add article

swisstable -- a joke.md

@@ -0,0 +1,155 @@
+## swisstable -- a joke
+
+`swisstable`是`abseil-cpp`中`flat_hash_set/map`中使用的hash表实现，使用的是二次探测法，号称性能优于STL，下面讲讲这个`swisstable`是怎么回事
+
+
+
+这个hash表使用了一个`group`的概念，将一块连续的内存分为若干个`group`，每个`group`有16个元素包括`meta`和`slot`两部分，其中`meta`存放64位的`hash`值的7位（称为h2)，`slot`用于存放Key，Key通过`hash`值的57位（称为h1）来索引，使用SSE2同时比较128位的ctrl值，快速找到Key在`group`中的偏移，这也是为什么是16个`meta`是一组（128 / 8 = 16），而`meta`又有三个特殊值`-1`、`-2`和`-128`分别对应，sentinel、invalid（delete）和empty，一开始所有`meta`被初始化位`empty`
+
+
+
+查找过程：
+
+1. 计算hash，得到h1和h2
+
+2. 通过h2得到起始的`group`
+
+3. 使用h2和这一`group`的`meta`匹配 （使用SSE2）
+
+4. 若匹配，返回到起始位置的offset
+
+5. 若匹配到 `empty` 则返回不存在
+
+代码如下
+
+```c++
+auto pattern = _mm_set1_epi8(H2(hash)); // 1
+prober seq { H1(hash), groups_ - 1 }; // 1
+matcher m { 0 };
+
+while (true) {
+    group g { ctrl_ + seq.offset() }; // 2
+    m = g.match(pattern); // 3
+
+    while (m) {
+        offset = seq.offset(m.index());
+        assert(offset < cap_);
+        if (likely(slot_[offset] == key)) // 4
+            return true;
+        ++m;
+    }
+    if (likely(g.match_empty())) // 5
+        return false;
+    seq.next();
+}
+```
+
+这个`swisstable`宣传查找比STL要快，但不管是使用`absl::flat_hash_set`的官方实现，还是本人的实现，结果都不如STL（少数时候能比STL快一点点）
+
+```shell
+abby@Serenity ~/s/build> ./bench2
+----------- insert ------------
+  unordered_set => 183.605811ms
+  flat_hash_set => 41.932002ms
+----------- search ------------
+  unordered_set => 4.378100ms
+  flat_hash_set => 22.928702ms
+unordered_set cap 1056323 size 787268 load_factor 0.745291
+flat_hash_set cap 1048575 size 787268 load_factor 0.750798
+abby@Serenity ~/s/build> ./bench2
+----------- insert ------------
+  unordered_set => 182.890869ms
+  flat_hash_set => 39.940193ms
+----------- search ------------
+  unordered_set => 4.542800ms
+  flat_hash_set => 21.498796ms
+unordered_set cap 1056323 size 786505 load_factor 0.744569
+flat_hash_set cap 1048575 size 786505 load_factor 0.750070
+abby@Serenity ~/s/build> ./bench2
+----------- insert ------------
+  unordered_set => 183.804469ms
+  flat_hash_set => 38.301994ms
+----------- search ------------
+  unordered_set => 5.001399ms
+  flat_hash_set => 22.470496ms
+unordered_set cap 1056323 size 787110 load_factor 0.745141
+flat_hash_set cap 1048575 size 787110 load_factor 0.750647
+abby@Serenity ~/s/build> ./bench
+----------- insert ------------
+  unordered_set => 187.271974ms
+          swiss => 22.850596ms
+----------- search ------------
+  unordered_set => 4.307000ms
+          swiss => 4.016499ms
+unordered_set cap 1056323 size 786815 load_factor 0.744862
+swiss         cap 1048576 size 786815 load_factor 0.750365
+abby@Serenity ~/s/build> ./bench
+----------- insert ------------
+  unordered_set => 197.831773ms
+          swiss => 20.787797ms
+----------- search ------------
+  unordered_set => 4.811299ms
+          swiss => 4.107399ms
+unordered_set cap 1056323 size 787381 load_factor 0.745398
+swiss         cap 1048576 size 787381 load_factor 0.750905
+```
+
+
+
+据说rust也有使用了swisstable实现，实际测试如下
+
+```shell
+abby@Serenity ~/hash_test> cargo run --release ~/numbers.txt
+   Compiling libc v0.2.148
+   Compiling gcc v0.3.55
+   Compiling autocfg v1.1.0
+   Compiling version_check v0.9.4
+   Compiling ahash v0.8.3
+   Compiling num-traits v0.2.16
+   Compiling cfg-if v1.0.0
+   Compiling once_cell v1.18.0
+   Compiling fasthash-sys v0.3.2
+   Compiling cfg-if v0.1.10
+   Compiling rand v0.4.6
+   Compiling seahash v3.0.7
+   Compiling allocator-api2 v0.2.16
+   Compiling xoroshiro128 v0.3.0
+   Compiling hashbrown v0.14.1
+   Compiling fasthash v0.4.0
+   Compiling hash_test v0.1.0 (/home/abby/hash_test)
+    Finished release [optimized] target(s) in 12.99s
+     Running `target/release/hash_test /home/abby/numbers.txt`
+swiss insert => 73ms
+swiss search => 57ms
+std  insert => 76ms
+std  search => 69ms
+abby@Serenity ~/hash_test> cargo run --release ~/numbers.txt
+    Finished release [optimized] target(s) in 0.01s
+     Running `target/release/hash_test /home/abby/numbers.txt`
+swiss insert => 71ms
+swiss search => 56ms
+std  insert => 71ms
+std  search => 55ms
+abby@Serenity ~/hash_test> cargo run --release ~/numbers.txt
+    Finished release [optimized] target(s) in 0.02s
+     Running `target/release/hash_test /home/abby/numbers.txt`
+swiss insert => 73ms
+swiss search => 78ms
+std  insert => 72ms
+std  search => 61ms
+abby@Serenity ~/hash_test>
+```
+
+结论：
+
+为什么，swisstable实现会比STL的慢，可能时因为这里面的实现`meta`和`slot`是分开存放的，类似
+
+```
+| meta              |  slot                                  |
++-------------------+----------------------------------------+
+```
+
+导致在查找时需要在`meta`和`slot`之间来回跳转，对缓存不友好
+
+如果将`meta`和`slot`做到和 L1 cache对齐，效果应该要好一些
+