import pendulum from airflow import DAG from cdh.airflow import global_default_args from datetime import datetime
from datetime import datetime from airflow import DAG import pendulum from cdh.airflow import global_default_args
from cdh.variables import CDH_DAG_PREFIX, ... from cdh.variables import LSE_ADL_ROOT from cdh.airflow.sensors.adf_activity_run_sensor import ADFActivityRunSensor from cdh.py.dl_raw import partitioned from cdh.airflow.operators.cdh_hive_operator import CDHHiveOperator from cdh.airflow.sensors.cdh_table_source_file_is_ready_sensor import cdhTableSourceFileIsReadySensor from cdh.py.dl_raw import unpartitioned from cdh.airflow.operators.cdh_access_rights_operator import CDHAccessRightsOperator from cdh.airflow.operators.cdh_load_status_operator import CDHLoadStatusOperator from cdh.airflow.operators.cdh_compute_stats_operator import CDHComputeStatsOperator from cdh.airflow import global_default_args
from cdh.airflow import global_default_args from cdh.airflow.operators.cdh_access_rights_operator import CDHAccessRightsOperator from cdh.airflow.operators.cdh_compute_stats_operator import CDHComputeStatsOperator from cdh.airflow.operators.cdh_hive_operator import CDHHiveOperator from cdh.airflow.operators.cdh_load_status_operator import CDHLoadStatusOperator from cdh.airflow.sensors.adf_activity_run_sensor import ADFActivityRunSensor from cdh.airflow.sensors.cdh_table_source_file_is_ready_sensor import CDHTableSourceFileIsReadySensor from cdh.py.dl_raw import partitioned from cdh.py.dl_raw import unpartitioned from cdh.variables import CDH_DAG_PREFIX, ...
from cdh.variables import CDH_DAG_PREFIX, CDH_SCHEMA_PREFIX, CDH_WAREHOUSE_ROOT, DATA_FACTORY_V2, \ DATA_FACTORY_V1, HDL_TASK_PREFIX, CDH_INGRESS_ROOT, CDH_ENV_NAME, LOCAL_TZ
from cdh.variables import ( DATA_FACTORY_V1, DATA_FACTORY_V2, CDH_DAG_PREFIX, CDH_INGRESS_ROOT, CDH_SCHEMA_PREFIX, CDH_TASK_PREFIX, CDH_WAREHOUSE_ROOT, LOCAL_TZ, )
import ...
tuple_fields = "cdh_target_schema_name ..."
def test():
return
import ...
TUPLE_FIELDS = "cdh_target_schema_name ..."
def test():
return
self.creds_info = dss_api.get_credential(cred_name=self.cluster_name, cred_type="cdh")
self.credential_info = dss_api.get_credential( credential_name=self.cluster_name, credential_type="cdh", )
PartitionedTable = collections.namedtuple("PartitionedTable", ("cdh_target_schema_name cdh_target_table_name adf_activity_name adf_name " "adf_pipeline_name do_not_deduplicate primary_key_columns_list " "primary_key_sort_columns_list on_insert_sort_by min_adf_completion_count"))
PartitionedTable = collections.namedtuple( "PartitionedTable", " ".join([ "adf_name", "adf_activity_name", "adf_pipeline_name", "do_not_deduplicate", "cdh_target_schema_name", "cdh_target_table_name", "min_adf_completion_count", "on_insert_sort_by", "primary_key_columns_list", "primary_key_sort_colums_list", ]) )
my_array = [element1,
element2,
element3,
]
my_array = [ element1, element2, # ... element4, ]
my_array = [ element1, element2, # ... element4]
def my_methods(param1, param2, param3, ):
def my_methods( param1, param2, param3, ):
def my_methods( param1, param2, param3):
def my_methods(param1, param2, ):
articles_ids = [ articles["id"] for articles in articles_list if articles["type"] == "A" ]
articles_ids = [ articles["headid"] for articles in articles_list if articles["type"] == "A" ]
# defining skip function def skip_fn(*args, **kwargs): ...
# Define a skip function. def skip_fn(*args, **kwargs): ...
def skip_fn(*args, **kwargs): """ Define a placeholder function for the skip operator. """ return True
def skip_fn(*args, **kwargs): """Define a placeholder function for the skip operator.""" return True
def compute_params(context): """ Passing date and environment parameters to ADF Pipeline :param context: ... :return: pDayPath, pMonthPath, pYearPath, pDatePath
"""
def compute_params(context): """Pass the date and environment parameters to ADF Pipeline. :param context: ... :return: pDayPath, pMonthPath, pYearPath, pDatePath """
def skip_fn(*args, **kwargs): """Placeholder function for the skip operator. :param args: :param kwargs: """ return True
def skip_fn(*args, **kwargs): """Placeholder function for the skip operator.""" return True
query = {"query": 'metrics_resourcemanager_clustermetrics_CL' '| where ClusterType_s == "spark" and TimeGenerated > ago(5m) and ClusterName_s ' 'contains ' "\"" + CLUSTER_NAME + "\"" '| sort by AggregatedValue desc| where AggregatedValue > 0'}
query = f"""metrics_resourcemanager_clustermetrics_CL | where ClusterType_s == "spark" and TimeGenerated > ago(5m) and ClusterName_s contains "{CLUSTER_NAME}" | sort by AggregatedValue desc| where AggregatedValue > 0 """
query = {"query": '...' '(contains ' "\"" + CLUSTER_NAME_A + "\"" ' or ' "\"" + CLUSTER_NAME_B + "\"" ' or' "\"" + CLUSTER_NAME_C + "\")"
'...'}
query = """metrics_resourcemanager_clustermetrics_CL | where ClusterType_s == "spark" and TimeGenerated > ago(5m) | and ( ClusterName_s contains "{}" or "{}" or"{}" ) | sort by AggregatedValue desc| where AggregatedValue > 0 """.format( CLUSTER_NAME_A,
CLUSTER_NAME_B,
CLUSTER_NAME_C,
)
LOAD = HDLPartitionedDecentralizedDeltaInsertOperator( num_partitions_per_batch=100, max_partitions_in_total=600, megabytes_per_reducer_on_finalize=128, )
PARTITIONED_TABLE = PartitionedTable( num_partitions_per_batch=100, max_partitions_in_total=600, megabytes_per_reducer_on_finalize=128, )
LOAD = HDLPartitionedDecentralizedDeltaInsertOperator( num_partitions_per_batch=PARTITIONED_TABLE.num_partitions_per_batch, max_partitions_in_total=PARTITIONED_TABLE.max_partitions_in_total, megabytes_per_reducer_on_finalize=PARTITIONED_TABLE.megabytes_per_reducer_on_finalize, )
from airflow import DAG with DAG(...) as dag: loo = ... insert = ... loo >> insert dag.doc_md = __doc__ # The end of the file is here.
from airflow import DAG with DAG(...) as dag: loo = ... insert = ... loo >> insert dag.doc_md = __doc__ # Leave a new blank line with no content here as the end of the file.