwired for it, but how
would it know how to expand other expandable types?

  - Issues with exec_check_rw_parameter also being hardwired to only
optimize expanded objects for array append and prepend, I suspect this has
something to do with my issue above about mutating objects in place.

I may have missed something but hopefully that brings anyone up to speed
interested in this topic.

-Michel

---

From: Tom Lane <[email-masked]>
Date: Tue, 22 Oct 2024 15:33:40 -0400

> or it's completely unavoidable.

Right.  My recollection is that when we first invented expanded
objects, we only implemented expanded arrays, and so it seemed
premature to try to define generalized APIs.  So that went on the back
burner until we got some more cases to look at.  But now we also have
expanded records, and with your use-case as an example of an extension
trying to do similar things, I feel like we have enough examples to
move forward.

As far as the hack we were discussing upthread goes, I realized that
it should test for typlen == -1 not just !typbyval, since the
VARATT_IS_EXTERNAL_EXPANDED_RW test requires that there be a length
word.  With that fix and some comment updates, it looks like the
attached.  I'm inclined to just go ahead and push that.  It won't move
the needle hugely far, but it will help, and it seems simple and safe.

To make more progress, there are basically two areas that we need
to look at:

1. exec_assign_value() has hard-wired knowledge that it's a good idea
to expand an array that's being assigned to a plpgsql variable, and
likewise hard-wired knowledge that calling expand_array() is how to
do that.  The bit in plpgsql_exec_function() that we're patching
in the attached is the same thing, but for the initial assignment of
a function input parameter to a plpgsql variable.  At the time this
was written I was quite unsure that forcible expansion would be a net
win, but the code is nine years old now and there's been few or no
performance complaints.  So maybe it's okay to decide that "always
expand expandable types during assignment" is a suitable policy across
the board, and we don't need to figure out a smarter rule.  It sounds
like that'd probably be a win for your application, which gives me
more faith in the idea than I would've had before.  That leaves the
problem of how to find the right code to call to do the expansion.
Clearly, we need to attach something to data types to make that
possible.  My first thought was to invent a pg_type column (and
CREATE TYPE/ALTER TYPE options, and pg_dump support, yadda yadda)
containing the OID of a function corresponding to expand_array().
However, that work would have to be done again the next time we
think of something we'd like to know about a data type.  So now
I'm thinking that we should steal ideas from the "prosupport" API
(see src/include/nodes/supportnodes.h) and invent a concept of a
"type support" function that can handle an extensible set of
different requests.  The first one would be to pass back the
address of an expansion function comparable to expand_array(),
if the type supports being converted to an expanded object.

2. Most of the performance gold is hidden in deciding when we
can optimize operations on expanded objects that look like

	plpgsql_var := f(plpgsql_var, other-parameters);

by passing a R/W rather than R/O expanded pointer to f() and letting
it munge the expanded object in-place.  If we fail to do that then
f() has to construct a new expanded object for its result.  It's
probably still better off getting a R/O pointer than a flat object,
but nonetheless we fail to avoid a lot of data copying.

The difficulty here is that we do not want to change the normal naive
semantics of such an assignment, in particular "if f() throws an error
then the value of plpgsql_var has not been modified".  This means that
we can only optimize when the R/W parameter is to be passed to the
top-level function of the expression (else, some function called later
could throw an error and ruin things).  Furthermore, we need a
guarantee from f() that it will not throw an error after modifying
the value.

As things stand, plpgsql has hard-wired knowledge that
array_subscript_handler(), array_append(), and array_prepend()
are safe in that way, but it knows nothing about anything else.
So one route to making things better seems fairly clear: invent a new
prosupport request that asks whether the function is prepared to make
such a guarantee.  I wonder though if you can guarantee any such thing
for your functions, when you are relying on a library that's probably
not designed with such a restriction in mind.  If this won't work then
we need a new concept.

One idea I was toying with is that it doesn't matter if f()
throws an error so long as the plpgsql function is not executing
within an exception block: if the error propagates out of the plpgsql
function then we no longer care about the value of the variable.
That would very substantially weaken the requirements on how f()
is implemented.  I'm not sure that we could make this work across
multiple levels of plpgsql functions (that is, if the value of the
variable ultimately resides in some outer function) but right now
that's not an issue since no plpgsql function as such would ever
promise to be safe, thus it would never receive a R/W pointer to
some outer function's variable.

> costs a full flatten/expand cycle.

I'm not hugely excited about that.  We could imagine extending
this concept to INOUT parameters of procedures, but it doesn't
seem like that buys anything except a small notational savings.
Maybe it would work to allow multiple parameters of a procedure
to be passed as R/W, whereas we're restricted to one for the
function-notation method.  So possibly there's a gain there but
I'm not sure how big.

