592 lines
29 KiB
Python
592 lines
29 KiB
Python
from sqlalchemy.orm import Session
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from sqlalchemy import text, inspect
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from typing import List, Optional, Dict, Any
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from ..models.level_data import LevelData
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from .base import BaseService
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from ..models.settlement_data import SettlementData
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from ..models.checkpoint import Checkpoint
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from ..models.section_data import SectionData
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from ..models.account import Account
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from ..core.database import engine
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import logging
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import os
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from datetime import datetime
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logger = logging.getLogger(__name__)
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class LevelDataService(BaseService[LevelData]):
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def __init__(self):
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super().__init__(LevelData)
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def get_by_nyid(self, db: Session, nyid: str) -> List[LevelData]:
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"""根据期数ID获取水准数据"""
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return self.get_by_field(db, "NYID", nyid)
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def get_by_nyids(self, db: Session, nyids: List[str]) -> List[LevelData]:
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"""根据多个期数ID获取水准数据"""
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return db.query(LevelData).filter(LevelData.NYID.in_(nyids)).all()
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def get_by_linecode(self, db: Session, linecode: str) -> List[LevelData]:
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"""根据水准线路编码获取水准数据"""
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return self.get_by_field(db, "linecode", linecode)
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def get_last_by_linecode(self, db: Session, linecode: str) -> Optional[LevelData]:
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"""根据水准线路编码获取最新的水准数据（按NYID降序）"""
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return db.query(LevelData).filter(
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LevelData.linecode == linecode
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).order_by(LevelData.NYID.desc()).first()
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def search_level_data(self, db: Session,
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id: Optional[str] = None,
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linecode: Optional[str] = None,
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nyid: Optional[str] = None,
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benchmarkids: Optional[str] = None) -> List[LevelData]:
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"""根据多个条件搜索水准数据"""
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conditions = {}
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if linecode is not None:
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conditions["linecode"] = linecode
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if nyid is not None:
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conditions["NYID"] = nyid
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if benchmarkids is not None:
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conditions["benchmarkids"] = benchmarkids
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if id is not None:
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conditions["id"] = id
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return self.search_by_conditions(db, conditions)
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def get_by_nyid_and_linecode(self, db: Session, nyid: str, linecode: str = None) -> Optional[LevelData]:
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"""根据期数ID和线路编码获取水准数据"""
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return db.query(LevelData).filter(
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LevelData.NYID == nyid if nyid else True,
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LevelData.linecode == linecode if linecode else True
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).first()
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def _check_settlement_exists(self, db: Session, nyid: str) -> bool:
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"""检查期数id沉降数据是否存在"""
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settlement = db.query(SettlementData).filter(SettlementData.NYID == nyid).first()
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return settlement is not None
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def batch_import_level_data(self, db: Session, data: List) -> Dict[str, Any]:
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"""
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批量导入水准数据 - 性能优化版
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使用批量查询和批量操作，大幅提升导入速度
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1.根据期数ID和线路编码判断是否重复，跳过重复数据，不进行更新
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2.判断沉降数据是否存在，不存在则记录并跳过插入操作
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支持事务回滚，失败时重试一次
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"""
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import logging
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logger = logging.getLogger(__name__)
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total_count = len(data)
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success_count = 0
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failed_count = 0
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failed_items = []
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if total_count == 0:
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return {
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'success': False,
