Merge 9154a4f08f into f5843fe588

Signed-off-by: dependabot[bot] <support@github.com>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>

.github/workflows/bashlib.sh

@@ -117,12 +117,6 @@ testdata() {
   say "::endgroup::"
 }
 
-codecov() {
-  say "::group::Upload code coverage"
-  bash ".github/workflows/codecov.sh" "$@"
-  say "::endgroup::"
-}
-
 cypress-install() {
   cd "$GITHUB_WORKSPACE/superset-frontend/cypress-base"
 
@@ -191,11 +185,6 @@ cypress-run-all() {
 
   cypress-run "sqllab/*" "Backend persist"
 
-  # Upload code coverage separately so each page can have separate flags
-  # -c will clean existing coverage reports, -F means add flags
-  # || true to prevent CI failure on codecov upload
-  codecov -c -F "cypress" || true
-
   say "::group::Flask log for backend persist"
   cat "$flasklog"
   say "::endgroup::"
@@ -225,8 +214,6 @@ cypress-run-applitools() {
 
   $cypress --spec "cypress/e2e/*/**/*.applitools.test.ts" --browser "$browser" --headless
 
-  codecov -c -F "cypress" || true
-
   say "::group::Flask log for default run"
   cat "$flasklog"
   say "::endgroup::"

.github/workflows/superset-docs-deploy.yml

@@ -4,6 +4,7 @@ on:
   push:
     paths:
       - "docs/**"
+      - "README.md"
     branches:
       - "master"
 

.github/workflows/superset-frontend.yml

@@ -20,7 +20,6 @@ jobs:
       - name: "Checkout ${{ github.ref }} ( ${{ github.sha }} )"
         uses: actions/checkout@v4
         with:
-          fetch-depth: 0 # Fetch all history
           persist-credentials: false
           submodules: recursive
       - name: Check npm lock file version
@@ -79,6 +78,8 @@ jobs:
         working-directory: ./superset-frontend/packages/generator-superset
         run: npx jest
       - name: Upload code coverage
-        if: steps.check.outputs.frontend
-        working-directory: ./superset-frontend
-        run: ../.github/workflows/codecov.sh -c -F javascript
+        uses: codecov/codecov-action@v4
+        with:
+          flags: javascript
+          token: ${{ secrets.CODECOV_TOKEN }}
+          verbose: true

.github/workflows/superset-python-integrationtest.yml

@@ -66,9 +66,11 @@ jobs:
         run: |
           ./scripts/python_tests.sh
       - name: Upload code coverage
-        if: steps.check.outputs.python
-        run: |
-          bash .github/workflows/codecov.sh -c -F python -F mysql
+        uses: codecov/codecov-action@v4
+        with:
+          flags: python,mysql
+          token: ${{ secrets.CODECOV_TOKEN }}
+          verbose: true
   test-postgres:
     runs-on: ubuntu-20.04
     strategy:
@@ -123,9 +125,11 @@ jobs:
         run: |
           ./scripts/python_tests.sh
       - name: Upload code coverage
-        if: steps.check.outputs.python
-        run: |
-          bash .github/workflows/codecov.sh -c -F python -F postgres
+        uses: codecov/codecov-action@v4
+        with:
+          flags: python,postgres
+          token: ${{ secrets.CODECOV_TOKEN }}
+          verbose: true
 
   test-sqlite:
     runs-on: ubuntu-20.04
@@ -171,6 +175,8 @@ jobs:
         run: |
           ./scripts/python_tests.sh
       - name: Upload code coverage
-        if: steps.check.outputs.python
-        run: |
-          bash .github/workflows/codecov.sh -c -F python -F sqlite
+        uses: codecov/codecov-action@v4
+        with:
+          flags: python,sqlite
+          token: ${{ secrets.CODECOV_TOKEN }}
+          verbose: true

.github/workflows/superset-python-presto-hive.yml

@@ -75,9 +75,11 @@ jobs:
         run: |
           ./scripts/python_tests.sh -m 'chart_data_flow or sql_json_flow'
       - name: Upload code coverage
-        if: steps.check.outputs.python
-        run: |
-          bash .github/workflows/codecov.sh -c -F python -F presto
+        uses: codecov/codecov-action@v4
+        with:
+          flags: python,presto
+          token: ${{ secrets.CODECOV_TOKEN }}
+          verbose: true
 
   test-postgres-hive:
     runs-on: ubuntu-20.04
@@ -138,6 +140,8 @@ jobs:
         run: |
           ./scripts/python_tests.sh -m 'chart_data_flow or sql_json_flow'
       - name: Upload code coverage
-        if: steps.check.outputs.python
-        run: |
-          bash .github/workflows/codecov.sh -c -F python -F hive
+        uses: codecov/codecov-action@v4
+        with:
+          flags: python,hive
+          token: ${{ secrets.CODECOV_TOKEN }}
+          verbose: true

.github/workflows/superset-python-unittest.yml

@@ -46,6 +46,8 @@ jobs:
         run: |
           pytest --durations-min=0.5 --cov-report= --cov=superset ./tests/common ./tests/unit_tests --cache-clear
       - name: Upload code coverage
-        if: steps.check.outputs.python
-        run: |
-          bash .github/workflows/codecov.sh -c -F python -F unit
+        uses: codecov/codecov-action@v4
+        with:
+          flags: python,unit
+          token: ${{ secrets.CODECOV_TOKEN }}
+          verbose: true

.pre-commit-config.yaml

@@ -47,7 +47,7 @@ repos:
     hooks:
       - id: check-docstring-first
       - id: check-added-large-files
-        exclude: \.(geojson)$
+        exclude: ^.*\.(geojson)$|^docs/static/img/screenshots/.*
       - id: check-yaml
         exclude: ^helm/superset/templates/
       - id: debug-statements

.rat-excludes

@@ -64,6 +64,7 @@ temporary_superset_ui/*
 # docs overrides for third party logos we don't have the rights to
 google-big-query.svg
 google-sheets.svg
+ibm-db2.svg
 postgresql.svg
 snowflake.svg
 

CHANGELOG/4.0.0.md

@@ -32,7 +32,6 @@ under the License.
 - [#26369](https://github.com/apache/superset/pull/26369) refactor: Removes the filters set feature (@michael-s-molina)
 - [#26416](https://github.com/apache/superset/pull/26416) fix: improve performance on reports log queries (@dpgaspar)
 - [#26290](https://github.com/apache/superset/pull/26290) feat(echarts-funnel): Implement % calculation type (@kgabryje)
-- [#26288](https://github.com/apache/superset/pull/26288) chore: Ensure Mixins are ordered according to the MRO (@john-bodley)
 
 **Features**
 
@@ -470,3 +469,4 @@ under the License.
 - [#26100](https://github.com/apache/superset/pull/26100) build(deps-dev): bump @types/node from 20.9.4 to 20.10.0 in /superset-websocket (@dependabot[bot])
 - [#26099](https://github.com/apache/superset/pull/26099) build(deps-dev): bump @types/cookie from 0.5.4 to 0.6.0 in /superset-websocket (@dependabot[bot])
 - [#26104](https://github.com/apache/superset/pull/26104) docs: update CVEs fixed on 2.1.2 (@dpgaspar)
+- [#26288](https://github.com/apache/superset/pull/26288) chore: Ensure Mixins are ordered according to the MRO (@john-bodley)

CONTRIBUTING.md

@@ -20,5 +20,5 @@ Contributions are welcome and are greatly appreciated! Every
 little bit helps, and credit will always be given.
 
 All matters related to contributions have moved to [this section of
-the official Superset documentation](https://superset.apache.org/docs/contributing/contributing/). Source for the documentation is
+the official Superset documentation](https://superset.apache.org/docs/contributing/). Source for the documentation is
 [located here](https://github.com/apache/superset/tree/master/docs/docs).

README.md

@@ -1,3 +1,7 @@
+---
+hide_title: true
+sidebar_position: 1
+---
 <!--
 Licensed to the Apache Software Foundation (ASF) under one
 or more contributor license agreements.  See the NOTICE file
@@ -30,12 +34,14 @@ under the License.
 
 <picture width="500">
   <source
+    width="600"
     media="(prefers-color-scheme: dark)"
-    src="https://github.com/apache/superset/raw/master/superset-frontend/src/assets/branding/superset-logo-horiz-apache-dark.png"
+    src="https://superset.apache.org/img/superset-logo-horiz-dark.svg"
     alt="Superset logo (dark)"
   />
   <img
-    src="https://github.com/apache/superset/raw/master/superset-frontend/src/assets/branding/superset-logo-horiz-apache.png"
+    width="600"
+    src="https://superset.apache.org/img/superset-logo-horiz-apache.svg"
     alt="Superset logo (light)"
   />
 </picture>
@@ -45,11 +51,11 @@ A modern, enterprise-ready business intelligence web application.
 [**Why Superset?**](#why-superset) |
 [**Supported Databases**](#supported-databases) |
 [**Installation and Configuration**](#installation-and-configuration) |
-[**Release Notes**](RELEASING/README.md#release-notes-for-recent-releases) |
+[**Release Notes**](https://github.com/apache/superset/blob/master/RELEASING/README.md#release-notes-for-recent-releases) |
 [**Get Involved**](#get-involved) |
 [**Contributor Guide**](#contributor-guide) |
 [**Resources**](#resources) |
-[**Organizations Using Superset**](RESOURCES/INTHEWILD.md)
+[**Organizations Using Superset**](https://github.com/apache/superset/blob/master/RESOURCES/INTHEWILD.md)
 
 ## Why Superset?
 
@@ -71,69 +77,69 @@ Superset provides:
 
 **Video Overview**
 <!-- File hosted here https://github.com/apache/superset-site/raw/lfs/superset-video-4k.mp4 -->
-https://user-images.githubusercontent.com/64562059/234390129-321d4f35-cb4b-45e8-89d9-20ae292f34fc.mp4
+https://superset.staged.apache.org/superset-video-4k.mp4
 
 <br/>
 
 **Large Gallery of Visualizations**
 
-<kbd><img title="Gallery" src="superset-frontend/src/assets/images/screenshots/gallery.jpg"/></kbd><br/>
+<kbd><img title="Gallery" src="https://superset.apache.org/img/screenshots/gallery.jpg"/></kbd><br/>
 
 **Craft Beautiful, Dynamic Dashboards**
 
-<kbd><img title="View Dashboards" src="superset-frontend/src/assets/images/screenshots/slack_dash.jpg"/></kbd><br/>
+<kbd><img title="View Dashboards" src="https://superset.apache.org/img/screenshots/slack_dash.jpg"/></kbd><br/>
 
 **No-Code Chart Builder**
 
-<kbd><img title="Slice & dice your data" src="superset-frontend/src/assets/images/screenshots/explore.jpg"/></kbd><br/>
+<kbd><img title="Slice & dice your data" src="https://superset.apache.org/img/screenshots/explore.jpg"/></kbd><br/>
 
 **Powerful SQL Editor**
 
-<kbd><img title="SQL Lab" src="superset-frontend/src/assets/images/screenshots/sql_lab.jpg"/></kbd><br/>
+<kbd><img title="SQL Lab" src="https://superset.apache.org/img/screenshots/sql_lab.jpg"/></kbd><br/>
 
 ## Supported Databases
 
-Superset can query data from any SQL-speaking datastore or data engine (Presto, Trino, Athena, [and more](https://superset.apache.org/docs/databases/installing-database-drivers/)) that has a Python DB-API driver and a SQLAlchemy dialect.
+Superset can query data from any SQL-speaking datastore or data engine (Presto, Trino, Athena, [and more](https://superset.apache.org/docs/configuration/databases)) that has a Python DB-API driver and a SQLAlchemy dialect.
 
 Here are some of the major database solutions that are supported:
 
 <p align="center">
-  <img src="superset-frontend/src/assets/images/redshift.png" alt="redshift" border="0" width="200" height="80"/>
-  <img src="superset-frontend/src/assets/images/google-biquery.png" alt="google-biquery" border="0" width="200" height="80"/>
-  <img src="superset-frontend/src/assets/images/snowflake.png" alt="snowflake" border="0" width="200" height="80"/>
-  <img src="superset-frontend/src/assets/images/trino.png" alt="trino" border="0" width="200" height="80"/>
-  <img src="superset-frontend/src/assets/images/presto.png" alt="presto" border="0" width="200" height="80"/>
-  <img src="superset-frontend/src/assets/images/databricks.png" alt="databricks" border="0" width="200" height="80" />
-  <img src="superset-frontend/src/assets/images/druid.png" alt="druid" border="0" width="200" height="80" />
-  <img src="superset-frontend/src/assets/images/firebolt.png" alt="firebolt" border="0" width="200" height="80" />
-  <img src="superset-frontend/src/assets/images/timescale.png" alt="timescale" border="0" width="200" height="80" />
-  <img src="superset-frontend/src/assets/images/rockset.png" alt="rockset" border="0" width="200" height="80" />
-  <img src="superset-frontend/src/assets/images/postgresql.png" alt="postgresql" border="0" width="200" height="80" />
-  <img src="superset-frontend/src/assets/images/mysql.png" alt="mysql" border="0" width="200" height="80" />
-  <img src="superset-frontend/src/assets/images/mssql-server.png" alt="mssql-server" border="0" width="200" height="80" />
-  <img src="superset-frontend/src/assets/images/db2.png" alt="db2" border="0" width="200" height="80" />
-  <img src="superset-frontend/src/assets/images/sqlite.png" alt="sqlite" border="0" width="200" height="80" />
-  <img src="superset-frontend/src/assets/images/sybase.png" alt="sybase" border="0" width="200" height="80" />
-  <img src="superset-frontend/src/assets/images/mariadb.png" alt="mariadb" border="0" width="200" height="80" />
-  <img src="superset-frontend/src/assets/images/vertica.png" alt="vertica" border="0" width="200" height="80" />
-  <img src="superset-frontend/src/assets/images/oracle.png" alt="oracle" border="0" width="200" height="80" />
-  <img src="superset-frontend/src/assets/images/firebird.png" alt="firebird" border="0" width="200" height="80" />
-  <img src="superset-frontend/src/assets/images/greenplum.png" alt="greenplum" border="0" width="200" height="80" />
-  <img src="superset-frontend/src/assets/images/clickhouse.png" alt="clickhouse" border="0" width="200" height="80" />
-  <img src="superset-frontend/src/assets/images/exasol.png" alt="exasol" border="0" width="200" height="80" />
-  <img src="superset-frontend/src/assets/images/monet-db.png" alt="monet-db" border="0" width="200" height="80" />
-  <img src="superset-frontend/src/assets/images/apache-kylin.png" alt="apache-kylin" border="0" width="200" height="80"/>
-  <img src="superset-frontend/src/assets/images/hologres.png" alt="hologres" border="0" width="200" height="80"/>
-  <img src="superset-frontend/src/assets/images/netezza.png" alt="netezza" border="0" width="200" height="80"/>
-  <img src="superset-frontend/src/assets/images/pinot.png" alt="pinot" border="0" width="200" height="80"/>
-  <img src="superset-frontend/src/assets/images/teradata.png" alt="teradata" border="0" width="200" height="80"/>
-  <img src="superset-frontend/src/assets/images/yugabyte.png" alt="yugabyte" border="0" width="200" height="80"/>
-  <img src="superset-frontend/src/assets/images/databend.png" alt="databend" border="0" width="200" height="80"/>
-  <img src="superset-frontend/src/assets/images/starrocks.png" alt="starrocks" border="0" width="200" height="80"/>
-  <img src="superset-frontend/src/assets/images/doris.png" alt="doris" border="0" width="200" height="80"/>
+  <img src="https://superset.apache.org/img/databases/redshift.png" alt="redshift" border="0" width="200"/>
+  <img src="https://superset.apache.org/img/databases/google-biquery.png" alt="google-biquery" border="0" width="200"/>
+  <img src="https://superset.apache.org/img/databases/snowflake.png" alt="snowflake" border="0" width="200"/>
+  <img src="https://superset.apache.org/img/databases/trino.png" alt="trino" border="0" width="150" />
+  <img src="https://superset.apache.org/img/databases/presto.png" alt="presto" border="0" width="200"/>
+  <img src="https://superset.apache.org/img/databases/databricks.png" alt="databricks" border="0" width="160" />
+  <img src="https://superset.apache.org/img/databases/druid.png" alt="druid" border="0" width="200" />
+  <img src="https://superset.apache.org/img/databases/firebolt.png" alt="firebolt" border="0" width="200" />
+  <img src="https://superset.apache.org/img/databases/timescale.png" alt="timescale" border="0" width="200" />
+  <img src="https://superset.apache.org/img/databases/rockset.png" alt="rockset" border="0" width="200" />
+  <img src="https://superset.apache.org/img/databases/postgresql.png" alt="postgresql" border="0" width="200" />
+  <img src="https://superset.apache.org/img/databases/mysql.png" alt="mysql" border="0" width="200" />
+  <img src="https://superset.apache.org/img/databases/mssql-server.png" alt="mssql-server" border="0" width="200" />
+  <img src="https://superset.apache.org/img/databases/imb-db2.svg" alt="db2" border="0" width="220" />
+  <img src="https://superset.apache.org/img/databases/sqlite.png" alt="sqlite" border="0" width="200" />
+  <img src="https://superset.apache.org/img/databases/sybase.png" alt="sybase" border="0" width="200" />
+  <img src="https://superset.apache.org/img/databases/mariadb.png" alt="mariadb" border="0" width="200" />
+  <img src="https://superset.apache.org/img/databases/vertica.png" alt="vertica" border="0" width="200" />
+  <img src="https://superset.apache.org/img/databases/oracle.png" alt="oracle" border="0" width="200" />
+  <img src="https://superset.apache.org/img/databases/firebird.png" alt="firebird" border="0" width="200" />
+  <img src="https://superset.apache.org/img/databases/greenplum.png" alt="greenplum" border="0" width="200"  />
+  <img src="https://superset.apache.org/img/databases/clickhouse.png" alt="clickhouse" border="0" width="200" />
+  <img src="https://superset.apache.org/img/databases/exasol.png" alt="exasol" border="0" width="160" />
+  <img src="https://superset.apache.org/img/databases/monet-db.png" alt="monet-db" border="0" width="200"  />
+  <img src="https://superset.apache.org/img/databases/apache-kylin.png" alt="apache-kylin" border="0" width="80"/>
+  <img src="https://superset.apache.org/img/databases/hologres.png" alt="hologres" border="0" width="80"/>
+  <img src="https://superset.apache.org/img/databases/netezza.png" alt="netezza" border="0" width="80"/>
+  <img src="https://superset.apache.org/img/databases/pinot.png" alt="pinot" border="0" width="200" />
+  <img src="https://superset.apache.org/img/databases/teradata.png" alt="teradata" border="0" width="200" />
+  <img src="https://superset.apache.org/img/databases/yugabyte.png" alt="yugabyte" border="0" width="200" />
+  <img src="https://superset.apache.org/img/databases/databend.png" alt="databend" border="0" width="200" />
+  <img src="https://superset.apache.org/img/databases/starrocks.png" alt="starrocks" border="0" width="200" />
+  <img src="https://superset.apache.org/img/databases/doris.png" alt="doris" border="0" width="200" />
 </p>
 
-**A more comprehensive list of supported databases** along with the configuration instructions can be found [here](https://superset.apache.org/docs/databases/installing-database-drivers).
+**A more comprehensive list of supported databases** along with the configuration instructions can be found [here](https://superset.apache.org/docs/configuration/databases).
 
