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Date: Sat, 9 Apr 2022 11:07:56 +0800 From: Hou Tao <houtao1@...wei.com> To: Andrii Nakryiko <andrii.nakryiko@...il.com> CC: Alexei Starovoitov <ast@...nel.org>, Yonghong Song <yhs@...com>, Daniel Borkmann <daniel@...earbox.net>, Martin KaFai Lau <kafai@...com>, Andrii Nakryiko <andrii@...nel.org>, Song Liu <songliubraving@...com>, KP Singh <kpsingh@...nel.org>, "David S . Miller" <davem@...emloft.net>, Jakub Kicinski <kuba@...nel.org>, John Fastabend <john.fastabend@...il.com>, Networking <netdev@...r.kernel.org>, bpf <bpf@...r.kernel.org> Subject: Re: [RFC PATCH bpf-next 0/2] bpf: Introduce ternary search tree for string key Hi, On 4/7/2022 1:38 AM, Andrii Nakryiko wrote: > On Thu, Mar 31, 2022 at 5:04 AM Hou Tao <houtao1@...wei.com> wrote: >> Hi, >> >> The initial motivation for the patchset is due to the suggestion of Alexei. >> During the discuss of supporting of string key in hash-table, he saw the >> space efficiency of ternary search tree under our early test and suggest >> us to post it as a new bpf map [1]. >> >> Ternary search tree is a special trie where nodes are arranged in a >> manner similar to binary search tree, but with up to three children >> rather than two. The three children correpond to nodes whose value is >> less than, equal to, and greater than the value of current node >> respectively. >> >> In ternary search tree map, only the valid content of string is saved. >> The trailing null byte and unused bytes after it are not saved. If there >> are common prefixes between these strings, the prefix is only saved once. >> Compared with other space optimized trie (e.g. HAT-trie, succinct trie), >> the advantage of ternary search tree is simple and being writeable. >> >> Below are diagrams for ternary search map when inserting hello, he, >> test and tea into it: >> >> 1. insert "hello" >> >> [ hello ] >> >> 2. insert "he": need split "hello" into "he" and "llo" >> >> [ he ] >> | >> * >> | >> [ llo ] >> >> 3. insert "test": add it as right child of "he" >> >> [ he ] >> | >> *-------x >> | | >> [ llo ] [ test ] >> >> 5. insert "tea": split "test" into "te" and "st", >> and insert "a" as left child of "st" >> >> [ he ] >> | >> x------*-------x >> | | | >> [ ah ] [ llo ] [ te ] >> | >> * >> | >> [ st ] >> | >> x----* >> | >> [ a ] >> >> As showed in above diagrams, the common prefix between "test" and "tea" >> is "te" and it only is saved once. Also add benchmarks to compare the >> memory usage and lookup performance between ternary search tree and >> hash table. When the common prefix is lengthy (~192 bytes) and the >> length of suffix is about 64 bytes, there are about 2~3 folds memory >> saving compared with hash table. But the memory saving comes at prices: >> the lookup performance of tst is about 2~3 slower compared with hash >> table. See more benchmark details on patch #2. >> >> Comments and suggestions are always welcome. >> > Have you heard and tried qp-trie ([0]) by any chance? It is elegant > and simple data structure. By all the available benchmarks it handily > beats Red-Black trees in terms of memory usage and performance (though > it of course depends on the data set, just like "memory compression" > for ternary tree of yours depends on large set of common prefixes). > qp-trie based BPF map seems (at least on paper) like a better > general-purpose BPF map that is dynamically sized (avoiding current > HASHMAP limitations) and stores keys in sorted order (and thus allows > meaningful ordered iteration *and*, importantly for longest prefix > match tree, allows efficient prefix matches). I did a quick experiment > about a month ago trying to replace libbpf's internal use of hashmap > with qp-trie for BTF string dedup and it was slightly slower than > hashmap (not surprisingly, though, because libbpf over-sizes hashmap > to avoid hash collisions and long chains in buckets), but it was still > very decent even in that scenario. So I've been mulling the idea of > implementing BPF map based on qp-trie elegant design and ideas, but > can't find time to do this. I have heard about it when check the space efficient of HAT trie [0], because qp-trie needs to save the whole string key in the leaf node and its space efficiency can not be better than ternary search tree for strings with common prefix, so I did not consider about it. But I will do some benchmarks to check the lookup performance and space efficiency of qp-trie and tst for string with common prefix and strings without much common prefix. If qp-trie is better, I think I can take the time to post it as a bpf map if you are OK with that. > > This prefix sharing is nice when you have a lot of long common > prefixes, but I'm a bit skeptical that as a general-purpose BPF data > structure it's going to be that beneficial. 192 bytes of common > prefixes seems like a very unusual dataset :) Yes. The case with common prefix I known is full file path. > More specifically about TST implementation in your paches. One global > per-map lock I think is a very big downside. We have LPM trie which is > very slow in big part due to global lock. It might be possible to > design more granular schema for TST, but this whole in-place splitting > logic makes this harder. I think qp-trie can be locked in a granular > fashion much more easily by having a "hand over hand" locking: lock > parent, find child, lock child, unlock parent, move into child node. > Something like that would be more scalable overall, especially if the > access pattern is not focused on a narrow set of nodes. Yes. The global lock is a problem but the splitting is not in-place. I will try to figure out whether the lock can be more scalable after the benchmark test between qp-trie and tst. Regards, Tao [0]: https://github.com/Tessil/hat-trie > > Anyways, I love data structures and this one is an interesting idea. > But just my few cents of "production-readiness" for general-purpose > data structures for BPF. > > [0] https://dotat.at/prog/qp/README.html > >> Regards, >> Tao >> >> [1]: https://lore.kernel.org/bpf/CAADnVQJUJp3YBcpESwR3Q1U6GS1mBM=Vp-qYuQX7eZOaoLjdUA@mail.gmail.com/ >> >> Hou Tao (2): >> bpf: Introduce ternary search tree for string key >> selftests/bpf: add benchmark for ternary search tree map >> >> include/linux/bpf_types.h | 1 + >> include/uapi/linux/bpf.h | 1 + >> kernel/bpf/Makefile | 1 + >> kernel/bpf/bpf_tst.c | 411 +++++++++++++++++ >> tools/include/uapi/linux/bpf.h | 1 + >> tools/testing/selftests/bpf/Makefile | 5 +- >> tools/testing/selftests/bpf/bench.c | 6 + >> .../selftests/bpf/benchs/bench_tst_map.c | 415 ++++++++++++++++++ >> .../selftests/bpf/benchs/run_bench_tst.sh | 54 +++ >> tools/testing/selftests/bpf/progs/tst_bench.c | 70 +++ >> 10 files changed, 964 insertions(+), 1 deletion(-) >> create mode 100644 kernel/bpf/bpf_tst.c >> create mode 100644 tools/testing/selftests/bpf/benchs/bench_tst_map.c >> create mode 100755 tools/testing/selftests/bpf/benchs/run_bench_tst.sh >> create mode 100644 tools/testing/selftests/bpf/progs/tst_bench.c >> >> -- >> 2.31.1 >> > .
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