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初窥openGauss 之参数自调优(X-Tuner)

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     TPC-H 是一个面向分析型业务(AP)的基准测试,它由一系列热点查询组成,这些热点查询都是高度复杂的,因此执行时间往往都比较长。
   在本次实验测试中,将手动向数据库加载TPC-H数据,并保存在名为 tpch 的数据库中。默认TPC-H数据库的表缺少索引,数据库的参数并没有做任何优化,因此执行效率会比较差。
   本实验比较浅显,使用openGauss的参数自调优(X-Tuner:gs_xtuner)功能,对数据库进行参数优化,以提升数据库运行性能,让大家对X-Tuner参数自调优有一个初步的了解。

环境信息

OS:            CentOS Linux release 7.6.1810
openGauss:2.0.0
CPU:          1core
Memory:    4GB

测试数据脚本清单如下:

[omm@lab01 ~]$ ls -l ~/tpch-kit-back/ total 1076780 -rw------- 1 omm dbgrp  24196144 Apr 24 15:39 customer.tbl -rw------- 1 omm dbgrp      3814 Apr 24 15:39 dss.ddl -rw------- 1 omm dbgrp 753862072 Apr 24 15:39 lineitem.tbl -rw------- 1 omm dbgrp       287 May 25 10:52 load.sh -rw------- 1 omm dbgrp      2199 Apr 24 15:16 nation.tbl -rw------- 1 omm dbgrp 170452161 Apr 24 15:16 orders.tbl -rw------- 1 omm dbgrp  10553197 Apr 24 15:11 out0 -rw------- 1 omm dbgrp 118184616 Apr 24 15:10 partsupp.tbl -rw------- 1 omm dbgrp  23935125 Apr 24 15:11 part.tbl drwx------ 3 omm dbgrp      4096 Apr 24 15:39 queries -rw------- 1 omm dbgrp       384 Apr 24 15:07 region.tbl -rw------- 1 omm dbgrp   1399184 Apr 24 15:07 supplier.tbl

1. 配置pip,并安装setuptools-rust模块

[root@lab01 ~]# wget https://bootstrap.pypa.io/get-pip.py [root@lab01 ~]# python3 get-pip.py [root@lab01 ~]# pip -V pip 21.1.2 from /usr/local/lib/python3.6/site-packages/pip (python 3.6) [root@lab01 ~]# pip install setuptools-rust

2. 安装依赖包

[omm@lab01 xtuner]$ pip install joblib [omm@lab01 xtuner]$ pip install threadpoolctl

3. 创建数据库并导入数据

-- 创建数据库tpch [omm@lab01 ~]$ gsql -d postgres -p 26000 -c "create database tpch with encoding='UTF-8';" -- 创建测试表 [omm@lab01 ~]$ gsql -d tpch -p 26000 -f ~/tpch-kit-back/dss.ddl -- 加载测试数据并统计分析 [omm@lab01 ~]$ vi load.sh --------------------------------------- for i in `ls *.tbl`; do  table=${i/.tbl/} echo "Loading $table..." sed 's/|$//' $i > /tmp/$i gsql -d tpch -p 26000 -c "TRUNCATE $table" gsql -d tpch -p 26000 -c "\\copy $table FROM '/home/omm/tpch-kit-back/$i' CSV DELIMITER '|'" gsql -d tpch -p 26000 -c "ANALYZE $table" done --------------------------------------- sh load.sh

4. 编辑requirements.txt文件

[omm@lab01 ~]$ cd /gauss/app/bin/dbmind/xtuner/ [omm@lab01 xtuner]$ vi requirements.txt --------------------------------------- 删除: tensorflow>=2.2.0 keras-rl2 ---------------------------------------

5. 生成gs_xtuner参数调优工具(需要连接外网)

[omm@lab01 ~]$ cd /gauss/app/bin/dbmind/xtuner [omm@lab01 xtuner]$ python3 setup.py install --user

6. 执行快速推荐命令(基于已经作业执行的信息进行推荐,信息来源pg_stat_database等)

