openEuler安装BenchmarkSQL

发布于:2025-06-19 ⋅ 阅读:(17) ⋅ 点赞:(0)

BenchmarkSQL是一个用于评估数据库性能的开源工具。它模拟TPC-C(Transaction Processing Performance Council)基准测试场景,该场景主要用于衡量数据库在处理大量并发事务时的能力。TPC-C测试场景模拟了一个典型的批发分销商的业务环境,包括新订单、支付、库存查询等操作。

openEuler版本:openEuler 22.03 (LTS-SP4)

安装依赖:

JDK,ANT,R语言

其中安装JDK不在此说明,网上很多教程

安装ANT步骤如下:

将ANT安装包上传至服务器,然后解压:

#tar -xvzf apache-ant-1.10.15-bin.tar.gz

设置环境变量:

编辑/etc/profile文件追以下内容:

export ANT_HOME=/opt/software/ant/apache-ant-1.10.15
export PATH=$PATH:$ANT_HOME/bin

执行:

#source /etc/profile

使环境变量设置生效

验证安装结果:

#ant -version

R语言安装步骤如下:

1.上传压缩包(R-4.4.2.tar.gz)到服务器

2.解压R-4.4.2.tar.gz:

#tar -xvf R-4.4.2.tar.gz

3.进入解压目录,进行编译安装(时间有点长,请耐心等待):

#./configure && make && make install

4.验证安装结果:

 #R --version

安装编译R语言过程中可能会出现下面3个错误:

报错1:configure: error: --with-x=yes (default) and X11 headers/libs are not available

解决方法:yum -y install xorg-x11-server-devel libX11-devel libXt-devel

报错2:configure: error: "liblzma library and headers are required"

解决方法:yum install xz-devel.x86_64

报错3:configure: error: libcurl >= 7.28.0 library and headers are required with support for https

解决方法:yum install libcurl-devel

安装 BenchmarkSQL:

创建数据库和用户

create user benchmarksql with password 'Benchmark123';

create database benchmarksql owner benchmarksql;

给用户授予权限:有建表权限,创建索引权限等等,为了方便修改用户为管理员

alter user benchmarksql with SYSADMIN;

解压benchmarksql

上传benchmark压缩包到服务器,然后解压:

#unzip benchmarksql-5.0.zip

编译benchmarksql

进入benchmark解压目录:

执行命令:

#ant

创建配置文件

进入run目录

#cd run

#cp props.pg my_postgres.properties

修改配置文件

#vi my_postgres.properties

修改内容:

