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feat(build): migrate from Prettier to Oxfmt for performant code formatting (#42434)
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Đỗ Trọng Hải
@@ -9,8 +9,8 @@ version: 2
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Users can configure automated alerts and reports to send dashboards or charts to an email recipient or Slack channel.
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- *Alerts* are sent when a SQL condition is reached
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- *Reports* are sent on a schedule
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- _Alerts_ are sent when a SQL condition is reached
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- _Reports_ are sent on a schedule
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Alerts and reports are disabled by default. To turn them on, you need to do some setup, described here.
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@@ -26,25 +26,25 @@ Alerts and reports are disabled by default. To turn them on, you need to do some
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- emails: `SMTP_*` settings
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- Slack messages: `SLACK_API_TOKEN`
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- Users can customize the email subject by including date code placeholders, which will automatically be replaced with the corresponding UTC date when the email is sent. To enable this functionality, activate the `"DATE_FORMAT_IN_EMAIL_SUBJECT"` [feature flag](/user-docs/6.0.0/configuration/configuring-superset#feature-flags). This enables date formatting in email subjects, preventing all reporting emails from being grouped into the same thread (optional for the reporting feature).
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- Use date codes from [strftime.org](https://strftime.org/) to create the email subject.
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- If no date code is provided, the original string will be used as the email subject.
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- Use date codes from [strftime.org](https://strftime.org/) to create the email subject.
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- If no date code is provided, the original string will be used as the email subject.
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##### Disable dry-run mode
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Screenshots will be taken but no messages actually sent as long as `ALERT_REPORTS_NOTIFICATION_DRY_RUN = True`, its default value in `docker/pythonpath_dev/superset_config.py`. To disable dry-run mode and start receiving email/Slack notifications, set `ALERT_REPORTS_NOTIFICATION_DRY_RUN` to `False` in [superset config](https://github.com/apache/superset/blob/master/docker/pythonpath_dev/superset_config.py).
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Screenshots will be taken but no messages actually sent as long as `ALERT_REPORTS_NOTIFICATION_DRY_RUN = True`, its default value in `docker/pythonpath_dev/superset_config.py`. To disable dry-run mode and start receiving email/Slack notifications, set `ALERT_REPORTS_NOTIFICATION_DRY_RUN` to `False` in [superset config](https://github.com/apache/superset/blob/master/docker/pythonpath_dev/superset_config.py).
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#### In your `Dockerfile`
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- You must install a headless browser, for taking screenshots of the charts and dashboards. Only Firefox and Chrome are currently supported.
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> If you choose Chrome, you must also change the value of `WEBDRIVER_TYPE` to `"chrome"` in your `superset_config.py`.
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Note: All the components required (Firefox headless browser, Redis, Postgres db, celery worker and celery beat) are present in the *dev* docker image if you are following [Installing Superset Locally](/user-docs/6.0.0/installation/docker-compose/).
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Note: All the components required (Firefox headless browser, Redis, Postgres db, celery worker and celery beat) are present in the _dev_ docker image if you are following [Installing Superset Locally](/user-docs/6.0.0/installation/docker-compose/).
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All you need to do is add the required config variables described in this guide (See `Detailed Config`).
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If you are running a non-dev docker image, e.g., a stable release like `apache/superset:3.1.0`, that image does not include a headless browser. Only the `superset_worker` container needs this headless browser to browse to the target chart or dashboard.
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If you are running a non-dev docker image, e.g., a stable release like `apache/superset:3.1.0`, that image does not include a headless browser. Only the `superset_worker` container needs this headless browser to browse to the target chart or dashboard.
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You can either install and configure the headless browser - see "Custom Dockerfile" section below - or when deploying via `docker compose`, modify your `docker-compose.yml` file to use a dev image for the worker container and a stable release image for the `superset_app` container.
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*Note*: In this context, a "dev image" is the same application software as its corresponding non-dev image, just bundled with additional tools. So an image like `3.1.0-dev` is identical to `3.1.0` when it comes to stability, functionality, and running in production. The actual "in-development" versions of Superset - cutting-edge and unstable - are not tagged with version numbers on Docker Hub and will display version `0.0.0-dev` within the Superset UI.
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_Note_: In this context, a "dev image" is the same application software as its corresponding non-dev image, just bundled with additional tools. So an image like `3.1.0-dev` is identical to `3.1.0` when it comes to stability, functionality, and running in production. The actual "in-development" versions of Superset - cutting-edge and unstable - are not tagged with version numbers on Docker Hub and will display version `0.0.0-dev` within the Superset UI.
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### Slack integration
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@@ -94,7 +94,7 @@ You need to replace default values with your custom Redis, Slack and/or SMTP con
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Superset uses Celery beat and Celery worker(s) to send alerts and reports.
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- The beat is the scheduler that tells the worker when to perform its tasks. This schedule is defined when you create the alert or report.
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- The worker will process the tasks that need to be performed when an alert or report is fired.
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- The worker will process the tasks that need to be performed when an alert or report is fired.
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In the `CeleryConfig`, only the `beat_schedule` is relevant to this feature, the rest of the `CeleryConfig` can be changed for your needs.
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@@ -201,7 +201,7 @@ Please refer to `ExecutorType` in the codebase for other executor types.
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It's also possible to specify a minimum interval between each report's execution through the config file:
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``` python
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```python
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# Set a minimum interval threshold between executions (for each Alert/Report)
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# Value should be an integer
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ALERT_MINIMUM_INTERVAL = int(timedelta(minutes=10).total_seconds())
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@@ -210,7 +210,7 @@ REPORT_MINIMUM_INTERVAL = int(timedelta(minutes=5).total_seconds())
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Alternatively, you can assign a function to `ALERT_MINIMUM_INTERVAL` and/or `REPORT_MINIMUM_INTERVAL`. This is useful to dynamically retrieve a value as needed:
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``` python
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```python
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def alert_dynamic_minimal_interval(**kwargs) -> int:
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"""
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Define logic here to retrieve the value dynamically
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@@ -277,17 +277,17 @@ Don't forget to set `WEBDRIVER_TYPE` and `WEBDRIVER_OPTION_ARGS` in your config
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## Troubleshooting
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There are many reasons that reports might not be working. Try these steps to check for specific issues.
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There are many reasons that reports might not be working. Try these steps to check for specific issues.
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### Confirm feature flag is enabled and you have sufficient permissions
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If you don't see "Alerts & Reports" under the *Manage* section of the Settings dropdown in the Superset UI, you need to enable the `ALERT_REPORTS` feature flag (see above). Enable another feature flag and check to see that it took effect, to verify that your config file is getting loaded.
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If you don't see "Alerts & Reports" under the _Manage_ section of the Settings dropdown in the Superset UI, you need to enable the `ALERT_REPORTS` feature flag (see above). Enable another feature flag and check to see that it took effect, to verify that your config file is getting loaded.
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Log in as an admin user to ensure you have adequate permissions.
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### Check the logs of your Celery worker
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This is the best source of information about the problem. In a docker compose deployment, you can do this with a command like `docker logs superset_worker --since 1h`.
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This is the best source of information about the problem. In a docker compose deployment, you can do this with a command like `docker logs superset_worker --since 1h`.
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### Check web browser and webdriver installation
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@@ -301,7 +301,7 @@ If you are handling the installation of that software on your own, or wish to us
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One symptom of an invalid connection to an email server is receiving an error of `[Errno 110] Connection timed out` in your logs when the report tries to send.
