1. 安装Sysbench
$ yum install -y sysbench

2. 准备测试
$ sysbench /usr/share/sysbench/oltp_read_write.lua \
–mysql-host=192.168.1.100 \
–mysql-port=3306 \
–mysql-user=fgedu@fgedu_tenant \
–mysql-password=fgedu123 \
–mysql-db=fgedudb \
–tables=10 \
–table-size=100000 \
–threads=64 \
prepare

3. 执行测试
$ sysbench /usr/share/sysbench/oltp_read_write.lua \
–mysql-host=192.168.1.100 \
–mysql-port=3306 \
–mysql-user=fgedu@fgedu_tenant \
–mysql-password=fgedu123 \
–mysql-db=fgedudb \
–tables=10 \
–table-size=100000 \，更多视频教程www.fgedu.net.cn。
–threads=64 \
–time=300 \
–report-interval=10 \
run

4. 测试结果
SQL statistics:
queries performed:
read: 1540280
write: 440080
other: 220040
total: 2200400
transactions: 110020 (366.70 per sec.)
queries: 2200400 (7334.00 per sec.)
ignored errors: 0 (0.00 per sec.)
reconnects: 0 (0.00 per sec.)

General statistics:
total time: 300.0014s
total number of events: 110020

Latency (ms):
min: 5.21
avg: 174.52
max: 1234.56
95th percentile: 456.78
sum: 19199999.99

Threads fairness:
events (avg/stddev): 1719.0625/45.23
execution time (avg/stddev): 299.9999/0.01

5. 清理数据
$ sysbench /usr/share/sysbench/oltp_read_write.lua \
–mysql-host=192.168.1.100 \
–mysql-port=3306 \
–mysql-user=fgedu@fgedu_tenant \
–mysql-password=fgedu123 \
–mysql-db=fgedudb \
cleanup，更多学习教程公众号风哥教程itpux_com。

1. 下载TPCC工具
$ git clone https://github.com/Percona-Lab/tpcc-mysql.git
$ cd tpcc-mysql/src
$ make

2. 创建测试表
$ mysql -h192.168.1.100 -P3306 -ufgedu@fgedu_tenant -p \
-Dfgedudb < create_table.sql 3. 加载数据 $ ./tpcc_load -h192.168.1.100 -P3306 \ -ufgedu@fgedu_tenant -pfgedu123 \ -dfgedudb -w 10 4. 执行测试 $ ./tpcc_start -h192.168.1.100 -P3306 \ -ufgedu@fgedu_tenant -pfgedu123 \ -dfgedudb -w 10 -c 32 -r 10 -l 300 5. 测试结果 *************************************** *** ###easy### TPC-C Load Generator *** ***************************************，from DB视频:www.itpux.com。 option h with value '192.168.1.100' option P with value '3306' option d with value 'fgedudb' option u with value 'fgedu@fgedu_tenant' option p with value 'fgedu123' option w with value '10' option c with value '32' option r with value '10' option l with value '300' ... [Current] NEW_ORDER: 12500, PAYMENT: 12000, ORDER_STATUS: 1000, DELIVERY: 1000, STOCK_LEVEL: 1000 [Current] NEW_ORDER: 12600, PAYMENT: 12100, ORDER_STATUS: 1010, DELIVERY: 1010, STOCK_LEVEL: 1010 ...
[0] sc:126000 lt:0 rt:0 fl:0
[1] sc:120000 lt:0 rt:0 fl:0
[2] sc:12000 lt:0 rt:0 fl:0
[3] sc:12000 lt:0 rt:0 fl:0
[4] sc:12000 lt:0 rt:0 fl:0
in 300 sec.

[0] sc:126000 lt:0 rt:0 fl:0
[1] sc:120000 lt:0 rt:0 fl:0
[2] sc:12000 lt:0 rt:0 fl:0
[3] sc:12000 lt:0 rt:0 fl:0
[4] sc:12000 lt:0 rt:0 fl:0

(all must be [OK])
[transaction percentage]
Payment: 43.48% (>=43.0%) [OK]
Order-Status: 4.35% (>= 4.0%) [OK]
Delivery: 4.35% (>= 4.0%) [OK]
Stock-Level: 4.35% (>= 4.0%) [OK]
[response time (at least 90% passed)]
New-Order: 100.00% [OK]
Payment: 100.00% [OK]
Order-Status: 100.00% [OK]
Delivery: 100.00% [OK]
Stock-Level: 100.00% [OK]

25200.000 TpmC

1. 测试脚本
#!/bin/bash
# custom_benchmark.sh
# from:www.itpux.com.qq113257174.wx:itpux-com

# 配置
HOST=”192.168.1.100″
PORT=”3306″
USER=”fgedu@fgedu_tenant”
PASS=”fgedu123″
DB=”fgedudb”
THREADS=”64″
DURATION=”300″

# 测试函数
run_test() {
local test_name=$1
local sql=$2

echo “Running test: $test_name”

# 执行测试
for i in $(seq 1 $THREADS); do
(
for j in $(seq 1 1000); do
mysql -h$HOST -P$PORT -u$USER -p$PASS -D$DB -e “$sql” > /dev/null 2>&1
done
) &
done

wait
echo “Test completed: $test_name”
}

# 测试场景
run_test “Point Select” “SELECT * FROM fgedu_order WHERE order_id = FLOOR(RAND() * 1000000)”
run_test “Range Select” “SELECT * FROM fgedu_order WHERE create_time > DATE_SUB(NOW(), INTERVAL 1 DAY) LIMIT 100”
run_test “Insert” “INSERT INTO fgedu_order (user_id, amount) VALUES (FLOOR(RAND() * 1000000), ROUND(RAND() * 1000, 2))”
run_test “Update” “UPDATE fgedu_order SET status = 1 WHERE order_id = FLOOR(RAND() * 1000000)”

echo “All tests completed”

2. 结果分析
#!/bin/bash
# analyze_results.sh

# 收集性能数据
obclient -e ”
SELECT
‘TPS’ as metric,
COUNT(*) / 300 as value
FROM oceanbase.__all_virtual_sql_audit
WHERE request_time > DATE_SUB(NOW(), INTERVAL 5 MINUTE)
UNION ALL
SELECT
‘Avg Latency(ms)’ as metric,
AVG(elapsed_time) / 1000 as value
FROM oceanbase.__all_virtual_sql_audit
WHERE request_time > DATE_SUB(NOW(), INTERVAL 5 MINUTE)
UNION ALL
SELECT
‘P99 Latency(ms)’ as metric,
percentile_cont(0.99) WITHIN GROUP (ORDER BY elapsed_time) / 1000 as value
FROM oceanbase.__all_virtual_sql_audit
WHERE request_time > DATE_SUB(NOW(), INTERVAL 5 MINUTE);
”