Source code for airflow.providers.amazon.aws.transfers.hive_to_dynamodb
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"""This module contains operator to move data from Hive to DynamoDB."""
import json
from typing import TYPE_CHECKING, Callable, Optional, Sequence
from airflow.models import BaseOperator
from airflow.providers.amazon.aws.hooks.dynamodb import AwsDynamoDBHook
from airflow.providers.apache.hive.hooks.hive import HiveServer2Hook
if TYPE_CHECKING:
from airflow.utils.context import Context
[docs]class HiveToDynamoDBOperator(BaseOperator):
"""
Moves data from Hive to DynamoDB, note that for now the data is loaded
into memory before being pushed to DynamoDB, so this operator should
be used for smallish amount of data.
:param sql: SQL query to execute against the hive database. (templated)
:type sql: str
:param table_name: target DynamoDB table
:type table_name: str
:param table_keys: partition key and sort key
:type table_keys: list
:param pre_process: implement pre-processing of source data
:type pre_process: function
:param pre_process_args: list of pre_process function arguments
:type pre_process_args: list
:param pre_process_kwargs: dict of pre_process function arguments
:type pre_process_kwargs: dict
:param region_name: aws region name (example: us-east-1)
:type region_name: str
:param schema: hive database schema
:type schema: str
:param hiveserver2_conn_id: Reference to the
:ref: `Hive Server2 thrift service connection id <howto/connection:hiveserver2>`.
:type hiveserver2_conn_id: str
:param aws_conn_id: aws connection
:type aws_conn_id: str
"""
[docs] template_fields: Sequence[str] = ('sql',)
[docs] template_ext: Sequence[str] = ('.sql',)
def __init__(
self,
*,
sql: str,
table_name: str,
table_keys: list,
pre_process: Optional[Callable] = None,
pre_process_args: Optional[list] = None,
pre_process_kwargs: Optional[list] = None,
region_name: Optional[str] = None,
schema: str = 'default',
hiveserver2_conn_id: str = 'hiveserver2_default',
aws_conn_id: str = 'aws_default',
**kwargs,
) -> None:
super().__init__(**kwargs)
self.sql = sql
self.table_name = table_name
self.table_keys = table_keys
self.pre_process = pre_process
self.pre_process_args = pre_process_args
self.pre_process_kwargs = pre_process_kwargs
self.region_name = region_name
self.schema = schema
self.hiveserver2_conn_id = hiveserver2_conn_id
self.aws_conn_id = aws_conn_id
[docs] def execute(self, context: 'Context'):
hive = HiveServer2Hook(hiveserver2_conn_id=self.hiveserver2_conn_id)
self.log.info('Extracting data from Hive')
self.log.info(self.sql)
data = hive.get_pandas_df(self.sql, schema=self.schema)
dynamodb = AwsDynamoDBHook(
aws_conn_id=self.aws_conn_id,
table_name=self.table_name,
table_keys=self.table_keys,
region_name=self.region_name,
)
self.log.info('Inserting rows into dynamodb')
if self.pre_process is None:
dynamodb.write_batch_data(json.loads(data.to_json(orient='records')))
else:
dynamodb.write_batch_data(
self.pre_process(data=data, args=self.pre_process_args, kwargs=self.pre_process_kwargs)
)
self.log.info('Done.')