db=postgres

driver=org.postgresql.Driver

conn=jdbc:postgresql://localhost:15000/benchmarksql

user=benchmarksql

password=Benchmark123

osCollectorDevices=net_ens33 blk_sda

  • 配置文件详解:
    • db=postgres //数据库类型,postgres,mysql
    • driver=org.postgresql.Driver //驱动,mysql8.0以上为com.mysql.cj.jdbc.Driver
    • conn=jdbc:postgresql://localhost:5432/postgres //PG数据库连接字符串,正常情况下,需要更改localhost为对应PG服务IP、5432位对应PG服务端口、postgres为对应测试数据库名
    • user=benchmarksql //数据库用户名,通常建议用默认,这就需要我们提前在数据库中建立benchmarksql用户
    • password=PWbmsql //如上用户密码
    • warehouses=1 //仓库数量,数量根据实际服务器内存配置,每个仓库 约 100MB,代表一个独立业务单元(TPC-C 标准)
    • loadWorkers=4 //用于在数据库中初始化数据的加载进程数量,默认为4,实际使用过程中可以根据实际情况调整,加载速度会随worker数量的增加而有所提升
    • terminals=1 //终端数,即并发客户端数量,通常设置为CPU线程总数的2~6倍
    • runTxnsPerTerminal=10 //每个终端(terminal)运行的固定事务数量,例如:如果该值设置为10,意味着每个terminal运行10个事务,如果有32个终端,那整体运行320个事务后,测试结束。该参数配置为非0值时,下面的runMins参数必须设置为0
    • runMins=0 //要测试的整体时间,单位为分钟,如果runMins设置为60,那么测试持续1小时候结束。该值设置为非0值时,runTxnsPerTerminal参数必须设置为0。这两个参数不能同时设置为正整数,如果设置其中一个,另一个必须为0,主要区别是runMins定义时间长度来控制测试时间;runTxnsPerTerminal定义事务总数来控制时间。
    • limitTxnsPerMin=300 //每分钟事务总数限制,该参数主要控制每分钟处理的事务数,事务数受terminals参数的影响,如果terminals数量大于limitTxnsPerMin值,意味着并发数大于每分钟事务总数,该参数会失效,想想也是如此,如果有1000个并发同时发起,那每分钟事务数设置为300就没意义了,上来就是1000个并发,所以要让该参数有效,可以设置数量大于并发数,或者让其失效,测试过程中目前采用的是默认300。
    • terminalWarehouseFixed=true //终端和仓库的绑定模式,设置为true时可以运行4.x兼容模式,意思为每个终端都有一个固定的仓库。设置为false时可以均匀的使用数据库整体配置。TPCC规定每个终端都必须有一个绑定的仓库,所以一般使用默认值true。
    • //下面五个值的总和必须等于100,默认值为:45, 43, 4, 4 & 4 ,与TPC-C测试定义的比例一致,实际操作过程中,可以调整比重来适应各种场景。
      newOrderWeight=45
      paymentWeight=43
      orderStatusWeight=4
      deliveryWeight=4
      stockLevelWeight=4
    • resultDirectory=my_result_%tY-%tm-%td_%tH%tM%tS //测试数据生成目录,默认无需修改,默认生成在run目录下面,名字形如my_result_xxxx的文件夹。
    • osCollectorScript=./misc/os_collector_linux.py //操作系统性能收集脚本,默认无需修改,需要操作系统具备有python环境
    • osCollectorInterval=1 //操作系统收集操作间隔,默认为1秒
    • //osCollectorSSHAddr=user@dbhost //操作系统收集所对应的主机,如果对本机数据库进行测试,该参数保持注销即可,如果要对远程服务器进行测试,请填写用户名和主机名。
    • osCollectorDevices=net_ens33 blk_sda //操作系统中被收集服务器的网卡名称和磁盘名称,例如:使用ifconfig查看操作系统网卡名称,找到测试所走的网卡,名称为ens33,那么下面网卡名设置为net_ens33(net_前缀固定);使用df -h查看数据库数据目录,名称为(/dev/sdb 33T 18T 16T 54% /hgdata),那么下面磁盘名设置为blk_sdb(blk_前缀固定)

创建数据库模式和加载初始数据

在run目录下执行:

./runDatabaseBuild.sh my_postgres.properties

执行成功后输出信息:

