airflow sql 源码
airflow sql 代码
文件路径：/airflow/providers/common/sql/operators/sql.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
import ast
import re
from typing import TYPE_CHECKING, Any, Callable, Iterable, Mapping, Sequence, SupportsAbs
from packaging.version import Version
from airflow.compat.functools import cached_property
from airflow.exceptions import AirflowException
from airflow.hooks.base import BaseHook
from airflow.models import BaseOperator, SkipMixin
from airflow.providers.common.sql.hooks.sql import DbApiHook, _backported_get_hook, fetch_all_handler
from airflow.version import version
if TYPE_CHECKING:
from airflow.utils.context import Context
def parse_boolean(val: str) -> str | bool:
"""Try to parse a string into boolean.
Raises ValueError if the input is not a valid true- or false-like string value.
"""
val = val.lower()
if val in ('y', 'yes', 't', 'true', 'on', '1'):
return True
if val in ('n', 'no', 'f', 'false', 'off', '0'):
return False
raise ValueError(f"{val!r} is not a boolean-like string value")
def _get_failed_checks(checks, col=None):
if col:
return [
f"Column: {col}\nCheck: {check},\nCheck Values: {check_values}\n"
for check, check_values in checks.items()
if not check_values["success"]
]
return [
f"\tCheck: {check},\n\tCheck Values: {check_values}\n"
for check, check_values in checks.items()
if not check_values["success"]
]
_PROVIDERS_MATCHER = re.compile(r'airflow\.providers\.(.*)\.hooks.*')
_MIN_SUPPORTED_PROVIDERS_VERSION = {
"amazon": "4.1.0",
"apache.drill": "2.1.0",
"apache.druid": "3.1.0",
"apache.hive": "3.1.0",
"apache.pinot": "3.1.0",
"databricks": "3.1.0",
"elasticsearch": "4.1.0",
"exasol": "3.1.0",
"google": "8.2.0",
"jdbc": "3.1.0",
"mssql": "3.1.0",
"mysql": "3.1.0",
"odbc": "3.1.0",
"oracle": "3.1.0",
"postgres": "5.1.0",
"presto": "3.1.0",
"qubole": "3.1.0",
"slack": "5.1.0",
"snowflake": "3.1.0",
"sqlite": "3.1.0",
"trino": "3.1.0",
"vertica": "3.1.0",
}
class BaseSQLOperator(BaseOperator):
"""
This is a base class for generic SQL Operator to get a DB Hook
The provided method is .get_db_hook(). The default behavior will try to
retrieve the DB hook based on connection type.
You can customize the behavior by overriding the .get_db_hook() method.
:param conn_id: reference to a specific database
"""
def __init__(
self,
*,
conn_id: str | None = None,
database: str | None = None,
hook_params: dict | None = None,
**kwargs,
):
super().__init__(**kwargs)
self.conn_id = conn_id
self.database = database
self.hook_params = {} if hook_params is None else hook_params
@cached_property
def _hook(self):
"""Get DB Hook based on connection type"""
self.log.debug("Get connection for %s", self.conn_id)
conn = BaseHook.get_connection(self.conn_id)
if Version(version) >= Version('2.3'):
# "hook_params" were introduced to into "get_hook()" only in Airflow 2.3.
hook = conn.get_hook(hook_params=self.hook_params) # ignore airflow compat check
else:
# For supporting Airflow versions < 2.3, we backport "get_hook()" method. This should be removed
# when "apache-airflow-providers-common-sql" will depend on Airflow >= 2.3.
hook = _backported_get_hook(conn, hook_params=self.hook_params)
if not isinstance(hook, DbApiHook):
from airflow.hooks.dbapi_hook import DbApiHook as _DbApiHook
if isinstance(hook, _DbApiHook):
# This case might happen if user installed common.sql provider but did not upgrade the
# Other provider's versions to a version that supports common.sql provider
class_module = hook.__class__.__module__
match = _PROVIDERS_MATCHER.match(class_module)
if match:
provider = match.group(1)
min_version = _MIN_SUPPORTED_PROVIDERS_VERSION.get(provider)
if min_version:
raise AirflowException(
f'You are trying to use common-sql with {hook.__class__.__name__},'
f' but the Hook class comes from provider {provider} that does not support it.'
f' Please upgrade provider {provider} to at least {min_version}.'