BTW, if I understand your example correctly then bfs_vector is
being passed to vxm() twice.  This brings up an interesting
point: if we pass the first instance as R/W, and vxm() manipulates it,
then the changes would also be visible in its other parameter "w".
This is certainly not per normal semantics.  A "safe" function would
have to either not have any possibility that two parameters could
refer to the same object, or be coded in a way that made it impervious
to this issue --- in your example, it couldn't look at "w" anymore
once it'd started modifying the first parameter.  Is that an okay
requirement, and if not what shall we do about it?

Anyway that's my brain dump for today.  Thoughts?

			regards, tom lane

diff --git a/src/pl/plpgsql/src/pl_exec.c b/src/pl/plpgsql/src/pl_exec.c
index ea9740e3f8..80b8654fc8 100644
--- a/src/pl/plpgsql/src/pl_exec.c
+++ b/src/pl/plpgsql/src/pl_exec.c
@@ -532,21 +532,22 @@ plpgsql_exec_function(PLpgSQL_function *func, FunctionCallInfo fcinfo,
 									  false);
 
 					/*
-					 * Force any array-valued parameter to be stored in
-					 * expanded form in our local variable, in hopes of
-					 * improving efficiency of uses of the variable.  (This is
-					 * a hack, really: why only arrays? Need more thought
-					 * about which cases are likely to win.  See also
-					 * typisarray-specific heuristic in exec_assign_value.)
-					 *
-					 * Special cases: If passed a R/W expanded pointer, assume
+					 * If it's a pass-by-reference type, check to see if we
+					 * received a R/W expanded-object pointer.  If so, assume
 					 * we can commandeer the object rather than having to copy
 					 * it.  If passed a R/O expanded pointer, just keep it as
 					 * the value of the variable for the moment.  (We'll force
 					 * it to R/W if the variable gets modified, but that may
 					 * very well never happen.)
+					 *
+					 * Also, force any flat array value to be stored in
+					 * expanded form in our local variable, in hopes of
+					 * improving efficiency of uses of the variable.  (This is
+					 * a hack, really: why only arrays? Need more thought
+					 * about which cases are likely to win.  See also
+					 * typisarray-specific heuristic in exec_assign_value.)
 					 */
-					if (!var->isnull && var->datatype->typisarray)
+					if (!var->isnull && var->datatype->typlen == -1)
 					{
 						if (VARATT_IS_EXTERNAL_EXPANDED_RW(DatumGetPointer(var->value)))
 						{
@@ -561,7 +562,7 @@ plpgsql_exec_function(PLpgSQL_function *func, FunctionCallInfo fcinfo,
 						{
 							/* R/O pointer, keep it as-is until assigned to */
 						}
-						else
+						else if (var->datatype->typisarray)
 						{
 							/* flat array, so force to expanded form */
 							assign_simple_var(&estate, var,

---

From: Michel Pelletier <[email-masked]>
Date: Tue, 22 Oct 2024 21:15:30 -0700

> But now we also have

Great!

> the needle hugely far, but it will help, and it seems simple and safe.

I made those changes and my code works a bit faster, it looks like it takes
a couple of the top level expansions out.  I'll have more data in the
morning.

> more faith in the idea than I would've had before.

Definitely a win, as the flattened format of my objects don't have any run
time use, so there is no chance for net loss for me.  I guess I'm using
this feature differently from how arrays are, which have a usable flattened
format so there is a need to weigh a trade off with expanding or not.   In
my case, only the expanded version is useful, and serializing the flat
version is expensive.  Formalizing something like expand_array would work
well for me, as my expand_matrix function has the identical function
signature and serves the exact same purpose.

   So now

> if the type supports being converted to an expanded object.

I'll look into the support code, I haven't seen that before.

> not designed with such a restriction in mind.  If this won't work then

This will work for the GraphBLAS API.  The expanded object in my case is
really just a small box struct around a GraphBLAS "handle" which is an
opaque pointer to data which I cannot mutate, only the library can change
the object behind the handle.  The API makes strong guarantees that it will
either do the operation and return a success code or not do the operation
and return an error code.  It's not possible (normally) to get a corrupt or
incomplete object back.

> some outer function's variable.

The water here is pretty deep for me but I'm pretty sure I get what you're
saying, I'll need to do some more studying of the plpgsql code which I've
been spending the last couple of days familiarizing myself with more.

> being passed to vxm() twice.

