Python实现Java mybatis-plus 产生的SQL自动化测试SQL速度和判断SQL是否走索引
Python实现Java mybatis-plus 产生的SQL自动化测试SQL速度和判断SQL是否走索引
文件目录如下
│ sql_speed_test.py
│
├─input
│ data-report_in_visit_20240704.log
│ resource_in_sso_20240704.log
│
└─output
data-report_in_visit_20240704.csv
resource_in_sso_20240704.csv
目前每次做实验都要将Java中的SQL做性能测试，否则就没法通过考核，属实难崩。
sql_speed_test.py是我用python写的程序，将从Java mybatis-plus控制台产生的日志复制到data-report_in_visit_20240704.log和resource_in_sso_20240704.log文件中，运行程序之后output文件夹会自动输出csv文件，下面为csv文件夹详情。
data-report_in_visit_20240704.log文件
-- 301 -- [2024-07-04 14:22:55.055] [org.apache.ibatis.logging.jdbc.BaseJdbcLogger] [http-nio-9006-exec-2] [143] [DEBUG] [traceId:] ==>
SELECT resource_id AS resource_id, resource_type AS resource_type, sum(IFNULL(internal_pv, pv)) AS internal_pv, sum(IFNULL(google_pv, pv)) AS google_pv, sum(IFNULL(other_pv, pv)) AS other_pv, sum(IFNULL(pv, 0)) AS pv FROM t_bw_article_daily_statistic where resource_type = 9 GROUP BY resource_id, resource_type order by resource_id, resource_type
-- 302 -- [2024-07-04 14:22:55.055] [org.apache.ibatis.logging.jdbc.BaseJdbcLogger] [http-nio-9006-exec-2] [143] [DEBUG] [traceId:] ==>
SELECT resource_id AS resource_id, resource_type AS resource_type, sum(IFNULL(internal_pv, pv)) AS internal_pv, sum(IFNULL(google_pv, pv)) AS google_pv, sum(IFNULL(other_pv, pv)) AS other_pv, sum(IFNULL(pv, 0)) AS pv FROM t_bw_article_daily_statistic_202406 where resource_type = 9 GROUP BY resource_id, resource_type order by resource_id, resource_type
data-report_in_visit_20240704.csv文件
| 序号 | SQL功能描述 | SQL | 预估业务数据量 | 实际测试数据量 | 执行时间 | 执行结果 | 索引是否生效 | 所属项目 | 所在库 |
|---|---|---|---|---|---|---|---|---|---|
| 1 | SELECT resource_id AS resource_id, resource_type AS resource_type, sum(IFNULL(internal_pv, pv)) AS internal_pv, sum(IFNULL(google_pv, pv)) AS google_pv, sum(IFNULL(other_pv, pv)) AS other_pv, sum(IFNULL(pv, 0)) AS pv FROM t_bw_article_daily_statistic where resource_type = 9 GROUP BY resource_id, resource_type order by resource_id, resource_type | t_bw_article_daily_statistic | t_bw_article_daily_statistic:5741行 | 0.419603 秒 | 462 | 是 | data-report | visit | |
| 2 | SELECT resource_id AS resource_id, resource_type AS resource_type, sum(IFNULL(internal_pv, pv)) AS internal_pv, sum(IFNULL(google_pv, pv)) AS google_pv, sum(IFNULL(other_pv, pv)) AS other_pv, sum(IFNULL(pv, 0)) AS pv FROM t_bw_article_daily_statistic_202406 where resource_type = 9 GROUP BY resource_id, resource_type order by resource_id, resource_type | t_bw_article_daily_statistic_202406 | t_bw_article_daily_statistic_202406:296358行 | 0.291532 秒 | 2691 | 是 | data-report | visit |
sql_speed_test.py文件
import os
import csv
import re
from pymysql import *
import time
"""
开发一个用于SQL性能测试的工具，避免一直做重复工作
将Java中的每一条SQL采用mybatis-plus-plugin插件抓出来转存至log文件中
抓住每条SQL做测试
"""
def extract_query_sql_table_names(sql):
# 正则表达式模式
pattern = re.compile(
r"\b(?:FROM|JOIN|INTO|UPDATE|TABLE|INTO)\s+([`\"\[\]]?[a-zA-Z_][\w$]*[`\"\[\]]?)",
re.IGNORECASE
)
# 查找所有匹配的表名
matches = pattern.findall(sql)
# 去掉引号和方括号
tables = [re.sub(r'[`"\[\]]', '', match) for match in matches]
filter_tables = []
for table in tables:
if "t_bw" in table:
filter_tables.append(table)
return filter_tables
def check_index_usage(connection, sql):
if not sql.startswith("select") and not sql.startswith("SELECT"):
return False
try:
with connection.cursor() as cursor:
# 使用 EXPLAIN 来获取查询计划
explain_sql = f"EXPLAIN {sql}"
cursor.execute(explain_sql)
explain_result = cursor.fetchall()
# 打印 EXPLAIN 结果
print("EXPLAIN 结果:")
for row in explain_result:
print(row)
# 检查每行是否使用了索引
for row in explain_result:
if row[5] is not None:
print(f"SQL 使用了索引: {row[5]}")
return True
print("SQL 未使用索引")
return False
finally:
pass