)
raise AirflowException(
f'You are trying to use `common-sql` with {hook.__class__.__name__},'
' but its provider does not support it. Please upgrade the provider to a version that'
' supports `common-sql`. The hook class should be a subclass of'
' `airflow.providers.common.sql.hooks.sql.DbApiHook`.'
f' Got {hook.__class__.__name__} Hook with class hierarchy: {hook.__class__.mro()}'
)
if self.database:
hook.schema = self.database
return hook
def get_db_hook(self) -> DbApiHook:
"""
Get the database hook for the connection.
:return: the database hook object.
:rtype: DbApiHook
"""
return self._hook
class SQLExecuteQueryOperator(BaseSQLOperator):
"""
Executes SQL code in a specific database
:param sql: the SQL code or string pointing to a template file to be executed (templated).
File must have a '.sql' extensions.
:param autocommit: (optional) if True, each command is automatically committed (default: False).
:param parameters: (optional) the parameters to render the SQL query with.
:param handler: (optional) the function that will be applied to the cursor (default: fetch_all_handler).
:param split_statements: (optional) if split single SQL string into statements (default: False).
:param return_last: (optional) if return the result of only last statement (default: True).
.. seealso::
For more information on how to use this operator, take a look at the guide:
:ref:`howto/operator:SQLExecuteQueryOperator`
"""
template_fields: Sequence[str] = ('sql', 'parameters')
template_ext: Sequence[str] = ('.sql', '.json')
template_fields_renderers = {"sql": "sql", "parameters": "json"}
ui_color = '#cdaaed'
def __init__(
self,
*,
sql: str | list[str],
autocommit: bool = False,
parameters: Mapping | Iterable | None = None,
handler: Callable[[Any], Any] = fetch_all_handler,
split_statements: bool = False,
return_last: bool = True,
**kwargs,
) -> None:
super().__init__(**kwargs)
self.sql = sql
self.autocommit = autocommit
self.parameters = parameters
self.handler = handler
self.split_statements = split_statements
self.return_last = return_last
def execute(self, context):
self.log.info('Executing: %s', self.sql)
hook = self.get_db_hook()
if self.do_xcom_push:
output = hook.run(
sql=self.sql,
autocommit=self.autocommit,
parameters=self.parameters,
handler=self.handler,
split_statements=self.split_statements,
return_last=self.return_last,
)
else:
output = hook.run(
sql=self.sql,
autocommit=self.autocommit,
parameters=self.parameters,
split_statements=self.split_statements,
)
if hasattr(self, '_process_output'):
for out in output:
self._process_output(*out)
return output
def prepare_template(self) -> None:
"""Parse template file for attribute parameters."""
if isinstance(self.parameters, str):
self.parameters = ast.literal_eval(self.parameters)
class SQLColumnCheckOperator(BaseSQLOperator):
"""
Performs one or more of the templated checks in the column_checks dictionary.
Checks are performed on a per-column basis specified by the column_mapping.
Each check can take one or more of the following options:
- equal_to: an exact value to equal, cannot be used with other comparison options
- greater_than: value that result should be strictly greater than
- less_than: value that results should be strictly less than
- geq_to: value that results should be greater than or equal to
- leq_to: value that results should be less than or equal to
- tolerance: the percentage that the result may be off from the expected value
:param table: the table to run checks on
:param column_mapping: the dictionary of columns and their associated checks, e.g.
