How to run a DAG in distributed airflow

[super017]

The version of airflow I deployed is 1.10.14.A master and three worker.I want several Workers to cooperate to complete a DAG.I wrote a simple test case.

from airflow import DAG
from airflow.operators.python_operator import PythonOperator
from airflow.utils.dates import days_ago
from airflow.operators.bash_operator import BashOperator
import time
import math
import argparse


default_args = {
    'owner':'airflow',
    'retries':3,
    'depends_on_past':False,
    'start_date': days_ago(2),
    'provide_context':True,
}
dag = DAG(
    'xhcyeh',
    default_args=default_args,
    schedule_interval=timedelta(minutes=5)
)


def function1(**kwargs):
    print("正在计算累加：\n")
    sum =2
    #x = kwargs['dag_run'].conf['x']
    #x = kwargs.get("dag_run").conf.get("x")
    x = 5
    for i in range(x):
        sum +=i
    print(sum)
    f = open('/home/lis/airflow/dags/x.txt','w')
    f.write(str(sum))
    f.close()
    kwargs['task_instance'].xcom_push(key='sea1',value=str(sum))
    return sum

def function2(**kwargs):
    print("正在计算平方：\n")
    sum = kwargs['task_instance'].xcom_pull(key='sea1',task_ids='function1')
    f = open('/home/ls/airflow/dags/y.txt','w')
    f.write(str(math.pow(int(sum),2)))
    f.close()
    return math.pow(int(sum),2)

run_this = PythonOperator(
    task_id='function1',
    python_callable=function1,
    queue='cdh6-2-node93',
    dag=dag,
)

t2 = PythonOperator(
    task_id='function2',
    python_callable= function2,
    queue='cdh6-2-node94',
    dag=dag,
)


run_this >> t2

I want these two workers to cooperate to complete this simple calculation.But what happens is that the second function stays in the scheduled state after the first operator completes.Then the log indicates celery failed, and the backend database has no record of parameter passing.What should I do?Or what changes I should make to my code

[turbaszek]

To run both task in paralel remove run_this >> t2. Otherwise task t2 will wait for completion of run_this.