概述
本文是前两篇文章 《大才能否小用？OceanBase一体化场景测试》、《使用 DBT-3 对 OceanBase 和 MariaDB 进行性能测试对比》 的后续及引申，主要介绍并测试 OceanBase（以下简称“OB”） 中表组（tablegroup）（以下简称“TG”）这一特性，并介绍 OB 自带的两个工具 env_checker.py 和 dooba.py。
OceanBase 的表组（Tablegroup）特性
在 OB 中，关系密切的表，可以通过表组干预它们的分区分布，使表组内所有的同号分区在同一个 Unit 内部，避免跨节点请求对性能的影响。
属于这样一个集合的表，需要满足一定的约束：所有表必须拥有相同的 Locality（副本类型、个数及位置），相同的 Primary Zone（leader 位置及其优先级），以及相同的分区方式。
不过，单节点下表组意义不大，更建议使用在3-3-3的场景下，将关联紧密的表设定为一个表组，从而减少跨zone访问带来的网络延迟。
本文案例是基于前两篇文章的进一步测试及特性演示，所以依旧是在单节点下进行测试。
TableGroup 基本用法
创建TG，添加表到TG，查看TG状态的语法如下：
mysql -uroot@tpcc -h127.1 -P2881 tpcc
# 创建 tablegroup
oceanbase> CREATE TABLEGROUP IF NOT EXISTS tg_1;
# 添加对应的表
oceanbase> ALTER TABLE sbtest1 SET TABLEGROUP tg_1;
oceanbase> ALTER TABLE TABLE2 SET TABLEGROUP tg_1;
# 查看 tablegroup
oceanbase> SHOW TABLEGROUPS;
oceanbase> SHOW CREATE TABLEGROUP tg_1\G
为测试表创建表组
从8张表的关系图，以及 SQL 的执行计划可以看出，customer、orders 和 lineitem 这三张表的关联关系密切，故将这三张表创建为一个表组。
# create tg
CREATE TABLEGROUP IF NOT EXISTS tg_dbt3;
# add table into tg
ALTER TABLE customer SET TABLEGROUP tg_dbt3;
ALTER TABLE orders SET TABLEGROUP tg_dbt3;
ALTER TABLE lineitem SET TABLEGROUP tg_dbt3;
# check tg
SHOW TABLEGROUPS;
+-----------------+----------------------------+---------------+
| Tablegroup_name | Table_name | Database_name |
+-----------------+----------------------------+---------------+
| oceanbase | NULL | NULL |
| tg_dbt3 | customer | tpcc |
| tg_dbt3 | lineitem | tpcc |
| tg_dbt3 | orders | tpcc |
+-----------------+----------------------------+---------------+
SHOW CREATE TABLEGROUP tg_dbt3\G
*************************** 1. row ***************************
Tablegroup: tg_dbt3
Create Tablegroup: CREATE TABLEGROUP IF NOT EXISTS `tg_dbt3` BINDING = FALSE
1 row in set (0.004 sec)
创建表组成功后，再次对6个SQL进行测试。
测试数据及执行计划如下。
测试 SQL 的执行计划
SQL-1
*************************** 1. row ***************************
Query Plan: ==============================================
|ID|OPERATOR |NAME |EST. ROWS|COST |
----------------------------------------------
|0 |SORT | |6 |4988325|
|1 | HASH GROUP BY| |6 |4988308|
|2 | TABLE SCAN |lineitem|2000405 |3261350|
==============================================
Outputs & filters:
-------------------------------------
0 - output([lineitem.l_returnflag], [lineitem.l_linestatus], [T_FUN_SUM(lineitem.l_quantity)], [T_FUN_SUM(lineitem.l_extendedprice)], [T_FUN_SUM(lineitem.l_extendedprice * ? - lineitem.l_discount)], [T_FUN_SUM(lineitem.l_extendedprice * ? - lineitem.l_discount * ? + lineitem.l_tax)], [T_FUN_SUM(lineitem.l_quantity) / cast(T_FUN_COUNT(lineitem.l_quantity), DECIMAL(20, 0))], [T_FUN_SUM(lineitem.l_extendedprice) / cast(T_FUN_COUNT(lineitem.l_extendedprice), DECIMAL(20, 0))], [T_FUN_SUM(lineitem.l_discount) / cast(T_FUN_COUNT(lineitem.l_discount), DECIMAL(20, 0))], [T_FUN_COUNT(*)]), filter(nil), sort_keys([lineitem.l_returnflag, ASC], [lineitem.l_linestatus, ASC])
