from __future__ import annotations
import datetime
import signal
from dataclasses import dataclass
from enum import Enum
from typing import Any, Dict, List, Optional
import numpy as np
import pandas as pd
import pyarrow as pa
import trino
from trino.dbapi import Cursor
from trino.exceptions import TrinoQueryError
from feast.infra.offline_stores.contrib.trino_offline_store.trino_type_map import (
trino_to_pa_value_type,
)
[docs]class QueryStatus(Enum):
PENDING = 0
RUNNING = 1
ERROR = 2
COMPLETED = 3
CANCELLED = 4
[docs]class Trino:
def __init__(
self,
host: str,
port: int,
user: str,
catalog: str,
source: Optional[str],
http_scheme: str,
verify: bool,
extra_credential: Optional[str],
auth: Optional[trino.Authentication],
):
self.host = host
self.port = port
self.user = user
self.catalog = catalog
self.source = source
self.http_scheme = http_scheme
self.verify = verify
self.extra_credential = extra_credential
self.auth = auth
self._cursor: Optional[Cursor] = None
def _get_cursor(self) -> Cursor:
if self._cursor is None:
headers = (
{trino.constants.HEADER_EXTRA_CREDENTIAL: self.extra_credential}
if self.extra_credential
else {}
)
self._cursor = trino.dbapi.connect(
host=self.host,
port=self.port,
user=self.user,
catalog=self.catalog,
source=self.source,
http_scheme=self.http_scheme,
verify=self.verify,
auth=self.auth,
http_headers=headers,
).cursor()
return self._cursor
[docs] def create_query(self, query_text: str) -> Query:
"""
Create a Query object without executing it.
"""
return Query(query_text=query_text, cursor=self._get_cursor())
[docs] def execute_query(self, query_text: str) -> Results:
"""
Create a Query object and execute it.
"""
query = Query(query_text=query_text, cursor=self._get_cursor())
return query.execute()
[docs]class Query(object):
def __init__(self, query_text: str, cursor: Cursor):
self.query_text = query_text
self.status = QueryStatus.PENDING
self._cursor = cursor
signal.signal(signal.SIGINT, self.cancel)
signal.signal(signal.SIGTERM, self.cancel)
[docs] def execute(self) -> Results:
try:
self.status = QueryStatus.RUNNING
start_time = datetime.datetime.utcnow()
self._cursor.execute(operation=self.query_text)
rows = self._cursor.fetchall()
end_time = datetime.datetime.utcnow()
self.execution_time = end_time - start_time
self.status = QueryStatus.COMPLETED
return Results(data=rows, columns=self._cursor._query.columns)
except TrinoQueryError as error:
self.status = QueryStatus.ERROR
raise error
finally:
self.close()
[docs] def close(self):
self._cursor.close()
[docs] def cancel(self, *args):
if self.status != QueryStatus.COMPLETED:
self._cursor.cancel()
self.status = QueryStatus.CANCELLED
self.close()
[docs]@dataclass
class Results:
"""Class for keeping track of the results of a Trino query"""
data: List[List[Any]]
columns: List[Dict]
@property
def columns_names(self) -> List[str]:
return [column["name"] for column in self.columns]
@property
def schema(self) -> Dict[str, str]:
return {column["name"]: column["type"] for column in self.columns}
@property
def pyarrow_schema(self) -> pa.Schema:
return pa.schema(
[
pa.field(column["name"], trino_to_pa_value_type(column["type"]))
for column in self.columns
]
)
[docs] def to_dataframe(self) -> pd.DataFrame:
df = pd.DataFrame(data=self.data, columns=self.columns_names)
for col_name, col_type in self.schema.items():
if col_type.startswith("timestamp"):
df[col_name] = pd.to_datetime(df[col_name])
return df.fillna(np.nan)