Below is the airflow DAG code. It runs perfectly both when airflow is hosted locally, and on cloud composer. However, the DAG itself isn't clickable in the Composer UI. I found a similar question and tried the accepted answer as linked in this question. My problem is similar.

import airflow
from airflow import DAG

from airflow.operators.dummy_operator import DummyOperator
from airflow.operators.python_operator import PythonOperator
from airflow.operators.mysql_operator import MySqlOperator
from airflow.contrib.operators.dataproc_operator import DataprocClusterCreateOperator
from airflow.contrib.operators.dataproc_operator import DataprocClusterDeleteOperator
from airflow.contrib.operators.dataproc_operator import DataProcSparkOperator

from datetime import datetime, timedelta
import sys

#copy this package to dag directory in GCP composer bucket
from schemas.schemaValidator import loadSchema
from schemas.schemaValidator import sparkArgListToMap

#change these paths to point to GCP Composer data directory

## cluster config
clusterConfig= loadSchema("somePath/jobConfig/cluster.yaml","cluster")

##per job yaml config
autoLoanCsvToParquetConfig= loadSchema("somePath/jobConfig/job.yaml","job")

default_args= {
        'owner': 'airflow',
        'depends_on_past': False,
        'start_date': datetime(2019, 1, 1),
        'retries': 1,
        'retry_delay': timedelta(minutes=3)

dag= DAG('usr_job', default_args=default_args, schedule_interval=None)

t1= DummyOperator(task_id= "start", dag=dag)

t2= DataprocClusterCreateOperator(
    task_id= "CreateCluster",
    cluster_name= clusterConfig["cluster"]["cluster_name"],
    project_id= clusterConfig["project_id"],
    num_workers= clusterConfig["cluster"]["worker_config"]["num_instances"],
    image_version= clusterConfig["cluster"]["dataproc_img"],
    master_machine_type= clusterConfig["cluster"]["worker_config"]["machine_type"],
    worker_machine_type= clusterConfig["cluster"]["worker_config"]["machine_type"],
    zone= clusterConfig["region"],

t3= DataProcSparkOperator(
    task_id= "csvToParquet",
    main_class= autoLoanCsvToParquetConfig["job"]["main_class"],
    arguments= autoLoanCsvToParquetConfig["job"]["args"],
    cluster_name= clusterConfig["cluster"]["cluster_name"],
    dataproc_spark_jars= autoLoanCsvToParquetConfig["job"]["jarPath"],
    dataproc_spark_properties= sparkArgListToMap(autoLoanCsvToParquetConfig["spark_params"]),

t4= DataprocClusterDeleteOperator(
    task_id= "deleteCluster",
    cluster_name= clusterConfig["cluster"]["cluster_name"],
    project_id= clusterConfig["project_id"],
    dag= dag

t5= DummyOperator(task_id= "stop", dag=dag)


The UI gives this error - "This DAG isn't available in the webserver DAG bag object. It shows up in this list because the scheduler marked it as active in the metadata database."

And yet, when I triggered the DAG manually on Composer, I found it ran successfully through the log files.

1 Answers

sudeepgupta90 On Best Solutions

The issue was with the path which was being provided for picking up the configuration files. I was giving path for the data folder in GCS. As per Google documentation, only dags folder is synced to all nodes, and not the data folder.

Needless to say, it was a issue encountered during dag parsing time, hence, it did not appear correctly on the UI. More interestingly, these debug messages were not exposed to Composer 1.5 and earlier. Now they are available to the end user to help in debugging. Thanks anyway to everyone who helped.