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Confirm via testing that your outbound email configuration is correct. Here is the simplest test, for an un-authenticated email SMTP email service running on port 25. If you are sending over SSL, for instance, study how [Superset's codebase sends emails](https://github.com/apache/superset/blob/master/superset/utils/core.py#L818) and then test with those commands and arguments.
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Confirm via testing that your outbound email configuration is correct. Here is the simplest test, for an un-authenticated email SMTP email service running on port 25. If you are sending over SSL, for instance, study how [Superset's codebase sends emails](https://github.com/apache/superset/blob/master/superset/utils/core.py#L818) and then test with those commands and arguments.
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Start Python in your worker environment, replace all example values, and run:
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@@ -327,16 +327,16 @@ This should send an email.
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Possible fixes:
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- Some cloud hosts disable outgoing unauthenticated SMTP email to prevent spam. For instance, [Azure blocks port 25 by default on some machines](https://learn.microsoft.com/en-us/azure/virtual-network/troubleshoot-outbound-smtp-connectivity). Enable that port or use another sending method.
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- Some cloud hosts disable outgoing unauthenticated SMTP email to prevent spam. For instance, [Azure blocks port 25 by default on some machines](https://learn.microsoft.com/en-us/azure/virtual-network/troubleshoot-outbound-smtp-connectivity). Enable that port or use another sending method.
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- Use another set of SMTP credentials that you verify works in this setup.
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### Browse to your report from the worker
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The worker may be unable to reach the report. It will use the value of `WEBDRIVER_BASEURL` to browse to the report. If that route is invalid, or presents an authentication challenge that the worker can't pass, the report screenshot will fail.
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The worker may be unable to reach the report. It will use the value of `WEBDRIVER_BASEURL` to browse to the report. If that route is invalid, or presents an authentication challenge that the worker can't pass, the report screenshot will fail.
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Check this by attempting to `curl` the URL of a report that you see in the error logs of your worker. For instance, from the worker environment, run `curl http://superset_app:8088/superset/dashboard/1/`. You may get different responses depending on whether the dashboard exists - for example, you may need to change the `1` in that URL. If there's a URL in your logs from a failed report screenshot, that's a good place to start. The goal is to determine a valid value for `WEBDRIVER_BASEURL` and determine if an issue like HTTPS or authentication is redirecting your worker.
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In a deployment with authentication measures enabled like HTTPS and Single Sign-On, it may make sense to have the worker navigate directly to the Superset application running in the same location, avoiding the need to sign in. For instance, you could use `WEBDRIVER_BASEURL="http://superset_app:8088"` for a docker compose deployment, and set `"force_https": False,` in your `TALISMAN_CONFIG`.
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In a deployment with authentication measures enabled like HTTPS and Single Sign-On, it may make sense to have the worker navigate directly to the Superset application running in the same location, avoiding the need to sign in. For instance, you could use `WEBDRIVER_BASEURL="http://superset_app:8088"` for a docker compose deployment, and set `"force_https": False,` in your `TALISMAN_CONFIG`.
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## Scheduling Queries as Reports
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@@ -225,7 +225,7 @@ RequestHeader set X-Forwarded-Proto "https"
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## Configuring the application root
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*Please be advised that this feature is in BETA.*
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_Please be advised that this feature is in BETA._
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Superset supports running the application under a non-root path. The root path
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prefix can be specified in one of two ways:
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@@ -311,10 +311,13 @@ AUTH_USER_REGISTRATION_ROLE = "Public"
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```
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In case you want to assign the `Admin` role on new user registration, it can be assigned as follows:
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```python
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AUTH_USER_REGISTRATION_ROLE = "Admin"
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```
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If you encounter the [issue](https://github.com/apache/superset/issues/13243) of not being able to list users from the Superset main page settings, although a newly registered user has an `Admin` role, please re-run `superset init` to sync the required permissions. Below is the command to re-run `superset init` using docker compose.
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```
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docker-compose exec superset superset init
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```
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@@ -22,10 +22,10 @@ The current list of countries can be found in the src
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The Country Maps visualization already ships with the maps for the following countries:
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<ul style={{columns: 3}}>
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{countriesData.countries.map((country, index) => (
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<li key={index}>{country}</li>
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))}
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<ul style={{ columns: 3 }}>
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{countriesData.countries.map((country, index) => (
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<li key={index}>{country}</li>
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))}
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</ul>
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## Adding a New Country
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@@ -4,6 +4,7 @@ hide_title: true
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sidebar_position: 1
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version: 1
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---
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# Connecting to Databases
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Superset does not ship bundled with connectivity to databases. The main step in connecting
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@@ -35,55 +36,55 @@ Some of the recommended packages are shown below. Please refer to
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[pyproject.toml](https://github.com/apache/superset/blob/master/pyproject.toml) for the versions that
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are compatible with Superset.
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| <div style={{width: '150px'}}>Database</div> | PyPI package | Connection String |
