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159 | from airflow import DAG
from template.dag_template import build_dag
from airflow.utils.dates import days_ago
from template.utils import set_config_variable_in_emr_steps
from airflow.models import Variable
from datetime import datetime
import logging
logging.basicConfig(
level=logging.INFO,
format="%(asctime)s %(filename)s:%(lineno)d [%(levelname)s] %(message)s",
handlers=[
logging.StreamHandler()
])
LOG = logging.getLogger()
# DAG(Job) specific parameters
dag_id = 'primary-audience-global-ind_v003'
ENVIRONMENT = "uat"
config = Variable.get("primary_audience_global_ind_conf", deserialize_json=True)
MEDIA_OWNER = config["MEDIA_OWNER"]
COUNTRY = config["COUNTRY"]
AUD_VERSION = config["AUD_VERSION"]
BUCKET_NAME = 's3a://viooh-datashare-jcd-' + COUNTRY.lower()
BUCKET_OVERRIDE = config["BUCKET_OVERRIDE"]
COMPUTATION_DATE = config["COMPUTATION_DATE"]
config['ENVIRONMENT'] = ENVIRONMENT
# primary-audience-global job checks
if len(BUCKET_OVERRIDE) > 0:
BUCKET_NAME = BUCKET_OVERRIDE
else:
LOG.info("Bucket not overrided using - " + BUCKET_NAME)
config['BUCKET_NAME'] = BUCKET_NAME
if COMPUTATION_DATE == "00000000":
COMPUTE_DATE = datetime.now().strftime("%Y%m%d%H%M%S")
LOG.info("Computation date equal "+ COMPUTE_DATE)
config["COMPUTATION_DATE"] = COMPUTE_DATE
if len(AUD_VERSION) == 0:
AUD_VERSION = datetime.now().strftime("%y%j")
LOG.info("Audience version equal " + AUD_VERSION)
else:
LOG.info("User provided version " + AUD_VERSION)
config["AUD_VERSION"] = AUD_VERSION
# Cluster configurations
CLUSTER_NAME = 'primary-audience-global-' + MEDIA_OWNER + '-' + AUD_VERSION
EMR_VERSION = "emr-6.0.0"
NUM_CORE_NODES = 1
NUM_TASK_NODES = 0
step_integrity = """{
"step-name": "PrimaryAudienceGlobal-integrity",
"py-script": "jobs/integrity_job.py",
"config-json": [
{"spark.app.audience.country":"$COUNTRY"},
{"spark.app.audience.media.owner":"$MEDIA_OWNER"},
{"spark.app.audience.version":"$AUD_VERSION"},
{"spark.app.audience.bucket.name":"$BUCKET_NAME"},
{"spark.app.audience.digital.file":"$DIGITAL_FILE_TO_PROCESS"},
{"spark.app.audience.static.file":"$STATIC_FILE_TO_PROCESS"},
{"spark.app.audience.demographic.file":"$DEMOGRAPHIC_FILE_TO_PROCESS"},
{"spark.app.audience.input.bucket":"s3://global-cn-audiences-input"},
{"spark.app.audience.output.bucket":"s3://global-cn-audiences-output"},
{"spark.app.audience.folder":"$FOLDER"},
{"spark.app.audience.computation.date":"$COMPUTATION_DATE"},
{"spark.executor.memoryOverhead":"2500"}
],
"artifact": "AudiencesPipeline"
}"""
step_etl = """{
"step-name": "PrimaryAudienceGlobal-load",
"py-script": "jobs/etl_job.py",
"config-file": "configs/primary-audience-global/1.0.0/job.json",
"config-json": [
{"spark.app.audience.country":"$COUNTRY"},
{"spark.app.audience.media.owner":"$MEDIA_OWNER"},
{"spark.app.audience.version":"$AUD_VERSION"},
{"spark.app.audience.digital.file":"$DIGITAL_FILE_TO_PROCESS"},
