mirror of
https://github.com/hanzo-ds/connect.git
synced 2026-10-30 20:31:24 +00:00
zeekay
75dd1132bd
The wire protocol was the last holdout and it was not cosmetic: the Hanzo Datastore server reads X-Datastore-User, and answers a request bearing X-ClickHouse-User with 401. Verified against the live server, both directions. So a client still sending the old headers is not merely off-brand, it cannot authenticate over HTTP. Everything else follows: types, dialects, error modules, docstrings and doc links now name Datastore, and doc URLs point at docs.hanzo.ai/datastore rather than the upstream vendor's site. Zero occurrences of the old name remain. Still cut from the pinned upstream version, so behaviour is unchanged.
876 lines
47 KiB
Python
876 lines
47 KiB
Python
import io
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import logging
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from datetime import tzinfo
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import pytz
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from abc import ABC, abstractmethod
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from typing import Iterable, Optional, Any, Union, Sequence, Dict, Generator, BinaryIO
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from pytz.exceptions import UnknownTimeZoneError
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from datastore_connect import common
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from datastore_connect.common import version
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from datastore_connect.datatypes.registry import get_from_name
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from datastore_connect.datatypes.base import DatastoreType
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from datastore_connect.datatypes import dynamic as dynamic_module
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from datastore_connect.driver import tzutil
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from datastore_connect.driver.common import dict_copy, StreamContext, coerce_int, coerce_bool
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from datastore_connect.driver.constants import CH_VERSION_WITH_PROTOCOL, PROTOCOL_VERSION_WITH_LOW_CARD
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from datastore_connect.driver.exceptions import ProgrammingError, OperationalError
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from datastore_connect.driver.external import ExternalData
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from datastore_connect.driver.insert import InsertContext
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from datastore_connect.driver.options import check_arrow, check_pandas, check_numpy
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from datastore_connect.driver.summary import QuerySummary
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from datastore_connect.driver.models import ColumnDef, SettingDef, SettingStatus
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from datastore_connect.driver.query import QueryResult, to_arrow, to_arrow_batches, QueryContext, arrow_buffer
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from datastore_connect.driver.binding import quote_identifier
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io.DEFAULT_BUFFER_SIZE = 1024 * 256
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logger = logging.getLogger(__name__)
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arrow_str_setting = 'output_format_arrow_string_as_string'
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# pylint: disable=too-many-public-methods,too-many-arguments,too-many-positional-arguments,too-many-instance-attributes
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class Client(ABC):
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"""
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Base Datastore Connect client
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"""
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compression: str = None
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write_compression: str = None
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protocol_version = 0
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valid_transport_settings = set()
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optional_transport_settings = set()
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database = None
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max_error_message = 0
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apply_server_timezone = False
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show_datastore_errors = True
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def __init__(self,
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database: str,
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query_limit: int,
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uri: str,
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query_retries: int,
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server_host_name: Optional[str],
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apply_server_timezone: Optional[Union[str, bool]],
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show_datastore_errors: Optional[bool]):
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"""
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Shared initialization of Datastore Connect client
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:param database: database name
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:param query_limit: default LIMIT for queries
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:param uri: uri for error messages
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"""
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self.query_limit = coerce_int(query_limit)
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self.query_retries = coerce_int(query_retries)
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if database and not database == '__default__':
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self.database = database
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if show_datastore_errors is not None:
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self.show_datastore_errors = coerce_bool(show_datastore_errors)
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self.server_host_name = server_host_name
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self.uri = uri
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self._init_common_settings(apply_server_timezone)
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def _init_common_settings(self, apply_server_timezone: Optional[Union[str, bool]]):
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self.server_tz, dst_safe = pytz.UTC, True
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self.server_version, server_tz = \
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tuple(self.command('SELECT version(), timezone()', use_database=False))
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try:
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server_tz = pytz.timezone(server_tz)
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server_tz, dst_safe = tzutil.normalize_timezone(server_tz)
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if apply_server_timezone is None:
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apply_server_timezone = dst_safe
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self.apply_server_timezone = apply_server_timezone == 'always' or coerce_bool(apply_server_timezone)
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self.server_tz = server_tz
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except UnknownTimeZoneError:
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logger.warning('Warning, server is using an unrecognized timezone %s, will use UTC default', server_tz)
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if not self.apply_server_timezone and not tzutil.local_tz_dst_safe:
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logger.warning('local timezone %s may return unexpected times due to Daylight Savings Time/' +
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'Summer Time differences', tzutil.local_tz.tzname(None))
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readonly = 'readonly'
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if not self.min_version('19.17'):
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readonly = common.get_setting('readonly')
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server_settings = self.query(f'SELECT name, value, {readonly} as readonly FROM system.settings LIMIT 10000')
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self.server_settings = {row['name']: SettingDef(**row) for row in server_settings.named_results()}
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if self.min_version(CH_VERSION_WITH_PROTOCOL) and common.get_setting('use_protocol_version'):
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# Unfortunately we have to validate that the client protocol version is actually used by Datastore
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# since the query parameter could be stripped off (in particular, by CHProxy)
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test_data = self.raw_query('SELECT 1 AS check', fmt='Native', settings={
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'client_protocol_version': PROTOCOL_VERSION_WITH_LOW_CARD
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})
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if test_data[8:16] == b'\x01\x01\x05check':
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self.protocol_version = PROTOCOL_VERSION_WITH_LOW_CARD
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if self._setting_status('date_time_input_format').is_writable:
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self.set_client_setting('date_time_input_format', 'best_effort')
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if self._setting_status('allow_experimental_json_type').is_set and \
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self._setting_status('cast_string_to_dynamic_use_inference').is_writable:
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self.set_client_setting('cast_string_to_dynamic_use_inference', '1')
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if self.min_version('24.8') and not self.min_version('24.10'):
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dynamic_module.json_serialization_format = 0
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def _validate_settings(self, settings: Optional[Dict[str, Any]]) -> Dict[str, str]:
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"""
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This strips any Datastore settings that are not recognized or are read only.