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'message': '导入数据不能为空',
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'total_count': 0,
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'success_count': 0,
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'failed_count': 0,
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'failed_items': []
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}
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for attempt in range(2): # 最多重试1次
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try:
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db.begin()
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success_count = 0
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failed_count = 0
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failed_items = []
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# ===== 性能优化1：批量查询沉降数据（IN查询） =====
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nyid_list = list(set(str(item.get('NYID')) for item in data if item.get('NYID')))
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logger.info(f"Checking {len(nyid_list)} unique NYIDs in settlement data")
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settlements = db.query(SettlementData).filter(SettlementData.NYID.in_(nyid_list)).all()
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settlement_map = {s.NYID: s for s in settlements}
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missing_nyids = set(nyid_list) - set(settlement_map.keys())
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# 记录缺失的NYID
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for item_data in data:
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nyid = str(item_data.get('NYID')) # 统一转换为字符串
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if nyid in missing_nyids:
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failed_count += 1
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failed_items.append({
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'data': item_data,
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'error': '期数ID在沉降表中不存在，跳过插入操作'
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})
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# 如果所有数据都失败，直接返回
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if failed_count == total_count:
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db.rollback()
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return {
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'success': False,
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'message': '所有期数ID在沉降表中都不存在',
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'total_count': total_count,
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'success_count': 0,
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'failed_count': total_count,
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'failed_items': failed_items
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}
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# ===== 性能优化2：批量查询现有水准数据（IN查询） =====
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# 只查询有效的NYID数据
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valid_items = [item for item in data if str(item.get('NYID')) not in missing_nyids]
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if valid_items:
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# 构建 (NYID, linecode) 组合键来查找重复数据
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existing_data = db.query(LevelData).filter(
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LevelData.NYID.in_(nyid_list)
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).all()
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# 使用组合键创建查找表：key = f"{NYID}_{linecode}"
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existing_map = {
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f"{item.NYID}_{item.linecode}": item
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for item in existing_data
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}
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logger.info(f"Found {len(existing_data)} existing level records")
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# ===== 性能优化3：批量处理插入和跳过 =====
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to_insert = []
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for item_data in valid_items:
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nyid = str(item_data.get('NYID')) # 统一转换为字符串
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linecode = item_data.get('linecode')
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# 构建组合键
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key = f"{nyid}_{linecode}"
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if key in existing_map:
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# 数据已存在，跳过
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logger.info(f"Continue level data: {nyid}-{linecode}")
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failed_count += 1
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failed_items.append({
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'data': item_data,
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'error': '数据已存在，跳过插入操作'
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})
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else:
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# 记录需要插入的数据
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to_insert.append(item_data)
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# ===== 执行批量插入 =====
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if to_insert:
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logger.info(f"Inserting {len(to_insert)} new records")
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# 分批插入，每批500条（避免SQL过长）
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batch_size = 500
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for i in range(0, len(to_insert), batch_size):
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batch = to_insert[i:i + batch_size]
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try:
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level_data_list = [
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LevelData(
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linecode=str(item.get('linecode')), # 统一转换为字符串
