3791966446
- Add explicit BEGIN TRANSACTION for clear transaction boundaries - Ensure IDENTITY_INSERT state is properly tracked and cleaned up - Add finally block to guarantee Access connection cleanup - Move table existence check inside sync loop for better scope Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
286 lines
12 KiB
Python
286 lines
12 KiB
Python
import time
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import os
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import sys
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import pyodbc
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from config import SQL_SERVER_CONN, ACCESS_DRIVER, SYNC_MAPPING, POLL_INTERVAL, LOG_TABLE_CONFIG, UPTIME_KUMA_CONFIG
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import db_utils
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from log_utils import (LoggerManager, log_success, log_error, log_warning, log_info, log_processing,
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log_skip, log_critical, log_start, log_stop, log_file, log_database, log_sync)
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from uptime_kuma_utils import UptimeKumaMonitor
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# 初始化日志管理器
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LoggerManager("run_incremental_sync", log_prefix="incremental")
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# 初始化 Uptime Kuma 监控器
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uptime_monitor = UptimeKumaMonitor(UPTIME_KUMA_CONFIG)
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uptime_monitor.set_logger(log_warning)
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# ================= 辅助函数 =================
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def has_identity_column(sql_cursor, schema, table):
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"""检查表是否包含标识列"""
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query = """
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SELECT COUNT(*)
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FROM sys.columns c
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JOIN sys.tables t ON c.object_id = t.object_id
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JOIN sys.schemas s ON t.schema_id = s.schema_id
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WHERE s.name = ? AND t.name = ? AND c.is_identity = 1
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"""
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sql_cursor.execute(query, (schema, table))
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return sql_cursor.fetchone()[0] > 0
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# ================= 主逻辑 =================
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def process_sync_task():
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"""
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逻辑重构：
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遍历 SYNC_MAPPING 中的每一个文件 -> 去日志表查询该文件下特定表的未同步记录。
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"""
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sql_conn = db_utils.get_sql_conn()
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sql_cursor = sql_conn.cursor()
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sql_cursor.fast_executemany = True # 高性能开关
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# 标记是否有工作被处理（用于控制轮询休眠时间）
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work_done = False
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cols = LOG_TABLE_CONFIG
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log_full_name = db_utils.fmt_table(cols['schema'], cols['table_name'])
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try:
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# === 核心循环：以配置文件为驱动 ===
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for clean_path, tables_map in SYNC_MAPPING.items():
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# 1. 准备查询条件
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# 获取该文件下所有需要同步的表名列表
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target_tables = list(tables_map.keys())
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if not target_tables:
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continue
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# 构造 TableAddress 的精确匹配条件
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# VBA 逻辑：网络路径带 ";DATABASE=", 本地路径带 "LOCAL:"
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# 我们直接构造这两个字符串，让 SQL Server 做精确匹配，效率极高
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# 注意：将路径转为 Windows 标准反斜杠
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win_path = os.path.normpath(clean_path)
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addr_candidates = [
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f";DATABASE={win_path}", # 情况1
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f"LOCAL={win_path}", # 情况2 (注意 VBA 代码里可能是 LOCAL: 或 LOCAL=，请核对)
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f"LOCAL:{win_path}", # 情况3
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win_path # 情况4 (兼容没有前缀的情况)
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]
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# 2. 构造动态 SQL 查询
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# WHERE Synced=0 AND Address IN (...) AND TableName IN (...)
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placeholders_addr = ','.join(['?'] * len(addr_candidates))
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placeholders_tbl = ','.join(['?'] * len(target_tables))
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query_log = f"""
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SELECT TOP 1000
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{cols['col_log_id']},
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{cols['col_table_name']},
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{cols['col_record_id']}
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FROM {log_full_name}
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WHERE {cols['col_synced']} = 0
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AND TableType = 'LINKED_ACCESS'
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AND {cols['col_address']} IN ({placeholders_addr})
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AND {cols['col_table_name']} IN ({placeholders_tbl})
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ORDER BY {cols['col_log_id']} ASC
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"""
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# 参数列表：先放地址，再放表名
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params = addr_candidates + target_tables
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sql_cursor.execute(query_log, params)
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logs = sql_cursor.fetchall()
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if not logs:
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continue # 这个文件没有需要同步的记录，检查下一个文件
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work_done = True # 标记有工作
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log_file(f"{os.path.basename(clean_path)} 发现 {len(logs)} 条待同步变更")
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# 3. 本地分组 (按表名)
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# 结构: table_tasks[TableName] = { ids: {}, log_ids: [] }
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table_tasks = {}
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for row in logs:
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log_id, acc_table, record_id = row
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if acc_table not in table_tasks:
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table_tasks[acc_table] = {'record_ids': set(), 'log_ids': []}
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table_tasks[acc_table]['record_ids'].add(record_id)
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table_tasks[acc_table]['log_ids'].append(log_id)
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# 4. 执行同步 (连接一次 Access，处理多张表)
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if not os.path.exists(clean_path):
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log_error(f"无法访问文件: {clean_path}")
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continue
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acc_conn = None
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try:
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acc_conn = db_utils.get_access_conn(clean_path)
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acc_cursor = acc_conn.cursor()
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log_database(f"已连接 Access 文件: {os.path.basename(clean_path)}")
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except Exception as conn_err:
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log_error(f"连接 Access 失败 [{os.path.basename(clean_path)}]: {conn_err}")
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continue
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# 统计每个文件的同步情况
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file_success_count = 0
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file_error_count = 0
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file_total_records = 0
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for acc_table, data in table_tasks.items():
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record_ids = list(data['record_ids'])
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log_ids = data['log_ids']
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# 读取目标配置
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target_conf = tables_map[acc_table]
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target_schema = target_conf['target_schema']
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target_table = target_conf['target_table']
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pk_col = target_conf['pk_col']
