linux 磁盘io利用率高,分析的正确姿势

一、背景简介

作为一个DBA难免不了会遇到性能问题,那么我们遇到性能问题该如何进行排查呢?例如我们在高并发的业务下,出现业务响应慢,处理时间长我们又该如何入手进行排查,本片文章将分析io高的情况下如何分析及定位。

二、环境复现

  • 环境配置:本次测试使用128C_512G_4TSSD服务器配置,MySQL版本为8.0.27
  • 场景模拟:使用sysbench创建5个表,每个表2亿条数据,执行产生笛卡尔积查询的sql语句,产生io,可以模拟业务压力。
    首先使用sysbench进行数据压测

三、系统层面底层故障排查

Shell> sysbench --test=/usr/local/share/sysbench/oltp_insert.lua --mysql-host=XXX --mysql-port=3306 --mysql-user=pcms --mysql-password=abc123 --mysql-db=sysbench --percentile=99 --table-size=2000000000 --tables=5 --threads=1000 prepare

使用sysbench进行模拟高并发

shell> sysbench --test=/usr/local/share/sysbench/oltp_write_only.lua --mysql-host=xxx --mysql-port=3306 --mysql-user=pcms --mysql-password=abc123 --mysql-db=sysbench --percentile=99 --table-size=2000000000 --tables=5 --threads=1000 --max-time=60000 --report-interval=1 --threads=1000 --max-requests=0 --mysql-ignore-errors=all run

执行笛卡尔积sql语句

mysql> select SQL_NO_CACHE b.id,a.k from sbtest_a a left join sbtest_b b on a.id=b.id  group by a.k order by b.c desc;

3.1 检查当前服务器状态

shell> top
top - 19:49:05 up 10 days,  8:16,  2 users,  load average: 72.56, 40.21, 17.08
Tasks: 1288 total,   1 running, 586 sleeping,   0 stopped,   0 zombie
%Cpu(s): 19.7 us,  4.2 sy,  0.0 ni, 75.9 id,  1.0 wa,  0.0 hi,  0.2 si,  0.0 st
KiB Mem : 53542118+total, 23667507+free, 22735366+used, 71392448 buff/cache
KiB Swap:        0 total,        0 free,        0 used. 23128006+avail Mem 

由上可知:目前一分钟负载为72.56,且呈上升趋势,并且存在io压力

3.2查看当前各个磁盘设备的io情况

shell> iostat -m -x 1
Linux 4.14.0-115.el7a.0.1.aarch64 (mysql-4) 	01/08/2022 	_aarch64_	(128 CPU)
Device:         rrqm/s   wrqm/s     r/s     w/s    rMB/s    wMB/s avgrq-sz avgqu-sz   await r_await w_await  svctm  %util
sda               0.00     0.00 14213.00 27430.00   222.08   465.15    33.80     5.39    0.13    0.14    0.12   0.02  86.00
sdb               0.00     0.00    0.00    0.00     0.00     0.00     0.00     0.00    0.00    0.00    0.00   0.00   0.00
dm-0              0.00     0.00    0.00    0.00     0.00     0.00     0.00     0.00    0.00    0.00    0.00   0.00   0.00
dm-1              0.00     0.00    0.00    0.00     0.00     0.00     0.00     0.00    0.00    0.00    0.00   0.00   0.00
dm-2              0.00     0.00    0.00    0.00     0.00     0.00     0.00     0.00    0.00    0.00    0.00   0.00   0.00

由上可知:目前有多块物理磁盘,sda磁盘的io压力较大

3.3 检查sda磁盘当前的io读写情况

shell> iostat -d /dev/sda -m -x 1
Linux 4.14.0-115.el7a.0.1.aarch64 (mysql-4) 	01/08/2022 	_aarch64_	(128 CPU)
Device:         rrqm/s   wrqm/s     r/s     w/s    rMB/s    wMB/s avgrq-sz avgqu-sz   await r_await w_await  svctm  %util
sda            0.00     0.17    7.86   81.23     0.29     3.96    97.88     0.23    2.53    0.22    2.76   0.04   0.33
Device:         rrqm/s   wrqm/s     r/s     w/s    rMB/s    wMB/s avgrq-sz avgqu-sz   await r_await w_await  svctm  %util
sda            0.00     0.00 21109.00 42839.00   329.81   710.90    33.33    19.47    0.30    0.16    0.37   0.02  96.00
Device:         rrqm/s   wrqm/s     r/s     w/s    rMB/s    wMB/s avgrq-sz avgqu-sz   await r_await w_await  svctm  %util
sda            0.00     0.00 19287.00 41404.00   301.36   692.29    33.53    15.73    0.26    0.18    0.30   0.02  93.00
Device:         rrqm/s   wrqm/s     r/s     w/s    rMB/s    wMB/s avgrq-sz avgqu-sz   await r_await w_await  svctm  %util
sda            0.00     0.00 22135.00 43044.00   345.86  1165.18    47.48   100.87    1.55    0.20    2.24   0.01  97.00

