superset/superset/tasks/async_queries.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.

import copy
import logging
from typing import Any, cast, Dict, Optional

from celery.exceptions import SoftTimeLimitExceeded
from flask import current_app, g

from superset.exceptions import SupersetVizException
from superset.extensions import (
    async_query_manager,
    cache_manager,
    celery_app,
    security_manager,
)
from superset.utils.cache import generate_cache_key, set_and_log_cache
from superset.views.utils import get_datasource_info, get_viz

logger = logging.getLogger(__name__)
query_timeout = current_app.config[
    "SQLLAB_ASYNC_TIME_LIMIT_SEC"
]  # TODO: new config key


def ensure_user_is_set(user_id: Optional[int]) -> None:
    user_is_not_set = not (hasattr(g, "user") and g.user is not None)
    if user_is_not_set and user_id is not None:
        g.user = security_manager.get_user_by_id(user_id)
    elif user_is_not_set:
        g.user = security_manager.get_anonymous_user()


@celery_app.task(name="load_chart_data_into_cache", soft_time_limit=query_timeout)
def load_chart_data_into_cache(
    job_metadata: Dict[str, Any], form_data: Dict[str, Any],
) -> None:
    # pylint: disable=import-outside-toplevel
    from superset.charts.commands.data import ChartDataCommand

    try:
        ensure_user_is_set(job_metadata.get("user_id"))
        command = ChartDataCommand()
        command.set_query_context(form_data)
        result = command.run(cache=True)
        cache_key = result["cache_key"]
        result_url = f"/api/v1/chart/data/{cache_key}"
        async_query_manager.update_job(
            job_metadata, async_query_manager.STATUS_DONE, result_url=result_url,
        )
    except SoftTimeLimitExceeded as exc:
        logger.warning("A timeout occurred while loading chart data, error: %s", exc)
        raise exc
    except Exception as exc:
        # TODO: QueryContext should support SIP-40 style errors
        error = exc.message if hasattr(exc, "message") else str(exc)  # type: ignore # pylint: disable=no-member
        errors = [{"message": error}]
        async_query_manager.update_job(
            job_metadata, async_query_manager.STATUS_ERROR, errors=errors
        )
        raise exc


@celery_app.task(name="load_explore_json_into_cache", soft_time_limit=query_timeout)
def load_explore_json_into_cache(  # pylint: disable=too-many-locals
    job_metadata: Dict[str, Any],
    form_data: Dict[str, Any],
    response_type: Optional[str] = None,
    force: bool = False,
) -> None:
    cache_key_prefix = "ejr-"  # ejr: explore_json request
    try:
        ensure_user_is_set(job_metadata.get("user_id"))
        datasource_id, datasource_type = get_datasource_info(None, None, form_data)

        # Perform a deep copy here so that below we can cache the original
        # value of the form_data object. This is necessary since the viz
        # objects modify the form_data object. If the modified version were
        # to be cached here, it will lead to a cache miss when clients
        # attempt to retrieve the value of the completed async query.
        original_form_data = copy.deepcopy(form_data)

        viz_obj = get_viz(
            datasource_type=cast(str, datasource_type),
            datasource_id=datasource_id,
            form_data=form_data,
            force=force,
        )
        # run query & cache results
        payload = viz_obj.get_payload()
        if viz_obj.has_error(payload):
            raise SupersetVizException(errors=payload["errors"])

        # Cache the original form_data value for async retrieval
        cache_value = {
            "form_data": original_form_data,
            "response_type": response_type,
        }
        cache_key = generate_cache_key(cache_value, cache_key_prefix)
        set_and_log_cache(cache_manager.cache, cache_key, cache_value)
        result_url = f"/superset/explore_json/data/{cache_key}"
        async_query_manager.update_job(
            job_metadata, async_query_manager.STATUS_DONE, result_url=result_url,
        )
    except SoftTimeLimitExceeded as ex:
        logger.warning("A timeout occurred while loading explore json, error: %s", ex)
        raise ex
    except Exception as exc:
        if isinstance(exc, SupersetVizException):
            errors = exc.errors  # pylint: disable=no-member
        else:
            error = (
                exc.message if hasattr(exc, "message") else str(exc)  # type: ignore # pylint: disable=no-member
            )
            errors = [error]

        async_query_manager.update_job(
            job_metadata, async_query_manager.STATUS_ERROR, errors=errors
        )
        raise exc