1 - output([lineitem.l_returnflag], [lineitem.l_linestatus], [T_FUN_SUM(lineitem.l_quantity)], [T_FUN_SUM(lineitem.l_extendedprice)], [T_FUN_SUM(lineitem.l_extendedprice * ? - lineitem.l_discount)], [T_FUN_SUM(lineitem.l_extendedprice * ? - lineitem.l_discount * ? + lineitem.l_tax)], [T_FUN_COUNT(lineitem.l_quantity)], [T_FUN_COUNT(lineitem.l_extendedprice)], [T_FUN_SUM(lineitem.l_discount)], [T_FUN_COUNT(lineitem.l_discount)], [T_FUN_COUNT(*)]), filter(nil),
group([lineitem.l_returnflag], [lineitem.l_linestatus]), agg_func([T_FUN_SUM(lineitem.l_quantity)], [T_FUN_SUM(lineitem.l_extendedprice)], [T_FUN_SUM(lineitem.l_extendedprice * ? - lineitem.l_discount)], [T_FUN_SUM(lineitem.l_extendedprice * ? - lineitem.l_discount * ? + lineitem.l_tax)], [T_FUN_COUNT(*)], [T_FUN_COUNT(lineitem.l_quantity)], [T_FUN_COUNT(lineitem.l_extendedprice)], [T_FUN_SUM(lineitem.l_discount)], [T_FUN_COUNT(lineitem.l_discount)])
2 - output([lineitem.l_returnflag], [lineitem.l_linestatus], [lineitem.l_quantity], [lineitem.l_extendedprice], [lineitem.l_discount], [lineitem.l_extendedprice * ? - lineitem.l_discount], [lineitem.l_extendedprice * ? - lineitem.l_discount * ? + lineitem.l_tax]), filter([cast(lineitem.l_shipDATE, DATETIME(-1, -1)) <= ?]),
access([lineitem.l_shipDATE], [lineitem.l_returnflag], [lineitem.l_linestatus], [lineitem.l_quantity], [lineitem.l_extendedprice], [lineitem.l_discount], [lineitem.l_tax]), partitions(p0)
1 row in set (0.006 sec)
SQL-5
*************************** 1. row ***************************
Query Plan: =================================================
|ID|OPERATOR |NAME |EST. ROWS|COST |
-------------------------------------------------
|0 |SORT | |25 |6968243|
|1 | HASH GROUP BY | |25 |6968114|
|2 | HASH JOIN | |7348 |6965295|
|3 | TABLE SCAN |region |1 |40 |
|4 | HASH JOIN | |36737 |6948838|
|5 | TABLE SCAN |nation |25 |42 |
|6 | HASH JOIN | |36737 |6914905|
|7 | TABLE SCAN |supplier|10000 |3973 |
|8 | HASH JOIN | |907292 |6522128|
|9 | HASH JOIN | |223710 |1232531|
|10| TABLE SCAN|customer|150000 |62265 |
|11| TABLE SCAN|orders |228275 |770751 |
|12| TABLE SCAN |lineitem|6001215 |2361773|
=================================================
Outputs & filters:
-------------------------------------
0 - output([nation.n_name], [T_FUN_SUM(lineitem.l_extendedprice * ? - lineitem.l_discount)]), filter(nil), sort_keys([T_FUN_SUM(lineitem.l_extendedprice * ? - lineitem.l_discount), DESC])
1 - output([nation.n_name], [T_FUN_SUM(lineitem.l_extendedprice * ? - lineitem.l_discount)]), filter(nil),
group([nation.n_name]), agg_func([T_FUN_SUM(lineitem.l_extendedprice * ? - lineitem.l_discount)])
2 - output([nation.n_name], [lineitem.l_extendedprice * ? - lineitem.l_discount]), filter(nil),
equal_conds([nation.n_regionkey = region.r_regionkey]), other_conds(nil)
3 - output([region.r_regionkey]), filter([region.r_name = 'EUROPE']),
access([region.r_regionkey], [region.r_name]), partitions(p0)
