作者：郭鹏霞

原文来源：https://tidb.net/blog/0b1b8ff3

 

问题背景：

通过granfan-->pd-->region health 图表监控到empty region 较多,且此集群目前业务并不多，数据量也很小，初始化时只创建了较表。

问题排查：

查看region merge相关参数：

l max-merge-region-size:

##控制region merge的大小上限，当region大于指定值时pd不会将相邻的region合并(默认20)

l max-merge-region-keys:

##控制region merge的key上限，当region大于指定值时pd不会将相邻的region合并(默认2000)

l merge-schedule-limit:

##同时进行region merge调度的任务数，设置为则关闭region merge(默认值8)

如下，这些参数都是默认值，

$ pd-ctl config show max-merge-region-size |grep max-merge-region-size  "max-merge-region-size": 20,   $ pd-ctl config show max-merge-region-keys |grep max-merge-region-keys    "max-merge-region-keys": 200000,$ pd-ctl config show merge-schedule-limit |grep merge-schedule-limit    "merge-schedule-limit": 8,

查看region的split和merge频率相关参数，

l patrol-region-interval:

##控制replicaChecker检查region监控状态的运行频率，越短则运行越快(10ms)

l split-merge-interval:

##控制对同一个region做split和merge的操作间隔，对应新split的region一段时间不会merge(默认1h)

$ pd-ctl config show patrol-region-interval |grep patrol    "patrol-region-interval": "100ms",$ pd-ctl config show split-merge-interval |grep split    "split-merge-interval": "1h0m0s",

 

测试ddl时与分配的region是否会merge:

突然想到，空regions多的集群在ddl时使用了region预分配参数，查看相关表时只有1个region,在社区咨询老师说是被merge了。

创建测试表并预分配region,查看region数是指定的：

mysql> ** create table guo004(id int, name varchar(10))  SHARD_ROW_ID_BITS=4 PRE_SPLIT_REGIONS=4;**Query OK, 0 rows affected (0.51 sec)mysql> show table guo004 regions;+-----------+-----------------------------+-----------------------------+-----------+-----------------+---------------------+------------+---------------+------------+----------------------+------------------+| REGION_ID | START_KEY                   | END_KEY                     | LEADER_ID | LEADER_STORE_ID | PEERS               | SCATTERING | WRITTEN_BYTES | READ_BYTES | APPROXIMATE_SIZE(MB) | APPROXIMATE_KEYS |+-----------+-----------------------------+-----------------------------+-----------+-----------------+---------------------+------------+---------------+------------+----------------------+------------------+|     25373 | t_437_                      | t_437_r_576460752303423488  |     25375 |               5 | 25374, 25375, 25376 |          0 |           341 |          0 |                    1 |                0 ||     25377 | t_437_r_576460752303423488  | t_437_r_1152921504606846976 |     25379 |               5 | 25378, 25379, 25380 |          0 |            29 |          0 |                    1 |                0 ||     25381 | t_437_r_1152921504606846976 | t_437_r_1729382256910270464 |     25383 |               5 | 25382, 25383, 25384 |          0 |             0 |          0 |                    1 |                0 ||     25385 | t_437_r_1729382256910270464 | t_437_r_2305843009213693952 |     25387 |               5 | 25386, 25387, 25388 |          0 |             0 |          0 |                    1 |                0 ||     25389 | t_437_r_2305843009213693952 | t_437_r_2882303761517117440 |     25391 |               5 | 25390, 25391, 25392 |          0 |            29 |          0 |                    1 |                0 ||     25393 | t_437_r_2882303761517117440 | t_437_r_3458764513820540928 |     25395 |               5 | 25394, 25395, 25396 |          0 |             0 |          0 |                    1 |                0 ||     25397 | t_437_r_3458764513820540928 | t_437_r_4035225266123964416 |     25399 |               5 | 25398, 25399, 25400 |          0 |            29 |          0 |                    1 |                0 ||     25401 | t_437_r_4035225266123964416 | t_437_r_4611686018427387904 |     25403 |               5 | 25402, 25403, 25404 |          0 |             0 |          0 |                    1 |                0 ||     25405 | t_437_r_4611686018427387904 | t_437_r_5188146770730811392 |     25407 |               5 | 25406, 25407, 25408 |          0 |            29 |          0 |                    1 |                0 ||     25409 | t_437_r_5188146770730811392 | t_437_r_5764607523034234880 |     25411 |               5 | 25410, 25411, 25412 |          0 |             0 |          0 |                    1 |                0 ||     25413 | t_437_r_5764607523034234880 | t_437_r_6341068275337658368 |     25415 |               5 | 25414, 25415, 25416 |          0 |            29 |          0 |                    1 |                0 ||     25417 | t_437_r_6341068275337658368 | t_437_r_6917529027641081856 |     25419 |               5 | 25418, 25419, 25420 |          0 |            29 |          0 |                    1 |                0 ||     25421 | t_437_r_6917529027641081856 | t_437_r_7493989779944505344 |     25423 |               5 | 25422, 25423, 25424 |          0 |             0 |          0 |                    1 |                0 ||     25425 | t_437_r_7493989779944505344 | t_437_r_8070450532247928832 |     25427 |               5 | 25426, 25427, 25428 |          0 |            29 |          0 |                    1 |                0 ||     25429 | t_437_r_8070450532247928832 | t_437_r_8646911284551352320 |     25431 |               5 | 25430, 25431, 25432 |          0 |             0 |          0 |                    1 |                0 ||     25169 | t_437_r_8646911284551352320 |                             |     25171 |               5 | 25170, 25171, 25172 |          0 |             0 |          0 |                    1 |                0 |+-----------+-----------------------------+-----------------------------+-----------+-----------------+---------------------+------------+---------------+------------+----------------------+------------------+16 rows in set (0.01 sec)