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:param settings: Dictionary of setting name and values
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:return: A filtered dictionary of settings with values rendered as strings
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"""
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validated = {}
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invalid_action = common.get_setting('invalid_setting_action')
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for key, value in settings.items():
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str_value = self._validate_setting(key, value, invalid_action)
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if str_value is not None:
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validated[key] = value
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return validated
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def _validate_setting(self, key: str, value: Any, invalid_action: str) -> Optional[str]:
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str_value = str(value)
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if value is True:
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str_value = '1'
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elif value is False:
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str_value = '0'
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if key not in self.valid_transport_settings:
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setting_def = self.server_settings.get(key)
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current_setting = self.get_client_setting(key)
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if setting_def and setting_def.value == str_value and (current_setting is None or current_setting == setting_def.value):
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return None # don't send settings that are already the expected value
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if setting_def is None or setting_def.readonly:
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if key in self.optional_transport_settings:
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return None
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if invalid_action == 'send':
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logger.warning('Attempting to send unrecognized or readonly setting %s', key)
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elif invalid_action == 'drop':
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logger.warning('Dropping unrecognized or readonly settings %s', key)
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return None
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else:
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raise ProgrammingError(f'Setting {key} is unknown or readonly') from None
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return str_value
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def _setting_status(self, key: str) -> SettingStatus:
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comp_setting = self.server_settings.get(key)
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if not comp_setting:
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return SettingStatus(False, False)
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return SettingStatus(comp_setting.value != '0', comp_setting.readonly != 1)
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def _prep_query(self, context: QueryContext):
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if context.is_select and not context.has_limit and self.query_limit:
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limit = f'\n LIMIT {self.query_limit}'
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if isinstance(context.query, bytes):
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return context.final_query + limit.encode()
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return context.final_query + limit
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return context.final_query
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def _check_tz_change(self, new_tz) -> Optional[tzinfo]:
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if new_tz:
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try:
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new_tzinfo = pytz.timezone(new_tz)
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if new_tzinfo != self.server_tz:
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return new_tzinfo
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except UnknownTimeZoneError:
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logger.warning('Unrecognized timezone %s received from Datastore', new_tz)
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return None
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@abstractmethod
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def _query_with_context(self, context: QueryContext):
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pass
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@abstractmethod
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def set_client_setting(self, key, value):
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"""
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Set a datastore setting for the client after initialization. If a setting is not recognized by Datastore,
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or the setting is identified as "read_only", this call will either throw a Programming exception or attempt
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to send the setting anyway based on the common setting 'invalid_setting_action'
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:param key: Datastore setting name
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:param value: Datastore setting value
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"""
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@abstractmethod
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def get_client_setting(self, key) -> Optional[str]:
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"""
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:param key: The setting key
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:return: The string value of the setting, if it exists, or None
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"""
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@abstractmethod
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def set_access_token(self, access_token: str):
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"""
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Set the Datastore access token for the client
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:param access_token: Access token string
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"""
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# pylint: disable=unused-argument,too-many-locals
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def query(self,
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query: Optional[str] = None,
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parameters: Optional[Union[Sequence, Dict[str, Any]]] = None,
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settings: Optional[Dict[str, Any]] = None,
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query_formats: Optional[Dict[str, str]] = None,
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column_formats: Optional[Dict[str, Union[str, Dict[str, str]]]] = None,
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encoding: Optional[str] = None,
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use_none: Optional[bool] = None,
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column_oriented: Optional[bool] = None,
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use_numpy: Optional[bool] = None,
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max_str_len: Optional[int] = None,
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context: QueryContext = None,
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query_tz: Optional[Union[str, tzinfo]] = None,
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column_tzs: Optional[Dict[str, Union[str, tzinfo]]] = None,
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external_data: Optional[ExternalData] = None,
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transport_settings: Optional[Dict[str, str]] = None) -> QueryResult:
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"""
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Main query method for SELECT, DESCRIBE and other SQL statements that return a result matrix. For
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parameters, see the create_query_context method
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:return: QueryResult -- data and metadata from response
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"""
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if query and query.lower().strip().startswith('select __connect_version__'):
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return QueryResult([[f'Datastore Connect v.{version()} ⓒ Datastore Inc.']], None,
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('connect_version',), (get_from_name('String'),))
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kwargs = locals().copy()
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del kwargs['self']
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query_context = self.create_query_context(**kwargs)
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if query_context.is_command:
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response = self.command(query,
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parameters=query_context.parameters,
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settings=query_context.settings,
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external_data=query_context.external_data,
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transport_settings=query_context.transport_settings)
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if isinstance(response, QuerySummary):
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return response.as_query_result()
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return QueryResult([response] if isinstance(response, list) else [[response]])
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return self._query_with_context(query_context)
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def query_column_block_stream(self,
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query: Optional[str] = None,
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parameters: Optional[Union[Sequence, Dict[str, Any]]] = None,
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settings: Optional[Dict[str, Any]] = None,
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query_formats: Optional[Dict[str, str]] = None,
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column_formats: Optional[Dict[str, Union[str, Dict[str, str]]]] = None,
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encoding: Optional[str] = None,
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use_none: Optional[bool] = None,
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context: QueryContext = None,
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query_tz: Optional[Union[str, tzinfo]] = None,
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column_tzs: Optional[Dict[str, Union[str, tzinfo]]] = None,
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external_data: Optional[ExternalData] = None,
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transport_settings: Optional[Dict[str, str]] = None) -> StreamContext:
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"""
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Variation of main query method that returns a stream of column oriented blocks. For
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parameters, see the create_query_context method.
