关于PostgreSQL的性能调优可以参考《PostgreSQL 9.0 High Performance》，以及朱贤文在2014 PostgreSQL中国用户大会上分享的《高性能Postgres 最佳实践》。当然，首先还是应该看看PostgreSQL手册的相关章节。我们在调优时不必每个细节都做到最优，抓住主要矛盾即可。因为有些东西不在你的控制之下，或者那样优化之后维护起来麻烦。下面尝试在虚机下进行快速的PostgreSQL参数调优。
1. 虚机环境
CPU: 4 core
Mem: 8G
OS: CentOS 6.3(64 Bit)
PostgreSQL:9.4.5
sysbench:0.4.12
文件系统:ext4
2.参数设置
基本的性能参数设置可以利用下面这个在线小工具评估。
填入系统信息，并固定最大连接数为300后，选择不同DB Type，这个工具会给出不同的参数。
Web applications
max_connections = 300 shared_buffers = 2GB effective_cache_size = 6GB work_mem = 6990kB maintenance_work_mem = 512MB checkpoint_segments = 32 checkpoint_completion_target = 0.7 wal_buffers = 16MB default_statistics_target = 100
Online transaction processing systems
max_connections = 300 shared_buffers = 2GB effective_cache_size = 6GB work_mem = 6990kB maintenance_work_mem = 512MB checkpoint_segments = 64 checkpoint_completion_target = 0.9 wal_buffers = 16MB default_statistics_target = 100
Data warehouses
max_connections = 300 shared_buffers = 2GB effective_cache_size = 6GB work_mem = 3495kB maintenance_work_mem = 1GB checkpoint_segments = 128 checkpoint_completion_target = 0.9 wal_buffers = 16MB default_statistics_target = 500
上面3种DB Type，越往后写越重，checkpoint的频率也调得越低。由于后面要做OLTP的性能评估，所以选用Online transaction processing systems的设置。
综合考虑log等需求，初步在postgresql.conf中设置参数如下
listen_addresses = '*' port = 5432 max_connections = 300 shared_buffers = 2GB effective_cache_size = 6GB work_mem = 6990kB maintenance_work_mem = 512MB checkpoint_segments = 64 checkpoint_completion_target = 0.9 wal_buffers = 16MB default_statistics_target = 100 logging_collector = on log_directory = 'pg_log' log_filename = 'postgresql-%Y-%m-%d_%H%M%S.log' log_truncate_on_rotation = on log_rotation_age = 1440 log_rotation_size = 100000 log_line_prefix='%m %p %x' wal_level = hot_standby
流复制时需要设置wal_level = hot_standby，单机场景下可以设置其它值以输出更少的WAL日志。
下面这几个参数有些需要在性能和持久性之间平衡，先全部采用默认值。
wal_sync_method = fsync commit_delay = 0 synchronous_commit = on full_page_writes = on fsync = on
3.测试方法
用sysbench 做oltp的性能测试，不管使用simple还是complex测试模式，sysbench prepare时创建单个相同的测试表（那就不可能测到join了）。
建表语句如下
CREATE TABLE sbtest (id SERIAL NOT NULL , k integer DEFAULT '0' NOT NULL, c char(120) DEFAULT '' NOT NULL, pad char(60) DEFAULT '' NOT NULL, PRIMARY KEY (id) ) CREATE INDEX k on sbtest(k) |
然后插入数据，插入数据量由oltp-table-size决定。
INSERT INTO sbtest(k, c, pad) VALUES (0,' ','qqqqqqqqqqwwwwwwwwwweeeeeeeeeerrrrrrrrrrtttttttttt') |
当插入数据量很大时，由于每个插入语句都是一次提交，因此速度很慢。我们可以用下面的方法手动准备数据，而不是使用sysbench的prepare。
DROP TABLE sbtest; CREATE TABLE sbtest (id SERIAL NOT NULL , k integer DEFAULT '0' NOT NULL, c char(120) DEFAULT '' NOT NULL, pad char(60) DEFAULT '' NOT NULL, PRIMARY KEY (id) ); CREATE INDEX k on sbtest(k); INSERT INTO sbtest(k, c, pad) select 0,' ','qqqqqqqqqqwwwwwwwwwweeeeeeeeeerrrrrrrrrrtttttttttt' from generate_series(1,5000000); |
插入500万记录后，数据表大小大约为1GB。
postgres=# \d+ List of relations Schema | Name | Type | Owner | Size | Description --------+------------------+----------+----------+------------+------------- public | sbtest | table | postgres | 1056 MB | public | sbtest_id_seq | sequence | postgres | 8192 bytes | (2 rows) |
simple模式的测试语句如下
SELECT c from sbtest where id=$1 |
$1是个取值在oltp-table-size范围内的随机数，随机数的生成算法由oltp-dist-type决定，包括uniform,gaussian,special三种，默认是special，生成的随机数有75%(由oltp-dist-pct控制)集中在一个1%(由oltp-dist-pct控制)的热点区域。
complex模式且oltp-read-only=on时的测试语句如下