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| --------------------------------------------------------- | ---------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------ |
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| [AWS Athena](/user-docs/6.0.0/configuration/databases#aws-athena) | `pip install pyathena[pandas]` , `pip install PyAthenaJDBC` | `awsathena+rest://{access_key_id}:{access_key}@athena.{region}.amazonaws.com/{schema}?s3_staging_dir={s3_staging_dir}&...` |
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| [AWS DynamoDB](/user-docs/6.0.0/configuration/databases#aws-dynamodb) | `pip install pydynamodb` | `dynamodb://{access_key_id}:{secret_access_key}@dynamodb.{region_name}.amazonaws.com?connector=superset` |
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| [AWS Redshift](/user-docs/6.0.0/configuration/databases#aws-redshift) | `pip install sqlalchemy-redshift` | `redshift+psycopg2://<userName>:<DBPassword>@<AWS End Point>:5439/<Database Name>` |
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| [Apache Doris](/user-docs/6.0.0/configuration/databases#apache-doris) | `pip install pydoris` | `doris://<User>:<Password>@<Host>:<Port>/<Catalog>.<Database>` |
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| [Apache Drill](/user-docs/6.0.0/configuration/databases#apache-drill) | `pip install sqlalchemy-drill` | `drill+sadrill://<username>:<password>@<host>:<port>/<storage_plugin>`, often useful: `?use_ssl=True/False` |
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| [Apache Druid](/user-docs/6.0.0/configuration/databases#apache-druid) | `pip install pydruid` | `druid://<User>:<password>@<Host>:<Port-default-9088>/druid/v2/sql` |
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| [Apache Hive](/user-docs/6.0.0/configuration/databases#hive) | `pip install pyhive` | `hive://hive@{hostname}:{port}/{database}` |
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| [Apache Impala](/user-docs/6.0.0/configuration/databases#apache-impala) | `pip install impyla` | `impala://{hostname}:{port}/{database}` |
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| [Apache Kylin](/user-docs/6.0.0/configuration/databases#apache-kylin) | `pip install kylinpy` | `kylin://<username>:<password>@<hostname>:<port>/<project>?<param1>=<value1>&<param2>=<value2>` |
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| [Apache Pinot](/user-docs/6.0.0/configuration/databases#apache-pinot) | `pip install pinotdb` | `pinot://BROKER:5436/query?server=http://CONTROLLER:5983/` |
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| [Apache Solr](/user-docs/6.0.0/configuration/databases#apache-solr) | `pip install sqlalchemy-solr` | `solr://{username}:{password}@{hostname}:{port}/{server_path}/{collection}` |
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| [Apache Spark SQL](/user-docs/6.0.0/configuration/databases#apache-spark-sql) | `pip install pyhive` | `hive://hive@{hostname}:{port}/{database}` |
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| [Ascend.io](/user-docs/6.0.0/configuration/databases#ascendio) | `pip install impyla` | `ascend://{username}:{password}@{hostname}:{port}/{database}?auth_mechanism=PLAIN;use_ssl=true` |
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| [Azure MS SQL](/user-docs/6.0.0/configuration/databases#sql-server) | `pip install pymssql` | `mssql+pymssql://UserName@presetSQL:TestPassword@presetSQL.database.windows.net:1433/TestSchema` |
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| [ClickHouse](/user-docs/6.0.0/configuration/databases#clickhouse) | `pip install clickhouse-connect` | `clickhousedb://{username}:{password}@{hostname}:{port}/{database}` |
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| [CockroachDB](/user-docs/6.0.0/configuration/databases#cockroachdb) | `pip install cockroachdb` | `cockroachdb://root@{hostname}:{port}/{database}?sslmode=disable` |
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| [Couchbase](/user-docs/6.0.0/configuration/databases#couchbase) | `pip install couchbase-sqlalchemy` | `couchbase://{username}:{password}@{hostname}:{port}?truststorepath={ssl certificate path}` |
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| [CrateDB](/user-docs/6.0.0/configuration/databases#cratedb) | `pip install sqlalchemy-cratedb` | `crate://{username}:{password}@{hostname}:{port}`, often useful: `?ssl=true/false` or `?schema=testdrive`. |
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| [Denodo](/user-docs/6.0.0/configuration/databases#denodo) | `pip install denodo-sqlalchemy` | `denodo://{username}:{password}@{hostname}:{port}/{database}` |
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| [Dremio](/user-docs/6.0.0/configuration/databases#dremio) | `pip install sqlalchemy_dremio` |`dremio+flight://{username}:{password}@{host}:32010`, often useful: `?UseEncryption=true/false`. For Legacy ODBC: `dremio+pyodbc://{username}:{password}@{host}:31010` |
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| [Elasticsearch](/user-docs/6.0.0/configuration/databases#elasticsearch) | `pip install elasticsearch-dbapi` | `elasticsearch+http://{user}:{password}@{host}:9200/` |
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| [Exasol](/user-docs/6.0.0/configuration/databases#exasol) | `pip install sqlalchemy-exasol` | `exa+pyodbc://{username}:{password}@{hostname}:{port}/my_schema?CONNECTIONLCALL=en_US.UTF-8&driver=EXAODBC` |
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| [Google BigQuery](/user-docs/6.0.0/configuration/databases#google-bigquery) | `pip install sqlalchemy-bigquery` | `bigquery://{project_id}` |
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| [Google Sheets](/user-docs/6.0.0/configuration/databases#google-sheets) | `pip install shillelagh[gsheetsapi]` | `gsheets://` |
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| [Firebolt](/user-docs/6.0.0/configuration/databases#firebolt) | `pip install firebolt-sqlalchemy` | `firebolt://{client_id}:{client_secret}@{database}/{engine_name}?account_name={name}` |
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| [Hologres](/user-docs/6.0.0/configuration/databases#hologres) | `pip install psycopg2` | `postgresql+psycopg2://<UserName>:<DBPassword>@<Database Host>/<Database Name>` |
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| [IBM Db2](/user-docs/6.0.0/configuration/databases#ibm-db2) | `pip install ibm_db_sa` | `db2+ibm_db://` |
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| [IBM Netezza Performance Server](/user-docs/6.0.0/configuration/databases#ibm-netezza-performance-server) | `pip install nzalchemy` | `netezza+nzpy://<UserName>:<DBPassword>@<Database Host>/<Database Name>` |
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| [MySQL](/user-docs/6.0.0/configuration/databases#mysql) | `pip install mysqlclient` | `mysql://<UserName>:<DBPassword>@<Database Host>/<Database Name>` |
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| [OceanBase](/user-docs/6.0.0/configuration/databases#oceanbase) | `pip install oceanbase_py` | `oceanbase://<UserName>:<DBPassword>@<Database Host>/<Database Name>` |
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| [Oracle](/user-docs/6.0.0/configuration/databases#oracle) | `pip install cx_Oracle` | `oracle://<username>:<password>@<hostname>:<port>` |
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| [Parseable](/user-docs/6.0.0/configuration/databases#parseable) | `pip install sqlalchemy-parseable` | `parseable://<UserName>:<DBPassword>@<Database Host>/<Stream Name>` |
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| [PostgreSQL](/user-docs/6.0.0/configuration/databases#postgres) | `pip install psycopg2` | `postgresql://<UserName>:<DBPassword>@<Database Host>/<Database Name>` |
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| [Presto](/user-docs/6.0.0/configuration/databases#presto) | `pip install pyhive` | `presto://{username}:{password}@{hostname}:{port}/{database}` |
