redis-sampler 是Redis作者@antirez 同学开发的一个ruby 小工具，用于对Redis存储概况进行抽样检测并给出分析结果。
项目地址：https://github.com/antirez/redis-sampler
使用方式：
下载源码，执行下面命令：
./redis-sampler.rb
host，port和db三个参数都不用解释（db默认为0），samplesize 就是这个抽样检测的样本数量。脚本输出如下例：
Sampling localhost:6379 DB:4 with 1000000 RANDOMKEYSTYPES =====zset: 873268 (87.33%) string: 124995 (12.50%) set: 1022 (0.10%)hash: 576 (0.06%) list: 139 (0.01%) STRINGS, SIZE OF VALUES =======================6: 61222 (48.98%) 7: 17056 (13.65%) 13: 8274 (6.62%)15: 7991 (6.39%) 5: 4629 (3.70%) 31: 3263 (2.61%)20: 2670 (2.14%) 2: 2518 (2.01%) 27: 1675 (1.34%)42: 1270 (1.02%) 159: 893 (0.71%) 1: 705 (0.56%)47: 641 (0.51%) 34: 594 (0.48%) 41: 521 (0.42%)38: 493 (0.39%) 28: 413 (0.33%) 22: 406 (0.32%)139: 351 (0.28%) 29: 343 (0.27%) 83: 337 (0.27%) (suppressed 172 items with perc < 0.5% for a total of 6.98%)Average: 15.97 Standard Deviation: 26.52Min: 0 Max: 1123Powers of two distribution: (NOTE <= p means: p/2 < x <= p)<= 8: 82913 (66.33%) <= 16: 16789 (13.43%) <= 32: 9571 (7.66%)<= 64: 6232 (4.99%) <= 128: 3333 (2.67%) <= 256: 2682 (2.15%)<= 2: 2518 (2.01%) <= 1: 740 (0.59%) <= 4: 199 (0.16%)<= 512: 14 (0.01%) <= 1024: 3 (0.00%) <= 2048: 1 (0.00%) LISTS, NUMBER OF ELEMENTS =========================2: 28 (20.14%) 5: 18 (12.95%) 9: 10 (7.19%)8: 9 (6.47%) 11: 9 (6.47%) 13: 7 (5.04%)12: 7 (5.04%) 14: 6 (4.32%) 15: 6 (4.32%)4: 4 (2.88%) 16: 4 (2.88%) 21: 4 (2.88%)27: 3 (2.16%) 7: 3 (2.16%) 10: 3 (2.16%)19: 2 (1.44%) 1: 2 (1.44%) 25: 2 (1.44%)41: 1 (0.72%) 3: 1 (0.72%) 17: 1 (0.72%) (suppressed 9 items with perc < 0.5% for a total of 6.47%)Average: 10.58 Standard Deviation: 8.58Min: 1 Max: 42Powers of two distribution: (NOTE <= p means: p/2 < x <= p)<= 16: 52 (37.41%) <= 8: 30 (21.58%) <= 2: 28 (20.14%)<= 32: 17 (12.23%) <= 64: 5 (3.60%) <= 4: 5 (3.60%)<= 1: 2 (1.44%) LISTS, SIZE OF ELEMENTS =======================7: 106 (76.26%) 6: 33 (23.74%)Average: 6.76 Standard Deviation: 0.43Min: 6 Max: 7Powers of two distribution: (NOTE <= p means: p/2 < x <= p)<= 8: 139 (100.00%) SETS, NUMBER OF ELEMENTS ========================1: 216361 (24.78%) 2: 106871 (12.24%) 3: 67648 (7.75%)4: 48207 (5.52%) 5: 36085 (4.13%) 6: 29597 (3.39%)7: 23765 (2.72%) 8: 22549 (2.58%) 9: 20143 (2.31%)10: 18069 (2.07%) 11: 16387 (1.88%) 12: 15009 (1.72%)13: 13869 (1.59%) 14: 12683 (1.45%) 15: 12319 (1.41%)16: 10794 (1.24%) 17: 10068 (1.15%) 18: 8925 (1.02%)19: 8007 (0.92%) 20: 7618 (0.87%) 22: 7240 (0.83%)21: 7055 (0.81%) 23: 5973 (0.68%) 24: 5771 (0.66%)25: 4934 (0.57%) (suppressed 2061 items with perc < 0.5% for a total of 15.72%)Average: 1.24 Standard Deviation: 2.34Min: 1 Max: 62Powers of two distribution: (NOTE <= p means: p/2 < x <= p)<= 1: 975 (95.40%) <= 2: 21 (2.05%) <= 8: 10 (0.98%)<= 4: 9 (0.88%) <= 16: 5 (0.49%) <= 32: 1 (0.10%)<= 64: 1 (0.10%) SETS, SIZE OF ELEMENTS ======================19: 871 (85.23%) 3: 66 (6.46%) 4: 65 (6.36%)5: 11 (1.08%) 2: 9 (0.88%)Average: 16.71 Standard Deviation: 5.50Min: 2 Max: 19Powers of two distribution: (NOTE <= p means: p/2 < x <= p)<= 32: 871 (85.23%) <= 4: 131 (12.82%) <= 8: 11 (1.08%)<= 2: 9 (0.88%) SORTED SETS, NUMBER OF ELEMENTS ===============================1: 216361 (24.78%) 2: 106871 (12.24%) 3: 67648 (7.75%)4: 48207 (5.52%) 5: 36085 (4.13%) 6: 29597 (3.39%)7: 23765 (2.72%) 8: 22549 (2.58%) 9: 20143 (2.31%)10: 18069 (2.07%) 11: 16387 (1.88%) 12: 15009 (1.72%)13: 13869 (1.59%) 14: 12683 (1.45%) 15: 12319 (1.41%)16: 10794 (1.24%) 17: 10068 (1.15%) 18: 8925 (1.02%)19: 8007 (0.92%) 20: 7618 (0.87%) 22: 7240 (0.83%)21: 7055 (0.81%) 23: 5973 (0.68%) 24: 5771 (0.66%)25: 4934 (0.57%) (suppressed 2061 items with perc < 0.5% for a total of 15.72%)Average: 25.47 Standard Deviation: 110.64Min: 1 Max: 7018Powers of two distribution: (NOTE <= p means: p/2 < x <= p)<= 1: 216361 (24.78%) <= 16: 119273 (13.66%) <= 4: 115855 (13.27%)<= 8: 111996 (12.82%) <= 2: 106871 (12.24%) <= 32: 92814 (10.63%)<= 64: 52715 (6.04%) <= 128: 29286 (3.35%) <= 256: 13988 (1.60%)<= 512: 7098 (0.81%) <= 1024: 4762 (0.55%) <= 2048: 1840 (0.21%)<= 4096: 393 (0.05%) <= 8192: 16 (0.00%) SORTED SETS, SIZE OF ELEMENTS =============================6: 710230 (81.33%) 5: 75292 (8.62%) 4: 68661 (7.86%)3: 17136 (1.96%) 2: 1412 (0.16%) 9: 253 (0.03%)1: 76 (0.01%) 8: 74 (0.01%) 7: 39 (0.00%)21: 6 (0.00%) 30: 6 (0.00%) 20: 6 (0.00%)23: 6 (0.00%) 26: 5 (0.00%) 34: 5 (0.00%)24: 4 (0.00%) 27: 4 (0.00%) 18: 4 (0.00%)15: 4 (0.00%) 38: 3 (0.00%) 43: 3 (0.00%) (suppressed 24 items with perc < 0.5% for a total of 0.00%)Average: 5.69 Standard Deviation: 0.77Min: 1 Max: 63Powers of two distribution: (NOTE <= p means: p/2 < x <= p)<= 8: 785635 (89.96%) <= 4: 85797 (9.82%) <= 2: 1412 (0.16%)<= 16: 262 (0.03%) <= 1: 76 (0.01%) <= 32: 58 (0.01%)<= 64: 28 (0.00%) HASHES, NUMBER OF FIELDS ========================1: 301 (52.26%) 12: 177 (30.73%) 11: 95 (16.49%)13: 2 (0.35%) 14: 1 (0.17%)Average: 6.09 Standard Deviation: 5.34Min: 1 Max: 14Powers of two distribution: (NOTE <= p means: p/2 < x <= p)<= 1: 301 (52.26%) <= 16: 275 (47.74%) HASHES, SIZE OF FIELDS ======================17: 301 (52.26%) 22: 179 (31.08%) 13: 95 (16.49%)12: 1 (0.17%)Average: 17.89 Standard Deviation: 3.11Min: 12 Max: 22Powers of two distribution: (NOTE <= p means: p/2 < x <= p)<= 32: 480 (83.33%) <= 16: 96 (16.67%) HASHES, SIZE OF VALUES ======================13: 116 (20.14%) 3: 103 (17.88%) 410: 44 (7.64%)409: 38 (6.60%) 408: 27 (4.69%) 14: 22 (3.82%)407: 17 (2.95%) 395: 12 (2.08%) 406: 12 (2.08%)392: 11 (1.91%) 396: 11 (1.91%) 393: 11 (1.91%)4: 10 (1.74%) 12: 10 (1.74%) 411: 9 (1.56%)5: 7 (1.22%) 376: 7 (1.22%) 405: 6 (1.04%)349: 5 (0.87%) 347: 5 (0.87%) 359: 5 (0.87%) (suppressed 43 items with perc < 0.5% for a total of 15.28%)Average: 207.90 Standard Deviation: 193.12Min: 1 Max: 416Powers of two distribution: (NOTE <= p means: p/2 < x <= p)<= 512: 298 (51.74%) <= 16: 151 (26.22%) <= 4: 113 (19.62%)<= 8: 10 (1.74%) <= 2: 3 (0.52%) <= 1: 1 (0.17%)原文地址：http://blog.nosqlfan.com/html/1717.html
）)
进行跟踪)
)