 Want to add support for your datastore or data engine? Read more [here](https://superset.apache.org/docs/frequently-asked-questions#does-superset-work-with-insert-database-engine-here) about the technical requirements.
 
@@ -159,9 +165,9 @@ how to set up a development environment.
 
 ## Resources
 
-- [Superset "In the Wild"](RESOURCES/INTHEWILD.md) - open a PR to add your org to the list!
-- [Feature Flags](RESOURCES/FEATURE_FLAGS.md) - the status of Superset's Feature Flags.
-- [Standard Roles](RESOURCES/STANDARD_ROLES.md) - How RBAC permissions map to roles.
+- [Superset "In the Wild"](https://github.com/apache/superset/blob/master/RESOURCES/INTHEWILD.md) - open a PR to add your org to the list!
+- [Feature Flags](https://github.com/apache/superset/blob/master/RESOURCES/FEATURE_FLAGS.md) - the status of Superset's Feature Flags.
+- [Standard Roles](https://github.com/apache/superset/blob/master/RESOURCES/STANDARD_ROLES.md) - How RBAC permissions map to roles.
 - [Superset Wiki](https://github.com/apache/superset/wiki) - Tons of additional community resources: best practices, community content and other information.
 - [Superset SIPs](https://github.com/orgs/apache/projects/170) - The status of Superset's SIPs (Superset Improvement Proposals) for both consensus and implementation status.
 
@@ -172,7 +178,7 @@ Understanding the Superset Points of View
 
 - Getting Started with Superset
   - [Superset in 2 Minutes using Docker Compose](https://superset.apache.org/docs/installation/docker-compose#installing-superset-locally-using-docker-compose)
-  - [Installing Database Drivers](https://superset.apache.org/docs/databases/docker-add-drivers/)
+  - [Installing Database Drivers](https://superset.apache.org/docs/configuration/databases#installing-database-drivers)
   - [Building New Database Connectors](https://preset.io/blog/building-database-connector/)
   - [Create Your First Dashboard](https://superset.apache.org/docs/using-superset/creating-your-first-dashboard/)
   - [Comprehensive Tutorial for Contributing Code to Apache Superset
@@ -198,10 +204,10 @@ Understanding the Superset Points of View
 - [Superset API](https://superset.apache.org/docs/rest-api)
 
 ## Repo Activity
-<a href="https://next.ossinsight.io/widgets/official/compose-last-28-days-stats?repo_id=39464018" target="_blank" style="display: block" align="center">
+<a href="https://next.ossinsight.io/widgets/official/compose-last-28-days-stats?repo_id=39464018" target="_blank" align="center">
   <picture>
-    <source media="(prefers-color-scheme: dark)" srcset="https://next.ossinsight.io/widgets/official/compose-last-28-days-stats/thumbnail.png?repo_id=39464018&image_size=auto&color_scheme=dark" width="655" height="auto">
-    <img alt="Performance Stats of apache/superset - Last 28 days" src="https://next.ossinsight.io/widgets/official/compose-last-28-days-stats/thumbnail.png?repo_id=39464018&image_size=auto&color_scheme=light" width="655" height="auto">
+    <source media="(prefers-color-scheme: dark)" srcset="https://next.ossinsight.io/widgets/official/compose-last-28-days-stats/thumbnail.png?repo_id=39464018&image_size=auto&color_scheme=dark" width="655" height="auto" />
+    <img alt="Performance Stats of apache/superset - Last 28 days" src="https://next.ossinsight.io/widgets/official/compose-last-28-days-stats/thumbnail.png?repo_id=39464018&image_size=auto&color_scheme=light" width="655" height="auto" />
   </picture>
 </a>
 

RELEASING/README.md

@@ -506,3 +506,18 @@ and re-push the proper images and tags through this interface. The action
 takes the version (ie `3.1.1`), the git reference (any SHA, tag or branch
 reference), and whether to force the `latest` Docker tag on the
 generated images.
+
+### Npm Release
+You might want to publish the latest @superset-ui release to npm
+```bash
+cd superset/superset-frontend
+```
+An automated GitHub action will run and generate a new tag, which will contain a version number provided as a parameter.
+```bash
+export GH_TOKEN={GITHUB_TOKEN}
+npx lerna version {VERSION} --conventional-commits --create-release github --no-private --yes --message {COMMIT_MESSAGE}
+```
+This action will publish the specified version to npm registry.
+```bash
+npx lerna publish from-package --yes
+```

RESOURCES/FEATURE_FLAGS.md

@@ -46,7 +46,7 @@ These features are **finished** but currently being tested. They are usable, but
 - CONFIRM_DASHBOARD_DIFF
 - DRILL_TO_DETAIL
 - DYNAMIC_PLUGINS: [(docs)](https://superset.apache.org/docs/configuration/running-on-kubernetes)
-- ENABLE_SUPERSET_META_DB: [(docs)](https://superset.apache.org/docs/databases/meta-database/)
+- ENABLE_SUPERSET_META_DB: [(docs)]()
 - ESTIMATE_QUERY_COST
 - GLOBAL_ASYNC_QUERIES [(docs)](https://github.com/apache/superset/blob/master/CONTRIBUTING.md#async-chart-queries)
 - HORIZONTAL_FILTER_BAR

UPDATING.md

@@ -43,6 +43,10 @@ assists people when migrating to a new version.
   set `SLACK_API_TOKEN` to fetch and serve Slack avatar links
 - [28134](https://github.com/apache/superset/pull/28134/) The default logging level was changed
   from DEBUG to INFO - which is the normal/sane default logging level for most software.
+- [28205](https://github.com/apache/superset/pull/28205) The permission `all_database_access` now
+  more clearly provides access to all databases, as specified in its name. Before it only allowed
+  listing all databases in CRUD-view and dropdown and didn't provide access to data as it
+  seemed the name would imply.
 
 ## 4.0.0
 

docker-compose.yml

@@ -39,7 +39,6 @@ x-common-build: &common-build
   cache_from:
     - apache/superset-cache:3.10-slim-bookworm
 
-version: "4.0"
 services:
   nginx:
     image: nginx:latest
@@ -94,12 +93,11 @@ services:
     depends_on: *superset-depends-on
     volumes: *superset-volumes
     environment:
-      CYPRESS_CONFIG: "${CYPRESS_CONFIG}"
+      CYPRESS_CONFIG: "${CYPRESS_CONFIG:-}"
 
   superset-websocket:
     container_name: superset_websocket
     build: ./superset-websocket
-    image: superset-websocket
     ports:
       - 8080:8080
     extra_hosts:
@@ -122,7 +120,7 @@ services:
       - /home/superset-websocket/dist
 
       # Mounting a config file that contains a dummy secret required to boot up.
-      # do no not use this docker-compose in production
+      # do not use this docker-compose in production
       - ./docker/superset-websocket/config.json:/home/superset-websocket/config.json
     environment:
       - PORT=8080
@@ -144,7 +142,7 @@ services:
     user: *superset-user
     volumes: *superset-volumes
     environment:
-      CYPRESS_CONFIG: "${CYPRESS_CONFIG}"
+      CYPRESS_CONFIG: "${CYPRESS_CONFIG:-}"
     healthcheck:
       disable: true
 
@@ -153,7 +151,7 @@ services:
     environment:
       # set this to false if you have perf issues running the npm i; npm run dev in-docker
       # if you do so, you have to run this manually on the host, which should perform better!
-      SCARF_ANALYTICS: "${SCARF_ANALYTICS}"
+      SCARF_ANALYTICS: "${SCARF_ANALYTICS:-}"
     container_name: superset_node
     command: ["/app/docker/docker-frontend.sh"]
     env_file:

docs/.gitignore

@@ -20,3 +20,6 @@ yarn-debug.log*
 yarn-error.log*
 
 docs/.zshrc
+
+# Gets copied from the root of the project at build time (yarn start / yarn build)
+docs/intro.md

docs/docs/configuration/alerts-reports.mdx

@@ -5,7 +5,7 @@ sidebar_position: 2
 version: 2
 ---
 
-## Alerts and Reports
+# Alerts and Reports
 
 Users can configure automated alerts and reports to send dashboards or charts to an email recipient or Slack channel.
 
@@ -14,11 +14,11 @@ Users can configure automated alerts and reports to send dashboards or charts to
 
 Alerts and reports are disabled by default. To turn them on, you need to do some setup, described here.
 
-### Requirements
+## Requirements
 
-#### Commons
+### Commons
 
-##### In your `superset_config.py` or `superset_config_docker.py`
+#### In your `superset_config.py` or `superset_config_docker.py`
 
 - `"ALERT_REPORTS"` [feature flag](/docs/configuration/configuring-superset#feature-flags) must be turned to True.
 - `beat_schedule` in CeleryConfig must contain schedule for `reports.scheduler`.
@@ -26,11 +26,11 @@ Alerts and reports are disabled by default. To turn them on, you need to do some
   - emails: `SMTP_*` settings
   - Slack messages: `SLACK_API_TOKEN`
 
-###### Disable dry-run mode
+##### Disable dry-run mode
 
 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).
 
-##### In your `Dockerfile`
+#### In your `Dockerfile`
 
 - You must install a headless browser, for taking screenshots of the charts and dashboards. Only Firefox and Chrome are currently supported.
   > If you choose Chrome, you must also change the value of `WEBDRIVER_TYPE` to `"chrome"` in your `superset_config.py`.
@@ -43,7 +43,7 @@ You can either install and configure the headless browser - see "Custom Dockerfi
 
 *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.
 
-#### Slack integration
+### Slack integration
 
 To send alerts and reports to Slack channels, you need to create a new Slack Application on your workspace.
 
@@ -61,14 +61,14 @@ To send alerts and reports to Slack channels, you need to create a new Slack App
 
 Note: when you configure an alert or a report, the Slack channel list takes channel names without the leading '#' e.g. use `alerts` instead of `#alerts`.
 
-#### Kubernetes-specific
+### Kubernetes-specific
 
 - You must have a `celery beat` pod running. If you're using the chart included in the GitHub repository under [helm/superset](https://github.com/apache/superset/tree/master/helm/superset), you need to put `supersetCeleryBeat.enabled = true` in your values override.
 - You can see the dedicated docs about [Kubernetes installation](/docs/installation/kubernetes) for more details.
 
-#### Docker Compose specific
+### Docker Compose specific
 
-##### You must have in your `docker-compose.yml`
+#### You must have in your `docker-compose.yml`
 
 - A Redis message broker
 - PostgreSQL DB instead of SQLlite
@@ -195,14 +195,14 @@ Please refer to `ExecutorType` in the codebase for other executor types.
   its default value of `http://0.0.0.0:8080/`.
 
 
-### Custom Dockerfile
+## Custom Dockerfile
 
 If you're running the dev version of a released Superset image, like `apache/superset:3.1.0-dev`, you should be set with the above.
 
 But if you're building your own image, or starting with a non-dev version, a webdriver (and headless browser) is needed to capture screenshots of the charts and dashboards which are then sent to the recipient.
 Here's how you can modify your Dockerfile to take the screenshots either with Firefox or Chrome.
 
-#### Using Firefox
+### Using Firefox
 
 ```docker
 FROM apache/superset:3.1.0
@@ -223,7 +223,7 @@ RUN pip install --no-cache gevent psycopg2 redis
 USER superset
 ```
 
-#### Using Chrome
+### Using Chrome
 
 ```docker
 FROM apache/superset:3.1.0
@@ -248,21 +248,21 @@ USER superset
 
 Don't forget to set `WEBDRIVER_TYPE` and `WEBDRIVER_OPTION_ARGS` in your config if you use Chrome.
 
-### Troubleshooting
+## Troubleshooting
 
 There are many reasons that reports might not be working.  Try these steps to check for specific issues.
 
-#### Confirm feature flag is enabled and you have sufficient permissions
+### Confirm feature flag is enabled and you have sufficient permissions
 
 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.
 
 Log in as an admin user to ensure you have adequate permissions.
 
-#### Check the logs of your Celery worker
+### Check the logs of your Celery worker
 
 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`.
 
-#### Check web browser and webdriver installation
+### Check web browser and webdriver installation
 
 To take a screenshot, the worker visits the dashboard or chart using a headless browser, then takes a screenshot. If you are able to send a chart as CSV or text but can't send as PNG, your problem may lie with the browser.
 
@@ -270,7 +270,7 @@ Superset docker images that have a tag ending with `-dev` have the Firefox headl
 
 If you are handling the installation of that software on your own, or wish to use Chromium instead, do your own verification to ensure that the headless browser opens successfully in the worker environment.
 
-#### Send a test email
+### Send a test email
 
 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.
 
@@ -301,7 +301,7 @@ Possible fixes:
 - 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.
 - Use another set of SMTP credentials that you verify works in this setup.
 
-#### Browse to your report from the worker
+### Browse to your report from the worker
 
 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.
 
@@ -309,7 +309,7 @@ Check this by attempting to `curl` the URL of a report that you see in the error
 
 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`.
 
-### Scheduling Queries as Reports
+## Scheduling Queries as Reports
 
 You can optionally allow your users to schedule queries directly in SQL Lab. This is done by adding
 extra metadata to saved queries, which are then picked up by an external scheduled (like

docs/docs/configuration/async-queries-celery.mdx

@@ -5,9 +5,9 @@ sidebar_position: 4
 version: 1
 ---
 
-## Async Queries via Celery
+# Async Queries via Celery
 
-### Celery
+## Celery
 
 On large analytic databases, it’s common to run queries that execute for minutes or hours. To enable
 support for long running queries that execute beyond the typical web request’s timeout (30-60
@@ -89,7 +89,7 @@ issues arise. Please clear your existing results cache store when upgrading an e
 - SQL Lab will _only run your queries asynchronously if_ you enable **Asynchronous Query Execution**
   in your database settings (Sources > Databases > Edit record).
 
-### Celery Flower
+## Celery Flower
 
 Flower is a web based tool for monitoring the Celery cluster which you can install from pip:
 

docs/docs/configuration/cache.mdx

@@ -5,7 +5,7 @@ sidebar_position: 3
 version: 1
 ---
 
-## Caching
+# Caching
 
 Superset uses [Flask-Caching](https://flask-caching.readthedocs.io/) for caching purposes.
 Flask-Caching supports various caching backends, including Redis (recommended), Memcached,
@@ -33,7 +33,7 @@ FILTER_STATE_CACHE_CONFIG = {
 }
 ```
 
-### Dependencies
+## Dependencies
 
 In order to use dedicated cache stores, additional python libraries must be installed
 
@@ -43,7 +43,7 @@ In order to use dedicated cache stores, additional python libraries must be inst
 
 These libraries can be installed using pip.
 
-### Fallback Metastore Cache
+## Fallback Metastore Cache
 
 Note, that some form of Filter State and Explore caching are required. If either of these caches
 are undefined, Superset falls back to using a built-in cache that stores data in the metadata
@@ -60,7 +60,7 @@ DATA_CACHE_CONFIG = {
 }
 ```
 
-### Chart Cache Timeout
+## Chart Cache Timeout
 
 The cache timeout for charts may be overridden by the settings for an individual chart, dataset, or
 database. Each of these configurations will be checked in order before falling back to the default
@@ -69,7 +69,7 @@ value defined in `DATA_CACHE_CONFIG`.
 Note, that by setting the cache timeout to `-1`, caching for charting data can be disabled, either
 per chart, dataset or database, or by default if set in `DATA_CACHE_CONFIG`.
 
-### SQL Lab Query Results
+## SQL Lab Query Results
 
 Caching for SQL Lab query results is used when async queries are enabled and is configured using
 `RESULTS_BACKEND`.
@@ -79,7 +79,7 @@ instead requires a cachelib object.
 
 See [Async Queries via Celery](/docs/configuration/async-queries-celery) for details.
 
-### Caching Thumbnails
+## Caching Thumbnails
 
 This is an optional feature that can be turned on by activating it’s [feature flag](/docs/configuration/configuring-superset#feature-flags) on config:
 

docs/docs/configuration/configuring-superset.mdx

@@ -5,28 +5,40 @@ sidebar_position: 1
 version: 1
 ---
 
-## Configuring Superset
+# Configuring Superset
 
-### Configuration
+## superset_config.py
 
-To configure your application, you need to create a file `superset_config.py`. Add this file to your
+Superset exposes hundreds of configurable parameters through its
+[config.py module](https://github.com/apache/superset/blob/master/superset/config.py). The
+variables and objects exposed act as a public interface of the bulk of what you may want
+to configure, alter and interface with. In this python module, you'll find all these
+parameters, sensible defaults, as well as rich documentation in the form of comments
 
-`PYTHONPATH` or create an environment variable `SUPERSET_CONFIG_PATH` specifying the full path of the `superset_config.py`.
+To configure your application, you need to create you own configuration module, which
+will allow you to override few or many of these parameters. Instead of altering the core module,
+You'll want to define your own module (typically a file named `superset_config.py`.
+Add this file to your `PYTHONPATH` or create an environment variable
+`SUPERSET_CONFIG_PATH` specifying the full path of the `superset_config.py`.
 
-For example, if deploying on Superset directly on a Linux-based system where your `superset_config.py` is under `/app` directory, you can run:
+For example, if deploying on Superset directly on a Linux-based system where your
+`superset_config.py` is under `/app` directory, you can run:
 
 ```bash
 export SUPERSET_CONFIG_PATH=/app/superset_config.py
 ```
 
-If you are using your own custom Dockerfile with official Superset image as base image, then you can add your overrides as shown below:
+If you are using your own custom Dockerfile with official Superset image as base image,
+then you can add your overrides as shown below:
 
 ```bash
 COPY --chown=superset superset_config.py /app/
 ENV SUPERSET_CONFIG_PATH /app/superset_config.py
 ```
 
-Docker compose deployments handle application configuration differently. See [https://github.com/apache/superset/tree/master/docker#readme](https://github.com/apache/superset/tree/master/docker#readme) for details.
+Docker compose deployments handle application configuration differently using specific conventions..
+Refer to the [docker-compose tips & configuration](/docs/installation/docker-compose#docker-compose-tips--configuration)
+for details.
 
 The following is an example of just a few of the parameters you can set in your `superset_config.py` file:
 
@@ -63,33 +75,39 @@ WTF_CSRF_TIME_LIMIT = 60 * 60 * 24 * 365
 MAPBOX_API_KEY = ''
 ```
 
-All the parameters and default values defined in
-[https://github.com/apache/superset/blob/master/superset/config.py](https://github.com/apache/superset/blob/master/superset/config.py)
+:::tip
+Note that it is typical to copy and paste [only] the portions of the
+core [superset/config.py](https://github.com/apache/superset/blob/master/superset/config.py) that
+you want to alter, along with the related comments into your own `superset_config.py` file.
+:::
+
+All the parameters and default values defined
+in [superset/config.py](https://github.com/apache/superset/blob/master/superset/config.py)
 can be altered in your local `superset_config.py`. Administrators will want to read through the file
 to understand what can be configured locally as well as the default values in place.
 