BEGIN SELECT c from sbtest where id=$1 SELECT c from sbtest where id=$1 SELECT c from sbtest where id=$1 SELECT c from sbtest where id=$1 SELECT c from sbtest where id=$1 SELECT c from sbtest where id=$1 SELECT c from sbtest where id=$1 SELECT c from sbtest where id=$1 SELECT c from sbtest where id=$1 SELECT c from sbtest where id=$1 SELECT c from sbtest where id between $1 and $2 SELECT SUM(K) from sbtest where id between $1 and $2 SELECT c from sbtest where id between $1 and $2 order by c SELECT DISTINCT c from sbtest where id between $1 and $2 order by c COMMIT |
上面的between范围查询，范围大小为100(由oltp-range-size控制)。
complex模式且oltp-read-only=off时的测试语句如下
BEGIN SELECT c from sbtest where id=$1 SELECT c from sbtest where id=$1 SELECT c from sbtest where id=$1 SELECT c from sbtest where id=$1 SELECT c from sbtest where id=$1 SELECT c from sbtest where id=$1 SELECT c from sbtest where id=$1 SELECT c from sbtest where id=$1 SELECT c from sbtest where id=$1 SELECT c from sbtest where id=$1 SELECT c from sbtest where id between $1 and $2 SELECT SUM(K) from sbtest where id between $1 and $2 SELECT c from sbtest where id between $1 and $2 order by c SELECT DISTINCT c from sbtest where id between $1 and $2 order by c UPDATE sbtest set k=k+1 where id=$1 UPDATE sbtest set c=$1 where id=$2 UPDATE sbtest set k=k+1 where id=$1 DELETE from sbtest where id=$1 INSERT INTO sbtest values($1,0,' ','aaaaaaaaaaffffffffffrrrrrrrrrreeeeeeeeeeyyyyyyyyyy') COMMIT |
但是在并发数很高的情况下，会报下面的错误
ERROR: duplicate key value violates unique constraint "sbtest_pkey"
为了回避这个问题，参考德哥的方法临时修改sysbench的代码（这个问题和PostgreSQL的MVCC实现机制有关，详见http://blog.chinaunix.net/uid-20726500-id-5289907.html）。
修改方法如下：
修改sysbench-0.4.12/sysbench/tests/oltp/sb_oltp.c
找到
/* Prepare the insert statement */ snprintf(query, MAX_QUERY_LEN, "INSERT INTO %s values(?,0,' '," "'aaaaaaaaaaffffffffffrrrrrrrrrreeeeeeeeeeyyyyyyyyyy')", args.table_name); |
改成
/* Prepare the insert statement */ if (args.auto_inc) snprintf(query, MAX_QUERY_LEN, "INSERT INTO %s(k,c,pad) values(0,' '," "'aaaaaaaaaaffffffffffrrrrrrrrrreeeeeeeeeeyyyyyyyyyy')", args.table_name); else snprintf(query, MAX_QUERY_LEN, "INSERT INTO %s values(?,0,' '," "'aaaaaaaaaaffffffffffrrrrrrrrrreeeeeeeeeeyyyyyyyyyy')", args.table_name); |
参考：http://blog.163.com/digoal@126/blog/static/1638770402013414549515/
修改后，最后一条INSERT句就变成了下面这样了
INSERT INTO sbtest(k,c,pad) values(0,' ','aaaaaaaaaaffffffffffrrrrrrrrrreeeeeeeeeeyyyyyyyyyy') |
注：其实更加正确的做法应该是使用sysbench 0.5而不是0.4，sysbench 0.5没有这个问题，而且0.5支持lua脚本，支持的测试方式更灵活。
4. 测试
simple模式
执行下面的命令，100并发，TPS为29200.43，测试时CPU被占满，达到CPU极限。
[postgres@node1 ~]$ sysbench --test=oltp --db-driver=pgsql --pgsql-host=127.0.0.1 --pgsql-port=5432 --pgsql-user=postgres --pgsql-password=postgres --pgsql-db=postgres --oltp-table-size=5000000 --num-threads=100 --max-requests=0 --max-time=60 --oltp-test-mode=simple --oltp-read-only=on run sysbench 0.4.12: multi-threaded system evaluation benchmark Running the test with following options: Number of threads: 100 Doing OLTP test. Running simple OLTP test Doing read-only test Using Special distribution (12 iterations, 1 pct of values are returned in 75 pct cases) Using "BEGIN" for starting transactions Using auto_inc on the id column Threads started! Time limit exceeded, exiting... (last message repeated 99 times) Done. OLTP test statistics: queries performed: read: 1752165 write: 0 other: 0 total: 1752165 transactions: 1752165 (29200.43 per sec.) deadlocks: 0 (0.00 per sec.) read/write requests: 1752165 (29200.43 per sec.) other operations: 0 (0.00 per sec.) Test execution summary: total time: 60.0048s total number of events: 1752165 total time taken by event execution: 5993.5646 per-request statistics: min: 0.04ms avg: 3.42ms max: 968.42ms approx. 95 percentile: 0.34ms Threads fairness: events (avg/stddev): 17521.6500/2549.74 execution time (avg/stddev): 59.9356/0.01