{"spark.app.audience.static.file":"$STATIC_FILE_TO_PROCESS"},
{"spark.app.audience.folder":"$FOLDER"},
{"spark.app.audience.computation.date":"$COMPUTATION_DATE"},
{"spark.executor.memoryOverhead":"2500"}
],
"artifact": "AudiencesPipeline"
}"""
step_save_to_db = """{
"step-name": "SaveToDataBase",
"py-script": "jobs/save_to_sql.py",
"config-file": "configs/primary-audience-global-masterdb-$ENVIRONMENT/1.0.0/job.json",
"config-json": [
{"spark.app.audience.country":"$COUNTRY"},
{"spark.app.audience.media.owner":"$MEDIA_OWNER"},
{"spark.app.audience.version":"$AUD_VERSION"},
{"spark.app.audience.output.bucket":"s3://global-cn-audiences-output"},
{"spark.app.audience.computation.date":"$COMPUTATION_DATE"},
{"spark.app.audience.database":"$AUD_DATABASE"},
{"spark.executor.memoryOverhead":"2500"}
],
"artifact": "AudiencesPipeline",
"packages": "mysql:mysql-connector-java:5.1.46"
}"""
INTEGRITY_JOB_FLAG = True if config["INTEGRITY_JOB_FLAG"] else False
ETL_JOB_FLAG = True if config["ETL_JOB_FLAG"] else False
SAVE_TO_DB_FLAG = True if config["SAVE_TO_DB_FLAG"] else False
global_job_steps = "[" + step_integrity + "," + step_etl + "," + step_save_to_db + "]"
if INTEGRITY_JOB_FLAG == True and ETL_JOB_FLAG == False and SAVE_TO_DB_FLAG == False:
global_job_steps = "[" + step_integrity + "]"
elif INTEGRITY_JOB_FLAG == False and ETL_JOB_FLAG == True and SAVE_TO_DB_FLAG == False:
global_job_steps = "[" + step_etl + "]"
elif INTEGRITY_JOB_FLAG == False and ETL_JOB_FLAG == False and SAVE_TO_DB_FLAG == True:
global_job_steps = "[" + step_save_to_db + "]"
elif INTEGRITY_JOB_FLAG == True and ETL_JOB_FLAG == True and SAVE_TO_DB_FLAG == False:
global_job_steps = "[" + step_integrity + "," + step_etl + "]"
elif INTEGRITY_JOB_FLAG == False and ETL_JOB_FLAG == True and SAVE_TO_DB_FLAG == True:
global_job_steps = "[" + step_etl + "," + step_save_to_db + "]"
elif INTEGRITY_JOB_FLAG == True and ETL_JOB_FLAG == True and SAVE_TO_DB_FLAG == True:
global_job_steps = "[" + step_integrity + "," + step_etl + "," + step_save_to_db + "]"
else:
LOG.error("Please check the job configurations...")
# cluster level parameters (optional)
cluster_args = {
"cluster-name": CLUSTER_NAME,
"audience-config-file": "primary_audience_global_ind_conf",
"master-instance-types": "m5.2xlarge,m5.4xlarge",
"core-instance-types": "m5.2xlarge,m5.4xlarge",
"task-instance-types": "m5.2xlarge,m5.4xlarge",
"core-instance-capacity": NUM_CORE_NODES,
"task-instance-capacity": NUM_TASK_NODES,
"emr-version": EMR_VERSION,
"audience-load-bootstrap": True
}
# set config variables in emr-steps
emr_steps = set_config_variable_in_emr_steps(global_job_steps, config)
# dag parameter
dag_args = {
'owner': 'data.engineers@viooh.com',
'start_date': days_ago(1)
}
dag = DAG(
dag_id,
schedule_interval=None, # cron expression
default_args=dag_args)
build_dag(emr_steps=emr_steps, dag=dag, cluster_args=cluster_args)
|