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| [SAP Hana](/user-docs/6.0.0/configuration/databases#hana) | `pip install hdbcli sqlalchemy-hana` or `pip install apache_superset[hana]` | `hana://{username}:{password}@{host}:{port}` |
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| [SingleStore](/user-docs/6.0.0/configuration/databases#singlestore) | `pip install sqlalchemy-singlestoredb` | `singlestoredb://{username}:{password}@{host}:{port}/{database}` |
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| [StarRocks](/user-docs/6.0.0/configuration/databases#starrocks) | `pip install starrocks` | `starrocks://<User>:<Password>@<Host>:<Port>/<Catalog>.<Database>` |
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| [Snowflake](/user-docs/6.0.0/configuration/databases#snowflake) | `pip install snowflake-sqlalchemy` | `snowflake://{user}:{password}@{account}.{region}/{database}?role={role}&warehouse={warehouse}` |
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| SQLite | No additional library needed | `sqlite://path/to/file.db?check_same_thread=false` |
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| [SQL Server](/user-docs/6.0.0/configuration/databases#sql-server) | `pip install pymssql` | `mssql+pymssql://<Username>:<Password>@<Host>:<Port-default:1433>/<Database Name>` |
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| [TDengine](/user-docs/6.0.0/configuration/databases#tdengine) | `pip install taospy` `pip install taos-ws-py` | `taosws://<user>:<password>@<host>:<port>` |
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| [Teradata](/user-docs/6.0.0/configuration/databases#teradata) | `pip install teradatasqlalchemy` | `teradatasql://{user}:{password}@{host}` |
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| [TimescaleDB](/user-docs/6.0.0/configuration/databases#timescaledb) | `pip install psycopg2` | `postgresql://<UserName>:<DBPassword>@<Database Host>:<Port>/<Database Name>` |
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| [Trino](/user-docs/6.0.0/configuration/databases#trino) | `pip install trino` | `trino://{username}:{password}@{hostname}:{port}/{catalog}` |
|
||||
| [Vertica](/user-docs/6.0.0/configuration/databases#vertica) | `pip install sqlalchemy-vertica-python` | `vertica+vertica_python://<UserName>:<DBPassword>@<Database Host>/<Database Name>` |
|
||||
| [YDB](/user-docs/6.0.0/configuration/databases#ydb) | `pip install ydb-sqlalchemy` | `ydb://{host}:{port}/{database_name}` |
|
||||
| [YugabyteDB](/user-docs/6.0.0/configuration/databases#yugabytedb) | `pip install psycopg2` | `postgresql://<UserName>:<DBPassword>@<Database Host>/<Database Name>` |
|
||||
| <div style={{width: '150px'}}>Database</div> | PyPI package | Connection String |
|
||||
| --------------------------------------------------------------------------------------------------------- | --------------------------------------------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
|
||||
| [AWS Athena](/user-docs/6.0.0/configuration/databases#aws-athena) | `pip install pyathena[pandas]` , `pip install PyAthenaJDBC` | `awsathena+rest://{access_key_id}:{access_key}@athena.{region}.amazonaws.com/{schema}?s3_staging_dir={s3_staging_dir}&...` |
|
||||
| [AWS DynamoDB](/user-docs/6.0.0/configuration/databases#aws-dynamodb) | `pip install pydynamodb` | `dynamodb://{access_key_id}:{secret_access_key}@dynamodb.{region_name}.amazonaws.com?connector=superset` |
|
||||
| [AWS Redshift](/user-docs/6.0.0/configuration/databases#aws-redshift) | `pip install sqlalchemy-redshift` | `redshift+psycopg2://<userName>:<DBPassword>@<AWS End Point>:5439/<Database Name>` |
|
||||
| [Apache Doris](/user-docs/6.0.0/configuration/databases#apache-doris) | `pip install pydoris` | `doris://<User>:<Password>@<Host>:<Port>/<Catalog>.<Database>` |
|
||||
| [Apache Drill](/user-docs/6.0.0/configuration/databases#apache-drill) | `pip install sqlalchemy-drill` | `drill+sadrill://<username>:<password>@<host>:<port>/<storage_plugin>`, often useful: `?use_ssl=True/False` |
|
||||
| [Apache Druid](/user-docs/6.0.0/configuration/databases#apache-druid) | `pip install pydruid` | `druid://<User>:<password>@<Host>:<Port-default-9088>/druid/v2/sql` |
|
||||
| [Apache Hive](/user-docs/6.0.0/configuration/databases#hive) | `pip install pyhive` | `hive://hive@{hostname}:{port}/{database}` |
|
||||
| [Apache Impala](/user-docs/6.0.0/configuration/databases#apache-impala) | `pip install impyla` | `impala://{hostname}:{port}/{database}` |
|
||||
| [Apache Kylin](/user-docs/6.0.0/configuration/databases#apache-kylin) | `pip install kylinpy` | `kylin://<username>:<password>@<hostname>:<port>/<project>?<param1>=<value1>&<param2>=<value2>` |
|
||||
| [Apache Pinot](/user-docs/6.0.0/configuration/databases#apache-pinot) | `pip install pinotdb` | `pinot://BROKER:5436/query?server=http://CONTROLLER:5983/` |
|
||||
| [Apache Solr](/user-docs/6.0.0/configuration/databases#apache-solr) | `pip install sqlalchemy-solr` | `solr://{username}:{password}@{hostname}:{port}/{server_path}/{collection}` |
|
||||
| [Apache Spark SQL](/user-docs/6.0.0/configuration/databases#apache-spark-sql) | `pip install pyhive` | `hive://hive@{hostname}:{port}/{database}` |
|
||||
| [Ascend.io](/user-docs/6.0.0/configuration/databases#ascendio) | `pip install impyla` | `ascend://{username}:{password}@{hostname}:{port}/{database}?auth_mechanism=PLAIN;use_ssl=true` |
|
||||
| [Azure MS SQL](/user-docs/6.0.0/configuration/databases#sql-server) | `pip install pymssql` | `mssql+pymssql://UserName@presetSQL:TestPassword@presetSQL.database.windows.net:1433/TestSchema` |
|
||||
| [ClickHouse](/user-docs/6.0.0/configuration/databases#clickhouse) | `pip install clickhouse-connect` | `clickhousedb://{username}:{password}@{hostname}:{port}/{database}` |
|
||||
| [CockroachDB](/user-docs/6.0.0/configuration/databases#cockroachdb) | `pip install cockroachdb` | `cockroachdb://root@{hostname}:{port}/{database}?sslmode=disable` |
|
||||
| [Couchbase](/user-docs/6.0.0/configuration/databases#couchbase) | `pip install couchbase-sqlalchemy` | `couchbase://{username}:{password}@{hostname}:{port}?truststorepath={ssl certificate path}` |
|
||||
| [CrateDB](/user-docs/6.0.0/configuration/databases#cratedb) | `pip install sqlalchemy-cratedb` | `crate://{username}:{password}@{hostname}:{port}`, often useful: `?ssl=true/false` or `?schema=testdrive`. |
|
||||
| [Denodo](/user-docs/6.0.0/configuration/databases#denodo) | `pip install denodo-sqlalchemy` | `denodo://{username}:{password}@{hostname}:{port}/{database}` |
|
||||
| [Dremio](/user-docs/6.0.0/configuration/databases#dremio) | `pip install sqlalchemy_dremio` | `dremio+flight://{username}:{password}@{host}:32010`, often useful: `?UseEncryption=true/false`. For Legacy ODBC: `dremio+pyodbc://{username}:{password}@{host}:31010` |
|
||||
| [Elasticsearch](/user-docs/6.0.0/configuration/databases#elasticsearch) | `pip install elasticsearch-dbapi` | `elasticsearch+http://{user}:{password}@{host}:9200/` |
|
||||
| [Exasol](/user-docs/6.0.0/configuration/databases#exasol) | `pip install sqlalchemy-exasol` | `exa+pyodbc://{username}:{password}@{hostname}:{port}/my_schema?CONNECTIONLCALL=en_US.UTF-8&driver=EXAODBC` |
|
||||
| [Google BigQuery](/user-docs/6.0.0/configuration/databases#google-bigquery) | `pip install sqlalchemy-bigquery` | `bigquery://{project_id}` |
|
||||
| [Google Sheets](/user-docs/6.0.0/configuration/databases#google-sheets) | `pip install shillelagh[gsheetsapi]` | `gsheets://` |
|
||||
| [Firebolt](/user-docs/6.0.0/configuration/databases#firebolt) | `pip install firebolt-sqlalchemy` | `firebolt://{client_id}:{client_secret}@{database}/{engine_name}?account_name={name}` |
|
||||
| [Hologres](/user-docs/6.0.0/configuration/databases#hologres) | `pip install psycopg2` | `postgresql+psycopg2://<UserName>:<DBPassword>@<Database Host>/<Database Name>` |
|
||||
| [IBM Db2](/user-docs/6.0.0/configuration/databases#ibm-db2) | `pip install ibm_db_sa` | `db2+ibm_db://` |
|
||||
| [IBM Netezza Performance Server](/user-docs/6.0.0/configuration/databases#ibm-netezza-performance-server) | `pip install nzalchemy` | `netezza+nzpy://<UserName>:<DBPassword>@<Database Host>/<Database Name>` |