4 - output([nation.n_name], [lineitem.l_extendedprice], [lineitem.l_discount], [nation.n_regionkey]), filter(nil),
equal_conds([supplier.s_nationkey = nation.n_nationkey]), other_conds(nil)
5 - output([nation.n_nationkey], [nation.n_regionkey], [nation.n_name]), filter(nil),
access([nation.n_nationkey], [nation.n_regionkey], [nation.n_name]), partitions(p0)
6 - output([lineitem.l_extendedprice], [lineitem.l_discount], [supplier.s_nationkey]), filter(nil),
equal_conds([lineitem.l_suppkey = supplier.s_suppkey], [customer.c_nationkey = supplier.s_nationkey]), other_conds(nil)
7 - output([supplier.s_suppkey], [supplier.s_nationkey]), filter(nil),
access([supplier.s_suppkey], [supplier.s_nationkey]), partitions(p0)
8 - output([lineitem.l_extendedprice], [lineitem.l_discount], [lineitem.l_suppkey], [customer.c_nationkey]), filter(nil),
equal_conds([lineitem.l_orderkey = orders.o_orderkey]), other_conds(nil)
9 - output([customer.c_nationkey], [orders.o_orderkey]), filter(nil),
equal_conds([customer.c_custkey = orders.o_custkey]), other_conds(nil)
10 - output([customer.c_custkey], [customer.c_nationkey]), filter(nil),
access([customer.c_custkey], [customer.c_nationkey]), partitions(p0)
11 - output([orders.o_custkey], [orders.o_orderkey]), filter([orders.o_orderDATE >= '1996-01-01'], [orders.o_orderDATE < ?]),
access([orders.o_custkey], [orders.o_orderkey], [orders.o_orderDATE]), partitions(p0)
12 - output([lineitem.l_orderkey], [lineitem.l_suppkey], [lineitem.l_extendedprice], [lineitem.l_discount]), filter(nil),
access([lineitem.l_orderkey], [lineitem.l_suppkey], [lineitem.l_extendedprice], [lineitem.l_discount]), partitions(p0)
1 row in set (0.035 sec)
SQL-6
*************************** 1. row ***************************
Query Plan: ===============================================
|ID|OPERATOR |NAME |EST. ROWS|COST |
-----------------------------------------------
|0 |SCALAR GROUP BY| |1 |5400125|
|1 | TABLE SCAN |lineitem|123843 |5376470|
===============================================
Outputs & filters:
-------------------------------------
0 - output([T_FUN_SUM(lineitem.l_extendedprice * lineitem.l_discount)]), filter(nil),
group(nil), agg_func([T_FUN_SUM(lineitem.l_extendedprice * lineitem.l_discount)])
1 - output([lineitem.l_extendedprice * lineitem.l_discount]), filter([(T_OP_BTW, lineitem.l_discount, ?, ?)], [lineitem.l_shipDATE >= '1996-01-01'], [lineitem.l_quantity < ?], [lineitem.l_shipDATE < ?]),
access([lineitem.l_shipDATE], [lineitem.l_discount], [lineitem.l_quantity], [lineitem.l_extendedprice]), partitions(p0)
1 row in set (0.004 sec)
SQL-10
*************************** 1. row ***************************
Query Plan: ================================================
|ID|OPERATOR |NAME |EST. ROWS|COST |
------------------------------------------------
|0 |LIMIT | |20 |9753872|
|1 | TOP-N SORT | |20 |9753869|