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:return: StreamContext -- Iterable stream context that returns column oriented blocks
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"""
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return self._context_query(locals(), use_numpy=False, streaming=True).column_block_stream
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def query_row_block_stream(self,
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query: Optional[str] = None,
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parameters: Optional[Union[Sequence, Dict[str, Any]]] = None,
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settings: Optional[Dict[str, Any]] = None,
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query_formats: Optional[Dict[str, str]] = None,
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column_formats: Optional[Dict[str, Union[str, Dict[str, str]]]] = None,
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encoding: Optional[str] = None,
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use_none: Optional[bool] = None,
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context: QueryContext = None,
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query_tz: Optional[Union[str, tzinfo]] = None,
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column_tzs: Optional[Dict[str, Union[str, tzinfo]]] = None,
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external_data: Optional[ExternalData] = None,
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transport_settings: Optional[Dict[str, str]] = None) -> StreamContext:
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"""
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Variation of main query method that returns a stream of row oriented blocks. For
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parameters, see the create_query_context method.
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:return: StreamContext -- Iterable stream context that returns blocks of rows
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"""
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return self._context_query(locals(), use_numpy=False, streaming=True).row_block_stream
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def query_rows_stream(self,
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query: Optional[str] = None,
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parameters: Optional[Union[Sequence, Dict[str, Any]]] = None,
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settings: Optional[Dict[str, Any]] = None,
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query_formats: Optional[Dict[str, str]] = None,
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column_formats: Optional[Dict[str, Union[str, Dict[str, str]]]] = None,
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encoding: Optional[str] = None,
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use_none: Optional[bool] = None,
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context: QueryContext = None,
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query_tz: Optional[Union[str, tzinfo]] = None,
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column_tzs: Optional[Dict[str, Union[str, tzinfo]]] = None,
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external_data: Optional[ExternalData] = None,
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transport_settings: Optional[Dict[str, str]] = None) -> StreamContext:
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"""
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Variation of main query method that returns a stream of row oriented blocks. For
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parameters, see the create_query_context method.
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:return: StreamContext -- Iterable stream context that returns blocks of rows
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"""
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return self._context_query(locals(), use_numpy=False, streaming=True).rows_stream
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@abstractmethod
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def raw_query(self, query: str,
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parameters: Optional[Union[Sequence, Dict[str, Any]]] = None,
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settings: Optional[Dict[str, Any]] = None,
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fmt: str = None,
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use_database: bool = True,
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external_data: Optional[ExternalData] = None,
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transport_settings: Optional[Dict[str, str]] = None) -> bytes:
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"""
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Query method that simply returns the raw Datastore format bytes
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:param query: Query statement/format string
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:param parameters: Optional dictionary used to format the query
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:param settings: Optional dictionary of Datastore settings (key/string values)
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:param fmt: Datastore output format
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:param use_database: Send the database parameter to Datastore so the command will be executed in the client
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database context.
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:param external_data: External data to send with the query
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:param transport_settings: Optional dictionary of transport level settings (HTTP headers, etc.)
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:return: bytes representing raw Datastore return value based on format
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"""
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@abstractmethod
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def raw_stream(self, query: str,
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parameters: Optional[Union[Sequence, Dict[str, Any]]] = None,
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settings: Optional[Dict[str, Any]] = None,
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fmt: str = None,
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use_database: bool = True,
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external_data: Optional[ExternalData] = None,
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transport_settings: Optional[Dict[str, str]] = None) -> io.IOBase:
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"""
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Query method that returns the result as an io.IOBase iterator
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:param query: Query statement/format string
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:param parameters: Optional dictionary used to format the query
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:param settings: Optional dictionary of Datastore settings (key/string values)
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:param fmt: Datastore output format
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:param use_database Send the database parameter to Datastore so the command will be executed in the client
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database context.
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:param external_data: External data to send with the query.
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:param transport_settings: Optional dictionary of transport level settings (HTTP headers, etc.)