 Since `superset_config.py` acts as a Flask configuration module, it can be used to alter the
-settings Flask itself, as well as Flask extensions like `flask-wtf`, `flask-caching`, `flask-migrate`,
-and `flask-appbuilder`. Flask App Builder, the web framework used by Superset, offers many
+settings Flask itself, as well as Flask extensions that Superset bundles like
+`flask-wtf`, `flask-caching`, `flask-migrate`,
+and `flask-appbuilder`. Each one of these extensions offers intricate configurability.
+Flask App Builder, the web framework used by Superset, also offers many
 configuration settings. Please consult the
 [Flask App Builder Documentation](https://flask-appbuilder.readthedocs.org/en/latest/config.html)
 for more information on how to configure it.
 
-Make sure to change:
+You'll want to change:
 
-- `SQLALCHEMY_DATABASE_URI`: by default it is stored at ~/.superset/superset.db
 - `SECRET_KEY`: to a long random string
-
-If you need to exempt endpoints from CSRF (e.g. if you are running a custom auth postback endpoint),
-you can add the endpoints to `WTF_CSRF_EXEMPT_LIST`:
+- `SQLALCHEMY_DATABASE_URI`: that by default points to sqlite database located at
+  ~/.superset/superset.db
 
 ```
 WTF_CSRF_EXEMPT_LIST = [‘’]
 ```
 
-### Specifying a SECRET_KEY
+## Specifying a SECRET_KEY
 
-#### Adding an initial SECRET_KEY
+### Adding an initial SECRET_KEY
 
 Superset requires a user-specified SECRET_KEY to start up. This requirement was [added in version 2.1.0 to force secure configurations](https://preset.io/blog/superset-security-update-default-secret_key-vulnerability/). Add a strong SECRET_KEY to your `superset_config.py` file like:
 
@@ -104,7 +122,7 @@ This key will be used for securely signing session cookies and encrypting sensit
 Your deployment must use a complex, unique key.
 :::
 
-#### Rotating to a newer SECRET_KEY
+### Rotating to a newer SECRET_KEY
 
 If you wish to change your existing SECRET_KEY, add the existing SECRET_KEY to your `superset_config.py` file as
 `PREVIOUS_SECRET_KEY = `and provide your new key as `SECRET_KEY =`. You can find your current SECRET_KEY with these
@@ -117,9 +135,13 @@ from flask import current_app; print(current_app.config["SECRET_KEY"])
 
 Save your `superset_config.py` with these values and then run `superset re-encrypt-secrets`.
 
-### Using a production metastore
+## Setting up a production metadata database
 
-By default, Superset is configured to use SQLite, which is a simple and fast way to get started
+Superset needs a database to store the information it manages, like the definitions of
+charts, dashboards, and many other things.
+
+By default, Superset is configured to use [SQLite](https://www.sqlite.org/),
+a self-contained, single-file database that offers a simple and fast way to get started
 (without requiring any installation). However, for production environments,
 using SQLite is highly discouraged due to security, scalability, and data integrity reasons.
 It's important to use only the supported database engines and consider using a different
@@ -139,10 +161,17 @@ Use the following database drivers and connection strings:
 | [PostgreSQL](https://www.postgresql.org/) | `pip install psycopg2`    | `postgresql://<UserName>:<DBPassword>@<Database Host>/<Database Name>` |
 | [MySQL](https://www.mysql.com/)           | `pip install mysqlclient` | `mysql://<UserName>:<DBPassword>@<Database Host>/<Database Name>`      |
 
+:::tip
+Properly setting up metadata store is beyond the scope of this documentation. We recommend
+using a hosted managed service such as [Amazon RDS](https://aws.amazon.com/rds/) or
+[Google Cloud Databases](https://cloud.google.com/products/databases?hl=en) to handle
+service and supporting infrastructure and backup strategy.
+:::
+
 To configure Superset metastore set `SQLALCHEMY_DATABASE_URI` config key on `superset_config`
 to the appropriate connection string.
 
-### Running on a WSGI HTTP Server
+## Running on a WSGI HTTP Server
 
 While you can run Superset on NGINX or Apache, we recommend using Gunicorn in async mode. This
 enables impressive concurrency even and is fairly easy to install and configure. Please refer to the
@@ -171,12 +200,12 @@ If you're not using Gunicorn, you may want to disable the use of `flask-compress
 Currently, Google BigQuery python sdk is not compatible with `gevent`, due to some dynamic monkeypatching on python core library by `gevent`.
 So, when you use `BigQuery` datasource on Superset, you have to use `gunicorn` worker type except `gevent`.
 
-### HTTPS Configuration
+## HTTPS Configuration
 
 You can configure HTTPS upstream via a load balancer or a reverse proxy (such as nginx) and do SSL/TLS Offloading before traffic reaches the Superset application. In this setup, local traffic from a Celery worker taking a snapshot of a chart for Alerts & Reports can access Superset at a `http://` URL, from behind the ingress point.
 You can also configure [SSL in Gunicorn](https://docs.gunicorn.org/en/stable/settings.html#ssl) (the Python webserver) if you are using an official Superset Docker image.
 
-### Configuration Behind a Load Balancer
+## Configuration Behind a Load Balancer
 
 If you are running superset behind a load balancer or reverse proxy (e.g. NGINX or ELB on AWS), you
 may need to utilize a healthcheck endpoint so that your load balancer knows if your superset
@@ -194,7 +223,7 @@ In case the reverse proxy is used for providing SSL encryption, an explicit defi
 RequestHeader set X-Forwarded-Proto "https"
 ```
 
-### Custom OAuth2 Configuration
+## Custom OAuth2 Configuration
 
 Superset is built on Flask-AppBuilder (FAB), which supports many providers out of the box
 (GitHub, Twitter, LinkedIn, Google, Azure, etc). Beyond those, Superset can be configured to connect
@@ -293,19 +322,19 @@ CUSTOM_SECURITY_MANAGER = CustomSsoSecurityManager
   ]
   ```
 
-### LDAP Authentication
+## LDAP Authentication
 
 FAB supports authenticating user credentials against an LDAP server.
 To use LDAP you must install the [python-ldap](https://www.python-ldap.org/en/latest/installing.html) package.
 See [FAB's LDAP documentation](https://flask-appbuilder.readthedocs.io/en/latest/security.html#authentication-ldap)
 for details.
 
-### Mapping LDAP or OAUTH groups to Superset roles
+## Mapping LDAP or OAUTH groups to Superset roles
 
 AUTH_ROLES_MAPPING in Flask-AppBuilder is a dictionary that maps from LDAP/OAUTH group names to FAB roles.
 It is used to assign roles to users who authenticate using LDAP or OAuth.
 
-#### Mapping OAUTH groups to Superset roles
+### Mapping OAUTH groups to Superset roles
 
 The following `AUTH_ROLES_MAPPING` dictionary would map the OAUTH group "superset_users" to the Superset roles "Gamma" as well as "Alpha", and the OAUTH group "superset_admins" to the Superset role "Admin".
 
@@ -315,7 +344,7 @@ AUTH_ROLES_MAPPING = {
 "superset_admins": ["Admin"],
 }
 ```
-#### Mapping LDAP groups to Superset roles
+### Mapping LDAP groups to Superset roles
 
 The following `AUTH_ROLES_MAPPING` dictionary would map the LDAP DN "cn=superset_users,ou=groups,dc=example,dc=com" to the Superset roles "Gamma" as well as "Alpha", and the LDAP DN "cn=superset_admins,ou=groups,dc=example,dc=com" to the Superset role "Admin".
 
@@ -327,11 +356,11 @@ AUTH_ROLES_MAPPING = {
 ```
 Note: This requires `AUTH_LDAP_SEARCH` to be set. For more details, please see the [FAB Security documentation](https://flask-appbuilder.readthedocs.io/en/latest/security.html).
 
-#### Syncing roles at login
+### Syncing roles at login
 
 You can also use the `AUTH_ROLES_SYNC_AT_LOGIN` configuration variable to control how often Flask-AppBuilder syncs the user's roles with the LDAP/OAUTH groups. If `AUTH_ROLES_SYNC_AT_LOGIN` is set to True, Flask-AppBuilder will sync the user's roles each time they log in. If `AUTH_ROLES_SYNC_AT_LOGIN` is set to False, Flask-AppBuilder will only sync the user's roles when they first register.
 
-### Flask app Configuration Hook
+## Flask app Configuration Hook
 
 `FLASK_APP_MUTATOR` is a configuration function that can be provided in your environment, receives
 the app object and can alter it in any way. For example, add `FLASK_APP_MUTATOR` into your
@@ -354,7 +383,7 @@ def FLASK_APP_MUTATOR(app: Flask) -> None:
     app.before_request_funcs.setdefault(None, []).append(make_session_permanent)
 ```
 
-### Feature Flags
+## Feature Flags
 
 To support a diverse set of users, Superset has some features that are not enabled by default. For
 example, some users have stronger security restrictions, while some others may not. So Superset

docs/docs/configuration/country-map-tools.mdx

@@ -1,13 +1,12 @@
 ---
 title: Country Map Tools
-hide_title: true
 sidebar_position: 10
 version: 1
 ---
 
 import countriesData from '../../data/countries.json';
 
-## The Country Map Visualization
+# The Country Map Visualization
 
 The Country Map visualization allows you to plot lightweight choropleth maps of
 your countries by province, states, or other subdivision types. It does not rely

docs/docs/configuration/event-logging.mdx

@@ -1,18 +1,18 @@
 ---
 title: Event Logging
-hide_title: true
 sidebar_position: 9
 version: 1
 ---
 
-## Logging
+# Logging
 
-### Event Logging
+## Event Logging
 
 Superset by default logs special action events in its internal database (DBEventLogger). These logs can be accessed
 on the UI by navigating to **Security > Action Log**. You can freely customize these logs by
 implementing your own event log class.
-**When custom log class is enabled DBEventLogger is disabled and logs stop being populated in UI logs view.**
+**When custom log class is enabled DBEventLogger is disabled and logs
+stop being populated in UI logs view.**
 To achieve both, custom log class should extend built-in DBEventLogger log class.
 
 Here's an example of a simple JSON-to-stdout class:
@@ -44,9 +44,10 @@ End by updating your config to pass in an instance of the logger you want to use
 EVENT_LOGGER = JSONStdOutEventLogger()
 ```
 
-### StatsD Logging
+## StatsD Logging
 
-Superset can be instrumented to log events to StatsD if desired. Most endpoints hit are logged as
+Superset can be configured to log events to [StatsD](https://github.com/statsd/statsd)
+if desired. Most endpoints hit are logged as
 well as key events like query start and end in SQL Lab.
 
 To setup StatsD logging, it’s a matter of configuring the logger in your `superset_config.py`.

docs/docs/configuration/importing-exporting-datasources.mdx

@@ -5,7 +5,7 @@ sidebar_position: 11
 version: 1
 ---
 
-## Importing and Exporting Datasources
+# Importing and Exporting Datasources
 
 The superset cli allows you to import and export datasources from and to YAML. Datasources include
 databases. The data is expected to be organized in the following hierarchy:
@@ -26,7 +26,7 @@ databases. The data is expected to be organized in the following hierarchy:
 |  └── ... (more databases)
 ```
 
-### Exporting Datasources to YAML
+## Exporting Datasources to YAML
 
 You can print your current datasources to stdout by running:
 
@@ -61,7 +61,7 @@ superset export_datasource_schema
 
 As a reminder, you can use the `-b` flag to include back references.
 
-### Importing Datasources
+## Importing Datasources
 
 In order to import datasources from a ZIP file, run:
 
@@ -75,9 +75,9 @@ The optional username flag **-u** sets the user used for the datasource import.
 superset import_datasources -p <path / filename> -u 'admin'
 ```
 
-### Legacy Importing Datasources
+## Legacy Importing Datasources
 
-#### From older versions of Superset to current version
+### From older versions of Superset to current version
 
 When using Superset version 4.x.x to import from an older version (2.x.x or 3.x.x) importing is supported as the command `legacy_import_datasources` and expects a JSON or directory of JSONs. The options are `-r` for recursive and `-u` for specifying a user. Example of legacy import without options:
 
@@ -85,7 +85,7 @@ When using Superset version 4.x.x to import from an older version (2.x.x or 3.x.
 superset legacy_import_datasources -p <path or filename>
 ```
 
-#### From older versions of Superset to older versions
+### From older versions of Superset to older versions
 
 When using an older Superset version (2.x.x & 3.x.x) of Superset, the command is `import_datasources`. ZIP and YAML files are supported and to switch between them the feature flag `VERSIONED_EXPORT` is used. When `VERSIONED_EXPORT` is `True`, `import_datasources` expects a ZIP file, otherwise YAML. Example:
 

docs/docs/configuration/networking-settings.mdx

@@ -1,13 +1,12 @@
 ---
-title: Additional Networking Settings
-hide_title: true
+title: Network and Security Settings
 sidebar_position: 7
 version: 1
 ---
 
-## Additional Networking Settings
+# Network and Security Settings
 
-### CORS
+## CORS
 
 To configure CORS, or cross-origin resource sharing, the following dependency must be installed:
 
@@ -21,7 +20,37 @@ The following keys in `superset_config.py` can be specified to configure CORS:
 - `CORS_OPTIONS`: options passed to Flask-CORS
   ([documentation](https://flask-cors.corydolphin.com/en/latest/api.html#extension))
 
-### Domain Sharding
+
+## HTTP headers
+
+Note that Superset bundles [flask-talisman](https://pypi.org/project/talisman/)
+Self-descried as a small Flask extension that handles setting HTTP headers that can help
+protect against a few common web application security issues.
+
+## CSRF settings
+
+Similarly, [flask-wtf](https://flask-wtf.readthedocs.io/en/0.15.x/config/) is used manage
+some CSRF configurations. If you need to exempt endpoints from CSRF (e.g. if you are
+running a custom auth postback endpoint), you can add the endpoints to `WTF_CSRF_EXEMPT_LIST`:
+
+
+## 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
+
+2. Create database w/ ssh tunnel enabled
+    - With the feature flag enabled you should now see ssh tunnel toggle.
+    - Click the toggle to enables ssh tunneling and add your credentials accordingly.
+        - Superset allows for 2 different type 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.
+
+
+## Domain Sharding
 
 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.
@@ -42,7 +71,7 @@ or add the following setting in your `superset_config.py` file if domain shards
 
 - `SESSION_COOKIE_DOMAIN = '.mydomain.com'`
 
-### Middleware
+## Middleware
 
 Superset allows you to add your own middleware. To add your own middleware, update the
 `ADDITIONAL_MIDDLEWARE` key in your `superset_config.py`. `ADDITIONAL_MIDDLEWARE` should be a list

docs/docs/configuration/setup-ssh-tunneling.mdx

@@ -4,18 +4,3 @@ hide_title: true
 sidebar_position: 8
 version: 1
 ---
-
-## 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
-
-2. Create database w/ ssh tunnel enabled
-    - With the feature flag enabled you should now see ssh tunnel toggle.
-    - Click the toggle to enables ssh tunneling and add your credentials accordingly.
-        - Superset allows for 2 different type 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.

docs/docs/configuration/sql-templating.mdx

@@ -5,9 +5,9 @@ sidebar_position: 5
 version: 1
 ---
 
-## SQL Templating
+# SQL Templating
 
-### Jinja Templates
+## Jinja Templates
 
 SQL Lab and Explore supports [Jinja templating](https://jinja.palletsprojects.com/en/2.11.x/) in queries.
 To enable templating, the `ENABLE_TEMPLATE_PROCESSING` [feature flag](/docs/configuration/configuring-superset#feature-flags) needs to be enabled in
@@ -168,7 +168,7 @@ FEATURE_FLAGS = {
 The available validators and names can be found in
 [sql_validators](https://github.com/apache/superset/tree/master/superset/sql_validators).
 
-### Available Macros
+## Available Macros
 
 In this section, we'll walkthrough the pre-defined Jinja macros in Superset.
 

docs/docs/configuration/timezones.mdx

@@ -5,7 +5,7 @@ sidebar_position: 6
 version: 1
 ---
 
-## Timezones
+# Timezones
 
 There are four distinct timezone components which relate to Apache Superset,
 
@@ -20,7 +20,7 @@ To help make the problem somewhat tractable—given that Apache Superset has no
 
 To strive for data consistency (regardless of the timezone of the client) the Apache Superset backend tries to ensure that any timestamp sent to the client has an explicit (or semi-explicit as in the case with [Epoch time](https://en.wikipedia.org/wiki/Unix_time) which is always in reference to UTC) timezone encoded within.
 
-The challenge however lies with the slew of [database engines](/docs/databases/installing-database-drivers#install-database-drivers) which Apache Superset supports and various inconsistencies between their [Python Database API (DB-API)](https://www.python.org/dev/peps/pep-0249/) implementations combined with the fact that we use [Pandas](https://pandas.pydata.org/) to read SQL into a DataFrame prior to serializing to JSON. Regrettably Pandas ignores the DB-API [type_code](https://www.python.org/dev/peps/pep-0249/#type-objects) relying by default on the underlying Python type returned by the DB-API. Currently only a subset of the supported database engines work correctly with Pandas, i.e., ensuring timestamps without an explicit timestamp are serializd to JSON with the server timezone, thus guaranteeing the client will display timestamps in a consistent manner irrespective of the client's timezone.
+The challenge however lies with the slew of [database engines](/docs/configuration/databases#installing-drivers-in-docker-images) which Apache Superset supports and various inconsistencies between their [Python Database API (DB-API)](https://www.python.org/dev/peps/pep-0249/) implementations combined with the fact that we use [Pandas](https://pandas.pydata.org/) to read SQL into a DataFrame prior to serializing to JSON. Regrettably Pandas ignores the DB-API [type_code](https://www.python.org/dev/peps/pep-0249/#type-objects) relying by default on the underlying Python type returned by the DB-API. Currently only a subset of the supported database engines work correctly with Pandas, i.e., ensuring timestamps without an explicit timestamp are serializd to JSON with the server timezone, thus guaranteeing the client will display timestamps in a consistent manner irrespective of the client's timezone.
 
 For example the following is a comparison of MySQL and Presto,
 

docs/docs/contributing/contributing.mdx

@@ -88,7 +88,7 @@ text strings from Superset's UI. You can jump into the existing
 language dictionaries at
 `superset/translations/<language_code>/LC_MESSAGES/messages.po`, or
 even create a dictionary for a new language altogether.
-See [Translating](#translating) for more details.
+See [Translating](howtos#contribute-translations) for more details.
 
 ### Ask Questions
 

docs/docs/databases/ascend.mdx

@@ -1,16 +0,0 @@
----
-title: Ascend.io
-hide_title: true
-sidebar_position: 10
-version: 1
----
-
-## Ascend.io
-
-The recommended connector library to Ascend.io is [impyla](https://github.com/cloudera/impyla).
-
-The expected connection string is formatted as follows:
-
-```
-ascend://{username}:{password}@{hostname}:{port}/{database}?auth_mechanism=PLAIN;use_ssl=true
-```

docs/docs/databases/athena.mdx

@@ -1,39 +0,0 @@
----
-title: Amazon Athena
-hide_title: true
-sidebar_position: 4
-version: 1
----
-
-## AWS Athena
-
-### PyAthenaJDBC
-
-[PyAthenaJDBC](https://pypi.org/project/PyAthenaJDBC/) is a Python DB 2.0 compliant wrapper for the
-[Amazon Athena JDBC driver](https://docs.aws.amazon.com/athena/latest/ug/connect-with-jdbc.html).
-
-The connection string for Amazon Athena is as follows:
-
-```
-awsathena+jdbc://{aws_access_key_id}:{aws_secret_access_key}@athena.{region_name}.amazonaws.com/{schema_name}?s3_staging_dir={s3_staging_dir}&...
-```
-
-Note that you'll need to escape & encode when forming the connection string like so:
-
-```
-s3://... -> s3%3A//...
-```
-
-### PyAthena
-
-You can also use the [PyAthena library](https://pypi.org/project/PyAthena/) (no Java required) with the
-following connection string:
-
-```
-awsathena+rest://{aws_access_key_id}:{aws_secret_access_key}@athena.{region_name}.amazonaws.com/{schema_name}?s3_staging_dir={s3_staging_dir}&...
-```
-
-The PyAthena library also allows to assume a specific IAM role which you can define by adding following parameters in Superset's Athena database connection UI under ADVANCED --> Other --> ENGINE PARAMETERS.
-```
-{"connect_args":{"role_arn":"<role arn>"}}
-```

docs/docs/databases/bigquery.mdx

@@ -1,92 +0,0 @@
----
-title: Google BigQuery
-hide_title: true
-sidebar_position: 20
-version: 1
----
-
-## Google BigQuery
-
-The recommended connector library for BigQuery is
-[sqlalchemy-bigquery](https://github.com/googleapis/python-bigquery-sqlalchemy).
-
-### Install BigQuery Driver
-
-Follow the steps [here](/docs/databases/docker-add-drivers) about how to
-install new database drivers when setting up Superset locally via docker compose.
-
-```
-echo "sqlalchemy-bigquery" >> ./docker/requirements-local.txt
-```
-
-### Connecting to BigQuery
-
-When adding a new BigQuery connection in Superset, you'll need to add the GCP Service Account
-credentials file (as a JSON).
-
-1. Create your Service Account via the Google Cloud Platform control panel, provide it access to the
-   appropriate BigQuery datasets, and download the JSON configuration file for the service account.
-2. In Superset, you can either upload that JSON or add the JSON blob in the following format (this should be the content of your credential JSON file):
-
-```
-{
-        "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": "..."
-    }
-```
-
-![CleanShot 2021-10-22 at 04 18 11](https://user-images.githubusercontent.com/52086618/138352958-a18ef9cb-8880-4ef1-88c1-452a9f1b8105.gif)
-
-3. Additionally, can connect via SQLAlchemy URI instead
-
-   The connection string for BigQuery looks like:
-
-   ```
-   bigquery://{project_id}
-   ```
-
-   Go to the **Advanced** tab, Add a JSON blob to the **Secure Extra** field in the database configuration form with
-   the following format:
-
-   ```
-   {
-   "credentials_info": <contents of credentials JSON file>
-   }
-   ```
-
-   The resulting file should have this structure:
-
-   ```
-   {
-    "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.
-
-![CleanShot 2021-10-22 at 04 47 08](https://user-images.githubusercontent.com/52086618/138354340-df57f477-d3e5-42d4-b032-d901c69d2213.gif)
-
-To be able to upload CSV or Excel files to BigQuery in Superset, you'll need to also add the
-[pandas_gbq](https://github.com/pydata/pandas-gbq) library.
-
-Currently, Google BigQuery python sdk is not compatible with `gevent`, due to some dynamic monkeypatching on python core library by `gevent`.
-So, when you deploy Superset with `gunicorn` server, you have to use worker type except `gevent`.