由上可知:目前sda磁盘的压力比较大,每秒写入比每秒读差距较大,证明目前有大量的io写入

3.4 检查sda磁盘中哪个应用程序占用的io比较高

shell> pidstat -d  1
Linux 4.14.0-115.el7a.0.1.aarch64 (mysql-4) 	01/08/2022 	_aarch64_	(128 CPU)
08:01:43 PM   UID       PID   kB_rd/s   kB_wr/s kB_ccwr/s  Command
08:01:44 PM  1000     73739  62018.35 171346.79      0.00  mysqld
08:01:44 PM   UID       PID   kB_rd/s   kB_wr/s kB_ccwr/s  Command
08:01:45 PM  1000     73739 145328.00 435216.00      0.00  mysqld
08:01:45 PM   UID       PID   kB_rd/s   kB_wr/s kB_ccwr/s  Command
08:01:46 PM  1000     73739 141488.00 433232.00      0.00  mysqld

由上可知:占用io高的应用程序是mysql,且pid为73739

3.5 分析应用程序中哪一个线程占用的io比较高

shell> pidstat -dt -p 73739 1  执行两三秒即可
Average:     1000         -     73823      0.00 233133.98      0.00  |__mysqld
Average:     1000         -     74674      0.00 174291.26      0.00  |__mysqld
11:56:18 PM  1000         -     74770 124928.00  74688.00      0.00  |__mysqld
11:56:17 PM  1000         -     74770 124603.77  73358.49      0.00  |__mysqld
Average:     1000         -     74770 124761.17  74003.88      0.00  |__mysqld

由上可知:74770这个线程占用的io比较高

3.6 分析这个线程在干什么?

Shell> perf trace -t 74770 -o /tmp/tmp_aa.pstrace
Shell> cat /tmp/tmp_aa.pstrace
  2850.656 ( 1.915 ms): futex(uaddr: 0x653ae9c4, op: WAIT|PRIVATE_FLAG, val: 1)               = 0
  2852.572 ( 0.001 ms): futex(uaddr: 0x653ae990, op: WAKE|PRIVATE_FLAG, val: 1)               = 0
  2852.601 ( 0.001 ms): clock_gettime(which_clock: MONOTONIC, tp: 0xfff7bd470f68)             = 0
  2852.690 ( 0.040 ms): write(fd: 159, buf: 0xd7a30020, count: 65536)                         = 65536
  2852.796 ( 0.001 ms): clock_gettime(which_clock: MONOTONIC, tp: 0xfff7bd470f68)             = 0
  2852.798 ( 0.001 ms): clock_gettime(which_clock: MONOTONIC, tp: 0xfff7bd470f58)             = 0
  2852.939 ( 0.001 ms): clock_gettime(which_clock: MONOTONIC, tp: 0xfff7bd470f38)             = 0
  2852.950 ( 0.001 ms): clock_gettime(which_clock: MONOTONIC, tp: 0xfff7bd470f68)             = 0
  2852.977 ( 0.001 ms): clock_gettime(which_clock: MONOTONIC, tp: 0xfff7bd470f68)             = 0
  2853.029 ( 0.035 ms): write(fd: 64, buf: 0xcd51e020, count: 65536)                          = 65536
  2853.164 ( 0.001 ms): clock_gettime(which_clock: MONOTONIC, tp: 0xfff7bd470f68)             = 0
  2853.167 ( 0.001 ms): clock_gettime(which_clock: MONOTONIC, tp: 0xfff7bd470f58)             = 0
  2853.302 ( 0.001 ms): clock_gettime(which_clock: MONOTONIC, tp: 0xfff7bd470f38)             = 0