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:return: io.IOBase stream/iterator for the result
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"""
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# pylint: disable=duplicate-code,unused-argument
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def query_np(self,
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query: Optional[str] = None,
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parameters: Optional[Union[Sequence, Dict[str, Any]]] = None,
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settings: Optional[Dict[str, Any]] = None,
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query_formats: Optional[Dict[str, str]] = None,
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column_formats: Optional[Dict[str, str]] = None,
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encoding: Optional[str] = None,
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use_none: Optional[bool] = None,
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max_str_len: Optional[int] = None,
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context: QueryContext = None,
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external_data: Optional[ExternalData] = None,
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transport_settings: Optional[Dict[str, str]] = None):
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"""
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Query method that returns the results as a numpy array. For parameter values, see the
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create_query_context method
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:return: Numpy array representing the result set
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"""
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check_numpy()
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return self._context_query(locals(), use_numpy=True).np_result
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# pylint: disable=duplicate-code,too-many-arguments,unused-argument
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def query_np_stream(self,
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query: Optional[str] = None,
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parameters: Optional[Union[Sequence, Dict[str, Any]]] = None,
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settings: Optional[Dict[str, Any]] = None,
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query_formats: Optional[Dict[str, str]] = None,
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column_formats: Optional[Dict[str, str]] = None,
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encoding: Optional[str] = None,
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use_none: Optional[bool] = None,
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max_str_len: Optional[int] = None,
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context: QueryContext = None,
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external_data: Optional[ExternalData] = None,
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transport_settings: Optional[Dict[str, str]] = None) -> StreamContext:
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"""
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Query method that returns the results as a stream of numpy arrays. For parameter values, see the
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create_query_context method
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:return: Generator that yield a numpy array per block representing the result set
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"""
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check_numpy()
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return self._context_query(locals(), use_numpy=True, streaming=True).np_stream
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# pylint: disable=duplicate-code,unused-argument
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def query_df(self,
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query: Optional[str] = None,
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parameters: Optional[Union[Sequence, Dict[str, Any]]] = None,
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settings: Optional[Dict[str, Any]] = None,
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query_formats: Optional[Dict[str, str]] = None,
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column_formats: Optional[Dict[str, str]] = None,
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encoding: Optional[str] = None,
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use_none: Optional[bool] = None,
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max_str_len: Optional[int] = None,
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use_na_values: Optional[bool] = None,
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query_tz: Optional[str] = None,
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column_tzs: Optional[Dict[str, Union[str, tzinfo]]] = None,
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context: QueryContext = None,
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external_data: Optional[ExternalData] = None,
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use_extended_dtypes: Optional[bool] = None,
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transport_settings: Optional[Dict[str, str]] = None):
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"""
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Query method that results the results as a pandas dataframe. For parameter values, see the
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create_query_context method
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:return: Pandas dataframe representing the result set
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"""
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check_pandas()
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return self._context_query(locals(), use_numpy=True, as_pandas=True).df_result
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# pylint: disable=duplicate-code,unused-argument
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def query_df_stream(self,
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query: Optional[str] = None,
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parameters: Optional[Union[Sequence, Dict[str, Any]]] = None,
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settings: Optional[Dict[str, Any]] = None,
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query_formats: Optional[Dict[str, str]] = None,
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|
column_formats: Optional[Dict[str, str]] = None,
|
|
encoding: Optional[str] = None,
|
|
use_none: Optional[bool] = None,
|
|
max_str_len: Optional[int] = None,
|
|
use_na_values: Optional[bool] = None,
|
|
query_tz: Optional[str] = None,
|
|
column_tzs: Optional[Dict[str, Union[str, tzinfo]]] = None,
|
|
context: QueryContext = None,
|
|
external_data: Optional[ExternalData] = None,
|
|
use_extended_dtypes: Optional[bool] = None,
|
|
transport_settings: Optional[Dict[str, str]] = None) -> StreamContext:
|
|
"""
|
|
Query method that returns the results as a StreamContext. For parameter values, see the
|
|
create_query_context method
|
|
:return: Generator that yields a Pandas dataframe per block representing the result set
|
|
"""
|
|
check_pandas()
|
|
return self._context_query(locals(), use_numpy=True,
|
|
as_pandas=True,
|
|
streaming=True).df_stream
|
|
|
|
def create_query_context(self,
|
|
query: Optional[Union[str, bytes]] = None,
|
|
parameters: Optional[Union[Sequence, Dict[str, Any]]] = None,
|
|
settings: Optional[Dict[str, Any]] = None,
|
|
query_formats: Optional[Dict[str, str]] = None,
|
|
column_formats: Optional[Dict[str, Union[str, Dict[str, str]]]] = None,
|
|
encoding: Optional[str] = None,
|
|
use_none: Optional[bool] = None,
|
|
column_oriented: Optional[bool] = None,
|
|
use_numpy: Optional[bool] = False,
|
|
max_str_len: Optional[int] = 0,
|
|
context: Optional[QueryContext] = None,
|
|
query_tz: Optional[Union[str, tzinfo]] = None,
|
|
column_tzs: Optional[Dict[str, Union[str, tzinfo]]] = None,
|
|
use_na_values: Optional[bool] = None,
|
|
streaming: bool = False,
|
|
as_pandas: bool = False,
|
|
external_data: Optional[ExternalData] = None,
|
|
use_extended_dtypes: Optional[bool] = None,
|
|
transport_settings: Optional[Dict[str, str]] = None) -> QueryContext:
|
|
"""
|
|
Creates or updates a reusable QueryContext object
|
|
:param query: Query statement/format string
|
|
:param parameters: Optional dictionary used to format the query
|
|
:param settings: Optional dictionary of Datastore settings (key/string values)
|
|
:param query_formats: See QueryContext __init__ docstring
|
|
:param column_formats: See QueryContext __init__ docstring
|
|
:param encoding: See QueryContext __init__ docstring
|
|
:param use_none: Use None for Datastore NULL instead of default values. Note that using None in Numpy
|
|
arrays will force the numpy array dtype to 'object', which is often inefficient. This effect also
|
|
will impact the performance of Pandas dataframes.