docs/docs/databases/clickhouse.mdx

@@ -1,42 +0,0 @@
----
-title: ClickHouse
-hide_title: true
-sidebar_position: 15
-version: 1
----
-
-## ClickHouse
-
-To use ClickHouse with Superset, you will need to add the following Python library:
-
-```
-clickhouse-connect>=0.6.8
-```
-
-If running Superset using Docker Compose, add the following to your `./docker/requirements-local.txt` file:
-
-```
-clickhouse-connect>=0.6.8
-```
-
-The recommended connector library for ClickHouse is
-[clickhouse-connect](https://github.com/ClickHouse/clickhouse-connect).
-
-The expected connection string is formatted as follows:
-
-```
-clickhousedb://<user>:<password>@<host>:<port>/<database>[?options…]clickhouse://{username}:{password}@{hostname}:{port}/{database}
-```
-
-Here's a concrete example of a real connection string:
-
-```
-clickhousedb://demo:demo@github.demo.trial.altinity.cloud/default?secure=true
-```
-
-If you're using Clickhouse locally on your computer, you can get away with using a http protocol URL that
-uses the default user without a password (and doesn't encrypt the connection):
-
-```
-clickhousedb://localhost/default
-```

docs/docs/databases/cockroachdb.mdx

@@ -1,17 +0,0 @@
----
-title: CockroachDB
-hide_title: true
-sidebar_position: 16
-version: 1
----
-
-## CockroachDB
-
-The recommended connector library for CockroachDB is
-[sqlalchemy-cockroachdb](https://github.com/cockroachdb/sqlalchemy-cockroachdb).
-
-The expected connection string is formatted as follows:
-
-```
-cockroachdb://root@{hostname}:{port}/{database}?sslmode=disable
-```

docs/docs/databases/cratedb.mdx

@@ -1,24 +0,0 @@
----
-title: CrateDB
-hide_title: true
-sidebar_position: 36
-version: 1
----
-
-## CrateDB
-
-The recommended connector library for CrateDB is
-[crate](https://pypi.org/project/crate/).
-You need to install the extras as well for this library.
-We recommend adding something like the following
-text to your requirements file:
-
-```
-crate[sqlalchemy]==0.26.0
-```
-
-The expected connection string is formatted as follows:
-
-```
-crate://crate@127.0.0.1:4200
-```

docs/docs/databases/databend.mdx

@@ -1,23 +0,0 @@
----
-title: Databend
-hide_title: true
-sidebar_position: 39
-version: 1
----
-
-## Databend
-
-The recommended connector library for Databend is [databend-sqlalchemy](https://pypi.org/project/databend-sqlalchemy/).
-Superset has been tested on `databend-sqlalchemy>=0.2.3`.
-
-The recommended connection string is:
-
-```
-databend://{username}:{password}@{host}:{port}/{database_name}
-```
-
-Here's a connection string example of Superset connecting to a Databend database:
-
-```
-databend://user:password@localhost:8000/default?secure=false
-```

docs/docs/databases/databricks.mdx

@@ -1,89 +0,0 @@
----
-title: Databricks
-hide_title: true
-sidebar_position: 37
-version: 1
----
-
-## Databricks
-
-Databricks now offer a native DB API 2.0 driver, `databricks-sql-connector`, that can be used with the `sqlalchemy-databricks` dialect. You can install both with:
-
-```bash
-pip install "apache-superset[databricks]"
-```
-
-To use the Hive connector you need the following information from your cluster:
-
-- Server hostname
-- Port
-- HTTP path
-
-These can be found under "Configuration" -> "Advanced Options" -> "JDBC/ODBC".
-
-You also need an access token from "Settings" -> "User Settings" -> "Access Tokens".
-
-Once you have all this information, add a database of type "Databricks Native Connector" and use the following SQLAlchemy URI:
-
-```
-databricks+connector://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/****"}
-}
-```
-
-## Older driver
-
-Originally Superset used `databricks-dbapi` to connect to Databricks. You might want to try it if you're having problems with the official Databricks connector:
-
-```bash
-pip install "databricks-dbapi[sqlalchemy]"
-```
-
-There are two ways to connect to Databricks when using `databricks-dbapi`: using a Hive connector or an ODBC connector. Both ways work similarly, but only ODBC can be used to connect to [SQL endpoints](https://docs.databricks.com/sql/admin/sql-endpoints.html).
-
-### Hive
-
-To connect to a Hive cluster add a database of type "Databricks Interactive Cluster" in Superset, and use the following SQLAlchemy URI:
-
-```
-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/****"}}
-```
-
-### ODBC
-
-For ODBC you first need to install the [ODBC drivers for your platform](https://databricks.com/spark/odbc-drivers-download).
-
-For a regular connection use this as the SQLAlchemy URI after selecting either "Databricks Interactive Cluster" or "Databricks SQL Endpoint" for the database, depending on your use case:
-
-```
-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"}}
-```
-
-The driver path should be:
-
-- `/Library/simba/spark/lib/libsparkodbc_sbu.dylib` (Mac OS)
-- `/opt/simba/spark/lib/64/libsparkodbc_sb64.so` (Linux)
-
-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"}}
-```

docs/docs/databases/db-connection-ui.mdx

@@ -1,76 +0,0 @@
----
-title: Using Database Connection UI
-hide_title: true
-sidebar_position: 3
-version: 1
----
-
-Here is the documentation on how to leverage the new DB Connection UI. This will provide admins the ability to enhance the UX for users who want to connect to new databases.
-
-![db-conn-docs](https://user-images.githubusercontent.com/27827808/125499607-94e300aa-1c0f-4c60-b199-3f9de41060a3.gif)
-
-There are now 3 steps when connecting to a database in the new UI:
-
-Step 1: First the admin must inform superset what engine they want to connect to. This page is powered by the `/available` endpoint which pulls on the engines currently installed in your environment, so that only supported databases are shown.
-
-Step 2: Next, the admin is prompted to enter database specific parameters. Depending on whether there is a dynamic form available for that specific engine, the admin will either see the new custom form or the legacy SQLAlchemy form. We currently have built dynamic forms for (Redshift, MySQL, Postgres, and BigQuery). The new form prompts the user for the parameters needed to connect (for example, username, password, host, port, etc.) and provides immediate feedback on errors.
-
-Step 3: Finally, once the admin has connected to their DB using the dynamic form they have the opportunity to update any optional advanced settings.
-
-We hope this feature will help eliminate a huge bottleneck for users to get into the application and start crafting datasets.
-
-### How to setup up preferred database options and images
-
-We added a new configuration option where the admin can define their preferred databases, in order:
-
-```python
-# A list of preferred databases, in order. These databases will be
-# displayed prominently in the "Add Database" dialog. You should
-# use the "engine_name" attribute of the corresponding DB engine spec
-# in `superset/db_engine_specs/`.
-PREFERRED_DATABASES: list[str] = [
-    "PostgreSQL",
-    "Presto",
-    "MySQL",
-    "SQLite",
-]
-```
-
-For copyright reasons the logos for each database are not distributed with Superset.
-
-### Setting images
-
-- To set the images of your preferred database, admins must create a mapping in the `superset_text.yml` file with engine and location of the image. The image can be host locally inside your static/file directory or online (e.g. S3)
-
-```python
-DB_IMAGES:
-  postgresql: "path/to/image/postgres.jpg"
-  bigquery: "path/to/s3bucket/bigquery.jpg"
-  snowflake: "path/to/image/snowflake.jpg"
-```
-
-### How to add new database engines to available endpoint
-
-Currently the new modal supports the following databases:
-
-- Postgres
-- Redshift
-- MySQL
-- BigQuery
-
-When the user selects a database not in this list they will see the old dialog asking for the SQLAlchemy URI. New databases can be added gradually to the new flow. In order to support the rich configuration a DB engine spec needs to have the following attributes:
-
-1. `parameters_schema`: a Marshmallow schema defining the parameters needed to configure the database. For Postgres this includes username, password, host, port, etc. ([see](https://github.com/apache/superset/blob/accee507c0819cd0d7bcfb5a3e1199bc81eeebf2/superset/db_engine_specs/base.py#L1309-L1320)).
-2. `default_driver`: the name of the recommended driver for the DB engine spec. Many SQLAlchemy dialects support multiple drivers, but usually one is the official recommendation. For Postgres we use "psycopg2".
-3. `sqlalchemy_uri_placeholder`: a string that helps the user in case they want to type the URI directly.
-4. `encryption_parameters`: parameters used to build the URI when the user opts for an encrypted connection. For Postgres this is `{"sslmode": "require"}`.
-
-In addition, the DB engine spec must implement these class methods:
-
-- `build_sqlalchemy_uri(cls, parameters, encrypted_extra)`: this method receives the distinct parameters and builds the URI from them.
-- `get_parameters_from_uri(cls, uri, encrypted_extra)`: this method does the opposite, extracting the parameters from a given URI.
-- `validate_parameters(cls, parameters)`: this method is used for `onBlur` validation of the form. It should return a list of `SupersetError` indicating which parameters are missing, and which parameters are definitely incorrect ([example](https://github.com/apache/superset/blob/accee507c0819cd0d7bcfb5a3e1199bc81eeebf2/superset/db_engine_specs/base.py#L1404)).
-
-For databases like MySQL and Postgres that use the standard format of `engine+driver://user:password@host:port/dbname` all you need to do is add the `BasicParametersMixin` to the DB engine spec, and then define the parameters 2-4 (`parameters_schema` is already present in the mixin).
-
-For other databases you need to implement these methods yourself. The BigQuery DB engine spec is a good example of how to do that.

docs/docs/databases/docker-add-drivers.mdx

@@ -1,63 +0,0 @@
----
-title: Adding New Drivers in Docker
-hide_title: true
-sidebar_position: 2
-version: 1
----
-
-## Adding New Database Drivers in Docker
-
-Superset requires a Python database driver to be installed for each additional type of database you want to connect to.
-
-In this example, we'll walk through how to install the MySQL connector library. The connector library installation process is the same for all additional libraries.
-
-### 1. Determine the driver you need
-
-Consult the [list of database drivers](/docs/databases/installing-database-drivers) and find the PyPI package needed to connect to your database. In this example, we're connecting to a MySQL database, so we'll need the `mysqlclient` connector library.
-
-### 2. Install the driver in the container
-
-We need to get the `mysqlclient` library installed into the Superset docker container (it doesn't matter if it's installed on the host machine). We could enter the running container with `docker exec -it <container_name> bash` and run `pip install mysqlclient` there, but that wouldn't persist permanently.
-
-To address this, the Superset `docker compose` deployment uses the convention of a `requirements-local.txt` file. All packages listed in this file will be installed into the container from PyPI at runtime. This file will be ignored by Git for the purposes of local development.
-
-Create the file `requirements-local.txt` in a subdirectory called `docker` that exists in the directory with your `docker-compose.yml` or `docker-compose-non-dev.yml` file.
-
-```
-# Run from the repo root:
-touch ./docker/requirements-local.txt
-```
-
-Add the driver identified in step above.  You can use a text editor or do it from the command line like:
-
-```
-echo "mysqlclient" >> ./docker/requirements-local.txt
-```
-
-**If you are running a stock (non-customized) Superset image**, you are done.  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 be present in the printed list.
-
-**If you're running a customized docker image**, rebuild your local image with the new driver baked in:
-
-```
-docker compose build --force-rm
-```
-
-After the rebuild of the Docker images is complete, relaunch Superset by running `docker compose up`.
-
-### 3. Connect to MySQL
-
-Now that you've got a MySQL driver installed in your container, you should be able to connect to your database via the Superset web UI.
-
-As an admin user, go to Settings -> Data: Database Connections and click the +DATABASE button. From there, follow the steps on the [Using Database Connection UI page](/docs/databases/db-connection-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, on the [MySQL page](/docs/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.
-
-Click the “Test Connection” button, which should result in a popup message saying, "Connection looks good!".
-
-### 4. Troubleshooting
-
-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 purposes of isolating the problem.
-
-Repeat this process for each different type of database you want Superset to be able to connect to.

docs/docs/databases/doris.mdx

@@ -1,26 +0,0 @@
----
-title: Apache Doris
-hide_title: true
-sidebar_position: 5
-version: 1
----
-
-## Doris
-
-The [sqlalchemy-doris](https://pypi.org/project/pydoris/) library is the recommended way to connect to Apache Doris through SQLAlchemy.
-
-You'll need the following setting values to form the connection string:
-
-- **User**: User Name
-- **Password**: Password
-- **Host**: Doris FE Host
-- **Port**: Doris FE port
-- **Catalog**: Catalog Name
-- **Database**: Database Name
-
-
-Here's what the connection string looks like:
-
-```
-doris://<User>:<Password>@<Host>:<Port>/<Catalog>.<Database>
-```

docs/docs/databases/dremio.mdx

@@ -1,26 +0,0 @@
----
-title: Dremio
-hide_title: true
-sidebar_position: 17
-version: 1
----
-
-## Dremio
-
-The recommended connector library for Dremio is
-[sqlalchemy_dremio](https://pypi.org/project/sqlalchemy-dremio/).
-
-The expected connection string for ODBC (Default port is 31010) is formatted as follows:
-
-```
-dremio://{username}:{password}@{host}:{port}/{database_name}/dremio?SSL=1
-```
-
-The expected connection string for Arrow Flight (Dremio 4.9.1+. Default port is 32010) is formatted as follows:
-
-```
-dremio+flight://{username}:{password}@{host}:{port}/dremio
-```
-
-This [blog post by Dremio](https://www.dremio.com/tutorials/dremio-apache-superset/) has some
-additional helpful instructions on connecting Superset to Dremio.

