datax-admin/app/routers/run.py

import datetime
import json
import time
from collections import defaultdict

import requests
from fastapi import APIRouter, Depends
from fastapi_pagination import paginate, Params
from pydantic import BaseModel
from sqlalchemy.orm import Session
from app import schemas, get_db, crud
from app.core.airflow.af_util import get_airflow_api_info, call_airflow_api, datetime2timestamp
from app.core.k8s.k8s_client import KubernetesTools
from utils import web_try, sxtimeit


class Item(BaseModel):
    data: dict


router_af_run = APIRouter(
    prefix="/af/af_run",
    tags=["airflow_run-运行管理"],
)


@router_af_run.get("/")
@web_try()
@sxtimeit
def get_runs(params: Params = Depends(), db: Session = Depends(get_db)):
    return paginate(crud.get_airflow_tasks(db), params)


@router_af_run.get("/{run_id}/status")
@web_try()
@sxtimeit
def get_airflow_run_status(run_id: int, db: Session = Depends(get_db)):
    item = crud.get_airflow_run_once(item_id=run_id, db=db)
    job_item = crud.get_airflow_job_once(db=db, item_id=item.job_id)
    print(f'job_item.job_mode  is {job_item.job_mode}，with af run id= {item.af_run_id}')
    if job_item.job_mode == 1:  # 常规模式
        if item.status in [2, 3]:
            return {"status": item.status}
        else:
            uri_prefix, headers = get_airflow_api_info()
            url = f'{uri_prefix}/dags/dag_{item.job_id}/dagRuns/{item.af_run_id}'
            state = requests.get(url, headers=headers).json().get('state', None)
            status = {"queued": 0, 'running': 1, 'success': 2, 'failed': 3}.get(state, -1)
            print(f'status is {status}, with state {state}')
            if item.status != status:  # queue or running
                item.status = status
                item.update(db)
                print(f'after update {item.status}')
            return {"status": status}
    else:
        uri_prefix, headers = get_airflow_api_info()
        url = f'{uri_prefix}/dags/dag_{item.job_id}/dagRuns/{item.af_run_id}'
        state = requests.get(url, headers=headers).json().get('state', None)
        status = {"queued": 0, 'running': 1, 'success': 2, 'failed': 3}.get(state, -1)
        print(f'status is {status}, with state {state}')

    return {"status": status}


@router_af_run.post("/")
@web_try()
@sxtimeit
def add_airflow_run(item: Item, db: Session = Depends(get_db)):
    print(item.data)
    job_item = crud.get_airflow_job_once(db=db, item_id=item.data["job_id"])
    sparks_dependence = {}
    debug_run = crud.get_airflow_run_once_debug_mode(job_id=item.data["job_id"], db=db)

    if job_item.job_mode == 1 or (job_item.job_mode == 2 and debug_run is None):  # 常规模式
        for task in schemas.AirflowJob(**job_item.to_dict()).tasks:
            if task.task_type == 'sparks':
                sparks = json.loads(task.script)
                dependence = []
                for (source, sink) in sparks['edges']:
                    dependence.append([f'{task.id}_{source}', f'{task.id}_{sink}'])
                sparks_dependence[task.id] = dependence

        item = schemas.AirflowRunCreate(**{"start_time": item.data["start_time"],
                                           "job_id": int(item.data["job_id"]),
                                           "run_ts": item.data['run_ts'],
                                           "af_run_id": item.data['af_run_id'],
                                           "details": {"tasks": {}, "dependence": {"tasks": job_item.dependence,
                                                                                   "sparks": sparks_dependence}},
                                           "status": 0},
                                        )
        crud.create_airflow_run(db, item)

    elif job_item.job_mode == 2:  # 调试模式
        run = crud.get_airflow_run_once_debug_mode(job_id=item.data["job_id"], db=db)
        sparks_task = schemas.AirflowTask(**job_item.tasks[0])
        assert sparks_task.task_type == 'sparks'
        sparks = json.loads(sparks_task.script)
        sparks_dependence[sparks_task.id] = [[f'{sparks_task.id}_{s}', f'{sparks_task.id}_{k}'] for (s, k) in
                                             sparks['edges']]
        spark_nodes = [sub_node['id'] for sub_node in sparks['sub_nodes']]
        run.details['dependence']['sparks'] = sparks_dependence
        run.details['tasks'] = {k: v for k, v in run.details['tasks'].items() if k in spark_nodes}
        update_run = schemas.AirflowRunUpdate(
            **{"details": run.details, "status": 1, "af_run_id": item.data['af_run_id']})
        crud.update_airflow_run(db=db, item_id=run.id, update_item=update_run)