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benchmarkids=item.get('benchmarkids'),
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wsphigh=item.get('wsphigh'),
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mtype=item.get('mtype'),
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NYID=str(item.get('NYID')),
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createDate=item.get('createDate'),
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wspversion=item.get('wspversion'),
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barometric=str(item.get('barometric')) if item.get('barometric') is not None else None,
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equipbrand=item.get('equipbrand'),
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instrumodel=item.get('instrumodel'),
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serialnum=item.get('serialnum'),
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sjname=item.get('sjname'),
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temperature=str(item.get('temperature')) if item.get('temperature') is not None else None,
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weather=str(item.get('weather')) if item.get('weather') is not None else None
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)
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for item in batch
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]
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db.add_all(level_data_list)
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success_count += len(batch)
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logger.info(f"Inserted batch {i//batch_size + 1}: {len(batch)} records")
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except Exception as e:
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failed_count += len(batch)
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failed_items.extend([
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{
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'data': item,
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'error': f'插入失败: {str(e)}'
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}
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for item in batch
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])
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logger.error(f"Failed to insert batch: {str(e)}")
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raise e
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# 如果有插入失败记录（不是跳过记录），不提交事务
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# 跳过记录不应该影响事务，只插入失败的记录才需要回滚
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insert_failed_items = [item for item in failed_items if '插入失败' in item.get('error', '')]
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if insert_failed_items:
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db.rollback()
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return {
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'success': False,
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'message': f'批量导入失败: {len(insert_failed_items)}条记录插入失败',
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'total_count': total_count,
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'success_count': success_count,
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'failed_count': failed_count,
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'failed_items': failed_items
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}
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db.commit()
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logger.info(f"Batch import level data completed. Success: {success_count}, Failed: {failed_count}")
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break
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except Exception as e:
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db.rollback()
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logger.warning(f"Batch import attempt {attempt + 1} failed: {str(e)}")
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if attempt == 1: # 最后一次重试失败
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logger.error("Batch import level data failed after retries")
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return {
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'success': False,
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'message': f'批量导入失败: {str(e)}',
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'total_count': total_count,
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'success_count': 0,
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'failed_count': total_count,
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'failed_items': failed_items
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}
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return {
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'success': True,
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'message': '批量导入完成' if failed_count == 0 else f'部分导入失败',
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'total_count': total_count,
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'success_count': success_count,
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'failed_count': failed_count,
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'failed_items': failed_items
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}
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def get_level_data_by_project_name(self, db: Session, project_name: str, nyid_max: bool = False) -> List[Dict[str, Any]]:
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"""
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通过project_name获取全部水准线路
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业务逻辑:
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1. 查询账号表获取账号数据 (通过project_name)
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2. 查询断面表获取断面数据 (通过account_id)
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3. 查询观测点表获取观测点数据 (通过section_id)
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4. 查询沉降数据表获取沉降数据 (通过point_id)
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5. 查询水准数据表获取水准数据 (通过NYID)
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6. 将水准数据依照linecode去重（同linecode只需保留一个）
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"""