|
||||
| [MySQL](/user-docs/6.0.0/configuration/databases#mysql) | `pip install mysqlclient` | `mysql://<UserName>:<DBPassword>@<Database Host>/<Database Name>` |
|
||||
| [OceanBase](/user-docs/6.0.0/configuration/databases#oceanbase) | `pip install oceanbase_py` | `oceanbase://<UserName>:<DBPassword>@<Database Host>/<Database Name>` |
|
||||
| [Oracle](/user-docs/6.0.0/configuration/databases#oracle) | `pip install cx_Oracle` | `oracle://<username>:<password>@<hostname>:<port>` |
|
||||
| [Parseable](/user-docs/6.0.0/configuration/databases#parseable) | `pip install sqlalchemy-parseable` | `parseable://<UserName>:<DBPassword>@<Database Host>/<Stream Name>` |
|
||||
| [PostgreSQL](/user-docs/6.0.0/configuration/databases#postgres) | `pip install psycopg2` | `postgresql://<UserName>:<DBPassword>@<Database Host>/<Database Name>` |
|
||||
| [Presto](/user-docs/6.0.0/configuration/databases#presto) | `pip install pyhive` | `presto://{username}:{password}@{hostname}:{port}/{database}` |
|
||||
| [SAP Hana](/user-docs/6.0.0/configuration/databases#hana) | `pip install hdbcli sqlalchemy-hana` or `pip install apache_superset[hana]` | `hana://{username}:{password}@{host}:{port}` |
|
||||
| [SingleStore](/user-docs/6.0.0/configuration/databases#singlestore) | `pip install sqlalchemy-singlestoredb` | `singlestoredb://{username}:{password}@{host}:{port}/{database}` |
|
||||
| [StarRocks](/user-docs/6.0.0/configuration/databases#starrocks) | `pip install starrocks` | `starrocks://<User>:<Password>@<Host>:<Port>/<Catalog>.<Database>` |
|
||||
| [Snowflake](/user-docs/6.0.0/configuration/databases#snowflake) | `pip install snowflake-sqlalchemy` | `snowflake://{user}:{password}@{account}.{region}/{database}?role={role}&warehouse={warehouse}` |
|
||||
| SQLite | No additional library needed | `sqlite://path/to/file.db?check_same_thread=false` |
|
||||
| [SQL Server](/user-docs/6.0.0/configuration/databases#sql-server) | `pip install pymssql` | `mssql+pymssql://<Username>:<Password>@<Host>:<Port-default:1433>/<Database Name>` |
|
||||
| [TDengine](/user-docs/6.0.0/configuration/databases#tdengine) | `pip install taospy` `pip install taos-ws-py` | `taosws://<user>:<password>@<host>:<port>` |
|
||||
| [Teradata](/user-docs/6.0.0/configuration/databases#teradata) | `pip install teradatasqlalchemy` | `teradatasql://{user}:{password}@{host}` |
|
||||
| [TimescaleDB](/user-docs/6.0.0/configuration/databases#timescaledb) | `pip install psycopg2` | `postgresql://<UserName>:<DBPassword>@<Database Host>:<Port>/<Database Name>` |
|
||||
| [Trino](/user-docs/6.0.0/configuration/databases#trino) | `pip install trino` | `trino://{username}:{password}@{hostname}:{port}/{catalog}` |
|
||||
| [Vertica](/user-docs/6.0.0/configuration/databases#vertica) | `pip install sqlalchemy-vertica-python` | `vertica+vertica_python://<UserName>:<DBPassword>@<Database Host>/<Database Name>` |
|
||||
| [YDB](/user-docs/6.0.0/configuration/databases#ydb) | `pip install ydb-sqlalchemy` | `ydb://{host}:{port}/{database_name}` |
|
||||
| [YugabyteDB](/user-docs/6.0.0/configuration/databases#yugabytedb) | `pip install psycopg2` | `postgresql://<UserName>:<DBPassword>@<Database Host>/<Database Name>` |
|
||||
|
||||
---
|
||||
|
||||
@@ -133,7 +134,7 @@ exists in the directory with your `docker-compose.yml` or `docker-compose-non-de
|
||||
touch ./docker/requirements-local.txt
|
||||
```
|
||||
|
||||
Add the driver identified in step above. You can use a text editor or do
|
||||
Add the driver identified in step above. You can use a text editor or do
|
||||
it from the command line like:
|
||||
|
||||
```bash
|
||||
@@ -145,7 +146,7 @@ Launch Superset with `docker compose -f docker-compose-non-dev.yml up` and
|
||||
the driver should be present.
|
||||
|
||||
You can check its presence by entering the running container with
|
||||
`docker exec -it <container_name> bash` and running `pip freeze`. The PyPI package should
|
||||
`docker exec -it <container_name> bash` and running `pip freeze`. The PyPI package should
|
||||
be present in the printed list.
|
||||
|
||||
**If you're running a customized docker image**, rebuild your local image with the new
|
||||
@@ -168,7 +169,7 @@ From there, follow the steps on the
|
||||
[Using Database Connection UI page](/user-docs/6.0.0/configuration/databases#connecting-through-the-ui).
|
||||
|
||||
Consult the page for your specific database type in the Superset documentation to determine
|
||||
the connection string and any other parameters you need to input. For instance,
|
||||
the connection string and any other parameters you need to input. For instance,
|
||||
on the [MySQL page](/user-docs/6.0.0/configuration/databases#mysql), we see that the connection string
|
||||
to a local MySQL database differs depending on whether the setup is running on Linux or Mac.
|
||||
|
||||
@@ -177,7 +178,7 @@ Click the “Test Connection” button, which should result in a popup message s
|
||||
|
||||
#### 4. Troubleshooting
|
||||
|
||||
If the test fails, review your docker logs for error messages. Superset uses SQLAlchemy
|
||||
If the test fails, review your docker logs for error messages. Superset uses SQLAlchemy
|
||||
to connect to databases; to troubleshoot the connection string for your database, you might
|
||||
start Python in the Superset application container or host environment and try to connect
|
||||
directly to the desired database and fetch data. This eliminates Superset for the
|
||||
@@ -248,9 +249,9 @@ The PyAthena library also allows to assume a specific IAM role which you can def
|
||||
|
||||
```json
|
||||
{
|
||||
"connect_args": {
|
||||
"role_arn": "<role arn>"
|
||||
}
|
||||
"connect_args": {
|
||||
"role_arn": "<role arn>"
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
@@ -464,7 +465,7 @@ You also need to add the following configuration to "Other" -> "Engine Parameter
|
||||
|
||||
```json
|
||||
{
|
||||
"connect_args": {"http_path": "sql/protocolv1/o/****"}
|
||||
"connect_args": { "http_path": "sql/protocolv1/o/****" }
|
||||
}
|
||||
```
|
||||
|
||||
@@ -489,7 +490,7 @@ databricks+pyhive://token:{access_token}@{server_hostname}:{port}/{database_name
|
||||
You also need to add the following configuration to "Other" -> "Engine Parameters", with your HTTP path:
|
||||
|
||||
```json
|
||||
{"connect_args": {"http_path": "sql/protocolv1/o/****"}}
|
||||
{ "connect_args": { "http_path": "sql/protocolv1/o/****" } }
|
||||
```
|
||||
|
||||
#### ODBC
|
||||
@@ -505,7 +506,12 @@ databricks+pyodbc://token:{access_token}@{server_hostname}:{port}/{database_name
|
||||
And for the connection arguments:
|
||||
|
||||
```json
|
||||
{"connect_args": {"http_path": "sql/protocolv1/o/****", "driver_path": "/path/to/odbc/driver"}}
|
||||
{
|
||||
"connect_args": {
|
||||
"http_path": "sql/protocolv1/o/****",
|
||||
"driver_path": "/path/to/odbc/driver"
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
The driver path should be:
|
||||
@@ -516,7 +522,12 @@ The driver path should be:
|
||||
For a connection to a SQL endpoint you need to use the HTTP path from the endpoint:
|
||||
|
||||
```json
|
||||
{"connect_args": {"http_path": "/sql/1.0/endpoints/****", "driver_path": "/path/to/odbc/driver"}}
|
||||
{
|
||||
"connect_args": {
|
||||
"http_path": "/sql/1.0/endpoints/****",
|
||||
"driver_path": "/path/to/odbc/driver"
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
##### OAuth2 Authentication
|
||||
@@ -561,6 +572,7 @@ DATABASE_OAUTH2_TIMEOUT = timedelta(seconds=30)
|
||||
```
|
||||
|
||||
Replace the following placeholders:
|
||||
|
||||
- `your-databricks-client-id`: Your Databricks OAuth2 application client ID
|
||||
- `your-databricks-client-secret`: Your Databricks OAuth2 application client secret
|
||||
- `your-superset-host:port`: Your Superset instance hostname and port
|
||||
@@ -665,7 +677,7 @@ We recommend reading the
|
||||
the [GitHub README](https://github.com/JohnOmernik/sqlalchemy-drill#usage-with-odbc) to learn how to
|
||||
work with Drill through ODBC.