.. code-block:: python
{
"col_name": {
"null_check": {
"equal_to": 0,
},
"min": {
"greater_than": 5,
"leq_to": 10,
"tolerance": 0.2,
},
"max": {"less_than": 1000, "geq_to": 10, "tolerance": 0.01},
}
}
:param partition_clause: a partial SQL statement that is added to a WHERE clause in the query built by
the operator that creates partition_clauses for the checks to run on, e.g.
.. code-block:: python
"date = '1970-01-01'"
:param conn_id: the connection ID used to connect to the database
:param database: name of database which overwrite the defined one in connection
.. seealso::
For more information on how to use this operator, take a look at the guide:
:ref:`howto/operator:SQLColumnCheckOperator`
"""
template_fields = ("partition_clause",)
column_checks = {
"null_check": "SUM(CASE WHEN column IS NULL THEN 1 ELSE 0 END) AS column_null_check",
"distinct_check": "COUNT(DISTINCT(column)) AS column_distinct_check",
"unique_check": "COUNT(column) - COUNT(DISTINCT(column)) AS column_unique_check",
"min": "MIN(column) AS column_min",
"max": "MAX(column) AS column_max",
}
def __init__(
self,
*,
table: str,
column_mapping: dict[str, dict[str, Any]],
partition_clause: str | None = None,
conn_id: str | None = None,
database: str | None = None,
**kwargs,
):
super().__init__(conn_id=conn_id, database=database, **kwargs)
for checks in column_mapping.values():
for check, check_values in checks.items():
self._column_mapping_validation(check, check_values)
self.table = table
self.column_mapping = column_mapping
self.partition_clause = partition_clause
# OpenLineage needs a valid SQL query with the input/output table(s) to parse
self.sql = f"SELECT * FROM {self.table};"
def execute(self, context: Context):
hook = self.get_db_hook()
failed_tests = []
for column in self.column_mapping:
checks = [*self.column_mapping[column]]
checks_sql = ",".join([self.column_checks[check].replace("column", column) for check in checks])
partition_clause_statement = f"WHERE {self.partition_clause}" if self.partition_clause else ""
self.sql = f"SELECT {checks_sql} FROM {self.table} {partition_clause_statement};"
records = hook.get_first(self.sql)
if not records:
raise AirflowException(f"The following query returned zero rows: {self.sql}")
self.log.info("Record: %s", records)
for idx, result in enumerate(records):
tolerance = self.column_mapping[column][checks[idx]].get("tolerance")
self.column_mapping[column][checks[idx]]["result"] = result
self.column_mapping[column][checks[idx]]["success"] = self._get_match(
self.column_mapping[column][checks[idx]], result, tolerance
)
failed_tests.extend(_get_failed_checks(self.column_mapping[column], column))
if failed_tests:
raise AirflowException(
f"Test failed.\nResults:\n{records!s}\n"
"The following tests have failed:"
f"\n{''.join(failed_tests)}"
)
self.log.info("All tests have passed")
def _get_match(self, check_values, record, tolerance=None) -> bool:
match_boolean = True
if "geq_to" in check_values:
if tolerance is not None:
match_boolean = record >= check_values["geq_to"] * (1 - tolerance)
else:
match_boolean = record >= check_values["geq_to"]
elif "greater_than" in check_values:
if tolerance is not None:
match_boolean = record > check_values["greater_than"] * (1 - tolerance)
else:
match_boolean = record > check_values["greater_than"]
if "leq_to" in check_values:
if tolerance is not None:
match_boolean = record <= check_values["leq_to"] * (1 + tolerance) and match_boolean
else:
match_boolean = record <= check_values["leq_to"] and match_boolean
elif "less_than" in check_values:
if tolerance is not None:
match_boolean = record < check_values["less_than"] * (1 + tolerance) and match_boolean
else:
match_boolean = record < check_values["less_than"] and match_boolean
if "equal_to" in check_values:
if tolerance is not None:
match_boolean = (
check_values["equal_to"] * (1 - tolerance)
<= record
<= check_values["equal_to"] * (1 + tolerance)
) and match_boolean
else:
match_boolean = record == check_values["equal_to"] and match_boolean
return match_boolean
def _column_mapping_validation(self, check, check_values):
if check not in self.column_checks:
raise AirflowException(f"Invalid column check: {check}.")
if (
"greater_than" not in check_values
and "geq_to" not in check_values
and "less_than" not in check_values
and "leq_to" not in check_values
and "equal_to" not in check_values
):
raise ValueError(
"Please provide one or more of: less_than, leq_to, "
"greater_than, geq_to, or equal_to in the check's dict."