检查预分配region是否merge

根据以上split-merge-interval参数，1小时后测试表的guo004空regions将被回收：

mysql> mysql> show table guo004 regions;+-----------+-----------+---------+-----------+-----------------+---------------------+------------+---------------+------------+----------------------+------------------+| REGION_ID | START_KEY | END_KEY | LEADER_ID | LEADER_STORE_ID | PEERS               | SCATTERING | WRITTEN_BYTES | READ_BYTES | APPROXIMATE_SIZE(MB) | APPROXIMATE_KEYS |+-----------+-----------+---------+-----------+-----------------+---------------------+------------+---------------+------------+----------------------+------------------+|     25425 | t_437_    |         |     25427 |               5 | 25426, 25427, 25428 |          0 |          1285 |          0 |                    1 |                0 |+-----------+-----------+---------+-----------+-----------------+---------------------+------------+---------------+------------+----------------------+------------------+1 row in set (0.01 sec)

即使是ddl预分配的region,如果没有regions为空的话，都会自动merge.

查看空regions 信息：

参数说明：

approximate_size：估算的region的数据量大小，单位为MB

approximate_keys：估算的region内的key的个数

注意关注approximate_size、approximate_keys 的值。

查看所有空region信息：

$ ./pd-ctl region check empty-region |more

$ ./pd-ctl region check empty-region |more{  "count": 272,  "regions": [    {      "id": 202,      "start_key": "7480000000000000FF5C00000000000000F8",      "end_key": "7480000000000000FF5E00000000000000F8",      "epoch": {        "conf_ver": 71639,        "version": 43      },      "peers": [        {          "id": 7796112,          "store_id": 21        },        {          "id": 7952908,          "store_id": 2        },        {          "id": 7955094,          "store_id": 19        }      ],      "leader": {        "id": 7796112,        "store_id": 21      },      "written_bytes": 0,      "read_bytes": 0,      "written_keys": 0,      "read_keys": 0,      "approximate_size": 1,      "approximate_keys": 0    },    {      "id": 217800,      "start_key": "7480000000000002FF8500000000000000F8",      "end_key": "7480000000000002FF8700000000000000F8",      "epoch": {        "conf_ver": 71369,        "version": 290      },      "peers": [        {          "id": 7932728,          "store_id": 3        },        {          "id": 7954710,          "store_id": 1        },        {          "id": 7955013,          "store_id": 5        }      ],      "leader": {        "id": 7932728,        "store_id": 3      },      "written_bytes": 0,      "read_bytes": 0,      "written_keys": 0,      "read_keys": 0,**      "approximate_size": 1,****      "approximate_keys": 0**    },--More--

查看单个region信息：

$ ./pd-ctl  region 217800

$ ./pd-ctl  region 217800{  "id": 217800,  "start_key": "7480000000000002FF8500000000000000F8",  "end_key": "7480000000000002FF8700000000000000F8",  "epoch": {    "conf_ver": 71369,    "version": 290  },  "peers": [    {      "id": 7932728,      "store_id": 3    },    {      "id": 7954710,      "store_id": 1    },    {      "id": 7955013,      "store_id": 5    }  ],  "leader": {    "id": 7932728,    "store_id": 3  },  "written_bytes": 0,  "read_bytes": 0,  "written_keys": 0,  "read_keys": 0,**  "approximate_size": 1,****  "approximate_keys": 0**}

