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Rr/sc 60366 sparse global order reader merge #5417
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stdx::reverse_comparator<stdx::or_equal<GlobalCellCmp>> cmp( | ||
stdx::or_equal<GlobalCellCmp>(array_schema_.domain())); | ||
if (tile_queue.empty()) { | ||
length = to_process.max_slab_length(global_order_lower_bound, cmp); |
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This needs some work. The intent of this code is correct (i.e. we must bound the slab here to avoid out-of-order results) but the implementation of that intent may not be.
Running on a real-world 2D array, with a highly selective subarray I observed horrid performance, and I believe this code here is responsible.
In my repro, the lower end of emit_bound
is (3352576, 2)
but the current coordinate from rc
is (3353524, 1484)
. The tile extents are 2048 in both dimensions, so this coordinate occurs after emit_bound
in the global order.
Surprisingly this doesn't lead to an incorrect result (or at least, a result which is different than with this code OFF), but it does cause the accumulation of lots of result slabs of length 1, which is horridly slow.
The next_global_order_tile
is {fragment_idx_ = 121, tile_idx_ = 643}
, what are the bounds of the previous tile which should occur earlier in global order?
Tile 642's MBR has a lower bound of (3352576, 40963)
and an upper bound of (3354623, 55294)
.
Tile 643's MBR has a lower bound of (3352576, 2)
and an upper bound of (3354905, 59234)
.
This smells kind of funky but it does check out if the MBR is the minimum bound on each dimension rather than the value of the minimum coordinate in the tile. Tile 643 straddles two tiles in dimension 0 so going up to 2 for dimension 1 is plausible.
And if that's the case (which I hope to confirm soon), then using the MBR here is not correct, we need a different way to get the safe-to-emit bound here.
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This is now mostly resolved - I say mostly because the changes I pushed in 2efe0fa are actually still not correct, but the code looks more similar to what I believe to be the correct code.
It is not only allowed, but commonplace for the MBRs of the tiles to be out of order with respect to each other.
I added a lengthy comment to preprocess_compute_result_tile_order
which goes into detail about what the merge bound should be instead.
I'm not going to resolve this yet. I want to add another 2D test for the condition which may provoke this. But I think this is definitely review-able now. There's a FIXME
comment which explains what the current problem might be.
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Review part 2, everything but the changes in the readers.
@@ -118,6 +118,8 @@ const std::string Config::SM_MEMORY_BUDGET_VAR = "10737418240"; // 10GB | |||
const std::string Config::SM_QUERY_DENSE_QC_COORDS_MODE = "false"; | |||
const std::string Config::SM_QUERY_DENSE_READER = "refactored"; | |||
const std::string Config::SM_QUERY_SPARSE_GLOBAL_ORDER_READER = "refactored"; | |||
const std::string Config::SM_QUERY_SPARSE_GLOBAL_ORDER_PREPROCESS_TILE_MERGE = | |||
"128"; |
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Let's add a TODO or a reference to a ticket to eventually
we will either want to recommend a value to customers, or choose one and flip this to a boolean.
if (tile_.has_value()) { | ||
return (*tile_)->coord((*tile_)->cell_num() - 1, d); | ||
} else { | ||
return mbr_.value().coord(d); |
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if (mbr_.has_value())
?
same for line 166.
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In its current state, one of the two optional
fields must be valid. I would prefer to express that using the constructors.
However this is the one part of this code which I expect needs some more tweaks - this may look different when I am done with that
: fragment_idx_(fragment_idx) { | ||
} | ||
|
||
unsigned fragment_idx_; |
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some more documentation on member variables and methods of this class would help.
} else if (!preprocess_tile_order_.enabled_) { | ||
return memory_used_for_coords_total_ != 0; | ||
} else if (preprocess_tile_order_.has_more_tiles()) { | ||
return false; |
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} else if (!preprocess_tile_order_.enabled_) { | |
return memory_used_for_coords_total_ != 0; | |
} else if (preprocess_tile_order_.has_more_tiles()) { | |
return false; | |
} else if (preprocess_tile_order_.enabled_ && preprocess_tile_order_.has_more_tiles()) { | |
return false; |
ratio_coords_.c_str(), | ||
&error) == TILEDB_OK); | ||
REQUIRE(error == nullptr); | ||
REQUIRE(memory_.apply(config) == nullptr); | ||
|
||
REQUIRE(tiledb_ctx_alloc(config, &ctx_) == TILEDB_OK); |
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Since you added a vfs_test_setup_ I'd expect not to allocate a fresh context but update the vfs_test_setup_.ctx_ instead and set ctx_ to that. Something like:
vfs_test_setup_.update_config(config.ptr().get());
ctx_ = vfs_test_setup_.ctx_c;
See for example: https://github.com/TileDB-Inc/TileDB/blob/main/test/src/test-capi-consolidation-plan.cc#L73
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Thanks for the link!