)
if "greater_than" in check_values and "less_than" in check_values:
if check_values["greater_than"] >= check_values["less_than"]:
raise ValueError(
"greater_than should be strictly less than "
"less_than. Use geq_to or leq_to for "
"overlapping equality."
)
if "greater_than" in check_values and "leq_to" in check_values:
if check_values["greater_than"] >= check_values["leq_to"]:
raise ValueError(
"greater_than must be strictly less than leq_to. "
"Use geq_to with leq_to for overlapping equality."
)
if "geq_to" in check_values and "less_than" in check_values:
if check_values["geq_to"] >= check_values["less_than"]:
raise ValueError(
"geq_to should be strictly less than less_than. "
"Use leq_to with geq_to for overlapping equality."
)
if "geq_to" in check_values and "leq_to" in check_values:
if check_values["geq_to"] > check_values["leq_to"]:
raise ValueError("geq_to should be less than or equal to leq_to.")
if "greater_than" in check_values and "geq_to" in check_values:
raise ValueError("Only supply one of greater_than or geq_to.")
if "less_than" in check_values and "leq_to" in check_values:
raise ValueError("Only supply one of less_than or leq_to.")
if (
"greater_than" in check_values
or "geq_to" in check_values
or "less_than" in check_values
or "leq_to" in check_values
) and "equal_to" in check_values:
raise ValueError(
"equal_to cannot be passed with a greater or less than "
"function. To specify 'greater than or equal to' or "
"'less than or equal to', use geq_to or leq_to."
)
class SQLTableCheckOperator(BaseSQLOperator):
"""
Performs one or more of the checks provided in the checks dictionary.
Checks should be written to return a boolean result.
:param table: the table to run checks on
:param checks: the dictionary of checks, e.g.:
.. code-block:: python
{
"row_count_check": {"check_statement": "COUNT(*) = 1000"},
"column_sum_check": {"check_statement": "col_a + col_b < col_c"},
}
:param partition_clause: a partial SQL statement that is added to a WHERE clause in the query built by
the operator that creates partition_clauses for the checks to run on, e.g.
.. code-block:: python
"date = '1970-01-01'"
:param conn_id: the connection ID used to connect to the database
:param database: name of database which overwrite the defined one in connection
.. seealso::
For more information on how to use this operator, take a look at the guide:
:ref:`howto/operator:SQLTableCheckOperator`
"""
template_fields = ("partition_clause",)
sql_check_template = """
SELECT '_check_name' AS check_name, MIN(_check_name) AS check_result
FROM (SELECT CASE WHEN check_statement THEN 1 ELSE 0 END AS _check_name FROM table) AS sq
"""
def __init__(
self,
*,
table: str,
checks: dict[str, dict[str, Any]],
partition_clause: str | None = None,
conn_id: str | None = None,
database: str | None = None,
**kwargs,
):
super().__init__(conn_id=conn_id, database=database, **kwargs)
self.table = table
self.checks = checks
self.partition_clause = partition_clause
# OpenLineage needs a valid SQL query with the input/output table(s) to parse
self.sql = f"SELECT * FROM {self.table};"
def execute(self, context: Context):
hook = self.get_db_hook()
checks_sql = " UNION ALL ".join(
[
self.sql_check_template.replace("check_statement", value["check_statement"])
.replace("_check_name", check_name)
.replace("table", self.table)
for check_name, value in self.checks.items()
]
)
partition_clause_statement = f"WHERE {self.partition_clause}" if self.partition_clause else ""
self.sql = f"""
SELECT check_name, check_result FROM ({checks_sql})
AS check_table {partition_clause_statement}
"""
records = hook.get_records(self.sql)
if not records:
raise AirflowException(f"The following query returned zero rows: {self.sql}")
self.log.info("Record:\n%s", records)
for row in records:
check, result = row
self.checks[check]["success"] = parse_boolean(str(result))
failed_tests = _get_failed_checks(self.checks)
if failed_tests:
raise AirflowException(
f"Test failed.\nQuery:\n{self.sql}\nResults:\n{records!s}\n"
"The following tests have failed:"
f"\n{', '.join(failed_tests)}"
)
self.log.info("All tests have passed")
class SQLCheckOperator(BaseSQLOperator):
"""
Performs checks against a db. The ``SQLCheckOperator`` expects
a sql query that will return a single row. Each value on that
first row is evaluated using python ``bool`` casting. If any of the
values return ``False`` the check is failed and errors out.