|
|
:param column_oriented: Deprecated. Controls orientation of the QueryResult result_set property
|
|
:param use_numpy: Return QueryResult columns as one-dimensional numpy arrays
|
|
:param max_str_len: Limit returned Datastore String values to this length, which allows a Numpy
|
|
structured array even with Datastore variable length String columns. If 0, Numpy arrays for
|
|
String columns will always be object arrays
|
|
:param context: An existing QueryContext to be updated with any provided parameter values
|
|
:param query_tz: Either a string or a pytz tzinfo object. (Strings will be converted to tzinfo objects).
|
|
Values for any DateTime or DateTime64 column in the query will be converted to Python datetime.datetime
|
|
objects with the selected timezone.
|
|
:param column_tzs: A dictionary of column names to tzinfo objects (or strings that will be converted to
|
|
tzinfo objects). The timezone will be applied to datetime objects returned in the query
|
|
:param use_na_values: Deprecated alias for use_advanced_dtypes
|
|
:param as_pandas Return the result columns as pandas.Series objects
|
|
:param streaming Marker used to correctly configure streaming queries
|
|
:param external_data Datastore "external data" to send with query
|
|
:param use_extended_dtypes: Only relevant to Pandas Dataframe queries. Use Pandas "missing types", such as
|
|
pandas.NA and pandas.NaT for Datastore NULL values, as well as extended Pandas dtypes such as IntegerArray
|
|
and StringArray. Defaulted to True for query_df methods
|
|
:param transport_settings: Optional dictionary of transport level settings (HTTP headers, etc.)
|
|
:return: Reusable QueryContext
|
|
"""
|
|
if context:
|
|
return context.updated_copy(query=query,
|
|
parameters=parameters,
|
|
settings=settings,
|
|
query_formats=query_formats,
|
|
column_formats=column_formats,
|
|
encoding=encoding,
|
|
server_tz=self.server_tz,
|
|
use_none=use_none,
|
|
column_oriented=column_oriented,
|
|
use_numpy=use_numpy,
|
|
max_str_len=max_str_len,
|
|
query_tz=query_tz,
|
|
column_tzs=column_tzs,
|
|
as_pandas=as_pandas,
|
|
use_extended_dtypes=use_extended_dtypes,
|
|
streaming=streaming,
|
|
external_data=external_data,
|
|
transport_settings=transport_settings)
|
|
if use_numpy and max_str_len is None:
|
|
max_str_len = 0
|
|
if use_extended_dtypes is None:
|
|
use_extended_dtypes = use_na_values
|
|
if as_pandas and use_extended_dtypes is None:
|
|
use_extended_dtypes = True
|
|
return QueryContext(query=query,
|
|
parameters=parameters,
|
|
settings=settings,
|
|
query_formats=query_formats,
|
|
column_formats=column_formats,
|
|
encoding=encoding,
|
|
server_tz=self.server_tz,
|
|
use_none=use_none,
|
|
column_oriented=column_oriented,
|
|
use_numpy=use_numpy,
|
|
max_str_len=max_str_len,
|
|
query_tz=query_tz,
|
|
column_tzs=column_tzs,
|
|
use_extended_dtypes=use_extended_dtypes,
|
|
as_pandas=as_pandas,
|
|
streaming=streaming,
|
|
apply_server_tz=self.apply_server_timezone,
|
|
external_data=external_data,
|
|
transport_settings=transport_settings)
|
|
|
|
def query_arrow(self,
|
|
query: str,
|
|
parameters: Optional[Union[Sequence, Dict[str, Any]]] = None,
|
|
settings: Optional[Dict[str, Any]] = None,
|
|
use_strings: Optional[bool] = None,
|
|
external_data: Optional[ExternalData] = None,
|
|
transport_settings: Optional[Dict[str, str]] = None):
|
|
"""
|
|
Query method using the Datastore Arrow format to return a PyArrow table
|
|
:param query: Query statement/format string
|
|
:param parameters: Optional dictionary used to format the query
|
|
:param settings: Optional dictionary of Datastore settings (key/string values)
|
|
:param use_strings: Convert Datastore String type to Arrow string type (instead of binary)
|
|
:param external_data: Datastore "external data" to send with query
|
|
:param transport_settings: Optional dictionary of transport level settings (HTTP headers, etc.)
