Mike Bridge e4e0b4b144 fix(migration): MySQL downgrade FK + AUTO_INCREMENT (sc-105349)
Two MySQL-only failures in the downgrade path, found by running the
full migration history against a fresh MySQL 8 container:

1. ``MySQLdb.OperationalError: (1553, "Cannot drop index 'PRIMARY':
   needed in a foreign key constraint")``. InnoDB uses the composite
   PK index to back the FK on the leftmost column. The downgrade
   tried to drop the composite PK before dropping the FKs, orphaning
   the FK's backing index. PostgreSQL and SQLite create separate
   indexes for FK columns and don't trip on this.

2. ``Field 'id' doesn't have a default value`` on subsequent INSERT.
   ``sa.Identity(always=False)`` only emits ``AUTO_INCREMENT`` on
   MySQL when the column is created with ``primary_key=True`` — our
   portable path adds the column first then creates the PK separately,
   so MySQL leaves the column without auto-generation. Existing rows
   would all collide on id=0; future inserts fail because no default.
   Postgres' ``GENERATED BY DEFAULT AS IDENTITY`` and SQLite's
   ``INTEGER PRIMARY KEY`` rowid alias don't have this gap.

Fix: extract ``_downgrade_mysql_table()`` that emits the canonical
MySQL idiom — drop FKs, then a single ALTER combining
``DROP PRIMARY KEY, ADD COLUMN id INT NOT NULL AUTO_INCREMENT,
ADD PRIMARY KEY (id)`` (which backfills existing rows with sequential
ids and preserves AUTO_INCREMENT), restore the redundant UNIQUE on
the 2 tables that originally had it, and re-add the FKs with their
original names. Postgres and SQLite keep the existing portable
``batch_alter_table`` path.

Raw SQL is unavoidable for the combined-ALTER form; per the
constitution it's allowed for dialect-specific DDL with no SQLA
equivalent, with triple-quoted strings for legibility.

Verified end-to-end: upgrade → downgrade → upgrade against a fresh
MySQL 8 container with INSERT-without-id sanity check showing the
restored ``id`` column auto-increments correctly.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-28 13:39:09 -06:00

Superset

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A modern, enterprise-ready business intelligence web application.

Documentation

  • User Guide — For analysts and business users. Explore data, build charts, create dashboards, and connect databases.
  • Administrator Guide — Install, configure, and operate Superset. Covers security, scaling, and database drivers.
  • Developer Guide — Contribute to Superset or build on its REST API and extension framework.

Why Superset? | Supported Databases | Release Notes | Get Involved | Resources | Organizations Using Superset

Why Superset?

Superset is a modern data exploration and data visualization platform. Superset can replace or augment proprietary business intelligence tools for many teams. Superset integrates well with a variety of data sources.

Superset provides:

  • A no-code interface for building charts quickly
  • A powerful, web-based SQL Editor for advanced querying
  • A lightweight semantic layer for quickly defining custom dimensions and metrics
  • Out of the box support for nearly any SQL database or data engine
  • A wide array of beautiful visualizations to showcase your data, ranging from simple bar charts to geospatial visualizations
  • Lightweight, configurable caching layer to help ease database load
  • Highly extensible security roles and authentication options
  • An API for programmatic customization
  • A cloud-native architecture designed from the ground up for scale

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Video Overview

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Large Gallery of Visualizations


Craft Beautiful, Dynamic Dashboards


No-Code Chart Builder


Powerful SQL Editor


Supported Databases

Superset can query data from any SQL-speaking datastore or data engine (Presto, Trino, Athena, and more) that has a Python DB-API driver and a SQLAlchemy dialect.

Here are some of the major database solutions that are supported:

Amazon Athena   Amazon DynamoDB   Amazon Redshift   Apache Doris   Apache Drill   Apache Druid   Apache Hive   Apache Impala   Apache Kylin   Apache Pinot   Apache Solr   Apache Spark SQL   Ascend   Aurora MySQL (Data API)   Aurora PostgreSQL (Data API)   Azure Data Explorer   Azure Synapse   ClickHouse   Cloudflare D1   CockroachDB   Couchbase   CrateDB   Databend   Databricks   Denodo   Dremio   DuckDB   Elasticsearch   Exasol   Firebird   Firebolt   Google BigQuery   Google Sheets   Greenplum   Hologres   IBM Db2   IBM Netezza Performance Server   MariaDB   Microsoft SQL Server   MonetDB   MongoDB   MotherDuck   OceanBase   Oracle   Presto   RisingWave   SAP HANA   SAP Sybase   Shillelagh   SingleStore   Snowflake   SQLite   StarRocks   Superset meta database   TDengine   Teradata   TimescaleDB   Trino   Vertica   YDB   YugabyteDB

A more comprehensive list of supported databases along with the configuration instructions can be found here.

Want to add support for your datastore or data engine? Read more here about the technical requirements.

Installation and Configuration

Try out Superset's quickstart guide or learn about the options for production deployments.

Get Involved

Contributor Guide

Interested in contributing? Check out our Developer Guide to find resources around contributing along with a detailed guide on how to set up a development environment.

Resources

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