Note that Python bool casting evals the following as ``False``:
* ``False``
* ``0``
* Empty string (``""``)
* Empty list (``[]``)
* Empty dictionary or set (``{}``)
Given a query like ``SELECT COUNT(*) FROM foo``, it will fail only if
the count ``== 0``. You can craft much more complex query that could,
for instance, check that the table has the same number of rows as
the source table upstream, or that the count of today's partition is
greater than yesterday's partition, or that a set of metrics are less
than 3 standard deviation for the 7 day average.
This operator can be used as a data quality check in your pipeline, and
depending on where you put it in your DAG, you have the choice to
stop the critical path, preventing from
publishing dubious data, or on the side and receive email alerts
without stopping the progress of the DAG.
:param sql: the sql to be executed. (templated)
:param conn_id: the connection ID used to connect to the database.
:param database: name of database which overwrite the defined one in connection
"""
template_fields: Sequence[str] = ("sql",)
template_ext: Sequence[str] = (
".hql",
".sql",
)
template_fields_renderers = {"sql": "sql"}
ui_color = "#fff7e6"
def __init__(
self, *, sql: str, conn_id: str | None = None, database: str | None = None, **kwargs
) -> None:
super().__init__(conn_id=conn_id, database=database, **kwargs)
self.sql = sql
def execute(self, context: Context):
self.log.info("Executing SQL check: %s", self.sql)
records = self.get_db_hook().get_first(self.sql)
self.log.info("Record: %s", records)
if not records:
raise AirflowException("The query returned None")
elif not all(bool(r) for r in records):
raise AirflowException(f"Test failed.\nQuery:\n{self.sql}\nResults:\n{records!s}")
self.log.info("Success.")
class SQLValueCheckOperator(BaseSQLOperator):
"""
Performs a simple value check using sql code.
:param sql: the sql to be executed. (templated)
:param conn_id: the connection ID used to connect to the database.