|
||||
|
||||
import useBaseUrl from "@docusaurus/useBaseUrl";
|
||||
import useBaseUrl from '@docusaurus/useBaseUrl';
|
||||
|
||||
#### Apache Druid
|
||||
|
||||
@@ -696,7 +708,7 @@ When adding a connection to Druid, you can customize the connection a few differ
|
||||
You can add certificates in the **Root Certificate** field when configuring the new database
|
||||
connection to Druid:
|
||||
|
||||
<img src={useBaseUrl("/img/root-cert-example.png")} />{" "}
|
||||
<img src={useBaseUrl('/img/root-cert-example.png')} />
|
||||
|
||||
When using a custom certificate, pydruid will automatically use https scheme.
|
||||
|
||||
@@ -781,9 +793,9 @@ please edit your Database and enter the settings of your specified time zone in
|
||||
|
||||
```json
|
||||
{
|
||||
"connect_args": {
|
||||
"time_zone": "Asia/Shanghai"
|
||||
}
|
||||
"connect_args": {
|
||||
"time_zone": "Asia/Shanghai"
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
@@ -874,17 +886,17 @@ credentials file (as a JSON).
|
||||
|
||||
```json
|
||||
{
|
||||
"type": "service_account",
|
||||
"project_id": "...",
|
||||
"private_key_id": "...",
|
||||
"private_key": "...",
|
||||
"client_email": "...",
|
||||
"client_id": "...",
|
||||
"auth_uri": "...",
|
||||
"token_uri": "...",
|
||||
"auth_provider_x509_cert_url": "...",
|
||||
"client_x509_cert_url": "..."
|
||||
}
|
||||
"type": "service_account",
|
||||
"project_id": "...",
|
||||
"private_key_id": "...",
|
||||
"private_key": "...",
|
||||
"client_email": "...",
|
||||
"client_id": "...",
|
||||
"auth_uri": "...",
|
||||
"token_uri": "...",
|
||||
"auth_provider_x509_cert_url": "...",
|
||||
"client_x509_cert_url": "..."
|
||||
}
|
||||
```
|
||||
|
||||
|
||||
@@ -910,19 +922,19 @@ credentials file (as a JSON).
|
||||
|
||||
```json
|
||||
{
|
||||
"credentials_info": {
|
||||
"type": "service_account",
|
||||
"project_id": "...",
|
||||
"private_key_id": "...",
|
||||
"private_key": "...",
|
||||
"client_email": "...",
|
||||
"client_id": "...",
|
||||
"auth_uri": "...",
|
||||
"token_uri": "...",
|
||||
"auth_provider_x509_cert_url": "...",
|
||||
"client_x509_cert_url": "..."
|
||||
}
|
||||
}
|
||||
"credentials_info": {
|
||||
"type": "service_account",
|
||||
"project_id": "...",
|
||||
"private_key_id": "...",
|
||||
"private_key": "...",
|
||||
"client_email": "...",
|
||||
"client_id": "...",
|
||||
"auth_uri": "...",
|
||||
"token_uri": "...",
|
||||
"auth_provider_x509_cert_url": "...",
|
||||
"client_x509_cert_url": "..."
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
You should then be able to connect to your BigQuery datasets.
|
||||
@@ -1134,7 +1146,8 @@ parseable://admin:admin@demo.parseable.com:443/ingress-nginx
|
||||
|
||||
Note: The stream_name in the URI represents the Parseable logstream you want to query. You can use both HTTP (port 80) and HTTPS (port 443) connections.
|
||||
|
||||
>>>>>>>
|
||||
> > > > > > >
|
||||
|
||||
#### Apache Pinot
|
||||
|
||||
The recommended connector library for Apache Pinot is [pinotdb](https://pypi.org/project/pinotdb/).
|
||||
@@ -1155,7 +1168,7 @@ If you want to use explore view or joins, window functions, etc. then enable [mu
|
||||
Add below argument while creating database connection in Advanced -> Other -> ENGINE PARAMETERS
|
||||
|
||||
```json
|
||||
{"connect_args":{"use_multistage_engine":"true"}}
|
||||
{ "connect_args": { "use_multistage_engine": "true" } }
|
||||
```
|
||||
|
||||
#### Postgres
|
||||
@@ -1221,17 +1234,17 @@ datasource. If you’re using an older version of Presto, you can configure it i
|
||||
|
||||
```json
|
||||
{
|
||||
"version": "0.123"
|
||||
"version": "0.123"
|
||||
}
|
||||
```
|
||||
|
||||
SSL Secure extra add json config to extra connection information.
|
||||
|
||||
```json
|
||||
{
|
||||
"connect_args":
|
||||
{"protocol": "https",
|
||||
"requests_kwargs":{"verify":false}
|
||||
{
|
||||
"connect_args": {
|
||||
"protocol": "https",
|
||||
"requests_kwargs": { "verify": false }
|
||||
}
|
||||
}
|
||||
```
|
||||
@@ -1285,27 +1298,27 @@ And if you want connect Snowflake with [Key Pair Authentication](https://docs.sn
|
||||
Please make sure you have the key pair and the public key is registered in Snowflake.
|
||||
To connect Snowflake with Key Pair Authentication, you need to add the following parameters to "SECURE EXTRA" field.
|
||||
|
||||
***Please note that you need to merge multi-line private key content to one line and insert `\n` between each line***
|
||||
**_Please note that you need to merge multi-line private key content to one line and insert `\n` between each line_**
|
||||
|
||||
```json
|
||||
{
|
||||
"auth_method": "keypair",
|
||||
"auth_params": {
|
||||
"privatekey_body": "-----BEGIN ENCRYPTED PRIVATE KEY-----\n...\n...\n-----END ENCRYPTED PRIVATE KEY-----",
|
||||
"privatekey_pass":"Your Private Key Password"
|
||||
}
|
||||
}
|
||||
"auth_method": "keypair",
|
||||
"auth_params": {
|
||||
"privatekey_body": "-----BEGIN ENCRYPTED PRIVATE KEY-----\n...\n...\n-----END ENCRYPTED PRIVATE KEY-----",
|
||||
"privatekey_pass": "Your Private Key Password"
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
If your private key is stored on server, you can replace "privatekey_body" with “privatekey_path” in parameter.
|
||||
|
||||
```json
|
||||
{
|
||||
"auth_method": "keypair",
|
||||
"auth_params": {
|
||||
"privatekey_path":"Your Private Key Path",
|
||||
"privatekey_pass":"Your Private Key Password"
|
||||
}
|
||||
"auth_method": "keypair",
|
||||
"auth_params": {
|
||||
"privatekey_path": "Your Private Key Path",
|
||||
"privatekey_pass": "Your Private Key Password"
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
@@ -1421,9 +1434,9 @@ teradatasql://{user}:{password}@{host}
|
||||
#### ODBC Driver
|
||||
|
||||
There's also an older connector named
|
||||
[sqlalchemy-teradata](https://github.com/Teradata/sqlalchemy-teradata) that
|
||||
requires the installation of ODBC drivers. The Teradata ODBC Drivers
|
||||
are available
|
||||
[sqlalchemy-teradata](https://github.com/Teradata/sqlalchemy-teradata) that
|
||||
requires the installation of ODBC drivers. The Teradata ODBC Drivers
|
||||
are available
|
||||
here: https://downloads.teradata.com/download/connectivity/odbc-driver/linux
|
||||
|
||||
Here are the required environment variables:
|
||||
@@ -1434,8 +1447,8 @@ export ODBCINST=/.../teradata/client/ODBC_64/odbcinst.ini
|
||||
```
|
||||
|
||||
We recommend using the first library because of the
|
||||
lack of requirement around ODBC drivers and
|
||||
because it's more regularly updated.