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try:
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logger.info(f"开始查询project_name={project_name}对应的水准线路数据")
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# 1. 查询账号表获取账号数据
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accounts = db.query(Account).filter(Account.project_name.like(f"%{project_name}%")).all()
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if not accounts:
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logger.warning(f"未查询到project_name={project_name}对应的账号")
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return []
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account_ids = [str(account.id) for account in accounts]
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logger.info(f"查询到{len(account_ids)}个账号: {account_ids}")
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# 2. 查询断面表获取断面数据 (通过account_id)
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sections = db.query(SectionData).filter(SectionData.account_id.in_(account_ids)).all()
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if not sections:
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logger.warning(f"未查询到对应的断面数据")
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return []
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section_ids = [section.section_id for section in sections]
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logger.info(f"查询到{len(section_ids)}个断面: {section_ids}")
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# 3. 查询观测点表获取观测点数据 (通过section_id)
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checkpoints = db.query(Checkpoint).filter(Checkpoint.section_id.in_(section_ids)).all()
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if not checkpoints:
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logger.warning(f"未查询到对应的观测点数据")
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return []
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point_ids = [checkpoint.point_id for checkpoint in checkpoints]
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logger.info(f"查询到{len(point_ids)}个观测点")
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# 4. 查询沉降数据表获取沉降数据 (通过point_id)
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settlements = db.query(SettlementData).filter(SettlementData.point_id.in_(point_ids)).all()
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if not settlements:
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logger.warning(f"未查询到对应的沉降数据")
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return []
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nyid_list = list(set([settlement.NYID for settlement in settlements if settlement.NYID]))
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logger.info(f"查询到{len(nyid_list)}个期数ID")
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if nyid_max:
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# 只获取最新期数的水准数据
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nyid_list = [max(nyid_list, key=int)]
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logger.info(f"筛选后只获取最新期数ID: {nyid_list}")
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level_data_list = db.query(LevelData).filter(LevelData.NYID.in_(nyid_list)).all()
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else:
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# 5. 查询水准数据表获取水准数据 (通过NYID)
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level_data_list = db.query(LevelData).filter(LevelData.NYID.in_(nyid_list)).all()
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if not level_data_list:
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logger.warning(f"未查询到对应的水准数据")
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return []
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# 6. 将水准数据依照linecode去重（同linecode只需保留一个）
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linecode_seen = set()
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unique_level_data = []
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for level in level_data_list:
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if level.linecode not in linecode_seen:
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linecode_seen.add(level.linecode)
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level_dict = {
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"id": level.id,
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"linecode": level.linecode,
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"benchmarkids": level.benchmarkids,
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"wsphigh": level.wsphigh,
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"NYID": level.NYID,
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"mtype": level.mtype,
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"createDate": level.createDate.strftime("%Y-%m-%d %H:%M:%S") if level.createDate else None,
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"wspversion": level.wspversion,
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"barometric": level.barometric,
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"equipbrand": level.equipbrand,
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"instrumodel": level.instrumodel,
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"serialnum": level.serialnum,
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"sjname": level.sjname,
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"temperature": level.temperature,
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"weather": level.weather
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}
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unique_level_data.append(level_dict)
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logger.info(f"查询完成，共{len(unique_level_data)}条去重后的水准数据")
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return unique_level_data
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except Exception as e:
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logger.error(f"查询project_name={project_name}的水准数据失败: {str(e)}", exc_info=True)
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raise e
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def batch_delete_by_linecodes(self, db: Session, linecodes: List[str]) -> Dict[str, Any]:
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"""
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根据水准线路编码列表批量删除相关数据