# connection.close()
def count_rows(connection, table_name):
try:
with connection.cursor() as cursor:
# 构建 SQL 语句
sql = f"SELECT COUNT(*) FROM {table_name}"
# 执行 SQL 语句
cursor.execute(sql)
# 获取结果
result = cursor.fetchone()
# 返回结果
return result[0]
except Exception as e:
print(e)
finally:
# connection.close()
pass
class SqlSpeedTest:
def __init__(self):
self.input_dir = "./input"
self.output_dir = "./output"
self.databases = {
"sso": {
"ip": "xxxxxx",
"database": "sso",
"username": "xxxx",
"password": "xxxx"
}
}
def get_all_input_files(self):
files = os.listdir(r'./input')
# file_paths = []
# for file in files:
# file_paths.append(self.input_dir + "/" + file)
return files
def handle_sql_log(self, project, database, lines):
sql_lines = []
row_count = 1
database_info = self.databases.get(database)
conn = connect(host=database_info.get("ip"),
port=3306,
user=database_info.get("username"),
password=database_info.get("password"),
database=database_info.get("database"),
charset='utf8mb4')
for index, line in enumerate(lines):
if line.startswith("--"):
continue
current_sql = line.replace("\n", "")
execute_info = self.execute_sql_and_get_execute_time(conn, database, current_sql)
tables = extract_query_sql_table_names(current_sql)
real_rows = ""
for table in tables:
total_rows = count_rows(conn, table)
real_rows += f"{table}:{total_rows}行 "
sql_line = {
"row_count": row_count,
"sql_description": "",
"sql": current_sql,
"expect_rows": ",".join(tables),
"real_rows": real_rows,
"execute_time": execute_info["execute_time"],
"execute_rows": execute_info["execute_rows"],
"index_has_work": execute_info["index_has_work"],
"project": project,
"project": project,
"database": database
}
sql_lines.append(sql_line)
row_count += 1
conn.close()
return sql_lines
def execute_sql_and_get_execute_time(self, conn, database, sql):
print(f"==================> {database}库正在执行SQL: {sql}")
# 记录开始时间
try:
cs = conn.cursor() # 获取光标
start_time = time.time()
cs.execute(sql)
rows = cs.fetchall()
# 记录结束时间
end_time = time.time()
# 计算执行时间
execution_time = end_time - start_time
conn.commit()
print(f"======>{database}库共花费{execution_time:.6f}秒执行完毕,{sql}")
except Exception as e:
print(e)
return {"execute_rows": "", "execute_time": "", "index_has_work": ""}
index_has_work = check_index_usage(conn, sql)
return {"execute_rows": len(rows), "execute_time": f"{execution_time:.6f} 秒",
"index_has_work": "是" if index_has_work else "否"}
def handle_log_file(self, filename):
with open(self.input_dir + "/" + filename, "r", encoding="utf-8") as file:
lines = file.readlines()
pre_filename = filename.split(".")[0]
with open(self.output_dir + "/" + pre_filename + ".csv", "w", newline='', encoding='utf-8-sig') as f:
writer = csv.writer(f, quoting=csv.QUOTE_MINIMAL)
csv_title = ["序号", "SQL功能描述", "SQL", "预估业务数据量", "实际测试数据量", "执行时间", "执行结果",
"索引是否生效", "所属项目", "所在库"]
writer.writerow(csv_title)
info = pre_filename.split("_in_")
project_name = info[0]
database_name = info[1].split("_")[0]
sql_lines = self.handle_sql_log(project_name, database_name, lines)
for sql_line in sql_lines:
write_line = [sql_line["row_count"],
sql_line["sql_description"],
sql_line["sql"],
sql_line["expect_rows"],
sql_line["real_rows"],
sql_line["execute_time"],
sql_line["execute_rows"],
sql_line["index_has_work"],
sql_line["project"],
sql_line["database"]]
writer.writerow(write_line)
def do_work(self):
files = self.get_all_input_files()
for file in files:
self.handle_log_file(file)
if __name__ == '__main__':
sql_speed_test = SqlSpeedTest()
sql_speed_test.do_work()
写在最后
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原文地址：https://blog.csdn.net/weixin_46294086/article/details/140647601
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