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."""
from __future__ import annotations
import json
from typing import TYPE_CHECKING, Callable, Sequence
from airflow.models import BaseOperator
from airflow.providers.amazon.aws.hooks.dynamodb import DynamoDBHook
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.
.. seealso::
For more information on how to use this operator, take a look at the guide:
:ref:`howto/transfer:HiveToDynamoDBOperator`
:param sql: SQL query to execute against the hive database. (templated)
:param table_name: target DynamoDB table
:param table_keys: partition key and sort key
:param pre_process: implement pre-processing of source data
:param pre_process_args: list of pre_process function arguments
:param pre_process_kwargs: dict of pre_process function arguments
:param region_name: aws region name (example: us-east-1)
:param schema: hive database schema
:param hiveserver2_conn_id: Reference to the
:ref: `Hive Server2 thrift service connection id <howto/connection:hiveserver2>`.
:param aws_conn_id: aws connection
"""
[docs] template_fields: Sequence[str] = ("sql",)
[docs] template_ext: Sequence[str] = (".sql",)
[docs] template_fields_renderers = {"sql": "hql"}
def __init__(
self,
*,
sql: str,
table_name: str,
table_keys: list,
pre_process: Callable | None = None,
pre_process_args: list | None = None,
pre_process_kwargs: list | None = None,
region_name: str | None = 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 = DynamoDBHook(
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.")