|2 | HASH GROUP BY | |273659 |8556264|
|3 | HASH JOIN | |273659 |8160619|
|4 | TABLE SCAN |nation |25 |41 |
|5 | HASH JOIN | |273659 |7908405|
|6 | HASH JOIN | |279244 |7017068|
|7 | TABLE SCAN|orders |166667 |770751 |
|8 | TABLE SCAN|lineitem|2000405 |5172554|
|9 | TABLE SCAN |customer|150000 |78809 |
================================================
Outputs & filters:
-------------------------------------
0 - output([customer.c_custkey], [customer.c_name], [T_FUN_SUM(lineitem.l_extendedprice * ? - lineitem.l_discount)], [customer.c_acctbal], [nation.n_name], [customer.c_address], [customer.c_phone], [customer.c_comment]), filter(nil), limit(20), offset(nil)
1 - output([customer.c_custkey], [customer.c_name], [T_FUN_SUM(lineitem.l_extendedprice * ? - lineitem.l_discount)], [customer.c_acctbal], [nation.n_name], [customer.c_address], [customer.c_phone], [customer.c_comment]), filter(nil), sort_keys([T_FUN_SUM(lineitem.l_extendedprice * ? - lineitem.l_discount), DESC]), topn(20)
2 - output([customer.c_custkey], [customer.c_name], [T_FUN_SUM(lineitem.l_extendedprice * ? - lineitem.l_discount)], [customer.c_acctbal], [nation.n_name], [customer.c_address], [customer.c_phone], [customer.c_comment]), filter(nil),
group([customer.c_custkey], [customer.c_name], [customer.c_acctbal], [customer.c_phone], [nation.n_name], [customer.c_address], [customer.c_comment]), agg_func([T_FUN_SUM(lineitem.l_extendedprice * ? - lineitem.l_discount)])
3 - output([customer.c_custkey], [customer.c_name], [customer.c_acctbal], [nation.n_name], [customer.c_address], [customer.c_phone], [customer.c_comment], [lineitem.l_extendedprice * ? - lineitem.l_discount]), filter(nil),
equal_conds([customer.c_nationkey = nation.n_nationkey]), other_conds(nil)
4 - output([nation.n_nationkey], [nation.n_name]), filter(nil),
access([nation.n_nationkey], [nation.n_name]), partitions(p0)
5 - output([customer.c_custkey], [customer.c_name], [lineitem.l_extendedprice], [lineitem.l_discount], [customer.c_acctbal], [customer.c_address], [customer.c_phone], [customer.c_comment], [customer.c_nationkey]), filter(nil),
equal_conds([customer.c_custkey = orders.o_custkey]), other_conds(nil)
6 - output([lineitem.l_extendedprice], [lineitem.l_discount], [orders.o_custkey]), filter(nil),
equal_conds([lineitem.l_orderkey = orders.o_orderkey]), other_conds(nil)
7 - output([orders.o_custkey], [orders.o_orderkey]), filter([cast(orders.o_orderDATE, DATETIME(-1, -1)) >= ?], [cast(orders.o_orderDATE, DATETIME(-1, -1)) < ?]),
access([orders.o_custkey], [orders.o_orderkey], [orders.o_orderDATE]), partitions(p0)
8 - output([lineitem.l_orderkey], [lineitem.l_extendedprice], [lineitem.l_discount]), filter([lineitem.l_returnflag = 'R']),
access([lineitem.l_orderkey], [lineitem.l_returnflag], [lineitem.l_extendedprice], [lineitem.l_discount]), partitions(p0)