|
||||
lack of requirement around ODBC drivers and
|
||||
because it's more regularly updated.
|
||||
|
||||
#### TimescaleDB
|
||||
|
||||
@@ -1496,21 +1509,21 @@ You can provide `username`/`password` in the connection string or in the `Secure
|
||||
|
||||
- In Connection String
|
||||
|
||||
```
|
||||
trino://{username}:{password}@{hostname}:{port}/{catalog}
|
||||
```
|
||||
```
|
||||
trino://{username}:{password}@{hostname}:{port}/{catalog}
|
||||
```
|
||||
|
||||
- In `Secure Extra` field
|
||||
|
||||
```json
|
||||
{
|
||||
"auth_method": "basic",
|
||||
"auth_params": {
|
||||
"username": "<username>",
|
||||
"password": "<password>"
|
||||
}
|
||||
```json
|
||||
{
|
||||
"auth_method": "basic",
|
||||
"auth_params": {
|
||||
"username": "<username>",
|
||||
"password": "<password>"
|
||||
}
|
||||
```
|
||||
}
|
||||
```
|
||||
|
||||
NOTE: if both are provided, `Secure Extra` always takes higher priority.
|
||||
|
||||
@@ -1539,11 +1552,11 @@ In `Secure Extra` field, config as following example:
|
||||
|
||||
```json
|
||||
{
|
||||
"auth_method": "certificate",
|
||||
"auth_params": {
|
||||
"cert": "/path/to/cert.pem",
|
||||
"key": "/path/to/key.pem"
|
||||
}
|
||||
"auth_method": "certificate",
|
||||
"auth_params": {
|
||||
"cert": "/path/to/cert.pem",
|
||||
"key": "/path/to/key.pem"
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
@@ -1555,10 +1568,10 @@ Config `auth_method` and provide token in `Secure Extra` field
|
||||
|
||||
```json
|
||||
{
|
||||
"auth_method": "jwt",
|
||||
"auth_params": {
|
||||
"token": "<your-jwt-token>"
|
||||
}
|
||||
"auth_method": "jwt",
|
||||
"auth_params": {
|
||||
"token": "<your-jwt-token>"
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
@@ -1883,11 +1896,11 @@ If you enable DML in the meta database users will be able to run DML queries on
|
||||
Second, you might want to change the value of `SUPERSET_META_DB_LIMIT`. The default value is 1000, and defines how many are read from each database before any aggregations and joins are executed. You can also set this value `None` if you only have small tables.
|
||||
|
||||
:::warning
|
||||
`SUPERSET_META_DB_LIMIT` is applied to **each** underlying table *before* the in-memory join runs, not to the final result. If any table involved in a join has more rows than the limit, the meta database will read only the first `SUPERSET_META_DB_LIMIT` rows of that table, which means matching rows can be silently dropped and the join can return **incomplete or even empty** results with no error. If you join tables larger than the limit, raise `SUPERSET_META_DB_LIMIT` to comfortably exceed your largest joined table, or set it to `None` when working only with small tables, to get correct results.
|
||||
`SUPERSET_META_DB_LIMIT` is applied to **each** underlying table _before_ the in-memory join runs, not to the final result. If any table involved in a join has more rows than the limit, the meta database will read only the first `SUPERSET_META_DB_LIMIT` rows of that table, which means matching rows can be silently dropped and the join can return **incomplete or even empty** results with no error. If you join tables larger than the limit, raise `SUPERSET_META_DB_LIMIT` to comfortably exceed your largest joined table, or set it to `None` when working only with small tables, to get correct results.
|
||||
:::
|
||||
|
||||
Additionally, you might want to restrict the databases to with the meta database has access to. This can be done in the database configuration, under "Advanced" -> "Other" -> "ENGINE PARAMETERS" and adding:
|
||||
|
||||
```json
|
||||
{"allowed_dbs":["Google Sheets","examples"]}
|
||||
{ "allowed_dbs": ["Google Sheets", "examples"] }
|
||||
```
|
||||
|
||||
@@ -117,10 +117,10 @@ datasets by saving the following YAML to file and then running the **import_data
|
||||
|
||||
```yaml
|
||||
databases:
|
||||
- database_name: main
|
||||
tables:
|
||||
- table_name: random_time_series
|
||||
columns:
|
||||
- column_name: ds
|
||||
verbose_name: datetime
|
||||
- database_name: main
|
||||
tables:
|
||||
- table_name: random_time_series
|
||||
columns:
|
||||
- column_name: ds
|
||||
verbose_name: datetime
|
||||
```
|
||||
|
||||
@@ -18,7 +18,9 @@ DECKGL_BASE_MAP = [
|
||||
['tile://https://your_personal_url/{z}/{x}/{y}.png', 'MyTile']
|
||||
]
|
||||
```
|
||||
|
||||
Openstreetmap tiles url can be added without prefix.
|
||||
|
||||
```python
|
||||
DECKGL_BASE_MAP = [
|
||||
['https://c.tile.openstreetmap.org/{z}/{x}/{y}.png', 'OpenStreetMap']
|
||||
@@ -26,6 +28,7 @@ DECKGL_BASE_MAP = [
|
||||
```
|
||||
|
||||
Default values are:
|
||||
|
||||
```python
|
||||
DECKGL_BASE_MAP = [
|
||||
['https://tile.openstreetmap.org/{z}/{x}/{y}.png', 'Streets (OSM)'],
|
||||
@@ -46,6 +49,7 @@ Setting `DECKGL_BASE_MAP` overwrite default values
|
||||
:::
|
||||
|
||||
After defining your map tiles, set them in these variables:
|
||||
|
||||
- `CORS_OPTIONS`
|
||||
- `connect-src` of `TALISMAN_CONFIG` and `TALISMAN_CONFIG_DEV` variables.
|
||||
|
||||
|
||||
@@ -8,12 +8,10 @@ version: 1
|
||||
|
||||
## CORS
|
||||
|
||||
|
||||
:::note
|
||||
In Superset versions prior to `5.x` you have to install to install `flask-cors` with `pip install flask-cors` to enable CORS support.
