起因
如果把很多地理数据可视化放入一个dashboard会出现这么个问题
环境
调研
[1]提到了二级缓存
[4]提到如果配置cache成功会有相关信息
准备工作
apt install redis
(virtualenv环境)pip installredis
编辑
~/.virtualenvs/python3.6/lib/python3.6/site-packages/superset/config.py
所有需要cache字样的全部配置成redis,具体改法见文末附录
配置效果
启动项目打开dashboard，log中会Serving from cache的字样,说明配置成功
说明配置成功
如果依然出现下面SQL语句:
说明配置失败
可视化效果
打开http://49.235.108.13:5000/superset/dashboard/3/
如果superset没有redis就会出现一大堆的close wait以及在dashboard上会因为timeout导致无法显示chart
相关命令
用SSH从远程服务器批量复制文件到本地（注意要在本地电脑上执行以下命令，而不是云主机上）
scp -r appleyuchi@49.235.108.13:/home/appleyuchi/.virtualenvs/python3.6/lib/python3.6/site-packages/superset/config.py /home/appleyuchi
scp -r /home/appleyuchi/config.py appleyuchi@49.235.108.13:/home/appleyuchi/.virtualenvs/python3.6/lib/python3.6/site-packages/superset
附录
config.py完整内容
(注意仅仅适用于apache-superset 0.37.1)
# 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## /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."""The main config file for SupersetAll configuration in this file can be overridden by providing a superset_configin your PYTHONPATH as there is a ``from superset_config import *``at the end of this file."""import impimport importlib.utilimport jsonimport loggingimport osimport sysfrom collections import OrderedDictfrom datetime import datefrom typing import Any, Callable, Dict, List, Optional, Type, TYPE_CHECKINGfrom cachelib.base import BaseCachefrom celery.schedules import crontabfrom dateutil import tzfrom flask import Blueprintfrom flask_appbuilder.security.manager import AUTH_DBfrom pandas.io.parsers import STR_NA_VALUESfrom superset.jinja_context import ( # pylint: disable=unused-importBaseTemplateProcessor,)from superset.stats_logger import DummyStatsLoggerfrom superset.typing import CacheConfigfrom superset.utils.log import DBEventLoggerfrom superset.utils.logging_configurator import DefaultLoggingConfiguratorlogger = logging.getLogger(__name__)if TYPE_CHECKING:from flask_appbuilder.security.sqla import models # pylint: disable=unused-importfrom superset.models.core import Database # pylint: disable=unused-import# Realtime stats logger, a StatsD implementation existsSTATS_LOGGER = DummyStatsLogger()EVENT_LOGGER = DBEventLogger()SUPERSET_LOG_VIEW = TrueBASE_DIR = os.path.abspath(os.path.dirname(__file__))if "SUPERSET_HOME" in os.environ:DATA_DIR = os.environ["SUPERSET_HOME"]else:DATA_DIR = os.path.join(os.path.expanduser("~"), ".superset")# ---------------------------------------------------------# Superset specific config# ---------------------------------------------------------VERSION_INFO_FILE = os.path.join(BASE_DIR, "static", "version_info.json")PACKAGE_JSON_FILE = os.path.join(BASE_DIR, "static", "assets", "package.json")# Multiple favicons can be specified here. The "href" property# is mandatory, but "sizes," "type," and "rel" are optional.# For example:# {#"href":path/to/image.png",#"sizes": "16x16",#"type": "image/png"#"rel": "icon"# },FAVICONS = [{"href": "/static/assets/images/favicon.png"}]def _try_json_readversion(filepath: str) -> Optional[str]:try:with open(filepath, "r") as f:return json.load(f).get("version")except Exception: # pylint: disable=broad-exceptreturn Nonedef _try_json_readsha( # pylint: disable=unused-argumentfilepath: str, length: int) -> Optional[str]:try:with open(filepath, "r") as f:return json.load(f).get("GIT_SHA")[:length]except Exception: # pylint: disable=broad-exceptreturn None# Depending on the context in which this config is loaded, the# version_info.json file may or may not be available, as it is# generated on install via setup.py. In the event that we're# actually running Superset, we will have already installed,# therefore it WILL exist. When unit tests are running, however,# it WILL NOT exist, so we fall back to reading package.jsonVERSION_STRING = _try_json_readversion(VERSION_INFO_FILE) or _try_json_readversion(PACKAGE_JSON_FILE)VERSION_SHA_LENGTH = 8VERSION_SHA = _try_json_readsha(VERSION_INFO_FILE, VERSION_SHA_LENGTH)ROW_LIMIT = 50000VIZ_ROW_LIMIT = 10000# max rows retreieved when requesting samples from datasource in explore viewSAMPLES_ROW_LIMIT = 1000# max rows retrieved by filter select auto completeFILTER_SELECT_ROW_LIMIT = 10000SUPERSET_WORKERS = 2 # deprecatedSUPERSET_CELERY_WORKERS = 32 # deprecatedSUPERSET_WEBSERVER_PROTOCOL = "http"SUPERSET_WEBSERVER_ADDRESS = "0.0.0.0"SUPERSET_WEBSERVER_PORT = 8088# This is an important setting, and should be lower than your# [load balancer / proxy / envoy / kong / ...] timeout settings.