[omm@lab01 xtuner]$ gs_xtuner recommend --db-name tpch --db-user omm --host 192.168.0.99 --host-user omm --port 26000 Please input the password of database: Please input the password of host: Start to recommend knobs. Just a moment, please. ***************************************************** Knob Recommendation Report ***************************************************** INFO: +---------------------------------------+----------------------+ |                 Metric               |       Value         | +---------------------------------------+----------------------+ |             workload_type             |         ap         | |         dirty_background_bytes       |          0           | |         current_locks_count         |         0.0         | |     current_prepared_xacts_count     |         0.0         | |         rollback_commit_ratio         |         0.0         | |         average_connection_age       |       0.004575       | | checkpoint_proactive_triggering_ratio | 0.00863557858376511 | |         fetched_returned_ratio       | 0.055316264644388206 | |             cache_hit_rate           |  0.5028061903026831 | |             os_cpu_count             |          1           | |         current_connections         |         1.0         | |       checkpoint_avg_sync_time       |   1.07037996545769   | |           write_tup_speed           |   101.161719229361   | |               used_mem               |     131846656.0     | |           all_database_size           |   2292057.41015625   | |     shared_buffer_heap_hit_rate     |  25.917067253117217 | |           current_free_mem           |       3270760       | |             temp_file_size           |   3573.07285767967   | |                 uptime               |   38.3688171772222   | |             os_mem_total             |       3879956       | | checkpoint_dirty_writing_time_window |        450.0         | |           read_write_ratio           |  47.82294541597867   | |             read_tup_speed           |   4837.86775193848   | |             max_processes             |         503         | |         track_activity_size         |        503.0         | |         search_modify_ratio         |  658741.9884425476   | |               ap_index               |         7.5         | |     shared_buffer_toast_hit_rate     |   76.6304347826087   | |               block_size             |         8.0         | |     shared_buffer_tidx_hit_rate     |   82.7893175074184   | |       shared_buffer_idx_hit_rate     |   97.6601060219748   | |           enable_autovacuum           |         True         | |               is_64bit               |         True         | |                 is_hdd               |         True         | |             load_average             | [1.19, 0.82, 0.8]   | +---------------------------------------+----------------------+ p.s: The unit of storage is kB. WARN: [0]. The number of CPU cores is a little small. Please do not run too high concurrency.     You are recommended to set max_connections based on the number of CPU cores.     If your job does not consume much CPU, you can also increase it. [1]. The value of wal_buffers is a bit high. Generally, an excessively large value does not bring better performance.     You can also set this parameter to -1.     The database automatically performs adaptation. ****************************************************** Recommended Knob Settings ****************************************************** +---------------------------+-----------+--------+---------+---------+ |           name           | recommend | min   |   max   | restart | +---------------------------+-----------+--------+---------+---------+ |       shared_buffers     |   121256 | 72752 |  139448 |   True | |     max_connections     |    134   |   15   |   269   |   True | |   effective_cache_size   |  2909967 | 121256 | 2909967 | False | |       wal_buffers       |    3789   |  2048 |   3789 |   True | |     random_page_cost     |    3.0   |  2.0   |   3.0   | False | | default_statistics_target |    1000   |  100   |   1000 | False | +---------------------------+-----------+--------+---------+---------+ 注意:修改该推荐值之前,请确保硬件条件满足,否则可能会造成数据库无法启动的问题。

7. [可选]迭代推荐命令(全局搜索算法,迭代式执行,每轮执行约2分钟)

1> 修改配置文件

vi /home/omm/.local/lib/python3.6/site-packages/openGauss_xtuner-2.0.0-py3.6.egg/tuner/xtuner.conf ------------------------------------------------- 修改如下行: max_iterations = 3 (从100轮改为3) benchmark_path = /home/omm/queries ------------------------------------------------

