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[SIP-84] Case-insensitive handling of datasets' column names #19773
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Hi @rumbin! Sorry, first time doing this. Are there any established examples/guidelines that I can look at, so to work on the sections left of the SIP? |
@agusfigueroa-htg same here ;-). #5602 might help, I guess. |
@rumbin @villebro sorry, this took me longer than expected. First iteration can be found below :) New or Changed Public Interfaces We will need:
New dependencies I don't see the need for any new packages. Migration Plan and Compatibility As this is metadata to be added at the column level, I don't see any URLs or references that may break. We will need though for visualizations to refer to "verbose_name", and for filters and calculations to the treated "column-name", by default lowercase and eventually modified by the check mark I stated in (2). |
Noticed there were two SIP-82s, I've renumbered this one to SIP-84 |
@rumbin thanks for this SIP. If it's ready for official discussion, in a lead-up to voting, please post it to the [email protected] email list as a [DISCUSS] thread. If you need help navigating those waters, say the word and I'll be happy to help. |
Closing this due to apparent lack of interest/activity here or on the mailing list. We'll also consider the SIP/proposal process closed as well. If you want to rekindle this proposal, please re-open this Issue, and send a new [DISCUSS] thread to the dev@ mailing list. Thank you! |
This is a big problem for us. We have some physical tables and some virtual tables that exist on the same dashboard connected to snowflake. There appears to be no way to force the column names in the virtual tables to lowercase and as a result the filters down apply to charts on the dashboard referencing the same underlying data but through a different structure. |
@JohnDietrich-Pepper this issue should be fixed as of #24471 and especially #24982 (this makes the change backwards compatible). Please let me know if you need help implementing the changes in those PRs. |
!!! warning "This document is still WIP; review of @villebro, @agusfigueroa-htg is required."
[SIP-84] Case-insensitive handling of datasets' column names
Motivation
The default case (upper/lower) and case sensitivity of object names (schemas, tables, columns,...) is handled very differently in the various DSMSes that are supported by Superset.
E.g., Postgres interprets unquoted column names as lowercase while Oracle and Snowflake treat them as UPPERCASE.
Superset is currently not consistently treating the case of column names. As a result, virtual datasets of an UPPERCASE DB like Snowflake are represented in UPPERCASE, while physical datasets of these DBs have lowercase column names in Superset.
See #18085 for more details and discussion on how this ought to be fixed.
The main issues, that arise from this inconsistency, are:
Proposed Change
In order to find a database-agnostic solution which dows not require upstream changes on SQLAlchemy drivers, this issue my best be tackled by making Superset handle column names case-insensitively. I.e., all columns should internally be treated in lowercase.
There is a small risk of datasets having two columns that would translate to the same case-insensitive (lowercase) representation of the column name. However, @villebro feels that only very few people would really have a need to distinguish columns based on their case.
However, we need to ensure that e.g. CamelCase column names keep their human readability. Thus, I suggest to auto-fill the
label
of the dataset column (a.k.a. theverbose_name
) with it's original, case-sensitive, name in cases where this field is not already filled (do not overwrite existing information).New or Changed Public Interfaces
@villebro, @agusfigueroa-htg - I need your input regarding this and the following sections of this SIP...
New dependencies
Migration Plan and Compatibility
Rejected Alternatives
Consistency could be introduced on a per-DBMS basis, i.e. per SQLAlchemy driver, so all datasets in UPPERCASE DBMSes would be represented in UPPERCASE, regardless of whether they are physical or virtual datasets. Thsi would fix the aforementioned issues 1 and 2. However, the 3rd issue would not be covered. Furthermore, this issue may be more error-prone, when introducing support for more DBMSes or when upstream changes occur.
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