:param database: name of database which overwrite the defined one in connection
"""
__mapper_args__ = {"polymorphic_identity": "SQLValueCheckOperator"}
template_fields: Sequence[str] = (
"sql",
"pass_value",
)
template_ext: Sequence[str] = (
".hql",
".sql",
)
template_fields_renderers = {"sql": "sql"}
ui_color = "#fff7e6"
def __init__(
self,
*,
sql: str,
pass_value: Any,
tolerance: Any = None,
conn_id: str | None = None,
database: str | None = None,
**kwargs,
):
super().__init__(conn_id=conn_id, database=database, **kwargs)
self.sql = sql
self.pass_value = str(pass_value)
tol = _convert_to_float_if_possible(tolerance)
self.tol = tol if isinstance(tol, float) else None
self.has_tolerance = self.tol is not None
def execute(self, context: Context):
self.log.info("Executing SQL check: %s", self.sql)
records = self.get_db_hook().get_first(self.sql)
if not records:
raise AirflowException("The query returned None")
pass_value_conv = _convert_to_float_if_possible(self.pass_value)
is_numeric_value_check = isinstance(pass_value_conv, float)
tolerance_pct_str = str(self.tol * 100) + "%" if self.tol is not None else None
error_msg = (
"Test failed.\nPass value:{pass_value_conv}\n"
"Tolerance:{tolerance_pct_str}\n"
"Query:\n{sql}\nResults:\n{records!s}"
).format(
pass_value_conv=pass_value_conv,
tolerance_pct_str=tolerance_pct_str,
sql=self.sql,
records=records,
)
if not is_numeric_value_check:
tests = self._get_string_matches(records, pass_value_conv)
elif is_numeric_value_check:
try:
numeric_records = self._to_float(records)
except (ValueError, TypeError):
raise AirflowException(f"Converting a result to float failed.\n{error_msg}")
tests = self._get_numeric_matches(numeric_records, pass_value_conv)
else:
tests = []
if not all(tests):
raise AirflowException(error_msg)
def _to_float(self, records):
return [float(record) for record in records]
def _get_string_matches(self, records, pass_value_conv):
return [str(record) == pass_value_conv for record in records]
def _get_numeric_matches(self, numeric_records, numeric_pass_value_conv):
if self.has_tolerance:
return [
numeric_pass_value_conv * (1 - self.tol) <= record <= numeric_pass_value_conv * (1 + self.tol)
for record in numeric_records
]
return [record == numeric_pass_value_conv for record in numeric_records]
class SQLIntervalCheckOperator(BaseSQLOperator):
"""
Checks that the values of metrics given as SQL expressions are within
a certain tolerance of the ones from days_back before.
:param table: the table name
:param conn_id: the connection ID used to connect to the database.
:param database: name of database which will overwrite the defined one in connection
:param days_back: number of days between ds and the ds we want to check
against. Defaults to 7 days
:param date_filter_column: The column name for the dates to filter on. Defaults to 'ds'
:param ratio_formula: which formula to use to compute the ratio between
the two metrics. Assuming cur is the metric of today and ref is
the metric to today - days_back.
max_over_min: computes max(cur, ref) / min(cur, ref)
relative_diff: computes abs(cur-ref) / ref
Default: 'max_over_min'
:param ignore_zero: whether we should ignore zero metrics
:param metrics_thresholds: a dictionary of ratios indexed by metrics
"""
__mapper_args__ = {"polymorphic_identity": "SQLIntervalCheckOperator"}
template_fields: Sequence[str] = ("sql1", "sql2")
template_ext: Sequence[str] = (
".hql",
".sql",
)
template_fields_renderers = {"sql1": "sql", "sql2": "sql"}
ui_color = "#fff7e6"
ratio_formulas = {
"max_over_min": lambda cur, ref: float(max(cur, ref)) / min(cur, ref),
"relative_diff": lambda cur, ref: float(abs(cur - ref)) / ref,
}
def __init__(
self,
*,
table: str,
metrics_thresholds: dict[str, int],
date_filter_column: str | None = "ds",
days_back: SupportsAbs[int] = -7,
ratio_formula: str | None = "max_over_min",
ignore_zero: bool = True,
conn_id: str | None = None,
database: str | None = None,
**kwargs,
):
super().__init__(conn_id=conn_id, database=database, **kwargs)
if ratio_formula not in self.ratio_formulas:
msg_template = "Invalid diff_method: {diff_method}. Supported diff methods are: {diff_methods}"
raise AirflowException(
msg_template.format(diff_method=ratio_formula, diff_methods=self.ratio_formulas)
)
self.ratio_formula = ratio_formula
self.ignore_zero = ignore_zero
self.table = table
self.metrics_thresholds = metrics_thresholds