@router_af_run.post("/notification")
@web_try()
@sxtimeit
def add_notification(item: Item, db: Session = Depends(get_db)):
    k8s_tool = KubernetesTools()
    labels = {"dag_id": item.data['dag_id'], "task_id": item.data['task_id'], "run_ts": item.data['run_ts']}
    logs = k8s_tool.get_pod_logs(namespaces="airflow", labels=labels)
    job_item = crud.get_airflow_job_once(db=db, item_id=item.data["job_id"])

    if job_item.job_mode == 1:  # normal model, one job-> many runs
        run = crud.get_airflow_run_once_normal_mode(af_run_id=item.data['af_run_id'], db=db)
    elif job_item.job_mode == 2:  # debug model, one job-> one run
        run = crud.get_airflow_run_once_debug_mode(job_id=item.data["job_id"], db=db)
    else:
        run = None

    if run is not None:
        update_run = schemas.AirflowRunUpdate(
            **{"details": run.details, "status": run.status, "af_run_id": item.data['af_run_id']})
        update_run.details['tasks'][item.data['task_id']] = {"log": logs,
                                                             "start_time": item.data["start_time"],
                                                             "end_time": item.data["end_time"],
                                                             "status": item.data['status']}
        crud.update_airflow_run(db=db, item_id=run.id, update_item=update_run)


@router_af_run.post("/sigal")
@web_try()
@sxtimeit
def add_notification(item: Item):
    print(f'receive sigal: {item.data} ')


@router_af_run.get("/tasks_status/{job_id}/{af_run_id}")
@web_try()
@sxtimeit
def get_airflow_dagrun(job_id: int, af_run_id: str, db: Session = Depends(get_db)):
    ret = call_airflow_api(method='get', uri=f'dags/dag_{job_id}/dagRuns/{af_run_id}/taskInstances', args_dict={})
    details = defaultdict(dict)

    for task in ret.json()['task_instances']:
        details['tasks'][task['task_id']] = {
            # "log": logs,
            "start_time":  datetime.datetime.strptime(task['start_date'], '%Y-%m-%dT%H:%M:%S.%f%z').timestamp(),
            "end_time": datetime.datetime.strptime(task['end_date'], '%Y-%m-%dT%H:%M:%S.%f%z').timestamp(),
            "status": task['state']
        }
        # print(f"{task['task_id']}:{task['duration']}")
    return details


@router_af_run.get("/running_status/{job_id}/{af_run_id}")
@web_try()
@sxtimeit
def get_airflow_dagrun_running_status(job_id: int, af_run_id: str, db: Session = Depends(get_db)):
    job_info = call_airflow_api(method='get', uri=f'dags/dag_{job_id}/dagRuns/{af_run_id}', args_dict={})
    tasks_info = call_airflow_api(method='get', uri=f'dags/dag_{job_id}/dagRuns/{af_run_id}/taskInstances', args_dict={})


    details = defaultdict(dict)
    for task in tasks_info.json()['task_instances']:
        details['tasks'][task['task_id']] = {
            # "log": logs,
            "start_time": datetime2timestamp(task['start_date']),
            "end_time": datetime2timestamp(task['end_date']),
            "status": task['state']
        }
        # print(f"{task['task_id']}:{task['duration']}")


    # item = schemas.AirflowRunUpdate(**{#"start_time": item.data["start_time"],
    #                                    #"job_id": int(job_id),
    #                                    # "run_ts": item.data['run_ts'],
    #                                    # "af_run_id": item.data['af_run_id'],
    #                                     "end_time":datetime2timestamp()
    #                                    "details": {"tasks": {}, "dependence": {"tasks": job_item.dependence,
    #                                                                            "sparks": sparks_dependence}},
    #                                    "status": 0},

    # item = schemas.AirflowRunCreate(**{"start_time": item.data["start_time"],
    #                                    "job_id": int(job_id),
    #                                    # "run_ts": item.data['run_ts'],
    #                                    # "af_run_id": item.data['af_run_id'],
    #                                    "details": {"tasks": {}, "dependence": {"tasks": job_item.dependence,
    #                                                                            "sparks": sparks_dependence}},
    #                                    "status": 0},

    # return ret.json()


@router_af_run.get("/task_log/{job_id}/{af_run_id}/{task_id}")
@web_try()
@sxtimeit
def get_airflow_dagrun_task_log(job_id: int, af_run_id: str, task_id: str):
    ret = call_airflow_api(method='get', uri=f'dags/dag_{job_id}/dagRuns/{af_run_id}/taskInstances/{task_id}/logs/1',
                           args_dict={})
    return {"log": ret.text}