由上可知:目前这个线程在写入多个文件,fd为文件句柄,文件句柄号有64、159

3.7 查看这个文件句柄是什么

shell> lsof -p 73739|grep 159u
mysqld 73739 mysql  159u   REG                8,0   212143246  7046482357 /mysql/mysqldata/16320fff-5fd5-4c47-889a-a9e1a8591d0d/tmp/#7046482357 (deleted)
[root@mysql-4 ~]# lsof -p 73739|grep 64u
mysqld 73739 mysql   64u   REG                8,0   211872724  6979323031 /mysql/mysqldata/16320fff-5fd5-4c47-889a-a9e1a8591d0d/tmp/#6979323031 (deleted)

由上可知:这个线程在大量的写入临时文件

四、分析MySQL应用程序

4.1 查看当前的会话列表

mysql> select * from information_schema.processlist where command !='sleep';
|  9 | pcms             | 172.16.76.12:57596 | sysbench | Query            |   67 | executing                                                     | select SQL_NO_CACHE b.id,a.k from sbtest_a a left join sbtest_b b on a.id=b.id  group by a.k order by b.c desc |   66477 |         0 |             0 |

由上可知:目前这个sql已经执行了67s,且此sql使用了group by和order by,必然会产生io

4.2 通过线程号查询会话

mysql> select * from threads where thread_os_id=74770\G;
*************************** 1. row ***************************
          THREAD_ID: 95
               NAME: thread/sql/one_connection
               TYPE: FOREGROUND
     PROCESSLIST_ID: 9
   PROCESSLIST_USER: pcms
   PROCESSLIST_HOST: 172.16.76.12
     PROCESSLIST_DB: sysbench
PROCESSLIST_COMMAND: Query
   PROCESSLIST_TIME: 91
  PROCESSLIST_STATE: NULL
   PROCESSLIST_INFO: select SQL_NO_CACHE b.id,a.k from sbtest_a a left join sbtest_b b on a.id=b.id  group by a.k order by b.c desc
   PARENT_THREAD_ID: 1
               ROLE: NULL
       INSTRUMENTED: YES
            HISTORY: YES
    CONNECTION_TYPE: TCP/IP
       THREAD_OS_ID: 74770
     RESOURCE_GROUP: USR_default
1 row in set (0.00 sec)

由上可知:通过查询threads表可以进行验证,该线程在频繁创建临时表的原因就来源于此sql

4.3 查看该sql语句的执行计划,进行进一步认证

mysql> explain select SQL_NO_CACHE b.id,a.k from sbtest_a a left join sbtest_b b on a.id=b.id  group by a.k order by b.c desc\G;
*************************** 1. row ***************************
           id: 1
  select_type: SIMPLE
        table: a
   partitions: NULL
         type: ALL
possible_keys: NULL
          key: NULL
      key_len: NULL
          ref: NULL
         rows: 1
     filtered: 100.00
        Extra: Using temporary; Using filesort
*************************** 2. row ***************************
           id: 1
  select_type: SIMPLE
        table: b
   partitions: NULL
         type: eq_ref
possible_keys: PRIMARY
          key: PRIMARY
      key_len: 4
          ref: sysbench.a.id
         rows: 1
     filtered: 100.00
        Extra: NULL
2 rows in set, 2 warnings (0.00 sec)

由上可知:该sql的执行计划用到了临时表及临时文件,符合

4.4 查看全局状态进一步进行确认

mysql> show global status like '%tmp%';
+-------------------------+-------+
| Variable_name           | Value |
+-------------------------+-------+
| Created_tmp_disk_tables | 3     |
| Created_tmp_files       | 22    |
| Created_tmp_tables      | 8     |
+-------------------------+-------+

多执行几次,可以看出tmp_files和tmp_disk_tables的值在增长,证明在大量的创建临时文件及磁盘临时表,符合该线程的行为

五、故障处理

通过上述的一系列排查,我们已经分析出来,目前sda磁盘的io使用率最高,且mysqld程序占用的最多,通过排查有一个线程在频繁的创建临时表或临时文件且通过登录mysql排查会话及线程视图可以找到是由某一个慢sql导致的,查看此慢sql的执行计划也会创建临时表和临时文件符合我们之前排查的预期。
此时我们就需要针对此慢sql进行优化,优化步骤由DBA进行处理,此处进行忽略。慢sql优化完成后可以进行io的继续观察,看io是否有下降