docs/docs/databases/drill.mdx

@@ -1,47 +0,0 @@
----
-title: Apache Drill
-hide_title: true
-sidebar_position: 6
-version: 1
----
-
-## Apache Drill
-
-### SQLAlchemy
-
-The recommended way to connect to Apache Drill is through SQLAlchemy. You can use the
-[sqlalchemy-drill](https://github.com/JohnOmernik/sqlalchemy-drill) package.
-
-Once that is done, you can connect to Drill in two ways, either via the REST interface or by JDBC.
-If you are connecting via JDBC, you must have the Drill JDBC Driver installed.
-
-The basic connection string for Drill looks like this:
-
-```
-drill+sadrill://<username>:<password>@<host>:<port>/<storage_plugin>?use_ssl=True
-```
-
-To connect to Drill running on a local machine running in embedded mode you can use the following
-connection string:
-
-```
-drill+sadrill://localhost:8047/dfs?use_ssl=False
-```
-
-### JDBC
-
-Connecting to Drill through JDBC is more complicated and we recommend following
-[this tutorial](https://drill.apache.org/docs/using-the-jdbc-driver/).
-
-The connection string looks like:
-
-```
-drill+jdbc://<username>:<password>@<host>:<port>
-```
-
-### ODBC
-
-We recommend reading the
-[Apache Drill documentation](https://drill.apache.org/docs/installing-the-driver-on-linux/) and read
-the [GitHub README](https://github.com/JohnOmernik/sqlalchemy-drill#usage-with-odbc) to learn how to
-work with Drill through ODBC.

docs/docs/databases/druid.mdx

@@ -1,71 +0,0 @@
----
-title: Apache Druid
-hide_title: true
-sidebar_position: 7
-version: 1
----
-
-import useBaseUrl from "@docusaurus/useBaseUrl";
-
-## Apache Druid
-
-A native connector to Druid ships with Superset (behind the `DRUID_IS_ACTIVE` flag) but this is
-slowly getting deprecated in favor of the SQLAlchemy / DBAPI connector made available in the
-[pydruid library](https://pythonhosted.org/pydruid/).
-
-The connection string looks like:
-
-```
-druid://<User>:<password>@<Host>:<Port-default-9088>/druid/v2/sql
-```
-Here's a breakdown of the key components of this connection string:
-
-- `User`: username portion of the credentials needed to connect to your database
-- `Password`: password portion of the credentials needed to connect to your database
-- `Host`: IP address (or URL) of the host machine that's running your database
-- `Port`: specific port that's exposed on your host machine where your database is running
-
-### Customizing Druid Connection
-
-When adding a connection to Druid, you can customize the connection a few different ways in the
-**Add Database** form.
-
-**Custom Certificate**
-
-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")} />{" "}
-
-When using a custom certificate, pydruid will automatically use https scheme.
-
-**Disable SSL Verification**
-
-To disable SSL verification, add the following to the **Extras** field:
-
-```
-engine_params:
-{"connect_args":
-	{"scheme": "https", "ssl_verify_cert": false}}
-```
-
-### Aggregations
-
-Common aggregations or Druid metrics can be defined and used in Superset. The first and simpler use
-case is to use the checkbox matrix exposed in your datasource’s edit view (**Sources -> Druid
-Datasources -> [your datasource] -> Edit -> [tab] List Druid Column**).
-
-Clicking the GroupBy and Filterable checkboxes will make the column appear in the related dropdowns
-while in the Explore view. Checking Count Distinct, Min, Max or Sum will result in creating new
-metrics that will appear in the **List Druid Metric** tab upon saving the datasource.
-
-By editing these metrics, you’ll notice that their JSON element corresponds to Druid aggregation
-definition. You can create your own aggregations manually from the **List Druid Metric** tab
-following Druid documentation.
-
-### Post-Aggregations
-
-Druid supports post aggregation and this works in Superset. All you have to do is create a metric,
-much like you would create an aggregation manually, but specify `postagg` as a `Metric Type`. You
-then have to provide a valid json post-aggregation definition (as specified in the Druid docs) in
-the JSON field.

docs/docs/databases/dynamodb.mdx

@@ -1,20 +0,0 @@
----
-title: Amazon DynamoDB
-hide_title: true
-sidebar_position: 4
-version: 1
----
-
-## AWS DynamoDB
-
-### PyDynamoDB
-
-[PyDynamoDB](https://pypi.org/project/PyDynamoDB/) is a Python DB API 2.0 (PEP 249) client for Amazon DynamoDB.
-
-The connection string for Amazon DynamoDB is as follows:
-
-```
-dynamodb://{aws_access_key_id}:{aws_secret_access_key}@dynamodb.{region_name}.amazonaws.com:443?connector=superset
-```
-
-To get more documentation, please visit: [PyDynamoDB WIKI](https://github.com/passren/PyDynamoDB/wiki/5.-Superset).

docs/docs/databases/elasticsearch.mdx

@@ -1,76 +0,0 @@
----
-title: Elasticsearch
-hide_title: true
-sidebar_position: 18
-version: 1
----
-
-## Elasticsearch
-
-The recommended connector library for Elasticsearch is
-[elasticsearch-dbapi](https://github.com/preset-io/elasticsearch-dbapi).
-
-The connection string for Elasticsearch looks like this:
-
-```
-elasticsearch+http://{user}:{password}@{host}:9200/
-```
-
-**Using HTTPS**
-
-```
-elasticsearch+https://{user}:{password}@{host}:9200/
-```
-
-Elasticsearch as a default limit of 10000 rows, so you can increase this limit on your cluster or
-set Superset’s row limit on config
-
-```
-ROW_LIMIT = 10000
-```
-
-You can query multiple indices on SQL Lab for example
-
-```
-SELECT timestamp, agent FROM "logstash"
-```
-
-But, to use visualizations for multiple indices you need to create an alias index on your cluster
-
-```
-POST /_aliases
-{
-    "actions" : [
-        { "add" : { "index" : "logstash-**", "alias" : "logstash_all" } }
-    ]
-}
-```
-
-Then register your table with the alias name logstash_all
-
-**Time zone**
-
-By default, Superset uses UTC time zone for elasticsearch query. If you need to specify a time zone,
-please edit your Database and enter the settings of your specified time zone in the Other > ENGINE PARAMETERS:
-
-```
-{
-    "connect_args": {
-        "time_zone": "Asia/Shanghai"
-    }
-}
-```
-
-Another issue to note about the time zone problem is that before elasticsearch7.8, if you want to convert a string into a `DATETIME` object,
-you need to use the `CAST` function,but this function does not support our `time_zone` setting. So it is recommended to upgrade to the version after elasticsearch7.8.
-After elasticsearch7.8, you can use the `DATETIME_PARSE` function to solve this problem.
-The DATETIME_PARSE function is to support our `time_zone` setting, and here you need to fill in your elasticsearch version number in the Other > VERSION setting.
-the superset will use the `DATETIME_PARSE` function for conversion.
-
-**Disable SSL Verification**
-
-To disable SSL verification, add the following to the **SQLALCHEMY URI** field:
-
-```
-elasticsearch+https://{user}:{password}@{host}:9200/?verify_certs=False
-```

docs/docs/databases/exasol.mdx

@@ -1,17 +0,0 @@
----
-title: Exasol
-hide_title: true
-sidebar_position: 19
-version: 1
----
-
-## Exasol
-
-The recommended connector library for Exasol is
-[sqlalchemy-exasol](https://github.com/exasol/sqlalchemy-exasol).
-
-The connection string for Exasol looks like this:
-
-```
-exa+pyodbc://{username}:{password}@{hostname}:{port}/my_schema?CONNECTIONLCALL=en_US.UTF-8&driver=EXAODBC
-```

docs/docs/databases/extra-settings.mdx

@@ -1,69 +0,0 @@
----
-title: Extra Database Settings
-hide_title: true
-sidebar_position: 40
-version: 1
----
-
-## Extra Database Settings
-
-### Deeper SQLAlchemy Integration
-
-It is possible to tweak the database connection information using the parameters exposed by
-SQLAlchemy. In the **Database edit** view, you can edit the **Extra** field as a JSON blob.
-
-This JSON string contains extra configuration elements. The `engine_params` object gets unpacked
-into the `sqlalchemy.create_engine` call, while the `metadata_params` get unpacked into the
-`sqlalchemy.MetaData` call. Refer to the SQLAlchemy docs for more information.
-
-### Schemas
-
-Databases like Postgres and Redshift use the **schema** as the logical entity on top of the
-**database**. For Superset to connect to a specific schema, you can set the **schema** parameter in
-the **Edit Tables** form (Sources > Tables > Edit record).
-
-### External Password Store for SQLAlchemy Connections
-
-Superset can be configured to use an external store for database passwords. This is useful if you a
-running a custom secret distribution framework and do not wish to store secrets in Superset’s meta
-database.
-
-Example: Write a function that takes a single argument of type `sqla.engine.url` and returns the
-password for the given connection string. Then set `SQLALCHEMY_CUSTOM_PASSWORD_STORE` in your config
-file to point to that function.
-
-```python
-def example_lookup_password(url):
-    secret = <<get password from external framework>>
-    return 'secret'
-
-SQLALCHEMY_CUSTOM_PASSWORD_STORE = example_lookup_password
-```
-
-A common pattern is to use environment variables to make secrets available.
-`SQLALCHEMY_CUSTOM_PASSWORD_STORE` can also be used for that purpose.
-
-```python
-def example_password_as_env_var(url):
-    # assuming the uri looks like
-    # mysql://localhost?superset_user:{SUPERSET_PASSWORD}
-    return url.password.format(**os.environ)
-
-SQLALCHEMY_CUSTOM_PASSWORD_STORE = example_password_as_env_var
-```
-
-### SSL Access to Databases
-
-You can use the `Extra` field in the **Edit Databases** form to configure SSL:
-
-```JSON
-{
-    "metadata_params": {},
-    "engine_params": {
-          "connect_args":{
-              "sslmode":"require",
-              "sslrootcert": "/path/to/my/pem"
-        }
-     }
-}
-```

docs/docs/databases/firebird.mdx

@@ -1,23 +0,0 @@
----
-title: Firebird
-hide_title: true
-sidebar_position: 38
-version: 1
----
-
-## Firebird
-
-The recommended connector library for Firebird is [sqlalchemy-firebird](https://pypi.org/project/sqlalchemy-firebird/).
-Superset has been tested on `sqlalchemy-firebird>=0.7.0, <0.8`.
-
-The recommended connection string is:
-
-```
-firebird+fdb://{username}:{password}@{host}:{port}//{path_to_db_file}
-```
-
-Here's a connection string example of Superset connecting to a local Firebird database:
-
-```
-firebird+fdb://SYSDBA:masterkey@192.168.86.38:3050//Library/Frameworks/Firebird.framework/Versions/A/Resources/examples/empbuild/employee.fdb
-```

docs/docs/databases/firebolt.mdx

@@ -1,26 +0,0 @@
----
-title: Firebolt
-hide_title: true
-sidebar_position: 39
-version: 1
----
-
-## Firebolt
-
-The recommended connector library for Firebolt is [firebolt-sqlalchemy](https://pypi.org/project/firebolt-sqlalchemy/).
-
-The recommended connection string is:
-
-```
-firebolt://{username}:{password}@{database}?account_name={name}
-or
-firebolt://{username}:{password}@{database}/{engine_name}?account_name={name}
-```
-
-It's also possible to connect using a service account:
-
-```
-firebolt://{client_id}:{client_secret}@{database}?account_name={name}
-or
-firebolt://{client_id}:{client_secret}@{database}/{engine_name}?account_name={name}
-```

docs/docs/databases/google-sheets.mdx

@@ -1,16 +0,0 @@
----
-title: Google Sheets
-hide_title: true
-sidebar_position: 21
-version: 1
----
-
-## Google Sheets
-
-Google Sheets has a very limited
-[SQL API](https://developers.google.com/chart/interactive/docs/querylanguage). The recommended
-connector library for Google Sheets is [shillelagh](https://github.com/betodealmeida/shillelagh).
-
-There are a few steps involved in connecting Superset to Google Sheets. This
-[tutorial](https://preset.io/blog/2020-06-01-connect-superset-google-sheets/) has the most up to date
-instructions on setting up this connection.

docs/docs/databases/hana.mdx

@@ -1,16 +0,0 @@
----
-title: Hana
-hide_title: true
-sidebar_position: 22
-version: 1
----
-
-## Hana
-
-The recommended connector library is [sqlalchemy-hana](https://github.com/SAP/sqlalchemy-hana).
-
-The connection string is formatted as follows:
-
-```
-hana://{username}:{password}@{host}:{port}
-```

docs/docs/databases/hive.mdx

@@ -1,16 +0,0 @@
----
-title: Apache Hive
-hide_title: true
-sidebar_position: 8
-version: 1
----
-
-## Apache Hive
-
-The [pyhive](https://pypi.org/project/PyHive/) library is the recommended way to connect to Hive through SQLAlchemy.
-
-The expected connection string is formatted as follows:
-
-```
-hive://hive@{hostname}:{port}/{database}
-```

docs/docs/databases/hologres.mdx

@@ -1,24 +0,0 @@
----
-title: Hologres
-hide_title: true
-sidebar_position: 33
-version: 1
----
-
-## Hologres
-
-Hologres is a real-time interactive analytics service developed by Alibaba Cloud. It is fully compatible with PostgreSQL 11 and integrates seamlessly with the big data ecosystem.
-
-Hologres sample connection parameters:
-
-- **User Name**: The AccessKey ID of your Alibaba Cloud account.
-- **Password**: The AccessKey secret of your Alibaba Cloud account.
-- **Database Host**: The public endpoint of the Hologres instance.
-- **Database Name**: The name of the Hologres database.
-- **Port**: The port number of the Hologres instance.
-
-The connection string looks like:
-
-```
-postgresql+psycopg2://{username}:{password}@{host}:{port}/{database}
-```

docs/docs/databases/ibm-db2.mdx

@@ -1,23 +0,0 @@
----
-title: IBM DB2
-hide_title: true
-sidebar_position: 23
-version: 1
----
-
-## IBM DB2
-
-The [IBM_DB_SA](https://github.com/ibmdb/python-ibmdbsa/tree/master/ibm_db_sa) library provides a
-Python / SQLAlchemy interface to IBM Data Servers.
-
-Here's the recommended connection string:
-
-```
-db2+ibm_db://{username}:{passport}@{hostname}:{port}/{database}
-```
-
-There are two DB2 dialect versions implemented in SQLAlchemy. If you are connecting to a DB2 version without `LIMIT [n]` syntax, the recommended connection string to be able to use the SQL Lab is:
-
-```
-ibm_db_sa://{username}:{passport}@{hostname}:{port}/{database}
-```

docs/docs/databases/impala.mdx

@@ -1,16 +0,0 @@
----
-title: Apache Impala
-hide_title: true
-sidebar_position: 9
-version: 1
----
-
-## Apache Impala
-
-The recommended connector library to Apache Impala is [impyla](https://github.com/cloudera/impyla).
-
-The expected connection string is formatted as follows:
-
-```
-impala://{hostname}:{port}/{database}
-```