Yes, this is not unusual in this form of linear algebra, as multiple
operations often accumulate into the same object to prevent a bunch of
copying during each iteration of a given algorithm.  There is also a "mask"
parameter where another or the same object can be provided to either mask
in or out (compliment mask) values during the accumulation phase.  This is
very useful for many algorithms, and good example is the Burkhardt method
of Triangle Counting (
https://journals.sagepub.com/doi/10.1177/1473871616666393) which in
GraphBLAS boils down to:

    GrB_mxm (C, A, NULL, semiring, A, A, GrB_DESC_S) ;
    GrB_reduce (&ntri, NULL, monoid, C, NULL) ;
    ntri /= 6 ;

In this case A is three of the parameters to mxm, the left operand, right
operand, and a structural mask.  This can be summed up as "A squared,
masked by A", which when reduced returns the number of triangles in the
graph (times 6).

>   This brings up an interesting

I *think*, if I understand you correctly, that this isn't an issue for the
GraphBLAS.  My expanded objects are just boxes around an opaque handle, I
don't actually mutate anything inside the box, and I can't see past the
opaque pointer.  SuiteSparse may be storing the matrix in one of many
different formats, or on a GPU, or who knows, all I have is a handle to "A"
which I pass to GraphBLAS methods which is the only way I can interact with
them.  Here's the definition of that vxm function:

https://github.com/OneSparse/OneSparse/blob/main/src/matrix.c#L907

It's pretty straightforward, get the arguments, and pass them to the
GraphBLAS API, there is no mutable structure inside the expanded "box",
just the handle.

I'm using the expanded object API to solve my two key problems, flatten an
object for disk storage, expand that object (through the GraphBLAS
serialize/deserialize API) and turn it into an object handle, which is
secretly just a pointer of course to the internal details of the object,
but I can't see or change that, only SuiteSparse can.

(btw sorry about the bad parameter names, "w" is the name from the API spec
which I've been sticking to, which is the optional output object to use, if
one is not passed, I create a new one, this is similar to the numpy "out"
parameter semantics) .

I added some debug instrumentation that might show a bit more of what's
going on for me, consider this function:

CREATE OR REPLACE FUNCTION test(graph matrix)
    RETURNS matrix LANGUAGE plpgsql AS
    $$
    DECLARE
      n bigint = nrows(graph);
      m bigint = ncols(graph);
    BEGIN
    RETURN graph;
    end;
    $$;

The graph passes straight through but first I call two methods to get the
number rows and columns.  When I run it on a graph:

postgres=# select pg_typeof(test(graph)) from test_graphs ;
DEBUG:  matrix_nvals
DEBUG:  DatumGetMatrix
DEBUG:  expand_matrix
DEBUG:  new_matrix
DEBUG:  context_callback_matrix_free
DEBUG:  matrix_ncols
DEBUG:  DatumGetMatrix
DEBUG:  expand_matrix
DEBUG:  new_matrix
DEBUG:  context_callback_matrix_free
 pg_typeof
-----------
 matrix
(1 row)

THe matrix gets expanded twice, presumably because the object comes in
flat, and both nrows() and ncols() expands it, which ends up being two
separate handles and thus two separate objects to the GraphBLAS.

Here's another example:

CREATE OR REPLACE FUNCTION test2(graph matrix)
    RETURNS bigint LANGUAGE plpgsql AS
    $$
    BEGIN
    perform set_element(graph, 1, 1, 1);
    RETURN nvals(graph);
    end;
    $$;
CREATE FUNCTION
postgres=# select test2(matrix('int32'));
DEBUG:  new_matrix
DEBUG:  matrix_get_flat_size
DEBUG:  flatten_matrix
DEBUG:  scalar_int32
DEBUG:  new_scalar
DEBUG:  matrix_set_element
DEBUG:  DatumGetMatrix
DEBUG:  expand_matrix
DEBUG:  new_matrix
DEBUG:  DatumGetScalar
DEBUG:  matrix_get_flat_size
DEBUG:  matrix_get_flat_size
DEBUG:  flatten_matrix
DEBUG:  context_callback_matrix_free
DEBUG:  context_callback_scalar_free
DEBUG:  matrix_nvals
DEBUG:  DatumGetMatrix
DEBUG:  expand_matrix
DEBUG:  new_matrix
DEBUG:  context_callback_matrix_free
DEBUG:  context_callback_matrix_free
 test2
-------
     0
(1 row)

I would expect that to return 1.  If I do "graph = set_element(graph, 1, 1,
1)" it works.

I hope that gives a bit more information about my use cases, in general I'm
very happy with the API, it's very algebraic, I have a lot of interesting
plans for supporting more operators and subscription syntax, but this issue
is not my top priority to see if we can resolve it.  I'm sure I missed
something in your detailed plan so I'll be going over it some more this
week.  Please let me know if you have any other questions about my use case
or concerns about my expectations.

Thank you!

-Michel