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业务逻辑：
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1. 根据linecodes查找水准数据(LevelData)
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2. 根据水准数据的NYID查找沉降数据(SettlementData)
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3. 根据沉降数据的point_id查找观测点数据(Checkpoint)
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4. 根据NYID查找原始数据(分表存储)
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5. 备份所有数据为SQL文件
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6. 按顺序删除：原始数据 → 沉降数据 → 观测点数据 → 水准数据
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Args:
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db: 数据库会话
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linecodes: 水准线路编码列表
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Returns:
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操作结果
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"""
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if not linecodes:
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return {
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'success': False,
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'message': '水准线路编码列表不能为空',
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'backup_file': None,
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'deleted_counts': None
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}
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try:
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logger.info(f"开始批量删除，linecodes: {linecodes}")
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# 1. 查找水准数据
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level_data_list = db.query(LevelData).filter(LevelData.linecode.in_(linecodes)).all()
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if not level_data_list:
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return {
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'success': False,
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'message': f'未找到linecodes={linecodes}对应的水准数据',
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'backup_file': None,
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'deleted_counts': None
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}
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nyid_list = list(set([level.NYID for level in level_data_list if level.NYID]))
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logger.info(f"找到{len(level_data_list)}条水准数据，{len(nyid_list)}个期数ID")
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# 2. 查找沉降数据
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settlement_list = db.query(SettlementData).filter(SettlementData.NYID.in_(nyid_list)).all()
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point_ids = list(set([s.point_id for s in settlement_list if s.point_id]))
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logger.info(f"找到{len(settlement_list)}条沉降数据，{len(point_ids)}个观测点ID")
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# 3. 查找观测点数据
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checkpoint_list = db.query(Checkpoint).filter(Checkpoint.point_id.in_(point_ids)).all() if point_ids else []
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logger.info(f"找到{len(checkpoint_list)}条观测点数据")
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# 4. 查找原始数据（分表存储）
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original_data_map = self._find_original_data_by_nyids(db, nyid_list)
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total_original_count = sum(len(data) for data in original_data_map.values())
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logger.info(f"找到{total_original_count}条原始数据，分布在{len(original_data_map)}个分表")
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# 5. 备份数据为SQL文件
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backup_file = self._backup_data_to_sql(
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db, level_data_list, settlement_list, checkpoint_list, original_data_map
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)
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logger.info(f"数据已备份到: {backup_file}")
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# 6. 执行删除（使用事务）
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deleted_counts = self._execute_batch_delete(
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db, level_data_list, settlement_list, checkpoint_list, original_data_map, nyid_list
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)
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return {
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'success': True,
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'message': '批量删除成功',
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'backup_file': backup_file,
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'deleted_counts': deleted_counts
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}
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except Exception as e:
|
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logger.error(f"批量删除失败: {str(e)}", exc_info=True)
|
||
db.rollback()
|
||
return {
|
||
'success': False,
|
||
'message': f'批量删除失败: {str(e)}',
|
||
'backup_file': None,
|
||
'deleted_counts': None
|
||
}
|
||
|
||
def _find_original_data_by_nyids(self, db: Session, nyid_list: List[str]) -> Dict[str, List[Dict]]:
|
||
"""
|
||
根据NYID列表查找所有分表中的原始数据
|
||
|
||
Returns:
|
||
{table_name: [row_dict, ...], ...}
|
||
"""
|
||
original_data_map = {}
|
||
|
||
# 获取所有原始数据分表
|
||
inspector = inspect(engine)
|
||
all_tables = inspector.get_table_names()
|
||
original_tables = [t for t in all_tables if t.startswith('original_data_')]
|
||
|
||
for table_name in original_tables:
|
||
try:
|
||
# 构建IN查询的参数
|
||
placeholders = ', '.join([f':nyid_{i}' for i in range(len(nyid_list))])
|
||
params = {f'nyid_{i}': nyid for i, nyid in enumerate(nyid_list)}
|
||
|
||
query = text(f"SELECT * FROM `{table_name}` WHERE NYID IN ({placeholders})")
|
||
result = db.execute(query, params)
|
||
rows = result.fetchall()
|
||
|
||
if rows:
|
||
# 获取列名
|
||
columns = result.keys()
|
||
original_data_map[table_name] = [dict(zip(columns, row)) for row in rows]
|
||
logger.info(f"表{table_name}找到{len(rows)}条原始数据")
|
||
except Exception as e:
|
||
logger.warning(f"查询表{table_name}失败: {str(e)}")
|
||
continue
|
||
|
||
return original_data_map