docs/docs/databases/installing-database-drivers.mdx

@@ -1,81 +0,0 @@
----
-title: Installing Database Drivers
-hide_title: true
-sidebar_position: 1
-version: 1
----
-
-## Install Database Drivers
-
-Superset requires a Python DB-API database driver and a SQLAlchemy
-dialect to be installed for each datastore you want to connect to.
-
-You can read more [here](/docs/databases/docker-add-drivers) about how to
-install new database drivers into your Superset configuration.
-
-### Supported Databases and Dependencies
-
-Superset does not ship bundled with connectivity to databases, except for SQLite,
-which is part of the Python standard library.
-You’ll need to install the required packages for the database you want to use as your metadata database
-as well as the packages needed to connect to the databases you want to access through Superset.
-
-Some of the recommended packages are shown below. Please refer to
-[pyproject.toml](https://github.com/apache/superset/blob/master/pyproject.toml) for the versions that
-are compatible with Superset.
-
-| Database                                                  | PyPI package                                                                       | Connection String                                                                                                                                      |
-| --------------------------------------------------------- | ---------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------ |
-| [Amazon Athena](/docs/databases/athena)                   | `pip install pyathena[pandas]` , `pip install PyAthenaJDBC`                        | `awsathena+rest://{aws_access_key_id}:{aws_secret_access_key}@athena.{region_name}.amazonaws.com/{schema_name}?s3_staging_dir={s3_staging_dir}&... `   |
-| [Apache Doris](/docs/databases/doris)                     | `pip install pydoris`                                                              | `doris://<User>:<Password>@<Host>:<Port>/<Catalog>.<Database>`                                            |
-| [Amazon DynamoDB](/docs/databases/dynamodb)               | `pip install pydynamodb`                                                           | `dynamodb://{access_key_id}:{secret_access_key}@dynamodb.{region_name}.amazonaws.com?connector=superset`                                               |
-| [Amazon Redshift](/docs/databases/redshift)               | `pip install sqlalchemy-redshift`                                                  | ` redshift+psycopg2://<userName>:<DBPassword>@<AWS End Point>:5439/<Database Name>`                                                                    |
-| [Apache Drill](/docs/databases/drill)                     | `pip install sqlalchemy-drill`                                                     | `drill+sadrill:// For JDBC drill+jdbc://`                                                                                                              |
-| [Apache Druid](/docs/databases/druid)                     | `pip install pydruid`                                                              | `druid://<User>:<password>@<Host>:<Port-default-9088>/druid/v2/sql`                                                                                    |
-| [Apache Hive](/docs/databases/hive)                       | `pip install pyhive`                                                               | `hive://hive@{hostname}:{port}/{database}`                                                                                                             |
-| [Apache Impala](/docs/databases/impala)                   | `pip install impyla`                                                               | `impala://{hostname}:{port}/{database}`                                                                                                                |
-| [Apache Kylin](/docs/databases/kylin)                     | `pip install kylinpy`                                                              | `kylin://<username>:<password>@<hostname>:<port>/<project>?<param1>=<value1>&<param2>=<value2>`                                                        |
-| [Apache Pinot](/docs/databases/pinot)                     | `pip install pinotdb`                                                              | `pinot://BROKER:5436/query?server=http://CONTROLLER:5983/`                                                                                             |
-| [Apache Solr](/docs/databases/solr)                       | `pip install sqlalchemy-solr`                                                      | `solr://{username}:{password}@{hostname}:{port}/{server_path}/{collection}`                                                                            |
-| [Apache Spark SQL](/docs/databases/spark-sql)             | `pip install pyhive`                                                               | `hive://hive@{hostname}:{port}/{database}`                                                                                                             |
-| [Ascend.io](/docs/databases/ascend)                       | `pip install impyla`                                                               | `ascend://{username}:{password}@{hostname}:{port}/{database}?auth_mechanism=PLAIN;use_ssl=true`                                                        |
-| [Azure MS SQL](/docs/databases/sql-server)                | `pip install pymssql`                                                              | `mssql+pymssql://UserName@presetSQL:TestPassword@presetSQL.database.windows.net:1433/TestSchema`                                                       |
-| [Big Query](/docs/databases/bigquery)                     | `pip install sqlalchemy-bigquery`                                                  | `bigquery://{project_id}`                                                                                                                              |
-| [ClickHouse](/docs/databases/clickhouse)                  | `pip install clickhouse-connect`                                                   | `clickhousedb://{username}:{password}@{hostname}:{port}/{database}`                                                                                    |
-| [CockroachDB](/docs/databases/cockroachdb)                | `pip install cockroachdb`                                                          | `cockroachdb://root@{hostname}:{port}/{database}?sslmode=disable`                                                                                      |
-| [Dremio](/docs/databases/dremio)                          | `pip install sqlalchemy_dremio`                                                    | `dremio://user:pwd@host:31010/`                                                                                                                        |
-| [Elasticsearch](/docs/databases/elasticsearch)            | `pip install elasticsearch-dbapi`                                                  | `elasticsearch+http://{user}:{password}@{host}:9200/`                                                                                                  |
-| [Exasol](/docs/databases/exasol)                          | `pip install sqlalchemy-exasol`                                                    | `exa+pyodbc://{username}:{password}@{hostname}:{port}/my_schema?CONNECTIONLCALL=en_US.UTF-8&driver=EXAODBC`                                            |
-| [Google Sheets](/docs/databases/google-sheets)            | `pip install shillelagh[gsheetsapi]`                                               | `gsheets://`                                                                                                                                           |
-| [Firebolt](/docs/databases/firebolt)                      | `pip install firebolt-sqlalchemy`                                                  | `firebolt://{client_id}:{client_secret}@{database}/{engine_name}?account_name={name}`                                                                  |
-| [Hologres](/docs/databases/hologres)                      | `pip install psycopg2`                                                             | `postgresql+psycopg2://<UserName>:<DBPassword>@<Database Host>/<Database Name>`                                                                        |
-| [IBM Db2](/docs/databases/ibm-db2)                        | `pip install ibm_db_sa`                                                            | `db2+ibm_db://`                                                                                                                                        |
-| [IBM Netezza Performance Server](/docs/databases/netezza) | `pip install nzalchemy`                                                            | `netezza+nzpy://<UserName>:<DBPassword>@<Database Host>/<Database Name>`                                                                               |
-| [MySQL](/docs/databases/mysql)                            | `pip install mysqlclient`                                                          | `mysql://<UserName>:<DBPassword>@<Database Host>/<Database Name>`                                                                                      |
-| [Oracle](/docs/databases/oracle)                          | `pip install cx_Oracle`                                                            | `oracle://`                                                                                                                                            |
-| [PostgreSQL](/docs/databases/postgres)                    | `pip install psycopg2`                                                             | `postgresql://<UserName>:<DBPassword>@<Database Host>/<Database Name>`                                                                                 |
-| [Presto](/docs/databases/presto)                          | `pip install pyhive`                                                               | `presto://`                                                                                                                                            |
-| [Rockset](/docs/databases/rockset)                        | `pip install rockset-sqlalchemy`                                                   | `rockset://<api_key>:@<api_server>`                                                                                                                    |
-| [SAP Hana](/docs/databases/hana)                          | `pip install hdbcli sqlalchemy-hana or pip install apache-superset[hana]`          | `hana://{username}:{password}@{host}:{port}`                                                                                                           |
-| [StarRocks](/docs/databases/starrocks)                    | `pip install starrocks`                                                            | `starrocks://<User>:<Password>@<Host>:<Port>/<Catalog>.<Database>`                                                                                     |
-| [Snowflake](/docs/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](/docs/databases/sql-server)                  | `pip install pymssql`                                                              | `mssql+pymssql://`                                                                                                                                     |
-| [Teradata](/docs/databases/teradata)                      | `pip install teradatasqlalchemy`                                                   | `teradatasql://{user}:{password}@{host}`                                                                                                               |
-| [TimescaleDB](/docs/databases/timescaledb)                | `pip install psycopg2`                                                             | `postgresql://<UserName>:<DBPassword>@<Database Host>:<Port>/<Database Name>`                                                                          |
-| [Trino](/docs/databases/trino)                            | `pip install trino`                                                                | `trino://{username}:{password}@{hostname}:{port}/{catalog}`                                                                                            |
-| [Vertica](/docs/databases/vertica)                        | `pip install sqlalchemy-vertica-python`                                            | `vertica+vertica_python://<UserName>:<DBPassword>@<Database Host>/<Database Name>`                                                                     |
-| [YugabyteDB](/docs/databases/yugabytedb)                  | `pip install psycopg2`                                                             | `postgresql://<UserName>:<DBPassword>@<Database Host>/<Database Name>`                                                                                 |
----
-
-Note that many other databases are supported, the main criteria being the existence of a functional
-SQLAlchemy dialect and Python driver. Searching for the keyword "sqlalchemy + (database name)"
-should help get you to the right place.
-
-If your database or data engine isn't on the list but a SQL interface
-exists, please file an issue on the
-[Superset GitHub repo](https://github.com/apache/superset/issues), so we can work on documenting and
-supporting it.
-
-If you'd like to build a database connector for Superset integration,
-read the [following tutorial](https://preset.io/blog/building-database-connector/).

docs/docs/databases/kusto.mdx

@@ -1,26 +0,0 @@
----
-name: Kusto
-hide_title: true
-sidebar_position: 41
-version: 2
----
-
-## Kusto
-
-The recommended connector library for Kusto is
-[sqlalchemy-kusto](https://pypi.org/project/sqlalchemy-kusto/2.0.0/)>=2.0.0.
-
-The connection string for Kusto (sql dialect) looks like this:
-
-```
-kustosql+https://{cluster_url}/{database}?azure_ad_client_id={azure_ad_client_id}&azure_ad_client_secret={azure_ad_client_secret}&azure_ad_tenant_id={azure_ad_tenant_id}&msi=False
-```
-
-The connection string for Kusto (kql dialect) looks like this:
-
-```
-kustokql+https://{cluster_url}/{database}?azure_ad_client_id={azure_ad_client_id}&azure_ad_client_secret={azure_ad_client_secret}&azure_ad_tenant_id={azure_ad_tenant_id}&msi=False
-```
-
-Make sure the user has privileges to access and use all required
-databases/tables/views.

docs/docs/databases/kylin.mdx

@@ -1,17 +0,0 @@
----
-title: Apache Kylin
-hide_title: true
-sidebar_position: 11
-version: 1
----
-
-## Apache Kylin
-
-The recommended connector library for Apache Kylin is
-[kylinpy](https://github.com/Kyligence/kylinpy).
-
-The expected connection string is formatted as follows:
-
-```
-kylin://<username>:<password>@<hostname>:<port>/<project>?<param1>=<value1>&<param2>=<value2>
-```

docs/docs/databases/meta-database.mdx

@@ -1,48 +0,0 @@
----
-title: Querying across databases
-hide_title: true
-sidebar_position: 42
-version: 1
----
-
-## Querying across databases
-
-Superset offers an experimental feature for querying across different databases. This is done via a special database called "Superset meta database" that uses the "superset://" SQLAlchemy URI. When using the database it's possible to query any table in any of the configured databases using the following syntax:
-
-```sql
-SELECT * FROM "database name.[[catalog.].schema].table name";
-```
-
-For example:
-
-```sql
-SELECT * FROM "examples.birth_names";
-```
-
-Spaces are allowed, but periods in the names must be replaced by `%2E`. Eg:
-
-```sql
-SELECT * FROM "Superset meta database.examples%2Ebirth_names";
-```
-
-The query above returns the same rows as `SELECT * FROM "examples.birth_names"`, and also shows that the meta database can query tables from any table — even itself!
-
-## Considerations
-
-Before enabling this feature, there are a few considerations that you should have in mind. First, the meta database enforces permissions on the queried tables, so users should only have access via the database to tables that they originally have access to. Nevertheless, the meta database is a new surface for potential attacks, and bugs could allow users to see data they should not.
-
-Second, there are performance considerations. The meta database will push any filtering, sorting, and limiting to the underlying databases, but any aggregations and joins will happen in memory in the process running the query. Because of this, it's recommended to run the database in async mode, so queries are executed in Celery workers, instead of the web workers. Additionally, it's possible to specify a hard limit on how many rows are returned from the underlying databases.
-
-## Enabling the meta database
-
-To enable the Superset meta database, first you need to set the `ENABLE_SUPERSET_META_DB` feature flag to true. Then, add a new database of type "Superset meta database" with the SQLAlchemy URI "superset://".
-
-If you enable DML in the meta database users will be able to run DML queries on underlying databases **as long as DML is also enabled in them**. This allows users to run queries that move data across databases.
-
-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.
-
-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"]}
-```

docs/docs/databases/mysql.mdx

@@ -1,30 +0,0 @@
----
-title: MySQL
-hide_title: true
-sidebar_position: 25
-version: 1
----
-
-## MySQL
-
-The recommended connector library for MySQL is [mysqlclient](https://pypi.org/project/mysqlclient/).
-
-Here's the connection string:
-
-```
-mysql://{username}:{password}@{host}/{database}
-```
-
-Host:
-
-- For Localhost: `localhost` or `127.0.0.1`
-- Docker running on Linux: `172.18.0.1`
-- For On Prem: IP address or Host name
-- For Docker running in OSX: `docker.for.mac.host.internal`
-  Port: `3306` by default
-
-One problem with `mysqlclient` is that it will fail to connect to newer MySQL databases using `caching_sha2_password` for authentication, since the plugin is not included in the client. In this case, you should use [mysql-connector-python](https://pypi.org/project/mysql-connector-python/) instead:
-
-```
-mysql+mysqlconnector://{username}:{password}@{host}/{database}
-```

docs/docs/databases/netezza.mdx

@@ -1,17 +0,0 @@
----
-title: IBM Netezza Performance Server
-hide_title: true
-sidebar_position: 24
-version: 1
----
-
-## IBM Netezza Performance Server
-
-The [nzalchemy](https://pypi.org/project/nzalchemy/) library provides a
-Python / SQLAlchemy interface to IBM Netezza Performance Server (aka Netezza).
-
-Here's the recommended connection string:
-
-```
-netezza+nzpy://{username}:{password}@{hostname}:{port}/{database}
-```

docs/docs/databases/ocient.mdx

@@ -1,37 +0,0 @@
----
-title: Ocient DB
-hide_title: true
-sidebar_position: 20
-version: 1
----
-
-## Ocient DB
-
-The recommended connector library for Ocient is [sqlalchemy-ocient](https://pypi.org/project/sqlalchemy-ocient).
-
-## Install the Ocient Driver
-
-```
-pip install sqlalchemy-ocient
-```
-
-## Connecting to Ocient
-
-The format of the Ocient DSN is:
-
-```shell
-ocient://user:password@[host][:port][/database][?param1=value1&...]
-```
-
-The DSN for connecting to an `exampledb` database hosted at `examplehost:4050` with TLS enabled is:
-```shell
-ocient://admin:abc123@examplehost:4050/exampledb?tls=on
-```
-
-**NOTE**: You must enter the `user` and `password` credentials.  `host` defaults to localhost,
-port defaults to 4050, database defaults to `system` and `tls` defaults
-to `unverified`.
-
-## User Access Control
-
-Make sure the user has privileges to access and use all required databases, schemas, tables, views, and warehouses, as the Ocient SQLAlchemy engine does not test for user or role rights by default.

docs/docs/databases/oracle.mdx

@@ -1,17 +0,0 @@
----
-title: Oracle
-hide_title: true
-sidebar_position: 26
-version: 1
----
-
-## Oracle
-
-The recommended connector library is
-[cx_Oracle](https://cx-oracle.readthedocs.io/en/latest/user_guide/installation.html).
-
-The connection string is formatted as follows:
-
-```
-oracle://<username>:<password>@<hostname>:<port>
-```

docs/docs/databases/pinot.mdx

@@ -1,22 +0,0 @@
----
-title: Apache Pinot
-hide_title: true
-sidebar_position: 12
-version: 1
----
-
-## Apache Pinot
-
-The recommended connector library for Apache Pinot is [pinotdb](https://pypi.org/project/pinotdb/).
-
-The expected connection string is formatted as follows:
-
-```
-pinot+http://<pinot-broker-host>:<pinot-broker-port>/query?controller=http://<pinot-controller-host>:<pinot-controller-port>/``
-```
-
-The expected connection string using username and password is formatted as follows:
-
-```
-pinot://<username>:<password>@<pinot-broker-host>:<pinot-broker-port>/query/sql?controller=http://<pinot-controller-host>:<pinot-controller-port>/verify_ssl=true``
-```

docs/docs/databases/postgres.mdx

@@ -1,42 +0,0 @@
----
-title: Postgres
-hide_title: true
-sidebar_position: 27
-version: 1
----
-
-## Postgres
-
-Note that, if you're using docker compose, the Postgres connector library [psycopg2](https://www.psycopg.org/docs/)
-comes out of the box with Superset.
-
-Postgres sample connection parameters:
-
-- **User Name**: UserName
-- **Password**: DBPassword
-- **Database Host**:
-  - For Localhost: localhost or 127.0.0.1
-  - For On Prem: IP address or Host name
-  - For AWS Endpoint
-- **Database Name**: Database Name
-- **Port**: default 5432
-
-The connection string looks like:
-
-```
-postgresql://{username}:{password}@{host}:{port}/{database}
-```
-
-You can require SSL by adding `?sslmode=require` at the end:
-
-```
-postgresql://{username}:{password}@{host}:{port}/{database}?sslmode=require
-```
-
-You can read about the other SSL modes that Postgres supports in
-[Table 31-1 from this documentation](https://www.postgresql.org/docs/9.1/libpq-ssl.html).
-
-More information about PostgreSQL connection options can be found in the
-[SQLAlchemy docs](https://docs.sqlalchemy.org/en/13/dialects/postgresql.html#module-sqlalchemy.dialects.postgresql.psycopg2)
-and the
-[PostgreSQL docs](https://www.postgresql.org/docs/9.1/libpq-connect.html#LIBPQ-PQCONNECTDBPARAMS).

docs/docs/databases/presto.mdx

@@ -1,48 +0,0 @@
----
-title: Presto
-hide_title: true
-sidebar_position: 28
-version: 1
----
-
-## Presto
-
-The [pyhive](https://pypi.org/project/PyHive/) library is the recommended way to connect to Presto through SQLAlchemy.
-
-The expected connection string is formatted as follows:
-
-```
-presto://{hostname}:{port}/{database}
-```
-
-You can pass in a username and password as well:
-
-```
-presto://{username}:{password}@{hostname}:{port}/{database}
-```
-
-Here is an example connection string with values:
-
-```
-presto://datascientist:securepassword@presto.example.com:8080/hive
-```
-
-By default Superset assumes the most recent version of Presto is being used when querying the
-datasource. If you’re using an older version of Presto, you can configure it in the extra parameter:
-
-```
-{
-    "version": "0.123"
-}
-```
-
-SSL Secure extra add json config to extra connection information.
-
-```
-   {
-     "connect_args":
-    {"protocol": "https",
-     "requests_kwargs":{"verify":false}
-  }
-}
-```

docs/docs/databases/redshift.mdx

@@ -1,66 +0,0 @@
----
-title: Amazon Redshift
-hide_title: true
-sidebar_position: 5
-version: 1
----
-
-## AWS Redshift
-
-The [sqlalchemy-redshift](https://pypi.org/project/sqlalchemy-redshift/) library is the recommended
-way to connect to Redshift through SQLAlchemy.
-
-This dialect requires either [redshift_connector](https://pypi.org/project/redshift-connector/) or [psycopg2](https://pypi.org/project/psycopg2/) to work properly.
-
-You'll need to set the following values to form the connection string:
-
-- **User Name**: userName
-- **Password**: DBPassword
-- **Database Host**: AWS Endpoint
-- **Database Name**: Database Name
-- **Port**: default 5439
-
-
-### psycopg2
-
-Here's what the SQLALCHEMY URI looks like:
-
-```
-redshift+psycopg2://<userName>:<DBPassword>@<AWS End Point>:5439/<Database Name>
-```
-
-
-### redshift_connector
-
-Here's what the SQLALCHEMY URI looks like:
-
-```
-redshift+redshift_connector://<userName>:<DBPassword>@<AWS End Point>:5439/<Database Name>
-```
-
-
-#### Using IAM-based credentials with Redshift cluster:
-
-[Amazon redshift cluster](https://docs.aws.amazon.com/redshift/latest/mgmt/working-with-clusters.html) also supports generating temporary IAM-based database user credentials.
-
-Your superset app's [IAM role should have permissions](https://docs.aws.amazon.com/redshift/latest/mgmt/generating-iam-credentials-role-permissions.html) to call the `redshift:GetClusterCredentials` operation.
-
-You have to define the following arguments in Superset's redshift database connection UI under ADVANCED --> Others --> ENGINE PARAMETERS.
-
-```
-{"connect_args":{"iam":true,"database":"<database>","cluster_identifier":"<cluster_identifier>","db_user":"<db_user>"}}
-```
-and SQLALCHEMY URI should be set to `redshift+redshift_connector://`
-
-
-#### Using IAM-based credentials with Redshift serverless:
-
-[Redshift serverless](https://docs.aws.amazon.com/redshift/latest/mgmt/serverless-whatis.html) supports connection using IAM roles.
-
-Your superset app's IAM role should have `redshift-serverless:GetCredentials` and `redshift-serverless:GetWorkgroup` permissions on Redshift serverless workgroup.
-
-You have to define the following arguments in Superset's redshift database connection UI under ADVANCED --> Others --> ENGINE PARAMETERS.
-
-```
-{"connect_args":{"iam":true,"is_serverless":true,"serverless_acct_id":"<aws account number>","serverless_work_group":"<redshift work group>","database":"<database>","user":"IAMR:<superset iam role name>"}}
-```

docs/docs/databases/risingwave.mdx

@@ -1,17 +0,0 @@
----
-title: RisingWave
-hide_title: true
-sidebar_position: 16
-version: 1
----
-
-## RisingWave
-
-The recommended connector library for RisingWave is
-[sqlalchemy-risingwave](https://github.com/risingwavelabs/sqlalchemy-risingwave).
-
-The expected connection string is formatted as follows:
-
-```
-risingwave://root@{hostname}:{port}/{database}?sslmode=disable
-```

docs/docs/databases/rockset.mdx

@@ -1,25 +0,0 @@
----
-title: Rockset
-hide_title: true
-sidebar_position: 35
-version: 1
----
-
-## Rockset
-
-The connection string for Rockset is:
-
-```
-rockset://{api key}:@{api server}
-```
-
-Get your API key from the [Rockset console](https://console.rockset.com/apikeys).
-Find your API server from the [API reference](https://rockset.com/docs/rest-api/#introduction). Omit the `https://` portion of the URL.
-
-To target to a specific virtual instance, use this URI format:
-
-```
-rockset://{api key}:@{api server}/{VI ID}
-```
-
-For more complete instructions, we recommend the [Rockset documentation](https://docs.rockset.com/apache-superset/).