self.metrics_sorted = sorted(metrics_thresholds.keys())
self.date_filter_column = date_filter_column
self.days_back = -abs(days_back)
sqlexp = ", ".join(self.metrics_sorted)
sqlt = f"SELECT {sqlexp} FROM {table} WHERE {date_filter_column}="
self.sql1 = sqlt + "'{{ ds }}'"
self.sql2 = sqlt + "'{{ macros.ds_add(ds, " + str(self.days_back) + ") }}'"
def execute(self, context: Context):
hook = self.get_db_hook()
self.log.info("Using ratio formula: %s", self.ratio_formula)
self.log.info("Executing SQL check: %s", self.sql2)
row2 = hook.get_first(self.sql2)
self.log.info("Executing SQL check: %s", self.sql1)
row1 = hook.get_first(self.sql1)
if not row2:
raise AirflowException(f"The query {self.sql2} returned None")
if not row1:
raise AirflowException(f"The query {self.sql1} returned None")
current = dict(zip(self.metrics_sorted, row1))
reference = dict(zip(self.metrics_sorted, row2))
ratios: dict[str, int | None] = {}
test_results = {}
for metric in self.metrics_sorted:
cur = current[metric]
ref = reference[metric]
threshold = self.metrics_thresholds[metric]
if cur == 0 or ref == 0:
ratios[metric] = None
test_results[metric] = self.ignore_zero
else:
ratio_metric = self.ratio_formulas[self.ratio_formula](current[metric], reference[metric])
ratios[metric] = ratio_metric
if ratio_metric is not None:
test_results[metric] = ratio_metric < threshold
else:
test_results[metric] = self.ignore_zero
self.log.info(
(
"Current metric for %s: %s\n"
"Past metric for %s: %s\n"
"Ratio for %s: %s\n"
"Threshold: %s\n"
),
metric,
cur,
metric,
ref,
metric,
ratios[metric],
threshold,
)
if not all(test_results.values()):
failed_tests = [it[0] for it in test_results.items() if not it[1]]
self.log.warning(
"The following %s tests out of %s failed:",
len(failed_tests),
len(self.metrics_sorted),
)
for k in failed_tests:
self.log.warning(
"'%s' check failed. %s is above %s",
k,
ratios[k],
self.metrics_thresholds[k],
)
raise AirflowException(f"The following tests have failed:\n {', '.join(sorted(failed_tests))}")
self.log.info("All tests have passed")
class SQLThresholdCheckOperator(BaseSQLOperator):
"""
Performs a value check using sql code against a minimum threshold
and a maximum threshold. Thresholds can be in the form of a numeric
value OR a sql statement that results a numeric.
:param sql: the sql to be executed. (templated)
:param conn_id: the connection ID used to connect to the database.
:param database: name of database which overwrite the defined one in connection
:param min_threshold: numerical value or min threshold sql to be executed (templated)
:param max_threshold: numerical value or max threshold sql to be executed (templated)
"""
template_fields: Sequence[str] = ("sql", "min_threshold", "max_threshold")
template_ext: Sequence[str] = (
".hql",
".sql",
)
template_fields_renderers = {"sql": "sql"}
def __init__(
self,
*,
sql: str,
min_threshold: Any,
max_threshold: Any,
conn_id: str | None = None,
database: str | None = None,
**kwargs,
):
super().__init__(conn_id=conn_id, database=database, **kwargs)
self.sql = sql
self.min_threshold = _convert_to_float_if_possible(min_threshold)
self.max_threshold = _convert_to_float_if_possible(max_threshold)
def execute(self, context: Context):
hook = self.get_db_hook()
result = hook.get_first(self.sql)[0]
if isinstance(self.min_threshold, float):
lower_bound = self.min_threshold
else:
lower_bound = hook.get_first(self.min_threshold)[0]
if isinstance(self.max_threshold, float):
upper_bound = self.max_threshold
else:
upper_bound = hook.get_first(self.max_threshold)[0]
meta_data = {
"result": result,
"task_id": self.task_id,
"min_threshold": lower_bound,
"max_threshold": upper_bound,
"within_threshold": lower_bound <= result <= upper_bound,
}
self.push(meta_data)
if not meta_data["within_threshold"]:
result = (
round(meta_data.get("result"), 2) # type: ignore[arg-type]
if meta_data.get("result") is not None
else "<None>"
)
error_msg = (
f'Threshold Check: "{meta_data.get("task_id")}" failed.\n'
f'DAG: {self.dag_id}\nTask_id: {meta_data.get("task_id")}\n'
f'Check description: {meta_data.get("description")}\n'
f"SQL: {self.sql}\n"
f'Result: {result} is not within thresholds '
f'{meta_data.get("min_threshold")} and {meta_data.get("max_threshold")}'
)
raise AirflowException(error_msg)
self.log.info("Test %s Successful.", self.task_id)
def push(self, meta_data):
"""
Optional: Send data check info and metadata to an external database.