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target_full_name = db_utils.fmt_table(target_schema, target_table)
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log_processing(f"正在同步表 [{acc_table}] → [{target_table}] ({len(record_ids)} 条记录)")
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# 检查目标表是否存在，不存在则自动创建
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if not db_utils.table_exists(sql_cursor, target_schema, target_table):
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db_utils.ensure_schema(sql_cursor, target_schema)
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acc_cursor.execute(f"SELECT TOP 1 * FROM [{acc_table}]")
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db_utils.create_table_from_access(
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sql_cursor, target_schema, target_table,
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acc_cursor.description, pk_col
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)
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log_info(f"目标表 [{target_table}] 不存在，已自动创建")
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# 事务状态追踪
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identity_enabled = False
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transaction_begun = False
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try:
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# --- 开始事务 ---
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sql_cursor.execute("BEGIN TRANSACTION")
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transaction_begun = True
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# --- A. Access 查新数据 ---
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ids_placeholders = ','.join(['?'] * len(record_ids))
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acc_sql = f"SELECT * FROM [{acc_table}] WHERE [{pk_col}] IN ({ids_placeholders})"
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acc_cursor.execute(acc_sql, record_ids)
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new_rows = acc_cursor.fetchall()
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acc_cols = [col[0] for col in acc_cursor.description]
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# --- B. SQL Server 删旧插新 ---
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# 1. 删除旧数据
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del_sql = f"DELETE FROM {target_full_name} WHERE [{pk_col}] IN ({ids_placeholders})"
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sql_cursor.execute(del_sql, record_ids)
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# 2. 插入新数据
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if new_rows:
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insert_sql = db_utils.generate_insert_sql(target_schema, target_table, acc_cols)
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# 检查并启用 IDENTITY_INSERT
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has_identity = has_identity_column(sql_cursor, target_schema, target_table)
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if has_identity:
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sql_cursor.execute(f"SET IDENTITY_INSERT {target_full_name} ON")
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identity_enabled = True
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sql_cursor.executemany(insert_sql, new_rows)
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# 关闭 IDENTITY_INSERT
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if identity_enabled:
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sql_cursor.execute(f"SET IDENTITY_INSERT {target_full_name} OFF")
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identity_enabled = False
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# 3. 标记日志 Synced = 1
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log_placeholders = ','.join(['?'] * len(log_ids))
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update_log_sql = f"""
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UPDATE {log_full_name}
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SET {cols['col_synced']} = 1
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WHERE {cols['col_log_id']} IN ({log_placeholders})
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"""
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sql_cursor.execute(update_log_sql, log_ids)
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# 提交事务
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sql_conn.commit()
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transaction_begun = False
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log_info(f"表 [{target_table}] 同步完成: {len(record_ids)} 条记录")
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file_success_count += 1
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file_total_records += len(record_ids)
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except Exception as tbl_err:
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# 回滚事务
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if transaction_begun:
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sql_conn.rollback()
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transaction_begun = False
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# 清理 IDENTITY_INSERT 状态
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if identity_enabled:
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try:
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sql_cursor.execute(f"SET IDENTITY_INSERT {target_full_name} OFF")
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except:
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pass
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log_error(f"表 [{acc_table}] 同步失败: {tbl_err}")
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file_error_count += 1
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finally:
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# 确保 Access 连接关闭
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try:
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if acc_conn:
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acc_conn.close()
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log_info(f"已关闭 Access 连接: {os.path.basename(clean_path)}")
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except Exception as close_err:
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log_warning(f"关闭 Access 连接时出错: {close_err}")
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# 输出文件级别的汇总
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if file_success_count > 0 or file_error_count > 0:
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summary = f"文件 [{os.path.basename(clean_path)}] 同步汇总: "
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summary += f"成功 {file_success_count} 张表 ({file_total_records} 条记录)"
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if file_error_count > 0:
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summary += f" | 失败 {file_error_count} 张表"
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log_sync(summary)
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return work_done
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except Exception as e:
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log_critical(f"全局异常: {e}")
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return False
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finally:
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try: sql_conn.close()
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except: pass
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# ================= Uptime Kuma 心跳 =================
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# 使用 uptime_kuma_utils.UptimeKumaMonitor 替代原有实现
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if __name__ == "__main__":
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log_start("增量同步服务已启动 (配置驱动模式)")
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log_info(f"轮询间隔: {POLL_INTERVAL} 秒")
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log_info(f"监控配置: {len(SYNC_MAPPING)} 个文件")
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if UPTIME_KUMA_CONFIG.get('enabled', False):
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log_info(f"心跳间隔: {UPTIME_KUMA_CONFIG['heartbeat_interval']} 秒")
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log_info("=" * 70)
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# 启动时发送第一次心跳
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uptime_monitor.send_heartbeat()
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try:
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while True:
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try:
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has_work = process_sync_task()
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# 检查是否需要发送心跳
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uptime_monitor.check_and_send_heartbeat()
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# 如果有工作，说明可能还有积压，休息短一点(0.1s)
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# 如果没工作，休息标准间隔(5s)
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time.sleep(0.1 if has_work else POLL_INTERVAL)
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except KeyboardInterrupt:
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log_info("=" * 70)
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log_stop("收到停止信号，服务正在关闭...")
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break
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except Exception as e:
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log_critical(f"主循环崩溃: {e}")
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time.sleep(5)
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finally:
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# 停止时发送心跳停止信号（可选）
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uptime_monitor.send_stop_signal() |