# You should also make sure to configure your WSGI server# (gunicorn, nginx, apache, ...) timeout setting to be <= to this settingSUPERSET_WEBSERVER_TIMEOUT = 60# this 2 settings are used by dashboard period force refresh feature# When user choose auto force refresh frequency# < SUPERSET_DASHBOARD_PERIODICAL_REFRESH_LIMIT# they will see warning message in the Refresh Interval Modal.# please check PR #9886SUPERSET_DASHBOARD_PERIODICAL_REFRESH_LIMIT = 0SUPERSET_DASHBOARD_PERIODICAL_REFRESH_WARNING_MESSAGE = NoneSUPERSET_DASHBOARD_POSITION_DATA_LIMIT = 65535CUSTOM_SECURITY_MANAGER = NoneSQLALCHEMY_TRACK_MODIFICATIONS = False# ---------------------------------------------------------# Your App secret keySECRET_KEY = ("\2\1thisismyscretkey\1\2\e\y\y\h" # pylint: disable=anomalous-backslash-in-string)# The SQLAlchemy connection string.SQLALCHEMY_DATABASE_URI = "sqlite:///" + os.path.join(DATA_DIR, "superset.db")# SQLALCHEMY_DATABASE_URI = 'mysql://myapp@localhost/myapp'# SQLALCHEMY_DATABASE_URI = 'postgresql://root:password@localhost/myapp'# In order to hook up a custom password store for all SQLACHEMY connections# implement a function that takes a single argument of type 'sqla.engine.url',# returns a password and set SQLALCHEMY_CUSTOM_PASSWORD_STORE.## e.g.:# def lookup_password(url):#return 'secret'# SQLALCHEMY_CUSTOM_PASSWORD_STORE = lookup_passwordSQLALCHEMY_CUSTOM_PASSWORD_STORE = None# The limit of queries fetched for query searchQUERY_SEARCH_LIMIT = 1000# Flask-WTF flag for CSRFWTF_CSRF_ENABLED = True# Add endpoints that need to be exempt from CSRF protectionWTF_CSRF_EXEMPT_LIST = ["superset.views.core.log"]# Whether to run the web server in debug mode or notDEBUG = os.environ.get("FLASK_ENV") == "development"FLASK_USE_RELOAD = True# Superset allows server-side python stacktraces to be surfaced to the# user when this feature is on. This may has security implications# and it's more secure to turn it off in production settings.SHOW_STACKTRACE = True# Use all X-Forwarded headers when ENABLE_PROXY_FIX is True.# When proxying to a different port, set "x_port" to 0 to avoid downstream issues.ENABLE_PROXY_FIX = FalsePROXY_FIX_CONFIG = {"x_for": 1, "x_proto": 1, "x_host": 1, "x_port": 1, "x_prefix": 1}# ------------------------------# GLOBALS FOR APP Builder# ------------------------------# Uncomment to setup Your App nameAPP_NAME = "Superset"# Uncomment to setup an App iconAPP_ICON = "/static/assets/images/superset-logo-horiz.png"APP_ICON_WIDTH = 126# Uncomment to specify where clicking the logo would take the user# e.g. setting it to '/welcome' would take the user to '/superset/welcome'LOGO_TARGET_PATH = None# Enables SWAGGER UI for superset openapi spec# ex: http://localhost:8080/swagger/v1FAB_API_SWAGGER_UI = True# Druid query timezone# tz.tzutc() : Using utc timezone# tz.tzlocal() : Using local timezone# tz.gettz('Asia/Shanghai') : Using the time zone with specific name# [TimeZone List]# See: /wiki/List_of_tz_database_time_zones# other tz can be overridden by providing a local_configDRUID_TZ = tz.tzutc()DRUID_ANALYSIS_TYPES = ["cardinality"]# Legacy Druid NoSQL (native) connector# Druid supports a SQL interface in its newer versions.# Setting this flag to True enables the deprecated, API-based Druid# connector. This feature may be removed at a future date.DRUID_IS_ACTIVE = False# If Druid is active whether to include the links to scan/refresh Druid datasources.# This should be disabled if you are trying to wean yourself off of the Druid NoSQL# connector.DRUID_METADATA_LINKS_ENABLED = True# ----------------------------------------------------# AUTHENTICATION CONFIG# ----------------------------------------------------# The authentication type# AUTH_OID : Is for OpenID# AUTH_DB : Is for database (username/password)# AUTH_LDAP : Is for LDAP# AUTH_REMOTE_USER : Is for using REMOTE_USER from web serverAUTH_TYPE = AUTH_DB# Uncomment to setup Full admin role name# AUTH_ROLE_ADMIN = 'Admin'# Uncomment to setup Public role name, no authentication needed# AUTH_ROLE_PUBLIC = 'Public'# Will allow user self registration# AUTH_USER_REGISTRATION = True# The default user self registration role# AUTH_USER_REGISTRATION_ROLE = "Public"# When using LDAP Auth, setup the LDAP server# AUTH_LDAP_SERVER = "ldap://ldapserver.new"# Uncomment to setup OpenID providers example for OpenID authentication# OPENID_PROVIDERS = [# { 'name': 'Yahoo', 'url': 'https://open./' },# { 'name': 'Flickr', 'url': '/<username>' },# ---------------------------------------------------# Roles config# ---------------------------------------------------# Grant public role the same set of permissions as for the GAMMA role.