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I won't claim I understood everything and was able to verify correctness or completeness of all the, again excellent, code of this PR. But the thorough testing gives me high confidence, so LGTM once tests pass :)
* *there are ways to get around this but they are not implemented. | ||
*/ | ||
template <InstanceType Instance> | ||
static bool can_complete_in_memory_budget( |
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I like the idea but I think that's too much logic to be the source of truth. We'd need to unit test this one too 😅 Anyway, no objection in keeping it, I was just thinking out loud.
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This one does get pretty heavy coverage! Since ::run
calls it on success or failure it does get some nice if-and-only-if coverage.
The problem with this one, though, is that it makes a strong assumption about what the merge bound is, and as I have since learned that assumption is only true in one dimension.
And yeah, I'm not intending to figure out how to adapt this for two dimensions, given that...
* Data tile 1 has a MBR of [(1, 1), (5, 4)]. | ||
* Data tile 2 has a MBR of [(5, 1), (10, 4)]. | ||
* | ||
* The lower bound of data tile 2's MBR is less than the upper bound |
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Thank you for the excellent analysis and documentation of each scenario and especially the tricky points here but also across this work!
The story contains more details, but in brief this pull request adds an additional mode to the sparse global order reader in which we pre-process the minimum bounding rectangles of all tiles from all fragments to determine a single global order in which all of the tiles must be loaded.
This pre-processing step is implemented using a "parallel merge" algorithm which merges the tiles from each fragment (which are arranged in global order within the fragment).
Parallel Merge
The parallel merge code lives in
tiledb/common/algorithm/parallel_merge.h
. It is written generically to merge streams of a copyable typeT
using any type which can compareT
(default isstd::less<T>
of course). An explanation of the algorithm is provided within the file.The top-level function
parallel_merge
is asynchronous, i.e. it returns a future which can be polled to see how much of the merge has already completed. This enables callers to begin processing merged data from the head of the eventual output before the tail of the eventual output has finished.Sparse Global Order Reader
We extend the sparse global order reader with a new configuration
sm.query.sparse_global_order.preprocess_tile_merge
. If nonzero, the sparse global order reader will run a parallel merge on the fragments to find the unified tile order and then use that to populate result tiles.preprocess_compute_result_tile_order
kicks off the parallel merge.create_result_tiles_using_preprocess
advances along the global tile order to create result tiles.The fields which are used for the old "per fragment result tiles" mode have been encapsulated into their own struct to emphasize that their use does not overlap with this new mode.
create_result_tiles_using_preprocess
does not need a per-fragment memory budget; instead it pulls tiles off of the globally ordered tile list until it has saturated the memory budget as much as it can.Tiles in the unified global order are arranged on their lower bound. The upper bounds of the tiles in the list may be out of order. To prevent cells from tile A to be emitted out of order with cells from tile B, we augment
add_next_cell_to_queue
to check the lower bound of the tiles which have not populated result tiles yet.The value of
sm.query.sparse_global_order.preprocess_tile_merge
configures the minimum amount of work that each parallel unit of the merge will do. This is so we can benchmark with different values without re-compiling; we will either want to recommend a value to customers, or choose one and flip this to a boolean.Serialization
The unified global tile order is state which must be communicated back and forth between the client and REST server. We can either serialize this whole list (16 bytes per tile across all fragments) or we can re-compute the parallel merge each time we run a
submit
on the REST server side. The current implementation chooses the latter, assuming that smaller messages are preferred to the additional CPU overhead.Testing
Testing of all changes is augmented using rapidcheck. With this library, rather than writing some test data examples, we write properties which contain generic claims about what the expected output must look like for a given input. The
rapidcheck
runtime generates arbitrary inputs to the property to test our claims.The parallel merge algorithm is tested in
unit_parallel_merge.cc
and has rapidcheck properties implemented for each step of the algorithm.The sparse global order reader tests are in
unit-sparse-global-order-reader.cc
. The gist is that we have a generic functionCSparseGlobalOrderFx::run
which writes a bunch of fragments, and then reads the data back in global order, comparing against an expected result. There's a fair bit of refactoring to support this. For 1D arrays we have testsSparse global order reader: fragment skew
,fragment interleave
, andfragment many overlap
which set up inputs which are expected to exercise some of the edge cases in the global order reader. And then we addrapidcheck 1D
andrapidcheck 2D
tests which generate totally arbitrary 1D and 2D inputs respectively.Performance Results
I still have more to do here, but things are looking pretty good... will fill in more details here as I have them. Notes are here.
TYPE: FEATURE | BUG | IMPROVEMENT
DESC: sparse global order reader determine global order of result tiles