[omm@hostName1 run]$ ./runDatabaseBuild.sh my_postgres.properties
# ------------------------------------------------------------
# Loading SQL file ./sql.common/tableCreates.sql
# ------------------------------------------------------------
create table bmsql_config (
cfg_name    varchar(30) primary key,
cfg_value   varchar(50)
);
create table bmsql_warehouse (
w_id        integer   not null,
w_ytd       decimal(12,2),
w_tax       decimal(4,4),
w_name      varchar(10),
w_street_1  varchar(20),
w_street_2  varchar(20),
w_city      varchar(20),
w_state     char(2),
w_zip       char(9)
);
create table bmsql_district (
d_w_id       integer       not null,
d_id         integer       not null,
d_ytd        decimal(12,2),
d_tax        decimal(4,4),
d_next_o_id  integer,
d_name       varchar(10),
d_street_1   varchar(20),
d_street_2   varchar(20),
d_city       varchar(20),
d_state      char(2),
d_zip        char(9)
);
create table bmsql_customer (
c_w_id         integer        not null,
c_d_id         integer        not null,
c_id           integer        not null,
c_discount     decimal(4,4),
c_credit       char(2),
c_last         varchar(16),
c_first        varchar(16),
c_credit_lim   decimal(12,2),
c_balance      decimal(12,2),
c_ytd_payment  decimal(12,2),
c_payment_cnt  integer,
c_delivery_cnt integer,
c_street_1     varchar(20),
c_street_2     varchar(20),
c_city         varchar(20),
c_state        char(2),
c_zip          char(9),
c_phone        char(16),
c_since        timestamp,
c_middle       char(2),
c_data         varchar(500)
);
create sequence bmsql_hist_id_seq;
create table bmsql_history (
hist_id  integer,
h_c_id   integer,
h_c_d_id integer,
h_c_w_id integer,
h_d_id   integer,
h_w_id   integer,
h_date   timestamp,
h_amount decimal(6,2),
h_data   varchar(24)
);
create table bmsql_new_order (
no_w_id  integer   not null,
no_d_id  integer   not null,
no_o_id  integer   not null
);
create table bmsql_oorder (
o_w_id       integer      not null,
o_d_id       integer      not null,
o_id         integer      not null,
o_c_id       integer,
o_carrier_id integer,
o_ol_cnt     integer,
o_all_local  integer,
o_entry_d    timestamp
);
create table bmsql_order_line (
ol_w_id         integer   not null,
ol_d_id         integer   not null,
ol_o_id         integer   not null,
ol_number       integer   not null,
ol_i_id         integer   not null,
ol_delivery_d   timestamp,
ol_amount       decimal(6,2),
ol_supply_w_id  integer,
ol_quantity     integer,
ol_dist_info    char(24)
);
create table bmsql_item (
i_id     integer      not null,
i_name   varchar(24),
i_price  decimal(5,2),
i_data   varchar(50),
i_im_id  integer
);
create table bmsql_stock (
s_w_id       integer       not null,
s_i_id       integer       not null,
s_quantity   integer,
s_ytd        integer,
s_order_cnt  integer,
s_remote_cnt integer,
s_data       varchar(50),
s_dist_01    char(24),
s_dist_02    char(24),
s_dist_03    char(24),
s_dist_04    char(24),
s_dist_05    char(24),
s_dist_06    char(24),
s_dist_07    char(24),
s_dist_08    char(24),
s_dist_09    char(24),
s_dist_10    char(24)
);
Starting BenchmarkSQL LoadData

driver=org.postgresql.Driver
conn=jdbc:postgresql://localhost:15000/benchmarksql
user=benchmarksql
password=***********
warehouses=10
loadWorkers=4
fileLocation (not defined)
csvNullValue (not defined - using default 'NULL')