|
|
:return: PyArrow.Table
|
|
"""
|
|
check_arrow()
|
|
settings = self._update_arrow_settings(settings, use_strings)
|
|
return to_arrow(self.raw_query(query,
|
|
parameters,
|
|
settings,
|
|
fmt='Arrow',
|
|
external_data=external_data,
|
|
transport_settings=transport_settings))
|
|
|
|
def query_arrow_stream(self,
|
|
query: str,
|
|
parameters: Optional[Union[Sequence, Dict[str, Any]]] = None,
|
|
settings: Optional[Dict[str, Any]] = None,
|
|
use_strings: Optional[bool] = None,
|
|
external_data: Optional[ExternalData] = None,
|
|
transport_settings: Optional[Dict[str, str]] = None) -> StreamContext:
|
|
"""
|
|
Query method that returns the results as a stream of Arrow tables
|
|
:param query: Query statement/format string
|
|
:param parameters: Optional dictionary used to format the query
|
|
:param settings: Optional dictionary of Datastore settings (key/string values)
|
|
:param use_strings: Convert Datastore String type to Arrow string type (instead of binary)
|
|
:param external_data: Datastore "external data" to send with query
|
|
:param transport_settings: Optional dictionary of transport level settings (HTTP headers, etc.)
|
|
:return: Generator that yields a PyArrow.Table for per block representing the result set
|
|
"""
|
|
check_arrow()
|
|
settings = self._update_arrow_settings(settings, use_strings)
|
|
return to_arrow_batches(self.raw_stream(query,
|
|
parameters,
|
|
settings,
|
|
fmt='ArrowStream',
|
|
external_data=external_data,
|
|
transport_settings=transport_settings))
|
|
|
|
def _update_arrow_settings(self,
|
|
settings: Optional[Dict[str, Any]],
|
|
use_strings: Optional[bool]) -> Dict[str, Any]:
|
|
settings = dict_copy(settings)
|
|
if self.database:
|
|
settings['database'] = self.database
|
|
str_status = self._setting_status(arrow_str_setting)
|
|
if use_strings is None:
|
|
if str_status.is_writable and not str_status.is_set:
|
|
settings[arrow_str_setting] = '1' # Default to returning strings if possible
|
|
elif use_strings != str_status.is_set:
|
|
if not str_status.is_writable:
|
|
raise OperationalError(f'Cannot change readonly {arrow_str_setting} to {use_strings}')
|
|
settings[arrow_str_setting] = '1' if use_strings else '0'
|
|
return settings
|
|
|
|
@abstractmethod
|
|
def command(self,
|
|
cmd: str,
|
|
parameters: Optional[Union[Sequence, Dict[str, Any]]] = None,
|
|
data: Union[str, bytes] = None,
|
|
settings: Dict[str, Any] = None,
|
|
use_database: bool = True,
|
|
external_data: Optional[ExternalData] = None,
|
|
transport_settings: Optional[Dict[str, str]] = None) -> Union[str, int, Sequence[str], QuerySummary]:
|
|
"""
|
|
Client method that returns a single value instead of a result set
|
|
:param cmd: Datastore query/command as a python format string
|
|
:param parameters: Optional dictionary of key/values pairs to be formatted
|
|
:param data: Optional 'data' for the command (for INSERT INTO in particular)
|
|
:param settings: Optional dictionary of Datastore settings (key/string values)
|
|
:param use_database: Send the database parameter to Datastore so the command will be executed in the client
|
|
database context. Otherwise, no database will be specified with the command. This is useful for determining
|
|
the default user database
|
|
:param external_data: Datastore "external data" to send with command/query
|
|
:param transport_settings: Optional dictionary of transport level settings (HTTP headers, etc.)
|
|
:return: Decoded response from Datastore as either a string, int, or sequence of strings, or QuerySummary
|
|
if no data returned
|
|
"""
|
|
|
|
@abstractmethod
|
|
def ping(self) -> bool:
|
|
"""
|
|
Validate the connection, does not throw an Exception (see debug logs)
|
|
:return: Datastore server is up and reachable
|
|
"""
|
|
|
|
def insert(self,
|
|
table: Optional[str] = None,
|
|
data: Sequence[Sequence[Any]] = None,
|
|
column_names: Union[str, Iterable[str]] = '*',
|
|
database: Optional[str] = None,
|
|
column_types: Sequence[DatastoreType] = None,
|
|
column_type_names: Sequence[str] = None,
|
|
column_oriented: bool = False,
|
|
settings: Optional[Dict[str, Any]] = None,
|
|
context: InsertContext = None,
|
|
transport_settings: Optional[Dict[str, str]] = None) -> QuerySummary:
|
|
"""
|
|
Method to insert multiple rows/data matrix of native Python objects. If context is specified arguments
|
|
other than data are ignored
|
|
:param table: Target table
|
|
:param data: Sequence of sequences of Python data
|
|
:param column_names: Ordered list of column names or '*' if column types should be retrieved from the
|
|
Datastore table definition
|
|
:param database: Target database -- will use client default database if not specified.