|
||||
:::
|
||||
|
||||
|
||||
The following keys in `superset_config.py` can be specified to configure CORS:
|
||||
|
||||
- `ENABLE_CORS`: Must be set to `True` in order to enable CORS
|
||||
@@ -63,7 +61,7 @@ Now anybody can directly access the dashboard's URL. You can embed it in an ifra
|
||||
width="600"
|
||||
height="400"
|
||||
seamless
|
||||
frameBorder="0"
|
||||
frameborder="0"
|
||||
scrolling="no"
|
||||
src="https://superset.my-domain.com/superset/dashboard/10/?standalone=1&height=400"
|
||||
>
|
||||
@@ -93,17 +91,17 @@ running a custom auth postback endpoint), you can add the endpoints to `WTF_CSRF
|
||||
## SSH Tunneling
|
||||
|
||||
1. Turn on feature flag
|
||||
- Change [`SSH_TUNNELING`](https://github.com/apache/superset/blob/eb8386e3f0647df6d1bbde8b42073850796cc16f/superset/config.py#L489) to `True`
|
||||
- If you want to add more security when establishing the tunnel we allow users to overwrite the `SSHTunnelManager` class [here](https://github.com/apache/superset/blob/eb8386e3f0647df6d1bbde8b42073850796cc16f/superset/config.py#L507)
|
||||
- You can also set the [`SSH_TUNNEL_LOCAL_BIND_ADDRESS`](https://github.com/apache/superset/blob/eb8386e3f0647df6d1bbde8b42073850796cc16f/superset/config.py#L508) this the host address where the tunnel will be accessible on your VPC
|
||||
- Change [`SSH_TUNNELING`](https://github.com/apache/superset/blob/eb8386e3f0647df6d1bbde8b42073850796cc16f/superset/config.py#L489) to `True`
|
||||
- If you want to add more security when establishing the tunnel we allow users to overwrite the `SSHTunnelManager` class [here](https://github.com/apache/superset/blob/eb8386e3f0647df6d1bbde8b42073850796cc16f/superset/config.py#L507)
|
||||
- You can also set the [`SSH_TUNNEL_LOCAL_BIND_ADDRESS`](https://github.com/apache/superset/blob/eb8386e3f0647df6d1bbde8b42073850796cc16f/superset/config.py#L508) this the host address where the tunnel will be accessible on your VPC
|
||||
|
||||
2. Create database w/ ssh tunnel enabled
|
||||
- With the feature flag enabled you should now see ssh tunnel toggle.
|
||||
- Click the toggle to enable SSH tunneling and add your credentials accordingly.
|
||||
- Superset allows for two different types of authentication (Basic + Private Key). These credentials should come from your service provider.
|
||||
- With the feature flag enabled you should now see ssh tunnel toggle.
|
||||
- Click the toggle to enable SSH tunneling and add your credentials accordingly.
|
||||
- Superset allows for two different types of authentication (Basic + Private Key). These credentials should come from your service provider.
|
||||
|
||||
3. Verify data is flowing
|
||||
- Once SSH tunneling has been enabled, go to SQL Lab and write a query to verify data is properly flowing.
|
||||
- Once SSH tunneling has been enabled, go to SQL Lab and write a query to verify data is properly flowing.
|
||||
|
||||
## Domain Sharding
|
||||
|
||||
|
||||
@@ -84,6 +84,7 @@ WHERE dttm_col > '{{ from_dttm | default("2024-01-01", true) }}'
|
||||
**Option 2: Use SQL Lab Parameters**
|
||||
|
||||
Set parameters in the SQL Lab UI (Parameters menu):
|
||||
|
||||
```json
|
||||
{
|
||||
"from_dttm": "2024-01-01",
|
||||
@@ -129,7 +130,7 @@ In the UI you can assign a set of parameters as JSON
|
||||
The parameters become available in your SQL (example: `SELECT * FROM {{ my_table }}` ) by using Jinja templating syntax.
|
||||
SQL Lab template parameters are stored with the dataset as `TEMPLATE PARAMETERS`.
|
||||
|
||||
There is a special ``_filters`` parameter which can be used to test filters used in the jinja template.
|
||||
There is a special `_filters` parameter which can be used to test filters used in the jinja template.
|
||||
|
||||
```json
|
||||
{
|
||||
@@ -150,7 +151,7 @@ WHERE action in {{ filter_values('action_type')|where_in }}
|
||||
GROUP BY action
|
||||
```
|
||||
|
||||
Note ``_filters`` is not stored with the dataset. It's only used within the SQL Lab UI.
|
||||
Note `_filters` is not stored with the dataset. It's only used within the SQL Lab UI.
|
||||
|
||||
Besides default Jinja templating, SQL lab also supports self-defined template processor by setting
|
||||
the `CUSTOM_TEMPLATE_PROCESSORS` in your superset configuration. The values in this dictionary
|
||||
@@ -284,16 +285,19 @@ cache key by adding the following parameter to your Jinja code:
|
||||
```
|
||||
|
||||
You can json-stringify the array by adding `|tojson` to your Jinja code:
|
||||
|
||||
```python
|
||||
{{ current_user_roles()|tojson }}
|
||||
```
|
||||
|
||||
You can use the `|where_in` filter to use your roles in a SQL statement. For example, if `current_user_roles()` returns `['admin', 'viewer']`, the following template:
|
||||
|
||||
```python
|
||||
SELECT * FROM users WHERE role IN {{ current_user_roles()|where_in }}
|
||||
```
|
||||
|
||||
Will be rendered as:
|
||||
|
||||
```sql
|
||||
SELECT * FROM users WHERE role IN ('admin', 'viewer')
|
||||
```
|
||||
@@ -447,7 +451,7 @@ The macro takes the following parameters:
|
||||
- `column`: Name of the temporal column. Leave undefined to reference the time range from a Dashboard Native Time Range
|
||||
filter (when present).
|
||||
- `default`: The default value to fall back to if the time filter is not present, or has the value `No filter`
|
||||
- `target_type`: The target temporal type as recognized by the target database (e.g. `TIMESTAMP`, `DATE` or
|
||||
- `target_type`: The target temporal type as recognized by the target database (e.g. `TIMESTAMP`, `DATE` or
|
||||
`DATETIME`). If `column` is defined, the format will default to the type of the column. This is used to produce
|
||||
the format of the `from_expr` and `to_expr` properties of the returned `TimeFilter` object.
|
||||
- `strftime`: format using the `strftime` method of `datetime` for custom time formatting.
|
||||
@@ -572,6 +576,7 @@ Dashboard filter without any value applied
|
||||
**To Datetime**
|
||||
|
||||
Loads a string as a `datetime` object. This is useful when performing date operations. For example:
|
||||
|
||||
```
|
||||
{% set from_expr = get_time_filter("dttm", strftime="%Y-%m-%d").from_expr %}
|
||||
{% set to_expr = get_time_filter("dttm", strftime="%Y-%m-%d").to_expr %}
|
||||
|
||||
@@ -4,6 +4,7 @@ hide_title: true
|
||||
sidebar_position: 12
|
||||
version: 1
|
||||
---
|
||||
|
||||
# Theming Superset
|
||||
|
||||
:::note
|
||||
@@ -34,11 +35,13 @@ You can also extend with Superset-specific tokens (documented in the default the
|
||||
When `ENABLE_UI_THEME_ADMINISTRATION = True` is configured, administrators can manage system-wide themes directly from the UI:
|
||||
|
||||
#### Setting System Themes
|
||||
|
||||
- **System Default Theme**: Click the sun icon on any theme to set it as the system-wide default
|
||||
- **System Dark Theme**: Click the moon icon on any theme to set it as the system dark mode theme
|
||||
- **Automatic OS Detection**: When both default and dark themes are set, Superset automatically detects and applies the appropriate theme based on OS preferences
|
||||
|
||||
#### Managing System Themes
|
||||
|
||||
- System themes are indicated with special badges in the theme list
|
||||
- Only administrators with write permissions can modify system theme settings
|
||||
- Removing a system theme designation reverts to configuration file defaults
|
||||
@@ -46,6 +49,7 @@ When `ENABLE_UI_THEME_ADMINISTRATION = True` is configured, administrators can m
|
||||
### Applying Themes to Dashboards
|
||||
|
||||
Once created, themes can be applied to individual dashboards:
|
||||
|
||||
- Edit any dashboard and select your custom theme from the theme dropdown
|
||||
- Each dashboard can have its own theme, allowing for branded or context-specific styling
|
||||
|
||||
|
||||
Reference in New Issue
Block a user