Worker 000: Loading ITEM
Worker 001: Loading Warehouse      1
Worker 002: Loading Warehouse      2
Worker 003: Loading Warehouse      3
Worker 000: Loading ITEM done
Worker 000: Loading Warehouse      4
Worker 002: Loading Warehouse      2 done
Worker 002: Loading Warehouse      5
Worker 001: Loading Warehouse      1 done
Worker 001: Loading Warehouse      6
Worker 003: Loading Warehouse      3 done
Worker 003: Loading Warehouse      7
Worker 000: Loading Warehouse      4 done
Worker 000: Loading Warehouse      8
Worker 002: Loading Warehouse      5 done
Worker 002: Loading Warehouse      9
Worker 001: Loading Warehouse      6 done
Worker 001: Loading Warehouse     10
Worker 003: Loading Warehouse      7 done
Worker 000: Loading Warehouse      8 done
Worker 002: Loading Warehouse      9 done
Worker 001: Loading Warehouse     10 done
# ------------------------------------------------------------
# Loading SQL file ./sql.common/indexCreates.sql
# ------------------------------------------------------------
alter table bmsql_warehouse add constraint bmsql_warehouse_pkey
primary key (w_id);
alter table bmsql_district add constraint bmsql_district_pkey
primary key (d_w_id, d_id);
alter table bmsql_customer add constraint bmsql_customer_pkey
primary key (c_w_id, c_d_id, c_id);
create index bmsql_customer_idx1
on  bmsql_customer (c_w_id, c_d_id, c_last, c_first);
alter table bmsql_oorder add constraint bmsql_oorder_pkey
primary key (o_w_id, o_d_id, o_id);
create unique index bmsql_oorder_idx1
on  bmsql_oorder (o_w_id, o_d_id, o_carrier_id, o_id);
alter table bmsql_new_order add constraint bmsql_new_order_pkey
primary key (no_w_id, no_d_id, no_o_id);
alter table bmsql_order_line add constraint bmsql_order_line_pkey
primary key (ol_w_id, ol_d_id, ol_o_id, ol_number);
alter table bmsql_stock add constraint bmsql_stock_pkey
primary key (s_w_id, s_i_id);
alter table bmsql_item add constraint bmsql_item_pkey
primary key (i_id);
# ------------------------------------------------------------
# Loading SQL file ./sql.common/foreignKeys.sql
# ------------------------------------------------------------
alter table bmsql_district add constraint d_warehouse_fkey
foreign key (d_w_id)
references bmsql_warehouse (w_id);
alter table bmsql_customer add constraint c_district_fkey
foreign key (c_w_id, c_d_id)
references bmsql_district (d_w_id, d_id);
alter table bmsql_history add constraint h_customer_fkey
foreign key (h_c_w_id, h_c_d_id, h_c_id)
references bmsql_customer (c_w_id, c_d_id, c_id);
alter table bmsql_history add constraint h_district_fkey
foreign key (h_w_id, h_d_id)
references bmsql_district (d_w_id, d_id);
alter table bmsql_new_order add constraint no_order_fkey
foreign key (no_w_id, no_d_id, no_o_id)
references bmsql_oorder (o_w_id, o_d_id, o_id);
alter table bmsql_oorder add constraint o_customer_fkey
foreign key (o_w_id, o_d_id, o_c_id)
references bmsql_customer (c_w_id, c_d_id, c_id);
alter table bmsql_order_line add constraint ol_order_fkey
foreign key (ol_w_id, ol_d_id, ol_o_id)
references bmsql_oorder (o_w_id, o_d_id, o_id);
alter table bmsql_order_line add constraint ol_stock_fkey
foreign key (ol_supply_w_id, ol_i_id)
references bmsql_stock (s_w_id, s_i_id);
alter table bmsql_stock add constraint s_warehouse_fkey
foreign key (s_w_id)
references bmsql_warehouse (w_id);
alter table bmsql_stock add constraint s_item_fkey
foreign key (s_i_id)
references bmsql_item (i_id);
# ------------------------------------------------------------
# Loading SQL file ./sql.postgres/extraHistID.sql
# ------------------------------------------------------------
-- ----
-- Extra Schema objects/definitions for history.hist_id in PostgreSQL
-- ----
-- ----
--      This is an extra column not present in the TPC-C
--      specs. It is useful for replication systems like
--      Bucardo and Slony-I, which like to have a primary
--      key on a table. It is an auto-increment or serial
--      column type. The definition below is compatible
--      with Oracle 11g, using a sequence and a trigger.
-- ----
-- Adjust the sequence above the current max(hist_id)
select setval('bmsql_hist_id_seq', (select max(hist_id) from bmsql_history));
-- Make nextval(seq) the default value of the hist_id column.
alter table bmsql_history
alter column hist_id set default nextval('bmsql_hist_id_seq');
-- Add a primary key history(hist_id)
alter table bmsql_history add primary key (hist_id);
# ------------------------------------------------------------
# Loading SQL file ./sql.postgres/buildFinish.sql
# ------------------------------------------------------------
-- ----
-- Extra commands to run after the tables are created, loaded,
-- indexes built and extra's created.
-- PostgreSQL version.
-- ----
vacuum analyze;