|
|
:param column_types: Datastore column types. If set then column data does not need to be retrieved from
|
|
the server
|
|
:param column_type_names: Datastore column type names. If set then column data does not need to be
|
|
retrieved from the server
|
|
:param column_oriented: If true the data is already "pivoted" in column form
|
|
:param settings: Optional dictionary of Datastore settings (key/string values)
|
|
:param context: Optional reusable insert context to allow repeated inserts into the same table with
|
|
different data batches
|
|
:param transport_settings: Optional dictionary of transport level settings (HTTP headers, etc.)
|
|
:return: QuerySummary with summary information, throws exception if insert fails
|
|
"""
|
|
if (context is None or context.empty) and data is None:
|
|
raise ProgrammingError('No data specified for insert') from None
|
|
if context is None:
|
|
context = self.create_insert_context(table,
|
|
column_names,
|
|
database,
|
|
column_types,
|
|
column_type_names,
|
|
column_oriented,
|
|
settings,
|
|
transport_settings=transport_settings)
|
|
if data is not None:
|
|
if not context.empty:
|
|
raise ProgrammingError('Attempting to insert new data with non-empty insert context') from None
|
|
context.data = data
|
|
return self.data_insert(context)
|
|
|
|
def insert_df(self, table: str = None,
|
|
df=None,
|
|
database: Optional[str] = None,
|
|
settings: Optional[Dict] = None,
|
|
column_names: Optional[Sequence[str]] = None,
|
|
column_types: Sequence[DatastoreType] = None,
|
|
column_type_names: Sequence[str] = None,
|
|
context: InsertContext = None,
|
|
transport_settings: Optional[Dict[str, str]] = None) -> QuerySummary:
|
|
"""
|
|
Insert a pandas DataFrame into Datastore. If context is specified arguments other than df are ignored
|
|
:param table: Datastore table
|
|
:param df: two-dimensional pandas dataframe
|
|
:param database: Optional Datastore database
|
|
:param settings: Optional dictionary of Datastore settings (key/string values)
|
|
:param column_names: An optional list of Datastore column names. If not set, the DataFrame column names
|
|
will be used
|
|
:param column_types: Datastore column types. If set then column data does not need to be retrieved from
|
|
the server
|
|
:param column_type_names: Datastore column type names. If set then column data does not need to be
|
|
retrieved from the server
|
|
:param context: Optional reusable insert context to allow repeated inserts into the same table with
|
|
different data batches
|
|
:param transport_settings: Optional dictionary of transport level settings (HTTP headers, etc.)
|
|
:return: QuerySummary with summary information, throws exception if insert fails
|
|
"""
|
|
check_pandas()
|
|
if context is None:
|
|
if column_names is None:
|
|
column_names = df.columns
|
|
elif len(column_names) != len(df.columns):
|
|
raise ProgrammingError('DataFrame column count does not match insert_columns') from None
|
|
return self.insert(table,
|
|
df,
|
|
column_names,
|
|
database,
|
|
column_types=column_types,
|
|
column_type_names=column_type_names,
|
|
settings=settings,
|
|
transport_settings=transport_settings,
|
|
context=context)
|
|
|
|
def insert_arrow(self, table: str,
|
|
arrow_table,
|
|
database: str = None,
|
|
settings: Optional[Dict] = None,
|
|
transport_settings: Optional[Dict[str, str]] = None) -> QuerySummary:
|
|
"""
|
|
Insert a PyArrow table DataFrame into Datastore using raw Arrow format
|
|
:param table: Datastore table
|
|
:param arrow_table: PyArrow Table object
|
|
:param database: Optional Datastore database
|
|
:param settings: Optional dictionary of Datastore settings (key/string values)
|
|
:param transport_settings: Optional dictionary of transport level settings (HTTP headers, etc.)
|
|
"""
|
|
check_arrow()
|
|
full_table = table if '.' in table or not database else f'{database}.{table}'
|
|
compression = self.write_compression if self.write_compression in ('zstd', 'lz4') else None
|
|
column_names, insert_block = arrow_buffer(arrow_table, compression)
|
|
return self.raw_insert(full_table, column_names, insert_block, settings, 'Arrow', transport_settings)
|
|
|
|
def create_insert_context(self,
|
|
table: str,
|
|
column_names: Optional[Union[str, Sequence[str]]] = None,
|
|
database: Optional[str] = None,
|
|
column_types: Sequence[DatastoreType] = None,
|
|
column_type_names: Sequence[str] = None,
|
|
column_oriented: bool = False,
|
|
settings: Optional[Dict[str, Any]] = None,
|
|
data: Optional[Sequence[Sequence[Any]]] = None,
|
|
transport_settings: Optional[Dict[str, str]] = None) -> InsertContext:
|
|
"""
|
|
Builds a reusable insert context to hold state for a duration of an insert
|
|
:param table: Target table
|
|
:param database: Target database. If not set, uses the client default database
|
|
:param column_names: Optional ordered list of column names. If not set, all columns ('*') will be assumed
|
|
in the order specified by the table definition
|
|
:param database: Target database -- will use client default database if not specified
|
|
:param column_types: Datastore column types. Optional Sequence of DatastoreType objects. If neither column
|
|
types nor column type names are set, actual column types will be retrieved from the server.
