1. introduce alpha. the value of 1.1 is optimal, so hard-code it.

2. hard-code ef_construction=10, best by test

3. rename hnsw_max_connection_per_layer to mhnsw_max_edges_per_node
   (max_connection is rather ambiguous in MariaDB) and add a help text

4. rename hnsw_ef_search to mhnsw_min_limit and add a help text

* mhnsw:
  * use primary key, innodb loves and (and the index cannot have dupes anyway)
    * MyISAM is ok with that, performance-wise
  * must be ha_rnd_init(0) because we aren't going to scan
    * MyISAM resets the position on ha_rnd_init(0) so query it before
    * oh, and use the correct handler, just in case
  * HA_ERR_RECORD_IS_THE_SAME is no error
* innodb:
  * return ref_length on create
  * don't assume table->pos_in_table_list is set
  * ok, assume away, but only for system versioned tables
* set alter_info on create (InnoDB needs to check for FKs)
* pair external_lock/external_unlock correctly

also add missing candidates.empty();

we know it every time

Now there's an FVector class which is a pure vector, an array of floats.
It doesn't necessarily corresponds to a row in the table, and usually
there is only one FVector instance - the one we're searching for.

And there's an FVectorNode class, which is a node in the graph.
It has a ref (identifying a row in the source table), possibly an array
of floats (or not — in which case it will be read lazily from the
source table as needed). There are many FVectorNodes and they're
cached to avoid re-reading them from the disk.

move everything into a query-local memroot which is freed at the end

instead of pointers to FVectorRef's (which are stored elsewhere)
let's return one big array of all refs. Freeing this array will
free the complete result set.

* sysvars should be REQUIRED_ARG
* fix a mix of US and UK spelling (use US)
* use consistent naming
* work if VEC_DISTANCE arguments are in the swapped order (const, col)
* work if VEC_DISTANCE argument is NULL/invalid or wrong length
* abort INSERT if the value is invalid or wrong length
* store the "number of neighbors" in a blob in endianness-independent way
* use field->store(longlong, bool) not field->store(double)
* a lot more error checking everywhere
* cleanup after errors
* simplify calling conventions, remove reinterpret_cast's
* todo/XXX comments
* whitespaces
* use float consistently

memory management is still totally PoC quality

Initial HNSW implementation

This commit includes the work done in collaboration with Hugo Wen from
Amazon:

    MDEV-33408 Alter HNSW graph storage and fix memory leak

    This commit changes the way HNSW graph information is stored in the
    second table. Instead of storing connections as separate records, it now
    stores neighbors for each node, leading to significant performance
    improvements and storage savings.

    Comparing with the previous approach, the insert speed is 5 times faster,
    search speed improves by 23%, and storage usage is reduced by 73%, based
    on ann-benchmark tests with random-xs-20-euclidean and
    random-s-100-euclidean datasets.

    Additionally, in previous code, vector objects were not released after
    use, resulting in excessive memory consumption (over 20GB for building
    the index with 90,000 records), preventing tests with large datasets.
    Now ensure that vectors are released appropriately during the insert and
    search functions. Note there are still some vectors that need to be
    cleaned up after search query completion. Needs to be addressed in a
    future commit.

    All new code of the whole pull request, including one or several files
    that are either new files or modified ones, are contributed under the
    BSD-new license. I am contributing on behalf of my employer Amazon Web
    Services, Inc.

As well as the commit:

    Introduce session variables to manage HNSW index parameters

    Three variables:

    hnsw_max_connection_per_layer
    hnsw_ef_constructor
    hnsw_ef_search

    ann-benchmark tool is also updated to support these variables in commit
    https://github.com/HugoWenTD/ann-benchmarks/commit/e09784e for branch
    https://github.com/HugoWenTD/ann-benchmarks/tree/mariadb-configurable

    All new code of the whole pull request, including one or several files
    that are either new files or modified ones, are contributed under the
    BSD-new license. I am contributing on behalf of my employer Amazon Web
    Services, Inc.
Co-authored-by: Hugo Wen <wenhug@amazon.com>

also add const to methods in List<> and Hash_set<>
while we're at it

MDEV-33407 Parser support for vector indexes

The syntax is

  create table t1 (... vector index (v) ...);

limitation:
* v is a binary string and NOT NULL
* only one vector index per table
* temporary tables are not supported

MDEV-33404 Engine-independent indexes: subtable method

added support for so-called "high level indexes", they are not visible
to the storage engine, implemented on the sql level. For every such
an index in a table, say, t1, the server implicitly creates a second
table named, like, t1#i#05 (where "05" is the index number in t1).
This table has a fixed structure, no frm, not accessible directly,
doesn't go into the table cache, needs no MDLs.

MDEV-33406 basic optimizer support for k-NN searches

for a query like SELECT ... ORDER BY func() optimizer will use
item_func->part_of_sortkey() to decide what keys can be used
to resolve ORDER BY.