# This is useful if one wants to enable anonymous users to view# dashboards. Explicit grant on specific datasets is still required.PUBLIC_ROLE_LIKE_GAMMA = False# ---------------------------------------------------# Babel config for translations# ---------------------------------------------------# Setup default languageBABEL_DEFAULT_LOCALE = "en"# Your application default translation pathBABEL_DEFAULT_FOLDER = "superset/translations"# The allowed translation for you appLANGUAGES = {"en": {"flag": "us", "name": "English"},"es": {"flag": "es", "name": "Spanish"},"it": {"flag": "it", "name": "Italian"},"fr": {"flag": "fr", "name": "French"},"zh": {"flag": "cn", "name": "Chinese"},"ja": {"flag": "jp", "name": "Japanese"},"de": {"flag": "de", "name": "German"},"pt": {"flag": "pt", "name": "Portuguese"},"pt_BR": {"flag": "br", "name": "Brazilian Portuguese"},"ru": {"flag": "ru", "name": "Russian"},"ko": {"flag": "kr", "name": "Korean"},}# ---------------------------------------------------# Feature flags# ---------------------------------------------------# Feature flags that are set by default go here. Their values can be# overwritten by those specified under FEATURE_FLAGS in super_config.py# For example, DEFAULT_FEATURE_FLAGS = { 'FOO': True, 'BAR': False } here# and FEATURE_FLAGS = { 'BAR': True, 'BAZ': True } in superset_config.py# will result in combined feature flags of { 'FOO': True, 'BAR': True, 'BAZ': True }DEFAULT_FEATURE_FLAGS: Dict[str, bool] = {# Experimental feature introducing a client (browser) cache"CLIENT_CACHE": False,"ENABLE_EXPLORE_JSON_CSRF_PROTECTION": False,"KV_STORE": False,"PRESTO_EXPAND_DATA": False,# Exposes API endpoint to compute thumbnails"THUMBNAILS": False,"REDUCE_DASHBOARD_BOOTSTRAP_PAYLOAD": True,"SHARE_QUERIES_VIA_KV_STORE": False,"SIP_38_VIZ_REARCHITECTURE": False,"TAGGING_SYSTEM": False,"SQLLAB_BACKEND_PERSISTENCE": False,"LIST_VIEWS_SIP34_FILTER_UI": False,}# This is merely a default.FEATURE_FLAGS: Dict[str, bool] = {}# A function that receives a dict of all feature flags# (DEFAULT_FEATURE_FLAGS merged with FEATURE_FLAGS)# can alter it, and returns a similar dict. Note the dict of feature# flags passed to the function is a deepcopy of the dict in the config,# and can therefore be mutated without side-effect## GET_FEATURE_FLAGS_FUNC can be used to implement progressive rollouts,# role-based features, or a full on A/B testing framework.## from flask import g, request# def GET_FEATURE_FLAGS_FUNC(feature_flags_dict: Dict[str, bool]) -> Dict[str, bool]:#if hasattr(g, "user") and g.user.is_active:# feature_flags_dict['some_feature'] = g.user and g.user.id == 5#return feature_flags_dictGET_FEATURE_FLAGS_FUNC: Optional[Callable[[Dict[str, bool]], Dict[str, bool]]] = None# ---------------------------------------------------# Thumbnail config (behind feature flag)# ---------------------------------------------------THUMBNAIL_SELENIUM_USER = "Admin"THUMBNAIL_CACHE_CONFIG: CacheConfig = {'CACHE_TYPE': 'redis', # 使用 Redis 'CACHE_REDIS_HOST': 'localhost', # 配置域名 'CACHE_REDIS_PORT': 6379, # 配置端口号 'CACHE_REDIS_URL': 'redis://localhost:6379' # 配置 URL}# ---------------------------------------------------# Image and file configuration# ---------------------------------------------------# The file upload folder, when using models with filesUPLOAD_FOLDER = BASE_DIR + "/app/static/uploads/"UPLOAD_CHUNK_SIZE = 4096# The image upload folder, when using models with imagesIMG_UPLOAD_FOLDER = BASE_DIR + "/app/static/uploads/"# The image upload url, when using models with imagesIMG_UPLOAD_URL = "/static/uploads/"# Setup image size default is (300, 200, True)# IMG_SIZE = (300, 