airflow presto_to_gcs 源码
airflow presto_to_gcs 代码
文件路径:/airflow/providers/google/cloud/transfers/presto_to_gcs.py
#
# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not use this file except in compliance
# with the License. You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
# KIND, either express or implied. See the License for the
# specific language governing permissions and limitations
# under the License.
from __future__ import annotations
from typing import Any
from prestodb.client import PrestoResult
from prestodb.dbapi import Cursor as PrestoCursor
from airflow.providers.google.cloud.transfers.sql_to_gcs import BaseSQLToGCSOperator
from airflow.providers.presto.hooks.presto import PrestoHook
class _PrestoToGCSPrestoCursorAdapter:
"""
An adapter that adds additional feature to the Presto cursor.
The implementation of cursor in the prestodb library is not sufficient.
The following changes have been made:
* The poke mechanism for row. You can look at the next row without consuming it.
* The description attribute is available before reading the first row. Thanks to the poke mechanism.
* the iterator interface has been implemented.
A detailed description of the class methods is available in
`PEP-249 <https://www.python.org/dev/peps/pep-0249/>`__.
"""
def __init__(self, cursor: PrestoCursor):
self.cursor: PrestoCursor = cursor
self.rows: list[Any] = []
self.initialized: bool = False
@property
def description(self) -> list[tuple]:
"""
This read-only attribute is a sequence of 7-item sequences.
Each of these sequences contains information describing one result column:
* ``name``
* ``type_code``
* ``display_size``
* ``internal_size``
* ``precision``
* ``scale``
* ``null_ok``
The first two items (``name`` and ``type_code``) are mandatory, the other
five are optional and are set to None if no meaningful values can be provided.
"""
if not self.initialized:
# Peek for first row to load description.
self.peekone()
return self.cursor.description
@property
def rowcount(self) -> int:
"""The read-only attribute specifies the number of rows"""
return self.cursor.rowcount
def close(self) -> None:
"""Close the cursor now"""
self.cursor.close()
def execute(self, *args, **kwargs) -> PrestoResult:
"""Prepare and execute a database operation (query or command)."""
self.initialized = False
self.rows = []
return self.cursor.execute(*args, **kwargs)
def executemany(self, *args, **kwargs):
"""
Prepare a database operation (query or command) and then execute it against all parameter
sequences or mappings found in the sequence seq_of_parameters.
"""
self.initialized = False
self.rows = []
return self.cursor.executemany(*args, **kwargs)
def peekone(self) -> Any:
"""Return the next row without consuming it."""
self.initialized = True
element = self.cursor.fetchone()
self.rows.insert(0, element)
return element
def fetchone(self) -> Any:
"""
Fetch the next row of a query result set, returning a single sequence, or
``None`` when no more data is available.
"""
if self.rows:
return self.rows.pop(0)
return self.cursor.fetchone()
def fetchmany(self, size=None) -> list:
"""
Fetch the next set of rows of a query result, returning a sequence of sequences
(e.g. a list of tuples). An empty sequence is returned when no more rows are available.
"""
if size is None:
size = self.cursor.arraysize
result = []
for _ in range(size):
row = self.fetchone()
if row is None:
break
result.append(row)
return result
def __next__(self) -> Any:
"""
Return the next row from the currently executing SQL statement using the same semantics as
``.fetchone()``. A ``StopIteration`` exception is raised when the result set is exhausted.
:return:
"""
result = self.fetchone()
if result is None:
raise StopIteration()
return result
def __iter__(self) -> _PrestoToGCSPrestoCursorAdapter:
"""Return self to make cursors compatible to the iteration protocol"""
return self
class PrestoToGCSOperator(BaseSQLToGCSOperator):
"""Copy data from PrestoDB to Google Cloud Storage in JSON, CSV or Parquet format.
:param presto_conn_id: Reference to a specific Presto hook.
"""
ui_color = "#a0e08c"
type_map = {
"BOOLEAN": "BOOL",
"TINYINT": "INT64",
"SMALLINT": "INT64",
"INTEGER": "INT64",
"BIGINT": "INT64",
"REAL": "FLOAT64",
"DOUBLE": "FLOAT64",
"DECIMAL": "NUMERIC",
"VARCHAR": "STRING",
"CHAR": "STRING",
"VARBINARY": "BYTES",
"JSON": "STRING",
"DATE": "DATE",
"TIME": "TIME",
# BigQuery don't time with timezone native.
"TIME WITH TIME ZONE": "STRING",
"TIMESTAMP": "TIMESTAMP",
# BigQuery supports a narrow range of time zones during import.
# You should use TIMESTAMP function, if you want have TIMESTAMP type
"TIMESTAMP WITH TIME ZONE": "STRING",
"IPADDRESS": "STRING",
"UUID": "STRING",
}
def __init__(self, *, presto_conn_id: str = "presto_default", **kwargs):
super().__init__(**kwargs)
self.presto_conn_id = presto_conn_id
def query(self):
"""Queries presto and returns a cursor to the results."""
presto = PrestoHook(presto_conn_id=self.presto_conn_id)
conn = presto.get_conn()
cursor = conn.cursor()
self.log.info("Executing: %s", self.sql)
cursor.execute(self.sql)
return _PrestoToGCSPrestoCursorAdapter(cursor)
def field_to_bigquery(self, field) -> dict[str, str]:
"""Convert presto field type to BigQuery field type."""
clear_field_type = field[1].upper()
# remove type argument e.g. DECIMAL(2, 10) => DECIMAL
clear_field_type, _, _ = clear_field_type.partition("(")
new_field_type = self.type_map.get(clear_field_type, "STRING")
return {"name": field[0], "type": new_field_type}
def convert_type(self, value, schema_type, **kwargs):
"""
Do nothing. Presto uses JSON on the transport layer, so types are simple.
:param value: Presto column value
:param schema_type: BigQuery data type
"""
return value
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