2> 执行命令,观察Reward数值变化,粉色输出的轮次为当前较优数值

[omm@lab01 ~]$ time gs_xtuner tune --db-name tpch --db-user omm --host localhost --host-user omm --port 26000 Please input the password of database: Please input the password of host: Start to recommend knobs. Just a moment, please. WARN: The database may restart several times during tuning, continue or not [yes|no]:yes 2021-05-26 11:09:12,710: Recorder is starting. |   iter   | target   | random... | ------------------------------------- 2021-05-26 11:10:58,017: [0] Current reward is -102.935543, knobs: {'random_page_cost': '2.64'}. 2021-05-26 11:10:58,018: [0] Best reward is -102.935543, knobs: {'random_page_cost': '2.64'}. 2021-05-26 11:10:58,018: [1] Database metrics: [0.6400000000000001, 0.6007798155874045, 0.65]. 2021-05-26 11:10:58,018: [1] Benchmark score: -102.899098, used mem: 36444544 kB, reward: -102.935543. |  1       | -102.9   |  0.6426   | 2021-05-26 11:12:30,939: [1] Current reward is -91.541441, knobs: {'random_page_cost': '2'}. 2021-05-26 11:12:30,941: [1] Best reward is -91.541441, knobs: {'random_page_cost': '2'}. 2021-05-26 11:12:30,941: [2] Database metrics: [0.0, 0.6107552017890537, 2.6]. 2021-05-26 11:12:30,942: [2] Benchmark score: -91.504996, used mem: 36444544 kB, reward: -91.541441. |  2       | -91.54   |  0.003251 | 2021-05-26 11:13:38,617: [2] Current reward is -66.684871, knobs: {'random_page_cost': '2.46'}. 2021-05-26 11:13:38,618: [2] Best reward is -66.684871, knobs: {'random_page_cost': '2.46'}. 2021-05-26 11:13:38,618: [3] Database metrics: [0.45999999999999996, 0.621014394376401, 3.47]. 2021-05-26 11:13:38,618: [3] Benchmark score: -66.648426, used mem: 36444544 kB, reward: -66.684871. |  3       | -66.68   |  0.4565   | 2021-05-26 11:14:53,250: [3] Current reward is -73.748742, knobs: {'random_page_cost': '2.9'}. 2021-05-26 11:14:53,252: [3] Best reward is -66.684871, knobs: {'random_page_cost': '2.46'}. 2021-05-26 11:14:53,252: [4] Database metrics: [0.8999999999999999, 0.6286889335789447, 3.65]. 2021-05-26 11:14:53,252: [4] Benchmark score: -73.712297, used mem: 36444544 kB, reward: -73.748742. |  4       | -73.75   |  0.9016   | 2021-05-26 11:15:58,798: [4] Current reward is -64.467620, knobs: {'random_page_cost': '2.45'}. 2021-05-26 11:15:58,799: [4] Best reward is -64.467620, knobs: {'random_page_cost': '2.45'}. 2021-05-26 11:15:58,799: [5] Database metrics: [0.4500000000000002, 0.633784310797396, 3.45]. 2021-05-26 11:15:58,799: [5] Benchmark score: -64.431175, used mem: 36444544 kB, reward: -64.467620. |  5       | -64.47   |  0.4544   | 2021-05-26 11:16:59,097: [5] Current reward is -59.161970, knobs: {'random_page_cost': '2.43'}. 2021-05-26 11:16:59,099: [5] Best reward is -59.161970, knobs: {'random_page_cost': '2.43'}. 2021-05-26 11:16:59,099: [6] Database metrics: [0.43000000000000016, 0.6393591990442545, 3.91]. 2021-05-26 11:16:59,099: [6] Benchmark score: -59.125525, used mem: 36444544 kB, reward: -59.161970. |  6       | -59.16   |  0.4304   | 2021-05-26 11:18:08,157: [6] Current reward is -67.964937, knobs: {'random_page_cost': '2.39'}. 2021-05-26 11:18:08,158: [6] Best reward is -59.161970, knobs: {'random_page_cost': '2.43'}. 2021-05-26 11:18:08,158: [7] Database metrics: [0.3900000000000001, 0.6445245622485726, 4.05]. 2021-05-26 11:18:08,158: [7] Benchmark score: -67.928493, used mem: 36444544 kB, reward: -67.964937. |  7       | -67.96   |  0.3854   | 2021-05-26 11:19:11,917: [7] Current reward is -62.842104, knobs: {'random_page_cost': '2.43'}. 2021-05-26 11:19:11,918: [7] Best reward is -59.161970, knobs: {'random_page_cost': '2.43'}. 2021-05-26 11:19:11,918: [8] Database metrics: [0.43000000000000016, 0.6489102035318035, 3.5]. 