200, True)CACHE_DEFAULT_TIMEOUT = 60 * 60 * 24CACHE_CONFIG: CacheConfig = {'CACHE_TYPE': 'redis', # 使用 Redis 'CACHE_REDIS_HOST': 'localhost', # 配置域名 'CACHE_REDIS_PORT': 6379, # 配置端口号 'CACHE_REDIS_URL': 'redis://localhost:6379' # 配置 URL}TABLE_NAMES_CACHE_CONFIG: CacheConfig = {'CACHE_TYPE': 'redis', # 使用 Redis 'CACHE_REDIS_HOST': 'localhost', # 配置域名 'CACHE_REDIS_PORT': 6379, # 配置端口号 'CACHE_REDIS_URL': 'redis://localhost:6379' # 配置 URL}# CORS OptionsENABLE_CORS = FalseCORS_OPTIONS: Dict[Any, Any] = {}# Chrome allows up to 6 open connections per domain at a time. When there are more# than 6 slices in dashboard, a lot of time fetch requests are queued up and wait for# next available socket. PR #5039 is trying to allow domain sharding for Superset,# and this feature will be enabled by configuration only (by default Superset# doesn't allow cross-domain request).SUPERSET_WEBSERVER_DOMAINS = None# Allowed format types for upload on Database viewEXCEL_EXTENSIONS = {"xlsx", "xls"}CSV_EXTENSIONS = {"csv", "tsv"}ALLOWED_EXTENSIONS = {*EXCEL_EXTENSIONS, *CSV_EXTENSIONS}# CSV Options: key/value pairs that will be passed as argument to DataFrame.to_csv# method.# note: index option should not be overriddenCSV_EXPORT = {"encoding": "utf-8"}# ---------------------------------------------------# Time grain configurations# ---------------------------------------------------# List of time grains to disable in the application (see list of builtin# time grains in superset/db_engine_specs.builtin_time_grains).# For example: to disable 1 second time grain:# TIME_GRAIN_BLACKLIST = ['PT1S']TIME_GRAIN_BLACKLIST: List[str] = []# Additional time grains to be supported using similar definitions as in# superset/db_engine_specs.builtin_time_grains.# For example: To add a new 2 second time grain:# TIME_GRAIN_ADDONS = {'PT2S': '2 second'}TIME_GRAIN_ADDONS: Dict[str, str] = {}# Implementation of additional time grains per engine.# The column to be truncated is denoted `{col}` in the expression.# For example: To implement 2 second time grain on clickhouse engine:# TIME_GRAIN_ADDON_EXPRESSIONS = {#'clickhouse': {# 'PT2S': 'toDateTime(intDiv(toUInt32(toDateTime({col})), 2)*2)'#}# }TIME_GRAIN_ADDON_EXPRESSIONS: Dict[str, Dict[str, str]] = {}# ---------------------------------------------------# List of viz_types not allowed in your environment# For example: Blacklist pivot table and treemap:# VIZ_TYPE_BLACKLIST = ['pivot_table', 'treemap']# ---------------------------------------------------VIZ_TYPE_BLACKLIST: List[str] = []# ---------------------------------------------------# List of data sources not to be refreshed in druid cluster# ---------------------------------------------------DRUID_DATA_SOURCE_BLACKLIST: List[str] = []# --------------------------------------------------# Modules, datasources and middleware to be registered# --------------------------------------------------DEFAULT_MODULE_DS_MAP = OrderedDict([("superset.connectors.sqla.models", ["SqlaTable"]),("superset.connectors.druid.models", ["DruidDatasource"]),])ADDITIONAL_MODULE_DS_MAP: Dict[str, List[str]] = {}ADDITIONAL_MIDDLEWARE: List[Callable[..., Any]] = []# 1) https://docs.python-/writing/logging/# 2) /2/library/logging.config.html# Default configurator will consume the LOG_* settings belowLOGGING_CONFIGURATOR = DefaultLoggingConfigurator()# Console Log SettingsLOG_FORMAT = "%(asctime)s:%(levelname)s:%(name)s:%(message)s"LOG_LEVEL = "DEBUG"# ---------------------------------------------------# Enable Time Rotate Log Handler# ---------------------------------------------------# LOG_LEVEL = DEBUG, INFO, WARNING, ERROR, CRITICALENABLE_TIME_ROTATE = FalseTIME_ROTATE_LOG_LEVEL = "DEBUG"FILENAME = os.path.join(DATA_DIR, "superset.log")ROLLOVER = "midnight"INTERVAL = 1BACKUP_COUNT = 30# Custom logger for auditing queries. This can be used to send ran queries to a# structured immutable store for auditing purposes. The function is called for# every query ran, in both SQL Lab and charts/dashboards.