 创建的表和初始化的数据量

运行基准测试

在run目录下执行:

./runBenchmark.sh my_postgres.properties

执行成功后输出信息:

19:27:06,712 [main] INFO   jTPCC : Term-00, 
19:27:06,715 [main] INFO   jTPCC : Term-00, +-------------------------------------------------------------+
19:27:06,715 [main] INFO   jTPCC : Term-00,      BenchmarkSQL v5.0
19:27:06,715 [main] INFO   jTPCC : Term-00, +-------------------------------------------------------------+
19:27:06,716 [main] INFO   jTPCC : Term-00,  (c) 2003, Raul Barbosa
19:27:06,716 [main] INFO   jTPCC : Term-00,  (c) 2004-2016, Denis Lussier
19:27:06,718 [main] INFO   jTPCC : Term-00,  (c) 2016, Jan Wieck
19:27:06,718 [main] INFO   jTPCC : Term-00, +-------------------------------------------------------------+
19:27:06,718 [main] INFO   jTPCC : Term-00, 
19:27:06,719 [main] INFO   jTPCC : Term-00, db=postgres
19:27:06,719 [main] INFO   jTPCC : Term-00, driver=org.postgresql.Driver
19:27:06,719 [main] INFO   jTPCC : Term-00, conn=jdbc:postgresql://localhost:17700/benchmarksql
19:27:06,719 [main] INFO   jTPCC : Term-00, user=benchmarksql
19:27:06,719 [main] INFO   jTPCC : Term-00, 
19:27:06,719 [main] INFO   jTPCC : Term-00, warehouses=1
19:27:06,719 [main] INFO   jTPCC : Term-00, terminals=1
19:27:06,723 [main] INFO   jTPCC : Term-00, runTxnsPerTerminal=10
19:27:06,723 [main] INFO   jTPCC : Term-00, limitTxnsPerMin=300
19:27:06,723 [main] INFO   jTPCC : Term-00, terminalWarehouseFixed=true
19:27:06,724 [main] INFO   jTPCC : Term-00, 
19:27:06,724 [main] INFO   jTPCC : Term-00, newOrderWeight=45
19:27:06,724 [main] INFO   jTPCC : Term-00, paymentWeight=43
19:27:06,724 [main] INFO   jTPCC : Term-00, orderStatusWeight=4
19:27:06,724 [main] INFO   jTPCC : Term-00, deliveryWeight=4
19:27:06,724 [main] INFO   jTPCC : Term-00, stockLevelWeight=4
19:27:06,724 [main] INFO   jTPCC : Term-00, 
19:27:06,725 [main] INFO   jTPCC : Term-00, resultDirectory=my_result_%tY-%tm-%td_%tH%tM%tS
19:27:06,725 [main] INFO   jTPCC : Term-00, osCollectorScript=./misc/os_collector_linux.py
19:27:06,725 [main] INFO   jTPCC : Term-00, 
19:27:06,742 [main] INFO   jTPCC : Term-00, copied my_postgres.properties to my_result_2025-01-04_192706/run.properties
19:27:06,743 [main] INFO   jTPCC : Term-00, created my_result_2025-01-04_192706/data/runInfo.csv for runID 2
19:27:06,743 [main] INFO   jTPCC : Term-00, writing per transaction results to my_result_2025-01-04_192706/data/result.csv
19:27:06,744 [main] INFO   jTPCC : Term-00, osCollectorScript=./misc/os_collector_linux.py
19:27:06,744 [main] INFO   jTPCC : Term-00, osCollectorInterval=1
19:27:06,744 [main] INFO   jTPCC : Term-00, osCollectorSSHAddr=null
19:27:06,744 [main] INFO   jTPCC : Term-00, osCollectorDevices=net_ens33 blk_sda
19:27:06,819 [main] INFO   jTPCC : Term-00,
19:27:06,915 [main] INFO   jTPCC : Term-00, C value for C_LAST during load: 246
19:27:06,915 [main] INFO   jTPCC : Term-00, C value for C_LAST this run:    143
19:27:06,916 [main] INFO   jTPCC : Term-00,                                                                                         Te19:27:08,952 [Thread-1] INFO   jTPCC : Term-00, nt tpmTOTAL: 84    Memory Usage: 18MB / 234MB             
19:27:08,953 [Thread-1] INFO   jTPCC : Term-00, 
19:27:08,953 [Thread-1] INFO   jTPCC : Term-00, Measured tpmC (NewOrders) = 89.1
19:27:08,953 [Thread-1] INFO   jTPCC : Term-00, Measured tpmTOTAL = 326.73
19:27:08,953 [Thread-1] INFO   jTPCC : Term-00, Session Start     = 2025-01-04 19:27:06
19:27:08,953 [Thread-1] INFO   jTPCC : Term-00, Session End       = 2025-01-04 19:27:08
19:27:08,953 [Thread-1] INFO   jTPCC : Term-00, Transaction Count = 10