9 - output([customer.c_custkey], [customer.c_nationkey], [customer.c_name], [customer.c_acctbal], [customer.c_address], [customer.c_phone], [customer.c_comment]), filter(nil),
access([customer.c_custkey], [customer.c_nationkey], [customer.c_name], [customer.c_acctbal], [customer.c_address], [customer.c_phone], [customer.c_comment]), partitions(p0)
1 row in set (0.023 sec)
SQL-17
*************************** 1. row ***************************
Query Plan: =================================================
|ID|OPERATOR |NAME |EST. ROWS|COST |
-------------------------------------------------
|0 |SCALAR GROUP BY | |1 |4485685|
|1 | SUBPLAN SCAN |VIEW1 |2035 |4485296|
|2 | WINDOW FUNCTION| |6104 |4483943|
|3 | SORT | |6104 |4482777|
|4 | HASH JOIN | |6104 |4464880|
|5 | TABLE SCAN |part |206 |261589 |
|6 | TABLE SCAN |lineitem|6001215 |2229397|
=================================================
Outputs & filters:
-------------------------------------
0 - output([T_FUN_SUM(VIEW1.lineitem.l_extendedprice) / 7.0]), filter(nil),
group(nil), agg_func([T_FUN_SUM(VIEW1.lineitem.l_extendedprice)])
1 - output([VIEW1.lineitem.l_extendedprice]), filter([VIEW1.lineitem.l_quantity < VIEW1.0.2 * avg(l_quantity)]),
access([VIEW1.0.2 * avg(l_quantity)], [VIEW1.lineitem.l_quantity], [VIEW1.lineitem.l_extendedprice])
2 - output([0.2 * T_FUN_SUM(lineitem.l_quantity) / cast(T_FUN_COUNT(lineitem.l_quantity), DECIMAL(20, 0))], [lineitem.l_quantity], [lineitem.l_extendedprice]), filter(nil),
win_expr(T_FUN_SUM(lineitem.l_quantity)), partition_by([part.__pk_increment]), order_by(nil), window_type(RANGE), upper(UNBOUNDED PRECEDING), lower(UNBOUNDED FOLLOWING)
win_expr(T_FUN_COUNT(lineitem.l_quantity)), partition_by([part.__pk_increment]), order_by(nil), window_type(RANGE), upper(UNBOUNDED PRECEDING), lower(UNBOUNDED FOLLOWING)
3 - output([lineitem.l_quantity], [part.__pk_increment], [lineitem.l_extendedprice]), filter(nil), sort_keys([part.__pk_increment, ASC])
4 - output([lineitem.l_quantity], [part.__pk_increment], [lineitem.l_extendedprice]), filter(nil),
equal_conds([part.p_partkey = lineitem.l_partkey]), other_conds(nil)
5 - output([part.p_partkey], [part.__pk_increment]), filter([part.p_container = 'WRAP DRUM'], [part.p_brand = 'Brand#43']),
access([part.p_partkey], [part.p_brand], [part.p_container], [part.__pk_increment]), partitions(p0)
6 - output([lineitem.l_partkey], [lineitem.l_quantity], [lineitem.l_extendedprice]), filter(nil),
access([lineitem.l_partkey], [lineitem.l_quantity], [lineitem.l_extendedprice]), partitions(p0)
1 row in set (0.014 sec)
SQL-18
*************************** 1. row ***************************
Query Plan: ==================================================
|ID|OPERATOR |NAME |EST. ROWS|COST |
--------------------------------------------------
|0 |LIMIT | |100 |8933274|
|1 | TOP-N SORT | |100 |8933260|
|2 | HASH JOIN | |3297 |8925142|
|3 | HASH JOIN | |3330 |8609940|