或者通过系统表TIKV_REGION_STATUS查看：

(我个人更倾向于查系统表，比对的可视度更强些)：

mysql> select REGION_ID,START_KEY,END_KEY,TABLE_ID,DB_NAME,TABLE_NAME,APPROXIMATE_SIZE,APPROXIMATE_KEYS from TIKV_REGION_STATUS where DB_NAME='dzdz' order by START_KEY limit 30;+-----------+--------------------------------------+--------------------------------------+----------+---------+--------------------------+------------------+------------------+| REGION_ID | START_KEY                            | END_KEY                              | TABLE_ID | DB_NAME | TABLE_NAME               | APPROXIMATE_SIZE | APPROXIMATE_KEYS |+-----------+--------------------------------------+--------------------------------------+----------+---------+--------------------------+------------------+------------------+|    217152 | 7480000000000001FFAD00000000000000F8 | 7480000000000001FFAF00000000000000F8 |      429 | dzdz    | qrtz_blob_triggers       |                1 |                0 ||    217152 | 7480000000000001FFAD00000000000000F8 | 7480000000000001FFAF00000000000000F8 |      429 | dzdz    | qrtz_blob_triggers       |                1 |                0 ||    217152 | 7480000000000001FFAD00000000000000F8 | 7480000000000001FFAF00000000000000F8 |      429 | dzdz    | qrtz_blob_triggers       |                1 |                0 ||    217156 | 7480000000000001FFAF00000000000000F8 | 7480000000000001FFB100000000000000F8 |      431 | dzdz    | qrtz_calendars           |                1 |                0 ||    217156 | 7480000000000001FFAF00000000000000F8 | 7480000000000001FFB100000000000000F8 |      431 | dzdz    | qrtz_calendars           |                1 |                0 ||    217160 | 7480000000000001FFB100000000000000F8 | 7480000000000001FFB300000000000000F8 |      433 | dzdz    | qrtz_cron_triggers       |                1 |                0 ||    217160 | 7480000000000001FFB100000000000000F8 | 7480000000000001FFB300000000000000F8 |      433 | dzdz    | qrtz_cron_triggers       |                1 |                0 ||    217164 | 7480000000000001FFB300000000000000F8 | 7480000000000001FFB500000000000000F8 |      435 | dzdz    | qrtz_fired_triggers      |                1 |                0 ||    217164 | 7480000000000001FFB300000000000000F8 | 7480000000000001FFB500000000000000F8 |      435 | dzdz    | qrtz_fired_triggers      |                1 |                0 ||    217164 | 7480000000000001FFB300000000000000F8 | 7480000000000001FFB500000000000000F8 |      435 | dzdz    | qrtz_fired_triggers      |                1 |                0 ||    217164 | 7480000000000001FFB300000000000000F8 | 7480000000000001FFB500000000000000F8 |      435 | dzdz    | qrtz_fired_triggers      |                1 |                0 ||    217164 | 7480000000000001FFB300000000000000F8 | 7480000000000001FFB500000000000000F8 |      435 | dzdz    | qrtz_fired_triggers      |                1 |                0 ||    217164 | 7480000000000001FFB300000000000000F8 | 7480000000000001FFB500000000000000F8 |      435 | dzdz    | qrtz_fired_triggers      |                1 |                0 ||    217164 | 7480000000000001FFB300000000000000F8 | 7480000000000001FFB500000000000000F8 |      435 | dzdz    | qrtz_fired_triggers      |                1 |                0 ||    217164 | 7480000000000001FFB300000000000000F8 | 7480000000000001FFB500000000000000F8 |      435 | dzdz    | qrtz_fired_triggers      |                1 |                0 ||    217168 | 7480000000000001FFB500000000000000F8 | 7480000000000001FFB700000000000000F8 |      437 | dzdz    | qrtz_job_details         |                1 |                0 ||    217168 | 7480000000000001FFB500000000000000F8 | 7480000000000001FFB700000000000000F8 |      437 | dzdz    | qrtz_job_details         |                1 |                0 ||    217168 | 7480000000000001FFB500000000000000F8 | 7480000000000001FFB700000000000000F8 |      437 | dzdz    | qrtz_job_details         |                1 |                0 ||    217168 | 7480000000000001FFB500000000000000F8 | 7480000000000001FFB700000000000000F8 |      437 | dzdz    | qrtz_job_details         |                1 |                0 ||    217172 | 7480000000000001FFB700000000000000F8 | 7480000000000001FFB900000000000000F8 |      439 | dzdz    | qrtz_locks               |                1 |                0 ||    217172 | 7480000000000001FFB700000000000000F8 | 7480000000000001FFB900000000000000F8 |      439 | dzdz    | qrtz_locks               |                1 |                0 ||    217176 | 7480000000000001FFB900000000000000F8 | 7480000000000001FFBB00000000000000F8 |      441 | dzdz    | qrtz_paused_trigger_grps |                1 |                0 ||    217176 | 7480000000000001FFB900000000000000F8 | 7480000000000001FFBB00000000000000F8 |      441 | dzdz    | qrtz_paused_trigger_grps |                1 |                0 ||    217180 | 7480000000000001FFBB00000000000000F8 | 7480000000000001FFBD00000000000000F8 |      443 | dzdz    | qrtz_scheduler_state     |               10 |            20343 ||    217180 | 7480000000000001FFBB00000000000000F8 | 7480000000000001FFBD00000000000000F8 |      443 | dzdz    | qrtz_scheduler_state     |               10 |            20343 ||    217184 | 7480000000000001FFBD00000000000000F8 | 7480000000000001FFBF00000000000000F8 |      445 | dzdz    | qrtz_simple_triggers     |                1 |                0 ||    217184 | 7480000000000001FFBD00000000000000F8 | 7480000000000001FFBF00000000000000F8 |      445 | dzdz    | qrtz_simple_triggers     |                1 |                0 ||    217188 | 7480000000000001FFBF00000000000000F8 | 7480000000000001FFC100000000000000F8 |      447 | dzdz    | qrtz_simprop_triggers    |                1 |                0 ||    217188 | 7480000000000001FFBF00000000000000F8 | 7480000000000001FFC100000000000000F8 |      447 | dzdz    | qrtz_simprop_triggers    |                1 |                0 ||    217192 | 7480000000000001FFC100000000000000F8 | 7480000000000001FFC300000000000000F8 |      449 | dzdz    | qrtz_triggers            |                1 |                0 |+-----------+--------------------------------------+--------------------------------------+----------+---------+--------------------------+------------------+------------------+30 rows in set (0.01 sec)mysql>