|
||
|
||
def _backup_data_to_sql(self, db: Session, level_data_list: List[LevelData],
|
||
settlement_list: List[SettlementData],
|
||
checkpoint_list: List[Checkpoint],
|
||
original_data_map: Dict[str, List[Dict]]) -> str:
|
||
"""
|
||
将数据备份为SQL文件
|
||
|
||
Returns:
|
||
备份文件路径
|
||
"""
|
||
# 创建备份目录
|
||
backup_dir = "backups"
|
||
os.makedirs(backup_dir, exist_ok=True)
|
||
|
||
# 生成备份文件名
|
||
timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
|
||
backup_file = os.path.join(backup_dir, f"backup_{timestamp}.sql")
|
||
|
||
with open(backup_file, 'w', encoding='utf-8') as f:
|
||
f.write(f"-- 数据备份文件\n")
|
||
f.write(f"-- 生成时间: {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}\n")
|
||
f.write(f"-- 备份内容: 水准数据、沉降数据、观测点数据、原始数据\n\n")
|
||
|
||
# 备份水准数据
|
||
f.write("-- ========== 水准数据 (level_data) ==========\n")
|
||
for level in level_data_list:
|
||
create_date = f"'{level.createDate.strftime('%Y-%m-%d %H:%M:%S')}'" if level.createDate else "NULL"
|
||
f.write(f"INSERT INTO `level_data` (`id`, `linecode`, `benchmarkids`, `wsphigh`, `NYID`, `createDate`, `mtype`, `wspversion`, `barometric`, `equipbrand`, `instrumodel`, `serialnum`, `sjname`, `temperature`, `weather`) VALUES ({level.id}, {self._sql_value(level.linecode)}, {self._sql_value(level.benchmarkids)}, {self._sql_value(level.wsphigh)}, {self._sql_value(level.NYID)}, {create_date}, {self._sql_value(level.mtype)}, {self._sql_value(level.wspversion)}, {self._sql_value(level.barometric)}, {self._sql_value(level.equipbrand)}, {self._sql_value(level.instrumodel)}, {self._sql_value(level.serialnum)}, {self._sql_value(level.sjname)}, {self._sql_value(level.temperature)}, {self._sql_value(level.weather)});\n")
|
||
f.write("\n")
|
||
|
||
# 备份沉降数据
|
||
f.write("-- ========== 沉降数据 (settlement_data) ==========\n")
|
||
for s in settlement_list:
|
||
mtime_w = f"'{s.MTIME_W.strftime('%Y-%m-%d %H:%M:%S')}'" if s.MTIME_W else "NULL"
|
||
createdate = f"'{s.createdate.strftime('%Y-%m-%d %H:%M:%S')}'" if s.createdate else "NULL"
|
||
f.write(f"INSERT INTO `settlement_data` (`id`, `point_id`, `CVALUE`, `MAVALUE`, `MTIME_W`, `NYID`, `PRELOADH`, `PSTATE`, `REMARK`, `WORKINFO`, `createdate`, `day`, `day_jg`, `isgzjdxz`, `mavalue_bc`, `mavalue_lj`, `sjName`, `useflag`, `workinfoname`, `upd_remark`) VALUES ({s.id}, {self._sql_value(s.point_id)}, {self._sql_value(s.CVALUE)}, {self._sql_value(s.MAVALUE)}, {mtime_w}, {self._sql_value(s.NYID)}, {self._sql_value(s.PRELOADH)}, {self._sql_value(s.PSTATE)}, {self._sql_value(s.REMARK)}, {self._sql_value(s.WORKINFO)}, {createdate}, {self._sql_value(s.day)}, {self._sql_value(s.day_jg)}, {self._sql_value(s.isgzjdxz)}, {self._sql_value(s.mavalue_bc)}, {self._sql_value(s.mavalue_lj)}, {self._sql_value(s.sjName)}, {self._sql_value(s.useflag)}, {self._sql_value(s.workinfoname)}, {self._sql_value(s.upd_remark)});\n")
|
||
f.write("\n")
|
||
|
||
# 备份观测点数据
|
||
f.write("-- ========== 观测点数据 (checkpoint) ==========\n")
|
||
for cp in checkpoint_list:
|
||
f.write(f"INSERT INTO `checkpoint` (`id`, `aname`, `burial_date`, `section_id`, `point_id`) VALUES ({cp.id}, {self._sql_value(cp.aname)}, {self._sql_value(cp.burial_date)}, {self._sql_value(cp.section_id)}, {self._sql_value(cp.point_id)});\n")
|
||
f.write("\n")
|
||
|
||
# 备份原始数据（分表）
|
||
f.write("-- ========== 原始数据 (original_data_*) ==========\n")
|
||
for table_name, rows in original_data_map.items():
|
||
f.write(f"-- 表: {table_name}\n")
|
||
for row in rows:
|
||
mtime = f"'{row['mtime'].strftime('%Y-%m-%d %H:%M:%S')}'" if row.get('mtime') and hasattr(row['mtime'], 'strftime') else self._sql_value(row.get('mtime'))
|
||
f.write(f"INSERT INTO `{table_name}` (`id`, `account_id`, `bfpcode`, `mtime`, `bffb`, `bfpl`, `bfpvalue`, `NYID`, `sort`) VALUES ({row.get('id')}, {row.get('account_id')}, {self._sql_value(row.get('bfpcode'))}, {mtime}, {self._sql_value(row.get('bffb'))}, {self._sql_value(row.get('bfpl'))}, {self._sql_value(row.get('bfpvalue'))}, {self._sql_value(row.get('NYID'))}, {row.get('sort') if row.get('sort') is not None else 'NULL'});\n")
|
||
f.write("\n")
|
||
|
||
return backup_file
|
||
|
||
def _sql_value(self, value) -> str:
|
||
"""将值转换为SQL格式"""
|
||
if value is None:
|
||
return "NULL"
|
||
if isinstance(value, str):
|
||
# 转义单引号
|
||
escaped = value.replace("'", "''")
|
||
return f"'{escaped}'"
|
||
return str(value)
|
||
|
||
def _execute_batch_delete(self, db: Session, level_data_list: List[LevelData],
|
||
settlement_list: List[SettlementData],
|
||
checkpoint_list: List[Checkpoint],
|
||
original_data_map: Dict[str, List[Dict]],
|
||
nyid_list: List[str]) -> Dict[str, int]:
|
||
"""
|
||
执行批量删除操作
|
||
删除顺序：原始数据 → 沉降数据 → 观测点数据 → 水准数据
|
||
|
||
Returns:
|
||
各表删除的记录数
|
||
"""
|
||
deleted_counts = {
|
||
'original_data': 0,
|
||
'settlement_data': 0,
|
||
'checkpoint': 0,
|
||
'level_data': 0
|
||
}
|
||
|
||
try:
|
||
# 1. 删除原始数据（分表）
|
||
for table_name, rows in original_data_map.items():
|
||
if rows:
|
||
placeholders = ', '.join([f':nyid_{i}' for i in range(len(nyid_list))])
|
||
params = {f'nyid_{i}': nyid for i, nyid in enumerate(nyid_list)}
|
||
|
||
delete_sql = text(f"DELETE FROM `{table_name}` WHERE NYID IN ({placeholders})")
|
||
result = db.execute(delete_sql, params)
|
||
deleted_counts['original_data'] += result.rowcount
|
||
logger.info(f"从表{table_name}删除{result.rowcount}条原始数据")
|
||
|
||
# 2. 删除沉降数据
|
||
if settlement_list:
|
||
settlement_ids = [s.id for s in settlement_list]
|
||
db.query(SettlementData).filter(SettlementData.id.in_(settlement_ids)).delete(synchronize_session=False)
|
||
deleted_counts['settlement_data'] = len(settlement_ids)
|
||
logger.info(f"删除{len(settlement_ids)}条沉降数据")
|
||
|
||
# 3. 删除观测点数据
|
||
if checkpoint_list:
|
||
checkpoint_ids = [cp.id for cp in checkpoint_list]
|
||
db.query(Checkpoint).filter(Checkpoint.id.in_(checkpoint_ids)).delete(synchronize_session=False)
|
||
deleted_counts['checkpoint'] = len(checkpoint_ids)
|
||
logger.info(f"删除{len(checkpoint_ids)}条观测点数据")
|
||
|
||
# 4. 删除水准数据
|
||
if level_data_list:
|
||
level_ids = [level.id for level in level_data_list]
|
||
db.query(LevelData).filter(LevelData.id.in_(level_ids)).delete(synchronize_session=False)
|
||
deleted_counts['level_data'] = len(level_ids)
|
||
logger.info(f"删除{len(level_ids)}条水准数据")
|
||
|
||
db.commit()
|
||
logger.info(f"批量删除完成: {deleted_counts}")
|
||
|
||
except Exception as e:
|
||
db.rollback()
|
||
logger.error(f"批量删除执行失败: {str(e)}")
|
||
raise e
|
||
|
||
return deleted_counts |