|4 | SUBPLAN SCAN |VIEW1 |3321 |5444449|
|5 | HASH GROUP BY| |3321 |5443991|
|6 | TABLE SCAN |lineitem|6001215 |2097020|
|7 | SUBPLAN SCAN |VIEW3 |1500000 |2666737|
|8 | HASH GROUP BY| |1500000 |2459704|
|9 | TABLE SCAN |orders |1500000 |552665 |
|10| SUBPLAN SCAN |VIEW2 |150000 |256232 |
|11| HASH GROUP BY | |150000 |235529 |
|12| TABLE SCAN |customer|150000 |62265 |
==================================================
Outputs & filters:
-------------------------------------
0 - output([VIEW2.customer.c_name], [VIEW2.customer.c_custkey], [VIEW3.orders.o_orderkey], [VIEW3.orders.o_orderDATE], [VIEW3.orders.o_totalprice], [cast(VIEW2.T_FUN_COUNT(*) * VIEW3.T_FUN_COUNT(*), DECIMAL(40, 0)) * VIEW1.T_FUN_SUM(lineitem.l_quantity)]), filter(nil), limit(100), offset(nil)
1 - output([VIEW2.customer.c_name], [VIEW2.customer.c_custkey], [VIEW3.orders.o_orderkey], [VIEW3.orders.o_orderDATE], [VIEW3.orders.o_totalprice], [VIEW2.T_FUN_COUNT(*)], [VIEW3.T_FUN_COUNT(*)], [VIEW1.T_FUN_SUM(lineitem.l_quantity)]), filter(nil), sort_keys([VIEW3.orders.o_totalprice, DESC], [VIEW3.orders.o_orderDATE, ASC]), topn(100)
2 - output([VIEW2.customer.c_name], [VIEW2.customer.c_custkey], [VIEW3.orders.o_orderkey], [VIEW3.orders.o_orderDATE], [VIEW3.orders.o_totalprice], [VIEW2.T_FUN_COUNT(*)], [VIEW3.T_FUN_COUNT(*)], [VIEW1.T_FUN_SUM(lineitem.l_quantity)]), filter(nil),
equal_conds([VIEW2.customer.c_custkey = VIEW3.orders.o_custkey]), other_conds(nil)
3 - output([VIEW3.orders.o_orderkey], [VIEW3.orders.o_orderDATE], [VIEW3.orders.o_totalprice], [VIEW3.T_FUN_COUNT(*)], [VIEW1.T_FUN_SUM(lineitem.l_quantity)], [VIEW3.orders.o_custkey]), filter(nil),
equal_conds([VIEW3.orders.o_orderkey = VIEW1.l_orderkey]), other_conds(nil)
4 - output([VIEW1.l_orderkey], [VIEW1.T_FUN_SUM(lineitem.l_quantity)]), filter(nil),
access([VIEW1.l_orderkey], [VIEW1.T_FUN_SUM(lineitem.l_quantity)])
5 - output([lineitem.l_orderkey], [T_FUN_SUM(lineitem.l_quantity)]), filter([T_FUN_SUM(lineitem.l_quantity) > ?]),
group([lineitem.l_orderkey]), agg_func([T_FUN_SUM(lineitem.l_quantity)])
6 - output([lineitem.l_orderkey], [lineitem.l_quantity]), filter(nil),
access([lineitem.l_orderkey], [lineitem.l_quantity]), partitions(p0)
7 - output([VIEW3.orders.o_custkey], [VIEW3.orders.o_orderkey], [VIEW3.orders.o_orderDATE], [VIEW3.orders.o_totalprice], [VIEW3.T_FUN_COUNT(*)]), filter(nil),
access([VIEW3.orders.o_custkey], [VIEW3.orders.o_orderkey], [VIEW3.orders.o_orderDATE], [VIEW3.orders.o_totalprice], [VIEW3.T_FUN_COUNT(*)])
8 - output([orders.o_custkey], [orders.o_orderkey], [orders.o_orderDATE], [orders.o_totalprice], [T_FUN_COUNT(*)]), filter(nil),
group([orders.o_custkey], [orders.o_orderkey], [orders.o_orderDATE], [orders.o_totalprice]), agg_func([T_FUN_COUNT(*)])
9 - output([orders.o_orderkey], [orders.o_custkey], [orders.o_orderDATE], [orders.o_totalprice]), filter(nil),
