Instead of lengthy blurbs, switch to single-line, machine-readable
standardized (https://spdx.dev) license identifiers. The Linux kernel
switched long ago, so there is strong precedent.
Three cases are handled: AGPL-only, Apache-only, and dual licensed.
For the latter case, I chose (AGPL-3.0-or-later and Apache-2.0),
reasoning that our changes are extensive enough to apply our license.
The changes we applied mechanically with a script, except to
licenses/README.md.
Closes#9937
This warning can catch a virtual function that thinks it
overrides another, but doesn't, because the two functions
have different signatures. This isn't very likely since most
of our virtual functions override pure virtuals, but it's
still worth having.
Enable the warning and fix numerous violations.
Closes#9347
Since key_compare does not conform to SimpleLessCompare, the benchmark
tests the non-optimized version of bptree (without SIMD key search).
We want to test the optimized version.
Closes#9180
If x is of type std::strong_ordering, then "x <=> 0" is equivalent to
x. These no-ops were inserted during #1449 fixes, but are now unnecessary.
They have potential for harm, since they can hide an accidental of the
type of x to an arithmetic type, so remove them.
Ref #1449.
Next patches will mark btree::iterator methods that modify
the tree itself as private, so stop using them in tests.
Signed-off-by: Pavel Emelyanov <xemul@scylladb.com>
It turned out that all the users of btree can already be converted
to use safer std::strong_ordering. The only meaningful change here
is the btree code itself -- no more ints there.
tests: unit(dev)
Signed-off-by: Pavel Emelyanov <xemul@scylladb.com>
Message-Id: <20210330153648.27049-1-xemul@scylladb.com>
In some places scylla clones collections of objects, so it's
sometimes needed to measure the speed of this operation.
This patch adds a placeholder for it, but no implementations
for any supported collections. It will be added soon for radix
tree.
Signed-off-by: Pavel Emelyanov <xemul@scylladb.com>
The design of the tree goes from the row-cache needs, which are
1. Insert/Remove do not invalidate iterators
2. Elements are LSA-manageable
3. Low key overhead
4. External tri-comparator
5. As little actions on insert/remove as possible
With the above the design is
Two types of nodes -- inner and leaf. Both types keep pointer on parent nodes
and N pointers on keys (not keys themselves). Two differences: inner nodes have
array of pointers on kids, leaf nodes keep pointer on the tree (to update left-
and rightmost tree pointers on node move).
Nodes do not keep pointers/references on trees, thus we have O(1) move of any
object, but O(logN) to get the tree size. Fortunately, with big keys-per-node
value this won't result in too many steps.
In turn, the tree has 3 pointers -- root, left- and rightmost leaves. The latter
is for constant-time begin() and end().
Keys are managed by user with the help of embeddable member_hook instance,
which is 1 pointer in size.
The code was copied from the B+ tree one, then heavily reworked, the internal
algorythms turned out to differ quite significantly.
For the sake of mutation_partition::apply_monotonically(), which needs to move
an element from one tree into another, there's a key_grabber helping wrapper
that allows doing this move respecting the exception-safety requirement.
As measured by the perf_collections test the B-tree with 8 keys is faster, than
the std::set, but slower than the B+tree:
vs set vs b+tree
fill: +13% -6%
find: +23% -35%
Another neat thing is that 1-key insertion-removal is ~40% faster than
for BST (the same number of allocations, but the key object is smaller,
less pointers to set-up and less instructions to execute when linking
node with root).
v4:
- equip insertion methods with on_alloc_point() calls to catch
potential exception guarantees violations eariler
- add unlink_leftmost_without_rebalance. The method is borrowed from
boost intrusive set, and is added to kill two birds -- provide it,
as it turns out to be popular, and use a bit faster step-by-step
tree destruction than plain begin+erase loop
v3:
- introduce "inline" root node that is embedded into tree object and in
which the 1st key is inserted. This greatly improves the 1-key-tree
performance, which is pretty common case for rows cache
v2:
- introduce "linear" root leaf that grows on demand
This improves the memory consumption for small trees. This linear node may
and should over-grow the NodeSize parameter. This comes from the fact that
there are two big per-key memory spikes on small trees -- 1-key root leaf
and the first split, when the tree becomes 1-key root with two half-filled
leaves. If the linear extention goes above NodeSize it can flatten even the
2nd peak
- mitigate the keys indirection a bit
Prefetching the keys while doing the intra-node linear scan and the nodes
while descending the tree gives ~+5% of fill and find
- generalize stress tests for B and B+ trees
- cosmetic changes
TODO:
- fix few inefficincies in the core code (walks the sub-tree twice sometimes)
- try to optimize the leaf nodes, that are not lef-/righmost not to carry
unused tree pointer on board
Signed-off-by: Pavel Emelyanov <xemul@scylladb.com>
In some cases a collection is used to keep several elements,
so it's good to know this timing.
For example, a mutation_partition keeps a set of rows, if used
in cache it can grow large, if used in mutation to apply, it's
typically small. Plain replacement of bst into b-tree caused
performance degardation of mutation application because b-tree
is only better at big sizes.
Signed-off-by: Pavel Emelyanov <xemul@scylladb.com>
This collection is widely used, any replacement should be
compared against it to better understand pros-n-cons.
Signed-off-by: Pavel Emelyanov <xemul@scylladb.com>
