MemCS bloom aggregate

Since: 3.6

MemCS primary index was populated with bloom aggregates. This type of
aggregates allows to use data-skipping base on bloom filter for
requests with equality filters. Also, this aggregate has a tunable fpr
parameter - false-positive rate of undrelying bloom filter. It must be
in (0..1) range. The higher fpr, the lower memory consumption. The
default value is 0.05 (5%).

Note that bloom aggregates support all fixed-size types and string
type (minmax supports only fied-size types).

Example:

local s = box.schema.create_space('test', {
    engine = 'memcs', field_count = 4,
    format = {{'a', 'uint64'}, {'b', 'uint64'}, {'c', 'uint64'},
	      {'d', 'string'}},
})
s:create_index('pk', {aggregates = {
    {type = 'bloom', field = 2, name = 'bloom_2', fpr = 0.1},
    {type = 'bloom', field = 3, name = 'bloom_3', fpr = 0.01},
    {type = 'bloom', field = 4, name = 'bloom_4'},
}})

Then filter with equality condition will automatically use bloom
aggregates, if any:

/* Create arrow stream options. */
box_arrow_options_t *options = box_arrow_options_new();

/*
 * Set filter `[2] = 42` so some rows with `[2] != 42` can be skipped.
 */
box_filter_t filter;
filter->type = FILTER_TYPE_EQ;
filter->field_no = 1; /* 0-indexation. */

char buf[16];
mp_encode_uint(buf, 42);
filter->value = buf;

box_arrow_options_set_filter(options, &filter);

/* Create stream. */
struct ArrowArrayStream stream;
int rc = box_index_arrow_stream(space_id, index_id, field_count, fields,
				key, key + key_size, options, &stream);

Regarding memory consumption, it's the same for all types - only fpr
parameter matters. Here are some memory consumption measurements:

• fpr = 0.01 - 10368 bytes consumed for each block.
• fpr = 0.05 (default value) - 7424 bytes consumed for each block.
• fpr = 0.1 - 5952 bytes consumed for each block.
• fpr = 0.5 - 1536 bytes consumed for each block.
  Any fpr higher than 0.5 has the same effect as fpr = 0.5.
  Requested by @drewdzzz in https://github.com/tarantool/tarantool-ee/commit/e6cb3bfe8bdd6576a5f94f7aaa5aff0f877346f1.

Start by locating the MemCS index and aggregate documentation, then compare it with the create_space/create_index Lua example and the box_index_arrow_stream C entry point shown here. Done means documenting bloom aggregates, supported types, fpr behavior, memory tradeoffs, and equality-filter usage with accurate examples.