access([orders.o_orderkey], [orders.o_custkey], [orders.o_orderDATE], [orders.o_totalprice]), partitions(p0)
10 - output([VIEW2.customer.c_custkey], [VIEW2.customer.c_name], [VIEW2.T_FUN_COUNT(*)]), filter(nil),
access([VIEW2.customer.c_custkey], [VIEW2.customer.c_name], [VIEW2.T_FUN_COUNT(*)])
11 - output([customer.c_custkey], [customer.c_name], [T_FUN_COUNT(*)]), filter(nil),
group([customer.c_custkey], [customer.c_name]), agg_func([T_FUN_COUNT(*)])
12 - output([customer.c_custkey], [customer.c_name]), filter(nil),
access([customer.c_custkey], [customer.c_name]), partitions(p0)
1 row in set (0.022 sec)
小结
将本次测试结果与前文测试结果合并，得到下表，从表中可知在当前测试环境下，是否设定表组的前后查询速度并没有太大波动，时间基本保持一致。
| SQL | OceanBase | OB(合并后) | OB(Tablegroup) | MariaDB |
|---|---|---|---|---|
| SQL-1 | 10.285 sec | 9.108 sec | 8.960 sec | 13.61 sec |
| SQL-5 | 24.593 sec | 4.477 sec | 4.559 sec | 23 min 52.91 sec |
| SQL-6 | 3.386 sec | 2.557 sec | 2.536 sec | 2.69 sec |
| SQL-10 | 6.043 sec | 3.727 sec | 3.815 sec | 43.29 sec |
| SQL-17 | 3.800 sec | 2.901 sec | 2.893 sec | 6 min 25.23 sec |
| SQL-18 | 7.332 sec | 6.016 sec | 6.110 sec | 1 min 43.55 sec |
再次验证上文所述，表组的设计目的是为了解决跨 zone 带来网络延迟问题。
OceanBase 工具
在阅读 OceanBase 的代码时，发现源码中提供了两个工具，分别是 env_checker.py 和 dooba.py。
代码链接：https://github.com/oceanbase/oceanbase/blob/master/tools/scripts/
- env_checker.py
该脚本用来检查操作系统的环境信息，基于python2编写，并需要安装依赖 subprocess32。
$ ./env_checker.py
Traceback (most recent call last):
File "./env_checker.py", line 15, in <module>
from subprocess32 import Popen, PIPE
ImportError: No module named subprocess32
$ pip install subprocess32 --user
Collecting subprocess32
Downloading https://pypi.doubanio.com/packages/32/c8/564be4d12629b912ea431f1a50eb8b3b9d00f1a0b1ceff17f266be190007/subprocess32-3.5.4.tar.gz (97kB)
100% |################################| 102kB 1.3MB/s
Installing collected packages: subprocess32
Running setup.py install for subprocess32 ... done
Successfully installed subprocess32
You are using pip version 8.1.2, however version 22.0.4 is available.
You should consider upgrading via the 'pip install --upgrade pip' command.
执行示例如下：
$ ./env_checker.py
==================== os info ====================
release: 3.10.0-1127.19.1.el7.x86_64
sysname: Linux
machine: x86_64
==================== cpu info ===================
count: 8 cores
...
==================== mem info ===================
...
memory_total: 15 GB
==================== net info ===================
lo
IPv4 address: 127.0.0.1
IPv6 address: ::1
...
=================== disk info ===================
device: /dev/mapper/centos-root
mountpoint: /
usage
...
- dooba.py
dooba 是使用 Python 2 开发的监控 OB 的性能监控脚本，运行画面如下图。
从画面中，可实时监控到OB运行状态，可以切换不同租户，查看某个租户的 QPS，和相应 SQL 的平均延时（RT），以及内存使用、IOPS 等情况。
总结
OceanBase 数据库体系结构是复杂的，但设计的尽量简约，使人易于理解。
上面的两个小工具只是点到为止，实战中可以使用 OCP 工具，现也已经开源。
性能测试的话题涉猎面很广，本文也只是繁星一点，希望对本文读者和 OB 使用者有些许帮助或提示。
最后修改时间：2022-05-01 22:56:23
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