docs/docs/databases/snowflake.mdx

@@ -1,68 +0,0 @@
----
-title: Snowflake
-hide_title: true
-sidebar_position: 29
-version: 1
----
-
-## Snowflake
-
-### Install Snowflake Driver
-
-Follow the steps [here](/docs/databases/docker-add-drivers) about how to
-install new database drivers when setting up Superset locally via docker compose.
-
-```
-echo "snowflake-sqlalchemy" >> ./docker/requirements-local.txt
-```
-
-The recommended connector library for Snowflake is
-[snowflake-sqlalchemy](https://pypi.org/project/snowflake-sqlalchemy/).
-
-The connection string for Snowflake looks like this:
-
-```
-snowflake://{user}:{password}@{account}.{region}/{database}?role={role}&warehouse={warehouse}
-```
-
-The schema is not necessary in the connection string, as it is defined per table/query. The role and
-warehouse can be omitted if defaults are defined for the user, i.e.
-
-```
-snowflake://{user}:{password}@{account}.{region}/{database}
-```
-
-Make sure the user has privileges to access and use all required
-databases/schemas/tables/views/warehouses, as the Snowflake SQLAlchemy engine does not test for
-user/role rights during engine creation by default. However, when pressing the “Test Connection”
-button in the Create or Edit Database dialog, user/role credentials are validated by passing
-“validate_default_parameters”: True to the connect() method during engine creation. If the user/role
-is not authorized to access the database, an error is recorded in the Superset logs.
-
-And if you want connect Snowflake with [Key Pair Authentication](https://docs.snowflake.com/en/user-guide/key-pair-auth.html#step-6-configure-the-snowflake-client-to-use-key-pair-authentication).
-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***
-
-```
-{
-     "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.
-
-```
-{
-    "auth_method": "keypair",
-    "auth_params": {
-        "privatekey_path":"Your Private Key Path",
-        "privatekey_pass":"Your Private Key Password"
-    }
-}
-```

docs/docs/databases/solr.mdx

@@ -1,17 +0,0 @@
----
-title: Apache Solr
-hide_title: true
-sidebar_position: 13
-version: 1
----
-
-## Apache Solr
-
-The [sqlalchemy-solr](https://pypi.org/project/sqlalchemy-solr/) library provides a
-Python / SQLAlchemy interface to Apache Solr.
-
-The connection string for Solr looks like this:
-
-```
-solr://{username}:{password}@{host}:{port}/{server_path}/{collection}[/?use_ssl=true|false]
-```

docs/docs/databases/spark-sql.mdx

@@ -1,16 +0,0 @@
----
-title: Apache Spark SQL
-hide_title: true
-sidebar_position: 14
-version: 1
----
-
-## Apache Spark SQL
-
-The recommended connector library for Apache Spark SQL [pyhive](https://pypi.org/project/PyHive/).
-
-The expected connection string is formatted as follows:
-
-```
-hive://hive@{hostname}:{port}/{database}
-```

docs/docs/databases/sql-server.mdx

@@ -1,23 +0,0 @@
----
-title: Microsoft SQL Server
-hide_title: true
-sidebar_position: 30
-version: 1
----
-
-## SQL Server
-
-The recommended connector library for SQL Server is [pymssql](https://github.com/pymssql/pymssql).
-
-The connection string for SQL Server looks like this:
-
-```
-mssql+pymssql://<Username>:<Password>@<Host>:<Port-default:1433>/<Database Name>/?Encrypt=yes
-```
-
-It is also possible to connect using [pyodbc](https://pypi.org/project/pyodbc) with the parameter [odbc_connect](https://docs.sqlalchemy.org/en/14/dialects/mssql.html#pass-through-exact-pyodbc-string)
-
-The connection string for SQL Server looks like this:
-```
-mssql+pyodbc:///?odbc_connect=Driver%3D%7BODBC+Driver+17+for+SQL+Server%7D%3BServer%3Dtcp%3A%3Cmy_server%3E%2C1433%3BDatabase%3Dmy_database%3BUid%3Dmy_user_name%3BPwd%3Dmy_password%3BEncrypt%3Dyes%3BConnection+Timeout%3D30
-```

docs/docs/databases/starrocks.mdx

@@ -1,26 +0,0 @@
----
-title: StarRocks
-hide_title: true
-sidebar_position: 5
-version: 1
----
-
-## StarRocks
-
-The [sqlalchemy-starrocks](https://pypi.org/project/starrocks/) library is the recommended
-way to connect to StarRocks through SQLAlchemy.
-
-You'll need to the following setting values to form the connection string:
-
-- **User**: User Name
-- **Password**: DBPassword
-- **Host**: StarRocks FE Host
-- **Catalog**: Catalog Name
-- **Database**: Database Name
-- **Port**: StarRocks FE port
-
-Here's what the connection string looks like:
-
-```
-starrocks://<User>:<Password>@<Host>:<Port>/<Catalog>.<Database>
-```

docs/docs/databases/teradata.mdx

@@ -1,36 +0,0 @@
----
-title: Teradata
-hide_title: true
-sidebar_position: 31
-version: 1
----
-
-## Teradata
-
-The recommended connector library is
-[teradatasqlalchemy](https://pypi.org/project/teradatasqlalchemy/).
-
-The connection string for Teradata looks like this:
-
-```
-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
-here: https://downloads.teradata.com/download/connectivity/odbc-driver/linux
-
-Here are the required environment variables:
-
-```
-export ODBCINI=/.../teradata/client/ODBC_64/odbc.ini
-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.

docs/docs/databases/timescaledb.mdx

@@ -1,38 +0,0 @@
----
-title: TimescaleDB
-hide_title: true
-sidebar_position: 31
-version: 1
----
-
-## TimescaleDB
-[TimescaleDB](https://www.timescale.com) is the open-source relational database for time-series and analytics to build powerful data-intensive applications.
-TimescaleDB is a PostgreSQL extension, and you can use the standard PostgreSQL connector library, [psycopg2](https://www.psycopg.org/docs/), to connect to the database.
-
-If you're using docker compose, psycopg2 comes out of the box with Superset.
-
-TimescaleDB sample connection parameters:
-
-- **User Name**: User
-- **Password**: Password
-- **Database Host**:
-  - For Localhost: localhost or 127.0.0.1
-  - For On Prem: IP address or Host name
-  - For [Timescale Cloud](https://console.cloud.timescale.com) service: Host name
-  - For [Managed Service for TimescaleDB](https://portal.managed.timescale.com) service: Host name
-- **Database Name**: Database Name
-- **Port**: default 5432 or Port number of the service
-
-The connection string looks like:
-
-```
-postgresql://{username}:{password}@{host}:{port}/{database name}
-```
-
-You can require SSL by adding `?sslmode=require` at the end (e.g. in case you use [Timescale Cloud](https://www.timescale.com/cloud)):
-
-```
-postgresql://{username}:{password}@{host}:{port}/{database name}?sslmode=require
-```
-
-[Learn more about TimescaleDB!](https://docs.timescale.com/)

docs/docs/databases/trino.mdx

@@ -1,117 +0,0 @@
----
-title: Trino
-hide_title: true
-sidebar_position: 34
-version: 1
----
-
-## Trino
-
-Supported trino version 352 and higher
-
-### Connection String
-The connection string format is as follows:
-```
-trino://{username}:{password}@{hostname}:{port}/{catalog}
-```
-
-If you are running Trino with docker on local machine, please use the following connection URL
-```
-trino://trino@host.docker.internal:8080
-```
-
-### Authentications
-#### 1. Basic Authentication
-You can provide `username`/`password` in the connection string or in the `Secure Extra` field at `Advanced / Security`
-* In Connection String
-    ```
-    trino://{username}:{password}@{hostname}:{port}/{catalog}
-    ```
-
-* In `Secure Extra` field
-    ```json
-    {
-        "auth_method": "basic",
-        "auth_params": {
-            "username": "<username>",
-            "password": "<password>"
-        }
-    }
-    ```
-
-NOTE: if both are provided, `Secure Extra` always takes higher priority.
-
-#### 2. Kerberos Authentication
-In `Secure Extra` field, config as following example:
-```json
-{
-    "auth_method": "kerberos",
-    "auth_params": {
-        "service_name": "superset",
-        "config": "/path/to/krb5.config",
-        ...
-    }
-}
-```
-
-All fields in `auth_params` are passed directly to the [`KerberosAuthentication`](https://github.com/trinodb/trino-python-client/blob/0.306.0/trino/auth.py#L40) class.
-
-NOTE: Kerberos authentication requires installing the [`trino-python-client`](https://github.com/trinodb/trino-python-client) locally with either the `all` or `kerberos` optional features, i.e., installing `trino[all]` or `trino[kerberos]` respectively.
-
-#### 3. Certificate Authentication
-In `Secure Extra` field, config as following example:
-```json
-{
-    "auth_method": "certificate",
-    "auth_params": {
-        "cert": "/path/to/cert.pem",
-        "key": "/path/to/key.pem"
-    }
-}
-```
-
-All fields in `auth_params` are passed directly to the [`CertificateAuthentication`](https://github.com/trinodb/trino-python-client/blob/0.315.0/trino/auth.py#L416) class.
-
-#### 4. JWT Authentication
-Config `auth_method` and provide token in `Secure Extra` field
-```json
-{
-    "auth_method": "jwt",
-    "auth_params": {
-        "token": "<your-jwt-token>"
-    }
-}
-```
-
-#### 5. Custom Authentication
-To use custom authentication, first you need to add it into
-`ALLOWED_EXTRA_AUTHENTICATIONS` allow list in Superset config file:
-```python
-from your.module import AuthClass
-from another.extra import auth_method
-
-ALLOWED_EXTRA_AUTHENTICATIONS: Dict[str, Dict[str, Callable[..., Any]]] = {
-    "trino": {
-        "custom_auth": AuthClass,
-        "another_auth_method": auth_method,
-    },
-}
-```
-
-Then in `Secure Extra` field:
-```json
-{
-    "auth_method": "custom_auth",
-    "auth_params": {
-        ...
-    }
-}
-```
-
-You can also use custom authentication by providing reference to your `trino.auth.Authentication` class
-or factory function (which returns an `Authentication` instance) to `auth_method`.
-
-All fields in `auth_params` are passed directly to your class/function.
-
-**Reference**:
-* [Trino-Superset-Podcast](https://trino.io/episodes/12.html)

docs/docs/databases/vertica.mdx

@@ -1,31 +0,0 @@
----
-title: Vertica
-hide_title: true
-sidebar_position: 32
-version: 1
----
-
-## Vertica
-
-The recommended connector library is
-[sqlalchemy-vertica-python](https://pypi.org/project/sqlalchemy-vertica-python/). The
-[Vertica](http://www.vertica.com/) connection parameters are:
-
-- **User Name:** UserName
-- **Password:** DBPassword
-- **Database Host:**
-  - For Localhost : localhost or 127.0.0.1
-  - For On Prem : IP address or Host name
-  - For Cloud: IP Address or Host Name
-- **Database Name:** Database Name
-- **Port:** default 5433
-
-The connection string is formatted as follows:
-
-```
-vertica+vertica_python://{username}:{password}@{host}/{database}
-```
-
-Other parameters:
-
-- Load Balancer - Backup Host

docs/docs/databases/yugabytedb.mdx

@@ -1,20 +0,0 @@
----
-title: YugabyteDB
-hide_title: true
-sidebar_position: 38
-version: 1
----
-
-## YugabyteDB
-
-[YugabyteDB](https://www.yugabyte.com/) is a distributed SQL database built on top of PostgreSQL.
-
-Note that, if you're using docker compose, the
-Postgres connector library [psycopg2](https://www.psycopg.org/docs/)
-comes out of the box with Superset.
-
-The connection string looks like:
-
-```
-postgresql://{username}:{password}@{host}:{port}/{database}
-```

docs/docs/faq.mdx

@@ -159,7 +159,7 @@ table afterwards to configure the Columns tab, check the appropriate boxes and s
 
 To clarify, the database backend is an OLTP database used by Superset to store its internal
 information like your list of users and dashboard definitions. While Superset supports a
-[variety of databases as data *sources*](/docs/databases/installing-database-drivers/),
+[variety of databases as data *sources*](/docs/configuration/databases#installing-database-drivers),
 only a few database engines are supported for use as the OLTP backend / metadata store.
 
 Superset is tested using MySQL, PostgreSQL, and SQLite backends. It’s recommended you install
@@ -189,7 +189,7 @@ Metadata attribute using the `label_colors` key.
 
 ## Does Superset work with [insert database engine here]?
 
-The [Connecting to Databases section](/docs/databases/installing-database-drivers) provides the best
+The [Connecting to Databases section](/docs/configuration/databases) provides the best
 overview for supported databases. Database engines not listed on that page may work too. We rely on
 the community to contribute to this knowledge base.
 

docs/docs/installation/docker-compose.mdx

@@ -5,23 +5,29 @@ sidebar_position: 3
 version: 1
 ---
 
-## Using Docker Compose
+import useBaseUrl from "@docusaurus/useBaseUrl";
 
-**DO NOT USE THIS FOR PRODUCTION!**
+# Using Docker Compose
 
-The fastest way to try Superset locally is using Docker Compose on a Linux or Mac OSX
-computer. Superset does not have official support for Windows. It's also the easiest
-way to launch a fully functioning **development environment** quickly.
+
+<img src={useBaseUrl("/img/docker-compose.webp" )} width="150" />
+<br /><br />
 
 :::caution
 Since `docker-compose` is primarily designed to run a set of containers on **a single host**
-and can't credibly support **high availability** as a result, we do not support nor recommend
+and can't support requirements for **high availability**, we do not support nor recommend
 using our `docker-compose` constructs to support production-type use-cases. For single host
 environments, we recommend using [minikube](https://minikube.sigs.k8s.io/docs/start/) along
 our [installing on k8s](https://superset.apache.org/docs/installation/running-on-kubernetes)
 documentation.
 :::
 
+
+As mentioned in our [quickstart guidee](/docs/quickstart), The fastest way to try
+Superset locally is using Docker Compose on a Linux or Mac OSX
+computer. Superset does not have official support for Windows. It's also the easiest
+way to launch a fully functioning **development environment** quickly.
+
 Note that there are 3 major ways we support to run docker-compose:
 1. **docker-compose.yml:** for interactive development, where we mount your local folder with the
   frontend/backend files that you can edit and experience the changes you
@@ -37,26 +43,26 @@ Note that there are 3 major ways we support to run docker-compose:
 
 More on these two approaches after setting up the requirements for either.
 
-### Requirements
+## Requirements
 
 Note that this documentation assumes that you have [Docker](https://www.docker.com),
 [docker-compose](https://docs.docker.com/compose/), and
 [git](https://git-scm.com/) installed.
 
 
-### 1. Clone Superset's GitHub repository
+## 1. Clone Superset's GitHub repository
 
 [Clone Superset's repo](https://github.com/apache/superset) in your terminal with the
 following command:
 
 ```bash
-git clone https://github.com/apache/superset.git
+git clone --depth=1  https://github.com/apache/superset.git
 ```
 
 Once that command completes successfully, you should see a new `superset` folder in your
 current directory.
 
-### 2. Launch Superset Through Docker Compose
+## 2. Launch Superset Through Docker Compose
 
 First let's assume you're familiar with docker-compose mechanics. Here we'll refer generally
 to `docker compose up` even though in some cases you may want to force a check for newer remote
@@ -86,13 +92,13 @@ perform those operations. In this case, we recommend you set the env var
 Simply trigger `npm i && npm run dev`, this should be MUCH faster.
 :::
 
-### Option #2 - build an immutable image from the local branch
+### Option #2 - build a set of immutable images from the local branch
 
 ```bash
 docker compose -f docker-compose-non-dev.yml up
 ```
 
-### Option #3 - pull and build a release image from docker-hub
+### Option #3 - boot up an official release
 
 ```bash
 export TAG=3.1.1
@@ -103,7 +109,7 @@ Here various release tags, github SHA, and latest `master` can be referenced by
 Refer to the docker-related documentation to learn more about existing tags you can point to
 from Docker Hub.
 
-## General tips & configuration
+## docker-compose tips & configuration
 
 :::caution
 All of the content belonging to a Superset instance - charts, dashboards, users, etc. - is stored in
@@ -119,7 +125,7 @@ You should see a wall of logging output from the containers being launched on yo
 this output slows, you should have a running instance of Superset on your local machine!  To avoid
 the wall of text on future runs, add the `-d` option to the end of the `docker compose up` command.
 
-#### Configuring Further
+### Configuring Further
 
 The following is for users who want to configure how Superset runs in Docker Compose; otherwise, you
 can skip to the next section.
@@ -170,7 +176,7 @@ To disable the Scarf telemetry pixel, set the `SCARF_ANALYTICS` environment vari
 your terminal and/or in your `docker/.env` file.
 :::
 
-### 3. Log in to Superset
+## 3. Log in to Superset
 
 Your local Superset instance also includes a Postgres server to store your data and is already
 pre-loaded with some example datasets that ship with Superset. You can access Superset now via your
@@ -187,7 +193,7 @@ username: admin
 password: admin
 ```
 
-### 4. Connecting Superset to your local database instance
+## 4. Connecting Superset to your local database instance
 
 When running Superset using `docker` or `docker compose` it runs in its own docker container, as if
 the Superset was running in a separate machine entirely. Therefore attempts to connect to your local

docs/docs/installation/kubernetes.mdx

@@ -5,12 +5,18 @@ sidebar_position: 1
 version: 1
 ---
 
-## Installing on Kubernetes
+import useBaseUrl from "@docusaurus/useBaseUrl";
+
+# Installing on Kubernetes
+
+
+<img src={useBaseUrl("/img/k8s.png" )} width="150" />
+<br /><br />
 
 Running Superset on Kubernetes is supported with the provided [Helm](https://helm.sh/) chart
 found in the official [Superset helm repository](https://apache.github.io/superset/index.yaml).
 