测试结束后,run目录下会生成一个新目录,它的命名格式为 my_result_%tY-%tm-%td_%tH%tM%tS。

使用 generateReport.sh my_result_* 脚本创建具有图形的 HTML 文件:

例如:

#./generateReport.sh my_result_2025-05-30_133047

使用generateReport.sh,需要安装R语言

生成的报告怎么看:

1)整体性能:

Overall tpmC: 124.67

Overall tpmTotal: 280.67

tpmC 是核心事务(NEW_ORDER)每分钟处理的事务数。

tpmTotal 是所有类型的事务(包括NEW_ORDER、Payment、Order Status、Delivery和Stock Level)每分钟的总事务数。

这里的tpmC为124.67,意味着每分钟大约处理124.67个NEW_ORDER事务,这是TPC-C基准测试中最为关键的性能指标。

2理论最大值:

理论最大值:12.86 NEW_ORDER 事务/分钟/仓库

TPC-C规范指出,在理想的条件下,每个仓库的NEW_ORDER事务理论最大值为12.86。要达到这个最大值,需要:

完美的负载分配(45%的事务是NEW_ORDER)。

系统在零响应时间下运行。

实际上,由于系统的延迟和负载不平衡,很难达到这个理论最大值。

3)实际性能 vs 理论性能:

124.67 tpmC 是理论最大值的 969.414%

这意味着系统的实际性能是理论最大值的约9.7倍。也就是说,相较于理想状态,当前的系统性能远超预期,表明该数据库配置在特定负载下的表现非常好。考虑到系统的实际响应时间和负载,这种超出理论最大值的表现通常表明系统在某些方面(如硬件配置、数据库优化、并行处理等)非常高效。

4)生成的两张图:

 

每分钟事务数量。

 

事务延迟。

TPCC表结构

 TPC-C测试系统数据库由9张表组成,它们的关系如下图所示,表框里的数字表示该表将要存放多少条记录,仓库数W的调整在测试中能够体现数据库所能够支持的数据规模的能力:

 

    Warehouse(仓库表,W表示仓数,能够体现数据库所能够支持的数据规模)
    District(区域表,W*10表每个仓为10个销售点供货)
    Customer(用户表,W*30k表示每个供货点为3000个客户提供服务)
    Stock(库存表,W*100k表示每个仓库维护10w种商品库存记录)
    Order(订单表)
    New-Order(新订单表)
    Item(商品表,表固定大小为10w)
    Order-Line(订单行)
    History(历史表)

TPCC事务模型

TPC-C需要处理的交易事务主要为以下几种:

新订单(New-Order,占比45%) :客户输入一笔新的订货交易;
支付操作(Payment,占比43%) :更新客户帐户余额以反映其支付状况;
发货(Delivery,占比4%) :发货(模拟批处理交易);
订单状态查询(Order-Status,占比4%) :查询客户最近交易的状态;
库存状态查询(Stock-Level,占比4%) :查询仓库库存状况,以便能够及时补货。

 

核心指标解读


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