mysql慢查询日志分析工具使用_MySQL

1.mysql-log-filter工具脚本使用说明：

google code上找到的一个分析工具.提供了 python 和 php 两种可执行的脚本。http://code.google.com/p/mysql-log-filter/ (需要搬*爬墙)，51cto下载链接：http://down.bitsCN.com/data/2123725

使用方法：（这里只介绍python的使用方法）

python mysql_filter_slow_log.py ./mysql1-slow.log --no-duplicates --sort-execution-count --top=10 >> mysql_slow_test.txt

备注：mysql1-slow.log 慢查询日志名称

--no-duplicates

--sort-execution-count

--top=10 取前十位

mysql_slow_test.txt 输出分析报告

附录：

官方给出的使用方法举例：

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# Filter slow queries executed for at least 3 seconds not from root, remove duplicates,
# apply execution count as first sorting value and save first 10 unique queries to file.
# In addition, remember last input file position and statistics.
php mysql_filter_slow_log.php -T=3 -eu=root --no-duplicates --sort-execution-count --top=10 --incremental linux-slow.log > mysql-slow-queries.log
# Start permanent filtering of all slow queries from now on: at least 3 seconds or examining 10000 rows, exclude users root and test
tail -f -n 0 linux-slow.log | python mysql_filter_slow_log.py -T=3 -R=10000 -eu=root -eu=test &
# (-n 0 outputs only lines generated after start of tail)
# Stop permanent filtering
kill `ps auxww | grep 'tail -f -n 0 linux-slow.log' | egrep -v grep | awk '{print $2}'`

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官方给出的命令参数：

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-T=min_query_time
-R=min_rows_examined
-ih, --include-host
-eh, --exclude-host
-iu, --include-user
-eu, --exclude-user
-iq, --include-query
--date=date_first-date_last Include only queries between date_first (and date_last).
                            Input:                    Date Range:
                            13.11.2006             -> 13.11.2006 - 14.11.2006 (exclusive)
                            13.11.2006-15.11.2006  -> 13.11.2006 - 16.11.2006 (exclusive)
                            15-11-2006-11/13/2006  -> 13.11.2006 - 16.11.2006 (exclusive)
                            >13.11.2006            -> 14.11.2006 - later
                            13.11.2006-            -> 13.11.2006 - later
                             earlier    - 13.11.2006 (exclusive)
                            -13.11.2006            -> earlier    - 14.11.2006 (exclusive)
                            Please do not forget to escape the greater or lesser than symbols (>13.11.2006').
                            Short dates are supported if you include a trailing separator (i.e. 13.11.-11/15/).
--incremental Remember input file positions and optionally --no-duplicates statistics between executions in mysql_filter_slow_log.sqlite3
--no-duplicates Powerful option to output only unique query strings with additional statistics:
                Execution count, first and last timestamp.
                Query time: avg / max / sum.
                Lock time: avg / max / sum.
                Rows examined: avg / max / sum.
                Rows sent: avg / max / sum.
--no-output Do not print statistics, just update database with incremental statistics
Default ordering of unique queries:
--sort-sum-query-time    [ 1. position]
--sort-avg-query-time    [ 2. position]
--sort-max-query-time    [ 3. position]
--sort-sum-lock-time     [ 4. position]
--sort-avg-lock-time     [ 5. position]
--sort-max-lock-time     [ 6. position]
--sort-sum-rows-examined [ 7. position]
--sort-avg-rows-examined [ 8. position]
--sort-max-rows-examined [ 9. position]
--sort-execution-count   [10. position]
--sort-sum-rows-sent     [11. position]
--sort-avg-rows-sent     [12. position]
--sort-max-rows-sent     [13. position]
--sort=sum-query-time,avg-query-time,max-query-time,...   You can include multiple sorting values separated by commas.
--sort=sqt,aqt,mqt,slt,alt,mlt,sre,are,mre,ec,srs,ars,mrs Every long sorting option has an equivalent short form (first character of each word).
--top=max_unique_query_count Output maximal max_unique_query_count different unique queries
--details                    Enables output of timestamp based unique query time lines after user list
                             (i.e. # Query_time: 81  Lock_time: 0  Rows_sent: 884  Rows_examined: 2448350).
--help Output this message only and quit
[multiple] options can be passed more than once to set multiple values.
[position] options take the position of their first occurrence into account.
           The first passed option will replace the default first sorting, ...
           Remaining default ordering options will keep their relative positions.

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官方给出的配置文件中管理慢日志参数的配置

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# I.e. you could add the following lines under the [mysqld] section of your my.ini or my.cnf configuration file:
# Log all queries taking more than 3 seconds
long_query_time=3  # minimum: 1, default: 10
# MySQL >= 5.1.21 (or patched): 3 seconds = 3000000 microseconds
# long_query_time=3.000000  # minimum: 0.000001 (1 microsecond)
# Activate the Slow Query Log
slow_query_log  # >= 5.1.29
# log-slow-queries  # deprecated since 5.1.29
# Write to a custom file name (>= 5.1.29)
# slow_query_log_file=file_name  # default: /data_dir/host_name-slow.log
# Log all queries without indexes
# log-queries-not-using-indexes
# Log only queries which examine at least N rows (>= 5.1.21)
# min_examined_row_limit=1000  # default: 0
# Log slow OPTIMIZE TABLE, ANALYZE TABLE, and ALTER TABLE statements
# log-slow-admin-statements
# Log slow queries executed by replication slaves (>= 5.1.21)
# log-slow-slave-statements
# MySQL 5.1.6 through 5.1.20 had a default value of log-output=TABLE, so you should force
# Attention: logging to TABLE only includes whole seconds information
log-output=FILE
## Admin query for online activation is possible since MySQL 5.1 (without server restart)
## SET @@global.slow_query_log=1
## SET @@global.long_query_time=1
## Show current variables related to the Slow Query Log
## SHOW GLOBAL VARIABLES WHERE Variable_name REGEXP 'admin|min_examined|log_output|log_queries|log_slave|long|slow_quer'

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注意：在执行脚本的时候会报数据类型的错误，具体错误指定469行，经过查看，实际慢查询日志中的query_time是float类型，而在这个脚本工具中定义的确实int类型。于是自行修改！

默认：

======================

query_time = (int(numbers[1].split()[0]), int(numbers[2].split()[0]),

int(numbers[3].split()[0]), int(numbers[4]))

======================

修改为：

======================

query_time = (float(numbers[1].split()[0]), float(numbers[2].split()[0]),

float(numbers[3].split()[0]), float(numbers[4]))