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This patch adds benchmark tests for comparing the performance of hashmap lookups without the bloom filter vs. hashmap lookups with the bloom filter. Checking the bloom filter first for whether the element exists should overall enable a higher throughput for hashmap lookups, since if the element does not exist in the bloom filter, we can avoid a costly lookup in the hashmap. On average, using 5 hash functions in the bloom filter tended to perform the best across the widest range of different entry sizes. The benchmark results using 5 hash functions (running on 8 threads on a machine with one numa node, and taking the average of 3 runs) were roughly as follows: value_size = 4 bytes - 10k entries: 30% faster 50k entries: 40% faster 100k entries: 40% faster 500k entres: 70% faster 1 million entries: 90% faster 5 million entries: 140% faster value_size = 8 bytes - 10k entries: 30% faster 50k entries: 40% faster 100k entries: 50% faster 500k entres: 80% faster 1 million entries: 100% faster 5 million entries: 150% faster value_size = 16 bytes - 10k entries: 20% faster 50k entries: 30% faster 100k entries: 35% faster 500k entres: 65% faster 1 million entries: 85% faster 5 million entries: 110% faster value_size = 40 bytes - 10k entries: 5% faster 50k entries: 15% faster 100k entries: 20% faster 500k entres: 65% faster 1 million entries: 75% faster 5 million entries: 120% faster Signed-off-by: Joanne Koong <joannekoong@fb.com> Signed-off-by: Alexei Starovoitov <ast@kernel.org> Link: https://lore.kernel.org/bpf/20211027234504.30744-6-joannekoong@fb.com |
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