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2996b38606
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>
93 lines
3.2 KiB
XML
93 lines
3.2 KiB
XML
<test>
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<substitutions>
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<substitution>
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<name>layout_suffix</name>
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<values>
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<value>HASHED</value>
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<value>SPARSE_HASHED</value>
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</values>
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</substitution>
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<substitution>
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<name>load_factor</name>
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<values>
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<!-- 0. will be prepended -->
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<value>5</value>
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<value>7</value>
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<value>99</value>
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</values>
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</substitution>
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</substitutions>
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<create_query>
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CREATE TABLE simple_key_dictionary_source_table
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(
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id UInt64,
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value_int UInt16
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) ENGINE = Memory
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</create_query>
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<create_query>
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CREATE TABLE complex_key_dictionary_source_table
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(
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id UInt64,
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id_key String,
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value_int UInt64
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) ENGINE = Memory
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</create_query>
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<create_query>
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CREATE DICTIONARY IF NOT EXISTS simple_key_{layout_suffix}_dictionary_l0_{load_factor}
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(
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id UInt64,
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value_int UInt64
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)
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PRIMARY KEY id
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SOURCE(CLICKHOUSE(TABLE 'simple_key_dictionary_source_table'))
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LAYOUT({layout_suffix}(MAX_LOAD_FACTOR 0.{load_factor}))
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LIFETIME(0)
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</create_query>
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<create_query>
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CREATE DICTIONARY IF NOT EXISTS complex_key_{layout_suffix}_dictionary_l0_{load_factor}
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(
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id UInt64,
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id_key String,
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value_int UInt64
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)
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PRIMARY KEY id, id_key
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SOURCE(CLICKHOUSE(TABLE 'complex_key_dictionary_source_table'))
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LAYOUT(COMPLEX_KEY_{layout_suffix}(MAX_LOAD_FACTOR 0.{load_factor}))
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LIFETIME(0)
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</create_query>
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<fill_query>INSERT INTO simple_key_dictionary_source_table SELECT number, number FROM numbers(3_000_000)</fill_query>
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<fill_query>INSERT INTO complex_key_dictionary_source_table SELECT number, toString(number), number FROM numbers(2_000_000)</fill_query>
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<fill_query>SYSTEM RELOAD DICTIONARY simple_key_{layout_suffix}_dictionary_l0_{load_factor}</fill_query>
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<fill_query>SYSTEM RELOAD DICTIONARY complex_key_{layout_suffix}_dictionary_l0_{load_factor}</fill_query>
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<query>SYSTEM RELOAD DICTIONARY simple_key_{layout_suffix}_dictionary_l0_{load_factor}</query>
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<query>SYSTEM RELOAD DICTIONARY complex_key_{layout_suffix}_dictionary_l0_{load_factor}</query>
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<query>
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WITH rand64() % 3_000_000 as key
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SELECT dictHas('default.simple_key_{layout_suffix}_dictionary_l0_{load_factor}', key)
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FROM numbers(3_000_000)
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FORMAT Null
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</query>
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<query>
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WITH (rand64() % 2_000_000, toString(rand64() % 2_000_000)) as key
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SELECT dictHas('default.complex_key_{layout_suffix}_dictionary_l0_{load_factor}', key)
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FROM numbers(2_000_000)
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FORMAT Null
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</query>
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<drop_query>DROP DICTIONARY simple_key_{layout_suffix}_dictionary_l0_{load_factor}</drop_query>
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<drop_query>DROP DICTIONARY complex_key_{layout_suffix}_dictionary_l0_{load_factor}</drop_query>
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<drop_query>DROP TABLE simple_key_dictionary_source_table</drop_query>
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<drop_query>DROP TABLE complex_key_dictionary_source_table</drop_query>
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</test>
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