Default functionality will log metadata.
"""
info = "\n".join(f"""{key}: {item}""" for key, item in meta_data.items())
self.log.info("Log from %s:\n%s", self.dag_id, info)
class BranchSQLOperator(BaseSQLOperator, SkipMixin):
"""
Allows a DAG to "branch" or follow a specified path based on the results of a SQL query.
:param sql: The SQL code to be executed, should return true or false (templated)
Template reference are recognized by str ending in '.sql'.
Expected SQL query to return Boolean (True/False), integer (0 = False, Otherwise = 1)
or string (true/y/yes/1/on/false/n/no/0/off).
:param follow_task_ids_if_true: task id or task ids to follow if query returns true
:param follow_task_ids_if_false: task id or task ids to follow if query returns false
:param conn_id: the connection ID used to connect to the database.
:param database: name of database which overwrite the defined one in connection
:param parameters: (optional) the parameters to render the SQL query with.
"""
template_fields: Sequence[str] = ("sql",)
template_ext: Sequence[str] = (".sql",)
template_fields_renderers = {"sql": "sql"}
ui_color = "#a22034"
ui_fgcolor = "#F7F7F7"
def __init__(
self,
*,
sql: str,
follow_task_ids_if_true: list[str],
follow_task_ids_if_false: list[str],
conn_id: str = "default_conn_id",
database: str | None = None,
parameters: Iterable | Mapping | None = None,
**kwargs,
) -> None:
super().__init__(conn_id=conn_id, database=database, **kwargs)
self.sql = sql
self.parameters = parameters
self.follow_task_ids_if_true = follow_task_ids_if_true
self.follow_task_ids_if_false = follow_task_ids_if_false
def execute(self, context: Context):
self.log.info(
"Executing: %s (with parameters %s) with connection: %s",
self.sql,
self.parameters,
self.conn_id,
)
record = self.get_db_hook().get_first(self.sql, self.parameters)
if not record:
raise AirflowException(
"No rows returned from sql query. Operator expected True or False return value."
)
if isinstance(record, list):
if isinstance(record[0], list):
query_result = record[0][0]
else:
query_result = record[0]
elif isinstance(record, tuple):
query_result = record[0]
else:
query_result = record
self.log.info("Query returns %s, type '%s'", query_result, type(query_result))
follow_branch = None
try:
if isinstance(query_result, bool):
if query_result:
follow_branch = self.follow_task_ids_if_true
elif isinstance(query_result, str):
# return result is not Boolean, try to convert from String to Boolean
if parse_boolean(query_result):
follow_branch = self.follow_task_ids_if_true
elif isinstance(query_result, int):
if bool(query_result):
follow_branch = self.follow_task_ids_if_true
else:
raise AirflowException(
f"Unexpected query return result '{query_result}' type '{type(query_result)}'"
)
if follow_branch is None:
follow_branch = self.follow_task_ids_if_false
except ValueError:
raise AirflowException(
f"Unexpected query return result '{query_result}' type '{type(query_result)}'"
)
self.skip_all_except(context["ti"], follow_branch)
def _convert_to_float_if_possible(s):
"""
A small helper function to convert a string to a numeric value
if appropriate
:param s: the string to be converted
"""
try:
ret = float(s)
except (ValueError, TypeError):
ret = s
return ret
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