== ======= ======= ======= =======
# Count 41 26566
# Exec time 19 274452s 5s 54s 10s 12s 5s 10s
# Lock time 0 24s 64us 40ms 885us 1ms 738us 839us
# Rows sent 0 80.00k 0 13 3.08 4.96 1.29 2.90
# Rows examine 8 1.15G 44.73k 45.59k 45.43k 44.45k 0 44.45k
# Query size 36 13.78M 542 544 543.73 537.02 0 537.02
# String:
# Databases im
# Hosts 10.100.252.38 (13301/50%)... 1 more
# Users im
# Query_time distribution
# 1us
# 10us
# 100us
# 1ms
# 10ms
# 100ms
# 1s ########################################################
# 10s+ ################################################################
# Tables
# SHOW TABLE STATUS FROM `im` LIKE 'gg_token'\G
# SHOW CREATE TABLE `im`.`gg_token`\G
# SHOW TABLE STATUS FROM `im` LIKE 'gg_tenant'\G
# SHOW CREATE TABLE `im`.`gg_tenant`\G
# EXPLAIN /*!50100 PARTITIONS*/
select token0_.token_id as token_id1_119_, token0_.tenant_id as tenant_10_119_, token0_.account as account2_119_, token0_.client_id as client_i3_119_, token0_.create_date as create_d4_119_, token0_.host as host5_119_, token0_.last_auth_date as last_aut6_119_, token0_.session_id as session_7_119_, token0_.token as token8_119_, token0_.user_id as user_id9_119_ from gg_token token0_ left outer join gg_tenant tenant1_ on token0_.tenant_id=tenant1_.tenant_id where token0_.user_id='00014806a5a95f25ab' and tenant1_.tenant_id='0001456d92804b00'\G
# Query 2: 0.00 QPS, 0.02x concurrency, ID 0x816F5D9DB1BD38C7 at byte 17658778
# This item is included in the report because it matches --limit.
# Scores: V/M = 314.49
# Time range: 2015-03-21 13:31:25 to 2015-07-18 15:11:32
# Attribute pct total min max avg 95% stddev median
# ============ === ======= ======= ======= ======= ======= ======= =======
# Count 23 15295
# Exec time 17 246397s 5s 2498s 16s 32s 71s 11s
# Lock time 51 32142s 0 2476s 2s 125us 71s 89us
# Rows sent 0 0 0 0 0 0 0 0
# Rows examine 0 0 0 0 0 0 0 0
# Query size 9 3.55M 221 258 243.36 246.02 7.37 234.30
# String:
# Databases im
# Hosts 10.101.252.35 (7709/50%)... 3 more
# Users im
# Query_time distribution
# 1us
# 10us
# 100us
# 1ms
# 10ms
# 100ms
# 1s #############################################
# 10s+ ################################################################
# Tables
# SHOW TABLE STATUS FROM `im` LIKE 'gg_login_history'\G
# SHOW CREATE TABLE `im`.`gg_login_history`\G
INSERT INTO gg_login_history(login_history_id,username,resource,clientId,login_time,logout_time) VALUES('930e0b3e-d26b-4cc3-a02f-be0b1009744c','000148b62c6a6e290','Android','354273054207050','2015-04-13 23:04:42','2015-04-13 23:07:46')\G
最常用的使用方法：
(1)直接分析慢查询文件:
pt-query-digest slow.log > slow_report.log
(2)分析最近1小时内的查询：
pt-query-digest --since=1h slow.log > slow_report.log
(3)分析指定时间范围内的查询：
pt-query-digest slow.log --since '2015-04-17 10:30:00' --until '2015-04-17 18:00:00'>slow_report.log
(4)分析指含有select语句的慢查询
pt-query-digest--filter '$event->{fingerprint} =~ m/^select/i' slow.log> slow_report.log
(5) 查询所有所有的全表扫描或full join的慢查询
pt-query-digest--filter '(($event->{Full_scan} || "") eq "yes") ||(($event->{Full_join} || "") eq "yes")' slow.log> slow_report.log
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