# def QUERY_LOGGER(#database,#query,#schema=None,#user=None,#client=None,#security_manager=None,#log_params=None,# ):#passQUERY_LOGGER = None# Set this API key to enable Mapbox visualizationsMAPBOX_API_KEY = os.environ.get("MAPBOX_API_KEY", "")# Maximum number of rows returned from a database# in async mode, no more than SQL_MAX_ROW will be returned and stored# in the results backend. This also becomes the limit when exporting CSVsSQL_MAX_ROW = 100000# Maximum number of rows displayed in SQL Lab UI# Is set to avoid out of memory/localstorage issues in browsers. Does not affect# exported CSVsDISPLAY_MAX_ROW = 10000# Default row limit for SQL Lab queries. Is overridden by setting a new limit in# the SQL Lab UIDEFAULT_SQLLAB_LIMIT = 1000# Maximum number of tables/views displayed in the dropdown window in SQL Lab.MAX_TABLE_NAMES = 3000# Adds a warning message on sqllab save query and schedule query modals.SQLLAB_SAVE_WARNING_MESSAGE = NoneSQLLAB_SCHEDULE_WARNING_MESSAGE = None# If defined, shows this text in an alert-warning box in the navbar# one example use case may be "STAGING" to make it clear that this is# not the production version of the site.WARNING_MSG = None# Default celery config is to use SQLA as a broker, in a production setting# you'll want to use a proper broker as specified here:# /en/latest/getting-started/brokers/index.htmlclass CeleryConfig: # pylint: disable=too-few-public-methodsBROKER_URL = "sqla+sqlite:///celerydb.sqlite"CELERY_IMPORTS = ("superset.sql_lab", "superset.tasks")CELERY_RESULT_BACKEND = "db+sqlite:///celery_results.sqlite"CELERYD_LOG_LEVEL = "DEBUG"CELERYD_PREFETCH_MULTIPLIER = 1CELERY_ACKS_LATE = FalseCELERY_ANNOTATIONS = {"sql_lab.get_sql_results": {"rate_limit": "100/s"},"email_reports.send": {"rate_limit": "1/s","time_limit": 120,"soft_time_limit": 150,"ignore_result": True,},}CELERYBEAT_SCHEDULE = {"email_reports.schedule_hourly": {"task": "email_reports.schedule_hourly","schedule": crontab(minute=1, hour="*"),}}CELERY_CONFIG = CeleryConfig # pylint: disable=invalid-name# Set celery config to None to disable all the above configuration# CELERY_CONFIG = None# Additional static HTTP headers to be served by your Superset server. Note# Flask-Talisman applies the relevant security HTTP headers.## DEFAULT_HTTP_HEADERS: sets default values for HTTP headers. These may be overridden# within the app# OVERRIDE_HTTP_HEADERS: sets override values for HTTP headers. These values will# override anything set within the appDEFAULT_HTTP_HEADERS: Dict[str, Any] = {}OVERRIDE_HTTP_HEADERS: Dict[str, Any] = {}HTTP_HEADERS: Dict[str, Any] = {}# The db id here results in selecting this one as a default in SQL LabDEFAULT_DB_ID = None# Timeout duration for SQL Lab synchronous queriesSQLLAB_TIMEOUT = 30# Timeout duration for SQL Lab query validationSQLLAB_VALIDATION_TIMEOUT = 10# SQLLAB_DEFAULT_DBIDSQLLAB_DEFAULT_DBID = None# The MAX duration (in seconds) a query can run for before being killed# by celery.SQLLAB_ASYNC_TIME_LIMIT_SEC = 60 * 60 * 6# Some databases support running EXPLAIN queries that allow users to estimate# query costs before they run. These EXPLAIN queries should have a small# timeout.SQLLAB_QUERY_COST_ESTIMATE_TIMEOUT = 10 # seconds# Flag that controls if limit should be enforced on the CTA (create table as queries).SQLLAB_CTAS_NO_LIMIT = False# This allows you to define custom logic around the "CREATE TABLE AS" or CTAS feature# in SQL Lab that defines where the target schema should be for a given user.# Database `CTAS Schema` has a precedence over this setting.# Example below returns a username and CTA queries will write tables into the schema# name `username`# SQLLAB_CTAS_SCHEMA_NAME_FUNC = lambda database, user, schema, sql: user.username# This is move involved example where depending on the database you can leverage data# available to assign schema for the CTA query:# def compute_schema_name(database: Database, user: User, schema: str, sql: str) -> str:#if database.name == 'mysql_payments_slave':# return 'tmp_superset_schema'#if database.name == 'presto_gold':# return user.username#if database.name == 'analytics':# if 'analytics' in [r.name for r in user.roles]:# return 'analytics_cta'# else:# return f'tmp_{schema}'# Function accepts database object, user object, schema name and sql that will be run.SQLLAB_CTAS_SCHEMA_NAME_FUNC: Optional[Callable[["Database", "models.User", str, str], str]] = None# If enabled, it can be used to store the results of long-running queries# in SQL Lab by using the "Run Async" button/featureRESULTS_BACKEND: