Commit Graph

3 Commits

Author SHA1 Message Date
Azat Khuzhin
7b5d156cc5 Optimize SPARSE_HASHED layout (by using PackedHashMap)
In case you want dictionary optimized for memory, SPARSE_HASHED is not
always gives you what you need.

Consider the following example <UInt64, UInt16> as <Key, Value>, but
this pair will also have a 6 byte padding (on amd64), so this is almost
40% of space wastage.

And because of this padding, even google::sparse_hash_map, does not make
picture better, in fact, sparse_hash_map is not very friendly to memory
allocators (especially jemalloc).

Here are some numbers for dictionary with 1e9 elements and UInt64 as
key, and UInt16 as value:

settings                         | load (sec) | read (sec) | read (million rows/s) | bytes_allocated | RSS
HASHED upstream                  | -          | -          | -                     | -               | 35GiB
SPARSE_HASHED upstream           | -          | -          | -                     | -               | 26GiB
-                                | -          | -          | -                     | -               | -
sparse_hash_map glibc hashbench  | -          | -          | -                     | -               | 17.5GiB
sparse_hash_map packed allocator | 101.878    | 231.48     | 4.32                  | -               | 17.7GiB
PackedHashMap                    | 15.514     | 42.35      | 23.61                 | 20GiB           | 22GiB

As you can see PackedHashMap looks way more better then HASHED, and
even better then SPARSE_HASHED, but slightly worse then sparse_hash_map
with packed allocator (it is done with a custom patch to google
sparse_hash_map).

v2: rebase on top of bucket_count fix
Signed-off-by: Azat Khuzhin <a.khuzhin@semrush.com>
2023-05-19 06:07:21 +02:00
Azat Khuzhin
925fd2c33a tests/performance: do not use scientific notation in hashed_dictionary_sharded
v2: fix few mistakes
Signed-off-by: Azat Khuzhin <a.khuzhin@semrush.com>
2023-01-13 13:39:26 +01:00
Azat Khuzhin
345c422e28 Add ability to load hashed dictionaries using multiple threads
Right now dictionaries (here I will talk about only
HASHED/SPARSE_HASHED/COMPLEX_KEY_HASHED/COMPLEX_KEY_SPARSE_HASHED)
can load data only in one thread, since it uses one hash table that
cannot be filled from multiple threads.

And in case you have very big dictionary (i.e. 10e9 elements), it can
take a awhile to load them, especially for SPARSE_HASHED variants (and
if you have such amount of elements there, you are likely use
SPARSE_HASHED, since it requires less memory), in my env it takes ~4
hours, which is enormous amount of time.

So this patch add support of shards for dictionaries, number of shards
determine how much hash tables will use this dictionary, also, and which
is more important, how much threads it can use to load the data.

And with 16 threads this works 2x faster, not perfect though, see the
follow up patches in this series.

v0: PARTITION BY
v1: SHARDS 1
v2: SHARDS(1)
v3: tried optimized mod - logical and, but it does not gain even 10%
v4: tried squashing more (max_block_size * shards), but it does not gain even 10% either
v5: move SHARDS into layout parameters (unknown simply ignored)
v6: tune params for perf tests (to avoid too long queries)
Signed-off-by: Azat Khuzhin <a.khuzhin@semrush.com>
2023-01-13 13:39:25 +01:00