2021-05-26 11:19:11,918: [8] Benchmark score: -62.805659, used mem: 36444544 kB, reward: -62.842104. |  8       | -62.84   |  0.4301   | ===================================== 2021-05-26 11:19:11,926: The tuning process is complete. The best reward is -59.161970, best knobs are: {'random_page_cost': '2.43'}. ***************************************************** Knob Recommendation Report ***************************************************** INFO: +---------------------------------------+-----------------------+ |                 Metric               |         Value         | +---------------------------------------+-----------------------+ |             workload_type             |           ap         | |         dirty_background_bytes       |           0           | |         current_locks_count         |          0.0         | |     current_prepared_xacts_count     |          0.0         | |         rollback_commit_ratio         | 0.0002477694554770677 | |         average_connection_age       |        0.004734       | | checkpoint_proactive_triggering_ratio |  0.00938967136150235 | |         fetched_returned_ratio       |  0.09276922373936373 | |                 uptime               |   0.224322521666667   | |             cache_hit_rate           |   0.6006356117493342 | |             os_cpu_count             |           1           | |         current_connections         |          1.0         | |       checkpoint_avg_sync_time       |    1.06359368331199   | |         search_modify_ratio         |   1007080.6984163317 | |             max_processes             |          137         | |         track_activity_size         |         137.0         | |           all_database_size           |    2292057.41015625   | |             temp_file_size           |    2694.18229367111   | |           current_free_mem           |        3298680       | |     shared_buffer_heap_hit_rate     |   36.42339765350299   | |               used_mem               |       36444544.0     | |             os_mem_total             |        3879956       | | checkpoint_dirty_writing_time_window |         450.0         | |               ap_index               |          7.5         | |     shared_buffer_toast_hit_rate     |   74.11273486430062   | |             read_tup_speed           |    7942.47638202933   | |               block_size             |          8.0         | |           read_write_ratio           |   80.26596656844558   | |     shared_buffer_tidx_hit_rate     |   84.41330998248687   | |       shared_buffer_idx_hit_rate     |   96.54182833084825   | |           write_tup_speed           |    98.9516516216125   | |           enable_autovacuum           |         True         | |               is_64bit               |         True         | |                 is_hdd               |         True         | |             load_average             |   [0.62, 1.08, 1.13] | +---------------------------------------+-----------------------+ p.s: The unit of storage is kB. WARN: [0]. The number of CPU cores is a little small. Please do not run too high concurrency. You are recommended to set max_connections based on the number of CPU cores. If your job does not consume much CPU, you can also increase it. BAD: [0]. The value of wal_buffers is too high. Generally, a large value does not bring better performance. ****************************************************** Recommended Knob Settings ****************************************************** +---------------------------+-----------+--------+---------+---------+ |           name           | recommend | min   |   max   | restart | +---------------------------+-----------+--------+---------+---------+ |     random_page_cost     |    2.43   |  2.0   |   3.0   | False | |       shared_buffers     |   121256 | 72752 |  139448 |   True | |     max_connections     |    134   |   15   |   269   |   True | |   effective_cache_size   |  2909967 | 121256 | 2909967 | False | |       wal_buffers       |    3789   |  1894 |   3789 |   True | | default_statistics_target |    1000   |  100   |   1000 | False | +---------------------------+-----------+--------+---------+---------+ real   10m12.961s user   0m6.827s sys     0m1.076s

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