Optional[BaseCache] = None# Use PyArrow and MessagePack for async query results serialization,# rather than JSON. This feature requires additional testing from the# community before it is fully adopted, so this config option is provided# in order to disable should breaking issues be discovered.RESULTS_BACKEND_USE_MSGPACK = True# The S3 bucket where you want to store your external hive tables created# from CSV files. For example, 'companyname-superset'CSV_TO_HIVE_UPLOAD_S3_BUCKET = None# The directory within the bucket specified above that will# contain all the external tablesCSV_TO_HIVE_UPLOAD_DIRECTORY = "EXTERNAL_HIVE_TABLES/"# Function that creates upload directory dynamically based on the# database used, user and schema provided.CSV_TO_HIVE_UPLOAD_DIRECTORY_FUNC: Callable[["Database", "models.User", str], Optional[str]] = lambda database, user, schema: CSV_TO_HIVE_UPLOAD_DIRECTORY# The namespace within hive where the tables created from# uploading CSVs will be stored.UPLOADED_CSV_HIVE_NAMESPACE: Optional[str] = None# Function that computes the allowed schemas for the CSV uploads.# Allowed schemas will be a union of schemas_allowed_for_csv_upload# db configuration and a result of this function.# mypy doesn't catch that if case ensures list content being always strALLOWED_USER_CSV_SCHEMA_FUNC: Callable[["Database", "models.User"], List[str]] = lambda database, user: [UPLOADED_CSV_HIVE_NAMESPACE] if UPLOADED_CSV_HIVE_NAMESPACE else []# Values that should be treated as nulls for the csv uploads.CSV_DEFAULT_NA_NAMES = list(STR_NA_VALUES)# A dictionary of items that gets merged into the Jinja context for# SQL Lab. The existing context gets updated with this dictionary,# meaning values for existing keys get overwritten by the content of this# dictionary.JINJA_CONTEXT_ADDONS: Dict[str, Callable[..., Any]] = {}# A dictionary of macro template processors that gets merged into global# template processors. The existing template processors get updated with this# dictionary, which means the existing keys get overwritten by the content of this# dictionary. The customized addons don't necessarily need to use jinjia templating# language. This allows you to define custom logic to process macro template.CUSTOM_TEMPLATE_PROCESSORS: Dict[str, Type[BaseTemplateProcessor]] = {}# Roles that are controlled by the API / Superset and should not be changes# by humans.ROBOT_PERMISSION_ROLES = ["Public", "Gamma", "Alpha", "Admin", "sql_lab"]CONFIG_PATH_ENV_VAR = "SUPERSET_CONFIG_PATH"# If a callable is specified, it will be called at app startup while passing# a reference to the Flask app. This can be used to alter the Flask app# in whatever way.# example: FLASK_APP_MUTATOR = lambda x: x.before_request = fFLASK_APP_MUTATOR = None# Set this to false if you don't want users to be able to request/grant# datasource access requests from/to other users.ENABLE_ACCESS_REQUEST = False# smtp server configurationEMAIL_NOTIFICATIONS = False # all the emails are sent using dryrunSMTP_HOST = "localhost"SMTP_STARTTLS = TrueSMTP_SSL = FalseSMTP_USER = "superset"SMTP_PORT = 25SMTP_PASSWORD = "superset"SMTP_MAIL_FROM = "superset@"ENABLE_CHUNK_ENCODING = False# Whether to bump the logging level to ERROR on the flask_appbuilder package# Set to False if/when debugging FAB related issues like# permission managementSILENCE_FAB = TrueFAB_ADD_SECURITY_VIEWS = TrueFAB_ADD_SECURITY_PERMISSION_VIEW = FalseFAB_ADD_SECURITY_VIEW_MENU_VIEW = FalseFAB_ADD_SECURITY_PERMISSION_VIEWS_VIEW = False# The link to a page containing common errors and their resolutions# It will be appended at the bottom of sql_lab errors.TROUBLESHOOTING_LINK = ""# CSRF token timeout, set to None for a token that never expiresWTF_CSRF_TIME_LIMIT = 60 * 60 * 24 * 7# This link should lead to a page with instructions on how to gain access to a# Datasource. It will be placed at the bottom of permissions errors.PERMISSION_INSTRUCTIONS_LINK = ""# Integrate external Blueprints to the app by passing them to your# configuration. These blueprints will get integrated in the appBLUEPRINTS: List[Blueprint] = []# Provide a callable that receives a tracking_url and returns another# URL. This is used to translate internal Hadoop job tracker URL# into a proxied oneTRACKING_URL_TRANSFORMER = lambda x: x# Interval between consecutive polls when using Hive EngineHIVE_POLL_INTERVAL = 5# Allow for javascript controls components# this enables programmers to customize certain charts (like the# geospatial ones) by inputing javascript in controls. This exposes# an XSS security vulnerabilityENABLE_JAVASCRIPT_CONTROLS = False# The id of a template dashboard that should be copied to every new userDASHBOARD_TEMPLATE_ID = None# A callable that allows altering the database conneciton URL and params# on the fly, at runtime. This allows for things like impersonation or# arbitrary logic. For instance you can wire different users to# use different connection parameters, or pass their email address as the# username. The function receives the connection uri object, connection# params, the username, and returns the mutated uri and params objects.# Example:# def DB_CONNECTION_MUTATOR(uri, params, username, security_manager, source):# user = security_manager.find_user(username=username)# if user and user.email:# uri.username = user.email# return uri, params## Note that the returned uri and params are passed directly to sqlalchemy's# as such `create_engine(url, **params)`DB_CONNECTION_MUTATOR = None# A function that intercepts the SQL to be executed and can alter it.# The use case is can be around adding some sort of comment header# with information such as the username and worker node information## def SQL_QUERY_MUTATOR(sql, username, security_manager):# dttm = datetime.now().isoformat()# return f"-- [SQL LAB] {username} {dttm}\n{sql}"SQL_QUERY_MUTATOR = None# Enable / disable scheduled email reportsENABLE_SCHEDULED_EMAIL_REPORTS = False# Enable / disable Alerts, where users can define custom SQL that# will send emails with screenshots of charts or dashboards periodically# if it meets the criteriaENABLE_ALERTS = False# Slack API token for the superset reportsSLACK_API_TOKEN = NoneSLACK_PROXY = None# If enabled, certail features are run in debug mode# Current list:# * Emails are sent using dry-run mode (logging only)SCHEDULED_EMAIL_DEBUG_MODE = False# Email reports - minimum time resolution (in minutes) for the crontabEMAIL_REPORTS_CRON_RESOLUTION = 15# The MAX duration (in seconds) a email schedule can run for before being killed# by celery.EMAIL_ASYNC_TIME_LIMIT_SEC = 300# Email report configuration# From address in emailsEMAIL_REPORT_FROM_ADDRESS = "reports@"# Send bcc of all reports to this address. Set to None to disable.# This is useful for maintaining an audit trail of all email deliveries.EMAIL_REPORT_BCC_ADDRESS = None# User credentials to use for generating reports# This user should have permissions to browse all the dashboards and# slices.# TODO: In the future, login as the owner of the item to generate reportsEMAIL_REPORTS_USER = "admin"EMAIL_REPORTS_SUBJECT_PREFIX = "[Report] "# The webdriver to use for generating reports. Use one of the following# firefox# Requires: geckodriver and firefox installations# Limitations: can be buggy at times# chrome:# Requires: headless chrome# Limitations: unable to generate screenshots of elementsEMAIL_REPORTS_WEBDRIVER = "firefox"# Window size - this will impact the rendering of the dataWEBDRIVER_WINDOW = {"dashboard": (1600, 2000), "slice": (3000, 1200)}# Any config options to be passed as-is to the webdriverWEBDRIVER_CONFIGURATION: Dict[Any, Any] = {}# The base URL to query for accessing the user interfaceWEBDRIVER_BASEURL = "http://0.0.0.0:8080/"# The base URL for the email report hyperlinks.WEBDRIVER_BASEURL_USER_FRIENDLY = WEBDRIVER_BASEURL# Time in seconds, selenium will wait for the page to load# and render for the email report.EMAIL_PAGE_RENDER_WAIT = 30# Send user to a link where they can report bugsBUG_REPORT_URL = None# Send user to a link where they can read more about SupersetDOCUMENTATION_URL = NoneDOCUMENTATION_TEXT = "Documentation"DOCUMENTATION_ICON = None # Recommended size: 16x16# Enables the replacement react views for all the FAB views (list, edit, show) with# designs introduced in SIP-34: /apache/incubator-superset/issues/8976# This is a work in progress so not all features available in FAB have been implementedENABLE_REACT_CRUD_VIEWS = False# What is the Last N days relative in the time selector to:# 'today' means