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	English image::benchmarks-set/vs/scattered successful looukp.xlsx.practice.png[width=250,window=_blank,link=_images/benchmarks-set/vs/scattered successful looukp.xlsx.practice.png] 172/10000 · 172
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	English image::benchmarks-set/vs/scattered successful looukp.xlsx.practice non-unique.png[width=250,window=_blank,link=_images/benchmarks-set/vs/scattered successful looukp.xlsx.practice non-unique.png] 194/10000 · 194
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	English image::benchmarks-set/vs/scattered successful looukp.xlsx.practice non-unique 5.png[width=250,window=_blank,link=_images/benchmarks-set/vs/scattered successful looukp.xlsx.practice non-unique 5.png] 198/10000 · 198
:284 :284

	English h\|non-duplicate elements h\|duplicate elements h\|duplicate elements, + max load factor 5 87/10000 · 87
:291 :291

	English Unsuccessful lookup 19/10000 · 19
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	English image::benchmarks-set/vs/scattered unsuccessful looukp.xlsx.practice.png[width=250,window=_blank,link=_images/benchmarks-set/vs/scattered unsuccessful looukp.xlsx.practice.png] 176/10000 · 176
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	English image::benchmarks-set/vs/scattered unsuccessful looukp.xlsx.practice non-unique.png[width=250,window=_blank,link=_images/benchmarks-set/vs/scattered unsuccessful looukp.xlsx.practice non-unique.png] 198/10000 · 198
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	English image::benchmarks-set/vs/scattered unsuccessful looukp.xlsx.practice non-unique 5.png[width=250,window=_blank,link=_images/benchmarks-set/vs/scattered unsuccessful looukp.xlsx.practice non-unique 5.png] 202/10000 · 202
:301 :301

	English h\|non-duplicate elements h\|duplicate elements h\|duplicate elements, + max load factor 5 87/10000 · 87
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	English boost::unordered_(flat\|node)_map 32/10000 · 32
:310 :310

	English All benchmarks were created using: 34/10000 · 34
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	English `https://abseil.io/docs/cpp/guides/container[absl::flat_hash_map^]<uint64_t, uint64_t>` 87/10000 · 87
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	English `boost::unordered_map<uint64_t, uint64_t>` 42/10000 · 42
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	English `boost::unordered_flat_map<uint64_t, uint64_t>` 47/10000 · 47
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	English `boost::unordered_node_map<uint64_t, uint64_t>` 47/10000 · 47
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	English The source code can be https://github.com/boostorg/boost_unordered_benchmarks/tree/boost_unordered_flat_map[found here^]. 121/10000 · 121
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	English The insertion benchmarks insert `n` random values, where `n` is between 10,000 and 10 million. 94/10000 · 94
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	English The erasure benchmarks erase traverse the `n` elements and erase those with odd key (50% on average). 101/10000 · 101
:323 :323

	English The successful lookup benchmarks are done by looking up all `n` values, in their original insertion order. 106/10000 · 106
:325 :325

	English The unsuccessful lookup benchmarks use `n` randomly generated integers but using a different seed value. 104/10000 · 104

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