|
|
:param column_type_names: Datastore column type names. Specified column types by name string
|
|
:param column_oriented: If true the data is already "pivoted" in column form
|
|
:param settings: Optional dictionary of Datastore settings (key/string values)
|
|
:param data: Initial dataset for insert
|
|
:param transport_settings: Optional dictionary of transport level settings (HTTP headers, etc.)
|
|
:return: Reusable insert context
|
|
"""
|
|
full_table = table
|
|
if '.' not in table:
|
|
if database:
|
|
full_table = f'{quote_identifier(database)}.{quote_identifier(table)}'
|
|
else:
|
|
full_table = quote_identifier(table)
|
|
column_defs = []
|
|
if column_types is None and column_type_names is None:
|
|
describe_result = self.query(f'DESCRIBE TABLE {full_table}')
|
|
column_defs = [ColumnDef(**row) for row in describe_result.named_results()
|
|
if row['default_type'] not in ('ALIAS', 'MATERIALIZED')]
|
|
if column_names is None or isinstance(column_names, str) and column_names == '*':
|
|
column_names = [cd.name for cd in column_defs]
|
|
column_types = [cd.ch_type for cd in column_defs]
|
|
elif isinstance(column_names, str):
|
|
column_names = [column_names]
|
|
if len(column_names) == 0:
|
|
raise ValueError('Column names must be specified for insert')
|
|
if not column_types:
|
|
if column_type_names:
|
|
column_types = [get_from_name(name) for name in column_type_names]
|
|
else:
|
|
column_map = {d.name: d for d in column_defs}
|
|
try:
|
|
column_types = [column_map[name].ch_type for name in column_names]
|
|
except KeyError as ex:
|
|
raise ProgrammingError(f'Unrecognized column {ex} in table {table}') from None
|
|
if len(column_names) != len(column_types):
|
|
raise ProgrammingError('Column names do not match column types') from None
|
|
return InsertContext(full_table,
|
|
column_names,
|
|
column_types,
|
|
column_oriented=column_oriented,
|
|
settings=settings,
|
|
transport_settings=transport_settings,
|
|
data=data)
|
|
|
|
def min_version(self, version_str: str) -> bool:
|
|
"""
|
|
Determine whether the connected server is at least the submitted version
|
|
For Altinity Stable versions like 22.8.15.25.altinitystable
|
|
the last condition in the first list comprehension expression is added
|
|
:param version_str: A version string consisting of up to 4 integers delimited by dots
|
|
:return: True if version_str is greater than the server_version, False if less than
|
|
"""
|
|
try:
|
|
server_parts = [int(x) for x in self.server_version.split('.') if x.isnumeric()]
|
|
server_parts.extend([0] * (4 - len(server_parts)))
|
|
version_parts = [int(x) for x in version_str.split('.')]
|
|
version_parts.extend([0] * (4 - len(version_parts)))
|
|
except ValueError:
|
|
logger.warning('Server %s or requested version %s does not match format of numbers separated by dots',
|
|
self.server_version, version_str)
|
|
return False
|
|
for x, y in zip(server_parts, version_parts):
|
|
if x > y:
|
|
return True
|
|
if x < y:
|
|
return False
|
|
return True
|
|
|
|
@abstractmethod
|
|
def data_insert(self, context: InsertContext) -> QuerySummary:
|
|
"""
|
|
Subclass implementation of the data insert
|
|
:context: InsertContext parameter object
|
|
:return: No return, throws an exception if the insert fails
|
|
"""
|
|
|
|
@abstractmethod
|
|
def raw_insert(self, table: str,
|
|
column_names: Optional[Sequence[str]] = None,
|
|
insert_block: Union[str, bytes, Generator[bytes, None, None], BinaryIO] = None,
|
|
settings: Optional[Dict] = None,
|
|
fmt: Optional[str] = None,
|
|
compression: Optional[str] = None,
|
|
transport_settings: Optional[Dict[str, str]] = None) -> QuerySummary:
|
|
"""
|
|
Insert data already formatted in a bytes object
|
|
:param table: Table name (whether qualified with the database name or not)
|
|
:param column_names: Sequence of column names
|
|
:param insert_block: Binary or string data already in a recognized Datastore format
|
|
:param settings: Optional dictionary of Datastore settings (key/string values)
|
|
:param fmt: Valid datastore format
|
|
:param compression: Recognized Datastore `Accept-Encoding` header compression value
|
|
:param transport_settings: Optional dictionary of transport level settings (HTTP headers, etc.)
|
|
"""
|
|
|
|
@abstractmethod
|
|
def close(self):
|
|
"""
|
|
Subclass implementation to close the connection to the server/deallocate the client
|
|
"""
|
|
|
|
@abstractmethod
|
|
def close_connections(self):
|
|
"""
|
|
Subclass implementation to disconnect all "re-used" client connections
|
|
"""
|
|
|
|
def _context_query(self, lcls: dict, **overrides):
|
|
kwargs = lcls.copy()
|
|
kwargs.pop('self')
|
|
kwargs.update(overrides)
|
|
return self._query_with_context((self.create_query_context(**kwargs)))
|
|
|
|
def __enter__(self):
|
|
return self
|
|
|
|
def __exit__(self, exc_type, exc_value, exc_traceback):
|
|
self.close()
|