Apache Airflow Hive Provider

# Hook imports for connecting to Hive services
from airflow.providers.apache.hive.hooks.hive import HiveCliHook, HiveMetastoreHook, HiveServer2Hook

# Operator imports for executing tasks
from airflow.providers.apache.hive.operators.hive import HiveOperator
from airflow.providers.apache.hive.operators.hive_stats import HiveStatsCollectionOperator

# Sensor imports for monitoring conditions
from airflow.providers.apache.hive.sensors.hive_partition import HivePartitionSensor
from airflow.providers.apache.hive.sensors.metastore_partition import MetastorePartitionSensor
from airflow.providers.apache.hive.sensors.named_hive_partition import NamedHivePartitionSensor

# Transfer operator imports for data movement
from airflow.providers.apache.hive.transfers.mysql_to_hive import MySqlToHiveOperator
from airflow.providers.apache.hive.transfers.s3_to_hive import S3ToHiveOperator
from airflow.providers.apache.hive.transfers.hive_to_mysql import HiveToMySqlOperator
# Additional transfer operators available

# Macro imports for template functions
from airflow.providers.apache.hive.macros.hive import max_partition, closest_ds_partition

from datetime import datetime, timedelta
from airflow import DAG
from airflow.providers.apache.hive.operators.hive import HiveOperator
from airflow.providers.apache.hive.sensors.hive_partition import HivePartitionSensor

# Define DAG
dag = DAG(
    'hive_example',
    default_args={
        'owner': 'data-team',
        'depends_on_past': False,
        'start_date': datetime(2024, 1, 1),
        'retries': 1,
        'retry_delay': timedelta(minutes=5),
    },
    description='Example Hive data processing pipeline',
    schedule_interval=timedelta(days=1),
    catchup=False,
)

# Wait for partition to be available
wait_for_partition = HivePartitionSensor(
    task_id='wait_for_partition',
    table='warehouse.daily_sales',
    partition="ds='{{ ds }}'",
    metastore_conn_id='hive_metastore_default',
    poke_interval=300,
    timeout=3600,
    dag=dag,
)

# Execute Hive query
process_data = HiveOperator(
    task_id='process_daily_sales',
    hql='''
        INSERT OVERWRITE TABLE warehouse.sales_summary
        PARTITION (ds='{{ ds }}')
        SELECT 
            region,
            product_category,
            SUM(amount) as total_sales,
            COUNT(*) as transaction_count
        FROM warehouse.daily_sales
        WHERE ds='{{ ds }}'
        GROUP BY region, product_category;
    ''',
    hive_cli_conn_id='hive_cli_default',
    schema='warehouse',
    dag=dag,
)

# Set task dependencies
wait_for_partition >> process_data

class HiveCliHook:
    def __init__(self, hive_cli_conn_id: str = 'hive_cli_default', **kwargs): ...
    def run_cli(self, hql: str, schema: str = 'default') -> None: ...
    def test_hql(self, hql: str) -> None: ...
    def load_file(self, filepath: str, table: str, **kwargs) -> None: ...

class HiveMetastoreHook:
    def __init__(self, metastore_conn_id: str = 'metastore_default'): ...
    def check_for_partition(self, schema: str, table: str, partition: str) -> bool: ...
    def get_table(self, schema: str, table_name: str) -> Any: ...
    def get_partitions(self, schema: str, table_name: str, **kwargs) -> list: ...

class HiveServer2Hook:
    def __init__(self, hiveserver2_conn_id: str = 'hiveserver2_default', **kwargs): ...
    def get_conn(self, schema: str = None) -> Any: ...
    def get_pandas_df(self, sql: str, parameters: list = None, **kwargs) -> 'pd.DataFrame': ...

class HiveOperator:
    def __init__(self, *, hql: str, hive_cli_conn_id: str = 'hive_cli_default', **kwargs): ...
    def execute(self, context: 'Context') -> None: ...

class HiveStatsCollectionOperator:
    def __init__(self, *, table: str, partition: Any, **kwargs): ...
    def execute(self, context: 'Context') -> None: ...

class HivePartitionSensor:
    def __init__(self, *, table: str, partition: str = "ds='{{ ds }}'", **kwargs): ...
    def poke(self, context: 'Context') -> bool: ...

class NamedHivePartitionSensor:
    def __init__(self, *, partition_names: list[str], **kwargs): ...
    def poke(self, context: 'Context') -> bool: ...

class MetastorePartitionSensor:
    def __init__(self, *, table: str, partition_name: str, **kwargs): ...
    def poke(self, context: 'Context') -> bool: ...

class MySqlToHiveOperator:
    def __init__(self, *, sql: str, table: str, **kwargs): ...

class S3ToHiveOperator:
    def __init__(self, *, s3_source_key: str, table: str, **kwargs): ...

class HiveToMySqlOperator:
    def __init__(self, *, sql: str, mysql_table: str, **kwargs): ...

# Additional transfer operators: MsSqlToHiveOperator, VerticaToHiveOperator, HiveToSambaOperator

def max_partition(table: str, schema: str = 'default', field: str = None, **kwargs) -> str: ...
def closest_ds_partition(table: str, ds: str, before: bool = True, **kwargs) -> str | None: ...