通过以上信息显示一个regions的END_KEY 是另一个region的START_KEY, 结合APPROXIMATE_SIZE和APPROXIMATE_KEYS字段的值，可知部分空region是连续的。

 

检查跨表合并是否启用

l enable-cross-table-merge：

##设置是否开启跨表merge(默认v4.0:false,v6.0:true)

$  ./pd-ctl config show enable-cross-table-merge |grep cross    "enable-cross-table-merge": "false",$如上跨表合并未启用

** **

测试启用跨表合并是否能降低空region数：

检查当前空region数：

测试环境的empty region 也比较多，如下图：

 

启用跨表合并：

确认夸表合并未启用：» config show{  "replication": {    "enable-placement-rules": "true",    "location-labels": "dc,host",    "max-replicas": 3,    "strictly-match-label": "false"  },  "schedule": {    "enable-cross-table-merge": "false",......  }}启用跨表合并：****» config set enable-cross-table-merge trueSuccess! 确认跨表合并启用：» config show{  "replication": {    "enable-placement-rules": "true",    "location-labels": "dc,host",    "max-replicas": 3,    "strictly-match-label": "false"  },  "schedule": {    "enable-cross-table-merge": "true",......  }}»

启用跨表何必后空region数：

在grafana上看region health状态，empty region 数量已经为0：

 

问题处理：

启用跨表合并，可以减少或至0空region数据量

操作命令：$ ./pd-ctl config set enable-cross-table-merge true 即可。

综上所述：

通过granfan-->pd-->region health 图表监控到empty region 较多：

查看region merge大小相关参数：

l max-merge-region-size:

##控制region merge的大小上限，当region大于指定值时pd不会将相邻的region合并(默认20)

l max-merge-region-keys:

##控制region merge的key上限，当region大于指定值时pd不会将相邻的region合并(默认2000)

l merge-schedule-limit:

##同时进行region merge调度的任务数，设置为则关闭region merge(默认值8)

 

如果以上参数设置太小或不合理可以适当调整让region加速merge

如果以上参数设置合理(一般默认值就可以)，请检查region merge频率参数

查看region的split和merge频率相关参数，

l patrol-region-interval:

##控制replicaChecker检查region监控状态的运行频率，越短则运行越快(10ms)

l split-merge-interval:

##控制对同一个region做split和merge的操作间隔，对应新split的region一段时间不会merge(默认1h)

 

如果以上参数设置过大或不合理可适当调小，但也不建议过小。

如果设置合理(一般默认值就可以)，请检查跨表合并参数。

检查跨表合并是否启用

l enable-cross-table-merge：

##设置是否开启跨表merge(默认v4.0:false,v5.0及其后版本:true)

 

跨表合并参数v5.0及其后版本默认已经启用，使用v5.0及其后版本的应该不太会出现这个问题。

使用v4.0、小于v5.0的版本或enable-cross-table-merge 未启用情况下可能会出现empty region较多。

一般多DDL on table情况下, enable-cross-table-merge结果较为明显。