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# to you under the Apache License, Version 2.0 (the
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#
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from __future__ import annotations

from datetime import datetime

from sqlalchemy import (
    Integer,
    Text,
    text,
)
from sqlalchemy.dialects.mysql import MEDIUMTEXT
from sqlalchemy.orm import Mapped

from airflow.models.base import StringID
from airflow.providers.common.compat.sqlalchemy.orm import mapped_column
from airflow.providers.edge3.models.edge_base import Base
from airflow.utils.log.logging_mixin import LoggingMixin
from airflow.utils.sqlalchemy import UtcDateTime


class EdgeLogsModel(Base, LoggingMixin):
    """
    Temporary collected logs from a Edge Worker while job runs on remote site.

    As the Edge Worker in most cases has a local file system and the web UI no access
    to read files from remote site, Edge Workers will send incremental chunks of logs
    of running jobs to the central site. As log storage backends in most cloud cases can not
    append logs, the table is used as buffer to receive. Upon task completion logs can be
    flushed to task log handler.

    Log data therefore is collected in chunks and is only temporary.
    """

    __tablename__ = "edge_logs"
    dag_id: Mapped[str] = mapped_column(StringID(), primary_key=True, nullable=False)
    task_id: Mapped[str] = mapped_column(StringID(), primary_key=True, nullable=False)
    run_id: Mapped[str] = mapped_column(StringID(), primary_key=True, nullable=False)
    map_index: Mapped[int] = mapped_column(
        Integer, primary_key=True, nullable=False, server_default=text("-1")
    )
    try_number: Mapped[int] = mapped_column(Integer, primary_key=True, default=0)
    log_chunk_time: Mapped[datetime] = mapped_column(UtcDateTime, primary_key=True, nullable=False)
    log_chunk_data: Mapped[str] = mapped_column(Text().with_variant(MEDIUMTEXT(), "mysql"), nullable=False)

    def __init__(
        self,
        dag_id: str,
        task_id: str,
        run_id: str,
        map_index: int,
        try_number: int,
        log_chunk_time: datetime,
        log_chunk_data: str,
    ):
        self.dag_id = dag_id
        self.task_id = task_id
        self.run_id = run_id
        self.map_index = map_index
        self.try_number = try_number
        self.log_chunk_time = log_chunk_time
        self.log_chunk_data = log_chunk_data
        super().__init__()
