ClickHouse/tests/performance/hashed_dictionary_load_factor.xml
Azat Khuzhin 2996b38606 Add ability to configure maximum load factor for the HASHED/SPARSE_HASHED layout
As it turns out, HashMap/PackedHashMap works great even with max load
factor of 0.99. By "great" I mean it least it works faster then
google sparsehash, and not to mention it's friendliness to the memory
allocator (it has zero fragmentation since it works with a continuious
memory region, in comparison to the sparsehash that doing lots of
realloc, which jemalloc does not like, due to it's slabs).

Here is a table of different setups:

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 0.5                | 15.514     | 42.35      | 23.61                 | 20GiB           | 22GiB
hashed 0.95                      | 34.903     | 115.615    | 8.65                  | 16GiB           | 18.7GiB
**PackedHashMap 0.95**           | **93.6**   | **19.883** | **10.68**             | **10GiB**       | **12.8GiB**
PackedHashMap 0.99               | 26.113     | 83.6       | 11.96                 | 10GiB           | 12.3GiB

As it shows, PackedHashMap with 0.95 max_load_factor, eats 2.6x less
memory then SPARSE_HASHED in upstream, and it also 2x faster for read!

v2: fix grower
Signed-off-by: Azat Khuzhin <a.khuzhin@semrush.com>
2023-05-19 06:07:21 +02:00

93 lines
3.2 KiB
XML

<test>
<substitutions>
<substitution>
<name>layout_suffix</name>
<values>
<value>HASHED</value>
<value>SPARSE_HASHED</value>
</values>
</substitution>
<substitution>
<name>load_factor</name>
<values>
<!-- 0. will be prepended -->
<value>5</value>
<value>7</value>
<value>99</value>
</values>
</substitution>
</substitutions>
<create_query>
CREATE TABLE simple_key_dictionary_source_table
(
id UInt64,
value_int UInt16
) ENGINE = Memory
</create_query>
<create_query>
CREATE TABLE complex_key_dictionary_source_table
(
id UInt64,
id_key String,
value_int UInt64
) ENGINE = Memory
</create_query>
<create_query>
CREATE DICTIONARY IF NOT EXISTS simple_key_{layout_suffix}_dictionary_l0_{load_factor}
(
id UInt64,
value_int UInt64
)
PRIMARY KEY id
SOURCE(CLICKHOUSE(TABLE 'simple_key_dictionary_source_table'))
LAYOUT({layout_suffix}(MAX_LOAD_FACTOR 0.{load_factor}))
LIFETIME(0)
</create_query>
<create_query>
CREATE DICTIONARY IF NOT EXISTS complex_key_{layout_suffix}_dictionary_l0_{load_factor}
(
id UInt64,
id_key String,
value_int UInt64
)
PRIMARY KEY id, id_key
SOURCE(CLICKHOUSE(TABLE 'complex_key_dictionary_source_table'))
LAYOUT(COMPLEX_KEY_{layout_suffix}(MAX_LOAD_FACTOR 0.{load_factor}))
LIFETIME(0)
</create_query>
<fill_query>INSERT INTO simple_key_dictionary_source_table SELECT number, number FROM numbers(3_000_000)</fill_query>
<fill_query>INSERT INTO complex_key_dictionary_source_table SELECT number, toString(number), number FROM numbers(2_000_000)</fill_query>
<fill_query>SYSTEM RELOAD DICTIONARY simple_key_{layout_suffix}_dictionary_l0_{load_factor}</fill_query>
<fill_query>SYSTEM RELOAD DICTIONARY complex_key_{layout_suffix}_dictionary_l0_{load_factor}</fill_query>
<query>SYSTEM RELOAD DICTIONARY simple_key_{layout_suffix}_dictionary_l0_{load_factor}</query>
<query>SYSTEM RELOAD DICTIONARY complex_key_{layout_suffix}_dictionary_l0_{load_factor}</query>
<query>
WITH rand64() % 3_000_000 as key
SELECT dictHas('default.simple_key_{layout_suffix}_dictionary_l0_{load_factor}', key)
FROM numbers(3_000_000)
FORMAT Null
</query>
<query>
WITH (rand64() % 2_000_000, toString(rand64() % 2_000_000)) as key
SELECT dictHas('default.complex_key_{layout_suffix}_dictionary_l0_{load_factor}', key)
FROM numbers(2_000_000)
FORMAT Null
</query>
<drop_query>DROP DICTIONARY simple_key_{layout_suffix}_dictionary_l0_{load_factor}</drop_query>
<drop_query>DROP DICTIONARY complex_key_{layout_suffix}_dictionary_l0_{load_factor}</drop_query>
<drop_query>DROP TABLE simple_key_dictionary_source_table</drop_query>
<drop_query>DROP TABLE complex_key_dictionary_source_table</drop_query>
</test>