import os
import sys

sys.path.append(os.path.dirname(sys.path[0]))
from utils.db_util import DBUtil, DbTypes
from utils.ssh_util import SSHUtil
from utils.common_util import CommonUtil
from utils.secure_db_client import get_remote_engine


def export_postgresql():
    pass


def export_postgresql_cluster():
    site_name = CommonUtil.get_sys_arg(1, None)
    date_info = CommonUtil.get_sys_arg(2, None)
    tb_type = CommonUtil.get_sys_arg(3, None)

    # 导出detail到集群
    CommonUtil.judge_is_work_hours(
        site_name=site_name,
        date_type="day",
        date_info=date_info,
        principal='hejiangming',
        priority=1,
        export_tools_type=1
    )

    db_type = DbTypes.postgresql_cluster.name
    print(f"导出到{db_type}中")
    #  date_info是日 日期格式 如"2026-03-31"
    d_month_now = CommonUtil.reformat_date(date_info, "%Y-%m-%d", "%Y_%m", )  # 获取年月 2026_03
    rel_date_info = CommonUtil.reformat_date(date_info, "%Y-%m-%d", "%Y-%m", )  # 获取年月 2026-03
    next_month = CommonUtil.get_month_offset(rel_date_info, 1) # 获取下一月
    # 导出表
    export_master_tb = f"{site_name}_{tb_type}_asin_detail"
    export_tb = f"{export_master_tb}_{d_month_now}"
    export_tb_copy = f"{export_tb}_copy" # copy临时表如 us_nsr_asin_detail_2026_04_copy
    # 存在就删除
    sql = f"""drop table if exists {export_tb_copy}"""
    DBUtil.exec_sql(db_type=db_type, site_name=site_name, sql=sql, dispose_flag=True)

    #   按主表结构新建
    sql = f"""create table {export_tb_copy} (  like {export_master_tb} including defaults including constraints );"""
    DBUtil.exec_sql(db_type=db_type, site_name=site_name, sql=sql, dispose_flag=True)

    #  Sqoop 导出需要一段时间，如果直接写正式分区表，导出期间业务查询可能读到一半的脏数据。用 copy 表先接收数据，全部就绪后再一次性切换到正式表，
    # 导出字段，顺序必须和 Hive 表 dwt_{tb_type}_asin_detail 一致
    cols_list = [
        "asin",
        "title",
        "img_url",
        "ao_val",
        "rating",
        "total_comments",
        "bsr_orders",
        "bsr_orders_change",
        "price",
        "weight",
        "launch_time",
        "date_info",
        "brand_name",
        "buy_box_seller_type",
        "account_name",
        "volume",
        "img_type",
        "last_update_time",
        "asin_type",
        "asin_air_freight_gross_margin",
        "asin_ocean_freight_gross_margin",
        "asin_unlaunch_time",
        "seller_id",
        "seller_country_name",
        "category_first_id",
        "first_category_rank",
        "first_category_rank_date",
        "package_quantity",
        "asin_launch_time_type",
        "seller_country_type",
        "asin_bought_month",
    ]

    # 旧写法：本地拼 sqoop 命令再 SSH 到集群执行
    # sh = CommonUtil.build_export_sh(
    #     site_name=site_name,
    #     db_type=db_type,
    #     hive_tb=f"dwt_{tb_type}_asin_detail",
    #     export_tb=export_tb_copy,
    #     col=cols_list,
    #     partition_dict={
    #         "site_name": site_name,
    #         "date_info": rel_date_info
    #     }
    # )
    # client = SSHUtil.get_ssh_client()
    # SSHUtil.exec_command_async(client, sh, ignore_err=False)
    # client.close()

    # 导出表名 导出到copy表，m=6 保持和原来一样的 map 数
    remote_engine = get_remote_engine(
        site_name=site_name,
        db_type="postgresql_cluster"
    )
    remote_engine.sqoop_raw_export(
        hive_table=f"dwt_{tb_type}_asin_detail",
        import_table=export_tb_copy,
        partitions={
            "site_name": site_name,
            "date_info": rel_date_info
        },
        m=6,
        cols=",".join(cols_list)
    )

    # 导出表 copy 表替换正式分区
    # 旧写法：DBUtil 的 SQLAlchemy engine，5 条 DDL 连着跑在同一个连接的事务里，
    # Citus 集群会在事务内攒下不同用户建立的 placement 连接，detach 分区时报
    # cannot perform query on placements that were modified in this transaction by a different user
    # engine = DBUtil.get_db_engine(db_type, site_name)
    # DBUtil.exchange_pg_part_distributed_tb(
    #     engine=engine,
    #     source_tb_name=export_tb_copy, # 数据来源：copy 表
    #     part_master_tb=export_master_tb, # 主表
    #     part_target_tb=export_tb, # 正式月分区子表
    #     part_val={ #  part_val = {'from': ['2026-04'], 'to': ['2026-05']},  # 分区范围
    #         "from": [rel_date_info],
    #         "to": [next_month]
    #     },
    #     drop_old=True
    # )
    # engine.dispose()
    df_part = remote_engine.read_sql(f"""
        select relid::varchar as relid from pg_partition_tree('{export_master_tb}') where relid::varchar = '{export_tb}'
    """)
    exist_flag = not df_part.empty
    print(f"分区{export_tb}是否已存在：{exist_flag}")

    if exist_flag:
        # 旧分区从主表摘下来并改名成 _back，让出正式分区表名
        remote_engine.execute(f"""alter table {export_master_tb} detach partition {export_tb}""")
        remote_engine.execute(f"""alter table {export_tb} rename to {export_tb}_back""")

    # 装满新数据的 copy 表改成正式分区名，再挂回主表，业务查询由此切到新数据
    remote_engine.execute(f"""alter table {export_tb_copy} rename to {export_tb}""")
    remote_engine.execute(f"""alter table {export_master_tb} attach partition {export_tb} for values from ('{rel_date_info}') to ('{next_month}')""")

    # 挂载成功后旧分区数据不再需要
    remote_engine.execute(f"""drop table if exists {export_tb}_back""")

    print(f"==================表{export_tb_copy}加入成功==================================")
    print("success")


pass

if __name__ == '__main__':
    export_postgresql_cluster()