-### Prerequisites
+## Prerequisites
 
 - A Kubernetes cluster
 - Helm installed
@@ -22,7 +28,7 @@ and works fantastically well with the Helm chart referenced here.
 :::
 
 
-### Running
+## Running
 
 1. Add the Superset helm repository
 
@@ -89,9 +95,9 @@ Depending how you configured external access, the URL will vary. Once you've ide
 - user: `admin`
 - password: `admin`
 
-### Important settings
+## Important settings
 
-#### Security settings
+### Security settings
 
 Default security settings and passwords are included but you **MUST** update them to run `prod` instances, in particular:
 
@@ -135,7 +141,7 @@ Superset uses [Scarf Gateway](https://about.scarf.sh/scarf-gateway) to collect t
 To opt-out of this data collection in your Helm-based installation, edit the `repository:` line in your `helm/superset/values.yaml` file, replacing `apachesuperset.docker.scarf.sh/apache/superset` with `apache/superset` to pull the image directly from Docker Hub.
 :::
 
-#### Dependencies
+### Dependencies
 
 Install additional packages and do any other bootstrap configuration in the bootstrap script.
 For production clusters it's recommended to build own image with this step done in CI.
@@ -145,7 +151,7 @@ For production clusters it's recommended to build own image with this step done
 Superset requires a Python DB-API database driver and a SQLAlchemy
 dialect to be installed for each datastore you want to connect to.
 
-See [Install Database Drivers](/docs/databases/installing-database-drivers) for more information.
+See [Install Database Drivers](/docs/configuration/databases) for more information.
 
 :::
 
@@ -161,7 +167,7 @@ bootstrapScript: |
   if [ ! -f ~/bootstrap ]; then echo "Running Superset with uid {{ .Values.runAsUser }}" > ~/bootstrap; fi
 ```
 
-#### superset_config.py
+### superset_config.py
 
 The default `superset_config.py` is fairly minimal and you will very likely need to extend it. This is done by specifying one or more key/value entries in `configOverrides`, e.g.:
 
@@ -181,7 +187,7 @@ The entire `superset_config.py` will be installed as a secret, so it is safe to
 
 Full python files can be provided by running `helm upgrade --install --values my-values.yaml --set-file configOverrides.oauth=set_oauth.py`
 
-#### Environment Variables
+### Environment Variables
 
 Those can be passed as key/values either with `extraEnv` or `extraSecretEnv` if they're sensitive. They can then be referenced from `superset_config.py` using e.g. `os.environ.get("VAR")`.
 
@@ -206,7 +212,7 @@ configOverrides:
     SMTP_PASSWORD = os.getenv("SMTP_PASSWORD","superset")
 ```
 
-#### System packages
+### System packages
 
 If new system packages are required, they can be installed before application startup by overriding the container's `command`, e.g.:
 
@@ -225,7 +231,7 @@ supersetWorker:
       . {{ .Values.configMountPath }}/superset_bootstrap.sh; celery --app=superset.tasks.celery_app:app worker
 ```
 
-#### Data sources
+### Data sources
 
 Data source definitions can be automatically declared by providing key/value yaml definitions in `extraConfigs`:
 
@@ -246,9 +252,9 @@ extraConfigs:
 
 Those will also be mounted as secrets and can include sensitive parameters.
 
-### Configuration Examples
+## Configuration Examples
 
-#### Setting up OAuth
+### Setting up OAuth
 
 :::note
 
@@ -302,11 +308,11 @@ configOverrides:
     AUTH_USER_REGISTRATION_ROLE = "Admin"
 ```
 
-#### Enable Alerts and Reports
+### Enable Alerts and Reports
 
 For this, as per the [Alerts and Reports doc](/docs/configuration/alerts-reports), you will need to:
 
-##### Install a supported webdriver in the Celery worker
+#### Install a supported webdriver in the Celery worker
 
 This is done either by using a custom image that has the webdriver pre-installed, or installing at startup time by overriding the `command`. Here's a working example for `chromedriver`:
 
@@ -335,7 +341,7 @@ supersetWorker:
       . {{ .Values.configMountPath }}/superset_bootstrap.sh; celery --app=superset.tasks.celery_app:app worker
 ```
 
-##### Run the Celery beat
+#### Run the Celery beat
 
 This pod will trigger the scheduled tasks configured in the alerts and reports UI section:
 
@@ -344,7 +350,7 @@ supersetCeleryBeat:
   enabled: true
 ```
 
-##### Configure the appropriate Celery jobs and SMTP/Slack settings
+#### Configure the appropriate Celery jobs and SMTP/Slack settings
 
 ```yaml
 extraEnv:
@@ -428,7 +434,7 @@ configOverrides:
         "--disable-extensions",
     ]
 ```
-#### Load the Examples data and dashboards
+### Load the Examples data and dashboards
 If you are trying Superset out and want some data and dashboards to explore, you can load some examples by creating a `my_values.yaml` and deploying it as described above in the **Configure your setting overrides** step of the **Running** section.
 To load the examples, add the following to the `my_values.yaml` file:
 ```yaml

docs/docs/installation/pypi.mdx

@@ -5,11 +5,16 @@ sidebar_position: 2
 version: 1
 ---
 
-## Installing Superset from PyPI
+import useBaseUrl from "@docusaurus/useBaseUrl";
+
+# Installing Superset from PyPI
+
+<img src={useBaseUrl("/img/pypi.png" )} width="150" />
+<br /><br />
 
 This page describes how to install Superset using the `apache-superset` package [published on PyPI](https://pypi.org/project/apache-superset/).
 
-### OS Dependencies
+## OS Dependencies
 
 Superset stores database connection information in its metadata database. For that purpose, we use
 the cryptography Python library to encrypt connection passwords. Unfortunately, this library has OS
@@ -91,7 +96,7 @@ export CFLAGS="-I$(brew --prefix openssl)/include"
 
 These will now be available when pip installing requirements.
 
-### Python Virtual Environment
+## Python Virtual Environment
 
 We highly recommend installing Superset inside of a virtual environment. Python ships with
 `virtualenv` out of the box. If you're using [pyenv](https://github.com/pyenv/pyenv), you can install [pyenv-virtualenv](https://github.com/pyenv/pyenv-virtualenv). Or you can install it with `pip`:

docs/docs/installation/upgrading-superset.mdx

@@ -5,9 +5,9 @@ sidebar_position: 4
 version: 1
 ---
 
-## Upgrading Superset
+# Upgrading Superset
 
-### Docker Compose
+## Docker Compose
 
 First make sure to wind down the running containers in Docker Compose:
 
@@ -27,12 +27,19 @@ Then, restart the containers and any changed Docker images will be automatically
 docker compose up
 ```
 
-### Updating Superset Manually
+## Updating Superset Manually
 
 To upgrade superset in a native installation, run the following commands:
 
 ```bash
 pip install apache-superset --upgrade
+```
+
+## Upgrading the Metadata Database
+
+Migrate the metadata database by running:
+
+```bash
 superset db upgrade
 superset init
 ```

docs/docs/intro.mdx

@@ -1,65 +0,0 @@
----
-title: Introduction
-hide_title: true
-sidebar_position: 1
----
-
-## What is Apache Superset?
-
-Apache Superset is a modern, enterprise-ready business intelligence web application. It
-is fast, lightweight, intuitive, and loaded with options that make it easy for users of all skill
-sets to explore and visualize their data, from simple pie charts to highly detailed deck.gl
-geospatial charts.
-
-Here are a **few different ways you can get started with Superset**:
-
-- Try a [Quickstart deployment](/docs/quickstart), powered by [Docker Compose](https://docs.docker.com/compose/)
-- Install Superset [from PyPI](/docs/installation/pypi/)
-- Deploy Superset [with Kubernetes](/docs/installation/kubernetes)
-- Download the [source code from Apache Foundation's website](https://dist.apache.org/repos/dist/release/superset/)
-
-#### Video Overview
-
-https://user-images.githubusercontent.com/64562059/234390129-321d4f35-cb4b-45e8-89d9-20ae292f34fc.mp4
-
-#### Features
-
-Superset provides:
-
-- An intuitive interface for visualizing datasets and crafting interactive dashboards
-- A wide array of beautiful visualizations to showcase your data
-- Code-free visualization builder to extract and present datasets
-- A world-class SQL IDE for preparing data for visualization, including a rich metadata browser
-- A lightweight semantic layer which empowers data analysts to quickly define custom dimensions and metrics
-- Out-of-the-box support for [most SQL-speaking databases](/docs/databases/installing-database-drivers/)
-- Seamless, in-memory asynchronous caching and queries
-- An extensible security model that allows configuration of very intricate rules on who can access which product features and datasets.
-- Integration with major authentication backends (database, OpenID, LDAP, OAuth, REMOTE_USER, etc)
-- The ability to add custom visualization plugins
-- An API for programmatic customization
-- A cloud-native architecture designed from the ground up for scale
-
-#### Backend Technology
-
-Superset is cloud-native and designed to be highly available. It was designed to scale out to large,
-distributed environments and works very well inside containers. While you can easily test drive
-Superset on a modest setup or simply on your laptop, there’s virtually no limit around scaling out
-the platform.
-
-Superset is also cloud-native in the sense that it is flexible and lets you choose the:
-
-- Web server (Gunicorn, Nginx, Apache),
-- Metadata database engine (PostgreSQL, MySQL, MariaDB),
-- Message queue (Celery, Redis, RabbitMQ, SQS, etc.),
-- Results backend (Redis, S3, Memcached, etc.),
-- Caching layer (Redis, Memcached, etc.)
-
-Superset also works well with [event-logging](/docs/configuration/event-logging/)
-services like StatsD, NewRelic, and DataDog.
-
-Superset is currently run at scale at many companies. For example, Superset is run in Airbnb’s
-production environment inside Kubernetes and serves 600+ daily active users viewing over 100K charts
-a day.
-
-You can find a partial list of industries and companies embracing Superset
-[on this page in GitHub](https://github.com/apache/superset/blob/master/RESOURCES/INTHEWILD.md).

docs/docs/quickstart.mdx

@@ -61,7 +61,7 @@ processes by running Docker Compose `stop` command. By doing so, you can avoid d
 
 From this point on, you can head on to:
 - [Create your first Dashboard](/docs/using-superset/creating-your-first-dashboard)
-- [Connect to a Database](/docs/databases/installing-database-drivers)
+- [Connect to a Database](/docs/configuration/databases)
 - [Using Docker Compose](/docs/installation/docker-compose)
 - [Configure Superset](/docs/configuration/configuring-superset/)
 - [Installing on Kubernetes](/docs/installation/kubernetes/)

docs/docusaurus.config.js

@@ -80,7 +80,7 @@ const config = {
             from: '/gallery.html',
           },
           {
-            to: '/docs/databases/druid',
+            to: '/docs/configuration/databases',
             from: '/druid.html',
           },
           {
@@ -128,7 +128,7 @@ const config = {
             from: '/docs/contributing/contribution-page',
           },
           {
-            to: '/docs/databases/yugabytedb',
+            to: '/docs/configuration/databases',
             from: '/docs/databases/yugabyte/',
           },
           {
@@ -231,6 +231,7 @@ const config = {
         items: [
           {
             label: 'Documentation',
+            to: '/docs/intro',
             items: [
               {
                 label: 'Getting Started',
@@ -244,6 +245,7 @@ const config = {
           },
           {
             label: 'Community',
+            to: '/community',
             items: [
               {
                 label: 'Resources',

docs/package.json

@@ -5,8 +5,9 @@
   "license": "Apache-2.0",
   "scripts": {
     "docusaurus": "docusaurus",
-    "start": "docusaurus start",
-    "build": "docusaurus build",
+    "_init": "cp ../README.md docs/intro.md",
+    "start": "npm run _init && docusaurus start",
+    "build": "npm run _init && docusaurus build",
     "swizzle": "docusaurus swizzle",
     "deploy": "docusaurus deploy",
     "clear": "docusaurus clear",
@@ -30,7 +31,7 @@
     "@svgr/webpack": "^8.1.0",
     "antd": "^4.19.3",
     "buffer": "^6.0.3",
-    "clsx": "^2.1.0",
+    "clsx": "^2.1.1",
     "docusaurus-plugin-less": "^2.0.2",
     "file-loader": "^6.2.0",
     "less": "^4.2.0",

docs/sidebars.js

@@ -60,14 +60,6 @@ const sidebars = {
         dirName: 'using-superset',
       }]
     },
-    {
-      type: 'category',
-      label: 'Databases',
-      items: [{
-        type: 'autogenerated',
-        dirName: 'databases',
-      }]
-    },
     {
       type: 'category',
       label: 'Contributing',

docs/src/pages/index.tsx

@@ -16,6 +16,7 @@
  * specific language governing permissions and limitations
  * under the License.
  */
+// @ts-nocheck
 import React, { useRef, useState, useEffect } from 'react';
 import Layout from '@theme/Layout';
 import Link from '@docusaurus/Link';
@@ -28,6 +29,8 @@ import SectionHeader from '../components/SectionHeader';
 import BlurredSection from '../components/BlurredSection';
 import '../styles/main.less';
 
+// @ts-ignore
+
 const features = [
   {
     image: 'powerful-yet-easy.jpg',
@@ -644,7 +647,7 @@ export default function Home(): JSX.Element {
               </div>
             </Carousel>
             <video autoPlay muted controls loop>
-              <source src="https://user-images.githubusercontent.com/64562059/234390129-321d4f35-cb4b-45e8-89d9-20ae292f34fc.mp4" type="video/mp4" />
+              <source src="https://superset.staged.apache.org/superset-video-4k.mp4" type="video/mp4" />
             </video>
           </StyledSliderSection>
           <StyledKeyFeatures>
@@ -731,7 +734,7 @@ export default function Home(): JSX.Element {
             </div>
             <span className="database-sub">
               ...and many other{' '}
-              <a href="/docs/databases/installing-database-drivers">
+              <a href="/docs/configuration/databases#installing-database-drivers">
                 compatible databases
               </a>
             </span>

docs/src/styles/custom.css

@@ -39,6 +39,12 @@
   font-weight: 700;
   font-style: bold;
 }
+
+/* Hiding ugly linkout icons */
+ul.dropdown__menu svg {
+  display: none;
+}
+
 :root {
   --ifm-color-primary: #20a7c9;
   --ifm-color-primary-dark: #1985a0;
@@ -60,4 +66,6 @@
   --ifm-border-color: #ededed;
   --ifm-primary-text: #484848;
   --ifm-secondary-text: #5f5f5f;
+  --ifm-code-padding-vertical: 3px;
+  --ifm-code-padding-horizontal: 5px;
 }

docs/static/.htaccess

@@ -23,3 +23,45 @@ RewriteCond %{HTTP_HOST} ^superset.incubator.apache.org$ [NC]
 RewriteRule ^(.*)$ https://superset.apache.org/$1 [R=301,L]
 
 Header set Content-Security-Policy "default-src data: blob: 'self' *.apache.org *.githubusercontent.com *.scarf.sh *.googleapis.com *.github.com *.algolia.net *.algolianet.com 'unsafe-inline' 'unsafe-eval'; frame-src *; frame-ancestors 'self' *.google.com https://sidebar.bugherd.com; form-action 'self'; worker-src blob:; img-src 'self' blob: data: https:; font-src 'self'; object-src 'none'"
+
+# REDIRECTS
+
+RewriteEngine On
+
+RewriteRule ^installation\.html$ /docs/installation/docker-compose [R=301,L]
+RewriteRule ^tutorials\.html$ /docs/intro [R=301,L]
+RewriteRule ^admintutorial\.html$ /docs/using-superset/creating-your-first-dashboard [R=301,L]
+RewriteRule ^usertutorial\.html$ /docs/using-superset/creating-your-first-dashboard [R=301,L]
+RewriteRule ^security\.html$ /docs/security/ [R=301,L]
+RewriteRule ^sqllab\.html$ /docs/configuration/sql-templating [R=301,L]
+RewriteRule ^gallery\.html$ /docs/intro [R=301,L]
+RewriteRule ^druid\.html$ /docs/configuration/databases [R=301,L]
+RewriteRule ^misc\.html$ /docs/configuration/country-map-tools [R=301,L]
+RewriteRule ^visualization\.html$ /docs/configuration/country-map-tools [R=301,L]
+RewriteRule ^videos\.html$ /docs/faq [R=301,L]
+RewriteRule ^faq\.html$ /docs/faq [R=301,L]
+RewriteRule ^tutorial\.html$ /docs/using-superset/creating-your-first-dashboard [R=301,L]
+RewriteRule ^docs/creating-charts-dashboards/first-dashboard$ /docs/using-superset/creating-your-first-dashboard [R=301,L]
+RewriteRule ^docs/rest-api$ /docs/api [R=301,L]
+RewriteRule ^docs/installation/email-reports$ /docs/configuration/alerts-reports [R=301,L]
+RewriteRule ^docs/roadmap$ /docs/intro [R=301,L]
+RewriteRule ^docs/contributing/contribution-guidelines$ /docs/contributing/ [R=301,L]
+RewriteRule ^docs/contributing/contribution-page$ /docs/contributing/ [R=301,L]
+RewriteRule ^docs/databases/yugabyte/$ /docs/configuration/databases [R=301,L]
+RewriteRule ^docs/frequently-asked-questions$ /docs/faq [R=301,L]
+RewriteRule ^docs/installation/running-on-kubernetes/$ /docs/installation/kubernetes [R=301,L]
+RewriteRule ^docs/contributing/testing-locally/$ /docs/contributing/howtos [R=301,L]
+RewriteRule ^docs/creating-charts-dashboards/creating-your-first-dashboard/$ /docs/using-superset/creating-your-first-dashboard [R=301,L]
+RewriteRule ^docs/creating-charts-dashboards/exploring-data/$ /docs/using-superset/creating-your-first-dashboard [R=301,L]
+RewriteRule ^docs/installation/installing-superset-using-docker-compose/$ /docs/installation/docker-compose [R=301,L]
+RewriteRule ^docs/contributing/creating-viz-plugins/$ /docs/contributing/howtos [R=301,L]
+RewriteRule ^docs/installation/$ /docs/installation/kubernetes [R=301,L]
+RewriteRule ^docs/installation/installing-superset-from-pypi/$ /docs/installation/pypi [R=301,L]
+RewriteRule ^docs/installation/configuring-superset/$ /docs/configuration/configuring-superset [R=301,L]
+RewriteRule ^docs/installation/cache/$ /docs/configuration/cache [R=301,L]
+RewriteRule ^docs/installation/async-queries-celery/$ /docs/configuration/async-queries-celery [R=301,L]
+RewriteRule ^docs/installation/event-logging/$ /docs/configuration/event-logging [R=301,L]
+
+RewriteRule ^docs/databases.*$ /docs/configuration/databases [R=301,L]
+
+RewriteRule ^docs/configuration/setup-ssh-tunneling$ /docs/configuration/networking-settings [R=301,L]

docs/static/img/databases/ibm-db2.svg

@@ -0,0 +1,51 @@
+<svg width="600" height="263" viewBox="0 0 600 263" fill="none" xmlns="http://www.w3.org/2000/svg">
+<g clip-path="url(#clip0)">
+<path fill-rule="evenodd" clip-rule="evenodd" d="M0.0488281 224.047H300.809V38.0058H0.0488281V224.047Z" fill="#1B1918"/>
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