六、代码分析

我们可以使用pstack进行跟踪线程号,获取当前的线程堆栈信息。切记pstack会调用gdb进行debug调试

shell> pstack 74770 >/tmp/74770.pstack
Thread 1 (process 74770):
#0  ha_innobase::general_fetch (this=0xea654228, buf=0xea662028 "\212t\317\030\002", direction=1, match_mode=0  ) at /builds/naiwei.fang/percona-server/storage/innobase/handler/ha_innodb.cc:11159
#1  0x0000000000d9913c in handler::ha_rnd_next (this=0xea654228, buf=0xea662028 "\212t\317\030\002") at /build
s/naiwei.fang/percona-server/sql/handler.cc:3173
#2  0x0000000000f77db0 in TableScanIterator::Read (this=0xd256d5e8) at /builds/naiwei.fang/percona-server/sql/
row_iterator.h:208
#3  0x000000000124c714 in WriteRowsToChunks (xxhash_seed=899339, write_to_build_chunk=true, write_rows_with_nu
ll_in_join_key=false, join_key_buffer=0xd01fdb98, tables_to_get_rowid_for=0, chunks=0xd01fdb58, join_condition
s=..., tables=..., iterator=0xd256d5e8, thd=0xdb888000) at /builds/naiwei.fang/percona-server/sql/hash_join_it
erator.cc:282
#4  HashJoinIterator::BuildHashTable (this=this@entry=0xd01fd028) at /builds/naiwei.fang/percona-server/sql/ha
sh_join_iterator.cc:495
#5  0x000000000124c8ac in Init (this=0xd01fd028) at /builds/naiwei.fang/percona-server/sql/hash_join_iterator.
cc:203
#6  HashJoinIterator::Init (this=0xd01fd028) at /builds/naiwei.fang/percona-server/sql/hash_join_iterator.cc:1
45
#7  0x00000000010eca14 in Query_expression::ExecuteIteratorQuery (this=0xdec3a8b8, thd=thd@entry=0xdb888000) a
t /builds/naiwei.fang/percona-server/sql/sql_union.cc:1224
#8  0x00000000010ecccc in Query_expression::execute (this=this@entry=0xdec3a8b8, thd=thd@entry=0xdb888000) at 
/builds/naiwei.fang/percona-server/sql/sql_union.cc:1284
#9  0x0000000001083db0 in Sql_cmd_dml::execute_inner (this=0xd256bcb0, thd=0xdb888000) at /builds/naiwei.fang/
percona-server/sql/sql_select.cc:791
#10 0x000000000108cac8 in Sql_cmd_dml::execute (this=0xd256bcb0, thd=0xdb888000) at /builds/naiwei.fang/percon
a-server/sql/sql_select.cc:575
#11 0x00000000010384e8 in mysql_execute_command (thd=thd@entry=0xdb888000, first_level=first_level@entry=true)
 at /builds/naiwei.fang/percona-server/sql/sql_parse.cc:4677
#12 0x000000000103b314 in dispatch_sql_command (thd=thd@entry=0xdb888000, parser_state=parser_state@entry=0xff
f7bd4735b0, update_userstat=update_userstat@entry=false) at /builds/naiwei.fang/percona-server/sql/sql_parse.c
c:5273
#13 0x000000000103ccf0 in dispatch_command (thd=thd@entry=0xdb888000, com_data=0xffffb467c4d0, com_data@entry=
0xfff7bd474640, command=COM_QUERY) at /builds/naiwei.fang/percona-server/sql/sql_parse.cc:1938
#14 0x000000000103da40 in do_command (thd=thd@entry=0xdb888000) at /builds/naiwei.fang/percona-server/sql/sql_
parse.cc:1386
#15 0x0000000001152ca8 in handle_connection (arg=arg@entry=0xda53ab10) at /builds/naiwei.fang/percona-server/s
ql/conn_handler/connection_handler_per_thread.cc:307
#16 0x00000000022bc3ec in pfs_spawn_thread (arg=<optimized out>) at /builds/naiwei.fang/percona-server/storage
/perfschema/pfs.cc:2899
#17 0x0000ffffb43c7c48 in start_thread () from /lib64/libpthread.so.0
#18 0x0000ffffb3c0f600 in thread_start () from /lib64/libc.so.6

Enjoy GreatSQL 😃

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posted @ 2022-01-17 09:19  GreatSQL  阅读(342)  评论(0编辑  收藏  举报