it is midnight (00:00:00) in the local timezone# 'now' means it is relative to the query issue time# If both start and end time is set to now, this will make the time# filter a moving window. By only setting the end time to now,# start time will be set to midnight, while end will be relative to# the query issue time.DEFAULT_RELATIVE_START_TIME = "today"DEFAULT_RELATIVE_END_TIME = "today"# Configure which SQL validator to use for each engineSQL_VALIDATORS_BY_ENGINE = {"presto": "PrestoDBSQLValidator"}# Do you want Talisman enabled?TALISMAN_ENABLED = False# If you want Talisman, how do you want it configured??TALISMAN_CONFIG = {"content_security_policy": None,"force_https": True,"force_https_permanent": False,}# Note that: RowLevelSecurityFilter is only given by default to the Admin role# and the Admin Role does have the all_datasources security permission.# But, if users create a specific role with access to RowLevelSecurityFilter MVC# and a custom datasource access, the table dropdown will not be correctly filtered# by that custom datasource access. So we are assuming a default security config,# a custom security config could potentially give access to setting filters on# tables that users do not have access to.ENABLE_ROW_LEVEL_SECURITY = False## Flask session cookie options## See /en/1.1.x/security/#set-cookie-options# for details#SESSION_COOKIE_HTTPONLY = True # Prevent cookie from being read by frontend JS?SESSION_COOKIE_SECURE = False # Prevent cookie from being transmitted over non-tls?SESSION_COOKIE_SAMESITE = "Lax" # One of [None, 'Lax', 'Strict']# Flask configuration variablesSEND_FILE_MAX_AGE_DEFAULT = 60 * 60 * 24 * 365 # Cache static resources# URI to database storing the example data, points to# SQLALCHEMY_DATABASE_URI by default if set to `None`SQLALCHEMY_EXAMPLES_URI = None# Some sqlalchemy connection strings can open Superset to security risks.# Typically these should not be allowed.PREVENT_UNSAFE_DB_CONNECTIONS = True# Path used to store SSL certificates that are generated when using custom certs.# Defaults to temporary directory.# Example: SSL_CERT_PATH = "/certs"SSL_CERT_PATH: Optional[str] = None# SIP-15 should be enabled for all new Superset deployments which ensures that the time# range endpoints adhere to [start, end). For existing deployments admins should provide# a dedicated period of time to allow chart producers to update their charts before# mass migrating all charts to use the [start, end) interval.## Note if no end date for the grace period is specified then the grace period is# indefinite.SIP_15_ENABLED = TrueSIP_15_GRACE_PERIOD_END: Optional[date] = None # exclusiveSIP_15_DEFAULT_TIME_RANGE_ENDPOINTS = ["unknown", "inclusive"]SIP_15_TOAST_MESSAGE = ("Action Required: Preview then save your chart using the "'new time range endpoints <a target="_blank" href="{url}" ''class="alert-link">here</a>.')# SQLA table mutator, every time we fetch the metadata for a certain table# (superset.connectors.sqla.models.SqlaTable), we call this hook# to allow mutating the object with this callback.# This can be used to set any properties of the object based on naming# conventions and such. You can find examples in the tests.SQLA_TABLE_MUTATOR = lambda table: tableif CONFIG_PATH_ENV_VAR in os.environ:# Explicitly import config module that is not necessarily in pythonpath; useful# for case where app is being executed via pex.try:cfg_path = os.environ[CONFIG_PATH_ENV_VAR]module = sys.modules[__name__]override_conf = imp.load_source("superset_config", cfg_path)for key in dir(override_conf):if key.isupper():setattr(module, key, getattr(override_conf, key))print(f"Loaded your LOCAL configuration at [{cfg_path}]")except Exception:logger.exception("Failed to import config for %s=%s", CONFIG_PATH_ENV_VAR, cfg_path)raiseelif importlib.util.find_spec("superset_config"):try:from superset_config import * # pylint: disable=import-error,wildcard-import,unused-wildcard-importimport superset_config # pylint: disable=import-errorprint(f"Loaded your LOCAL configuration at [{superset_config.__file__}]")except Exception:logger.exception("Found but failed to import local superset_config")raise
Reference:
[1]Caching charts in Superset
[2]Superset Timeouts
[3]cache的源码
[4]使用 Redis 做 Superset 的缓存
