codeant-ai-for-open-source[bot] commented on code in PR #30827:
URL: https://github.com/apache/superset/pull/30827#discussion_r3200706287
##########
superset-frontend/plugins/plugin-chart-table/src/transformProps.ts:
##########
@@ -244,6 +245,9 @@ const processColumns = memoizeOne(function processColumns(
const config = columnConfig[key] || {};
// for the purpose of presentation, only numeric values are treated as
metrics
// because users can also add things like `MAX(str_col)` as a metric.
+ const isFilterable = columnConfigs.find(
+ c => c.column_name === key,
+ )?.filterable;
Review Comment:
**Suggestion:** This does a linear search through all datasource columns for
every result column, creating O(n²) work during prop transformation. With wider
tables this becomes noticeably expensive; build a one-time lookup map keyed by
column name and read filterability in O(1). [performance]
<details>
<summary><b>Severity Level:</b> Minor đ§š</summary>
```mdx
- â ď¸ Table chart transformProps does redundant linear searches per column.
- â ď¸ Render cost grows with columns and metadata size.
```
</details>
<details>
<summary><b>Steps of Reproduction â
</b></summary>
```mdx
1. Open any dashboard or Explore view that uses a Table chart (registered in
`src/visualizations/presets/MainPreset.ts:24` as `new
TableChartPlugin().configure({ key:
VizType.Table })`), e.g. the "video game sales" dashboard mentioned in the
PR description.
2. `ChartRenderer` (`src/components/Chart/ChartRenderer.tsx:538-548`) renders
`<SuperChart>` with `vizType={VizType.Table}`, passing the dataset metadata
as
`datasource` and query results as `queriesResponse`.
3. `SuperChart` builds `chartProps` and invokes the Table plugin's
`transformProps`
function, which calls `processColumns` in
`plugins/plugin-chart-table/src/transformProps.ts:200-343`. There,
`colnames` (length N,
one per result column) and `props.datasource.columns` (length M, one per
dataset column)
are read.
4. For each entry in `(colnames || [])` at lines 237-243, `processColumns`
executes `const
isFilterable = columnConfigs.find(c => c.column_name === key)?.filterable;`
at lines
248-250, performing a linear search over the M datasource columns for each
of the N result
columns, yielding O(N*M) work on every Table chart render. With wider tables
(large N and
M) and frequent rerenders this adds unnecessary CPU overhead in the
transform stage,
though it is unlikely to be a critical bottleneck for typical Superset
datasets.
```
</details>
[Fix in
Cursor](https://app.codeant.ai/fix-in-ide?tool=cursor&prompt=This%20is%20a%20comment%20left%20during%20a%20code%20review.%0A%0A%2A%2APath%3A%2A%2A%20superset-frontend%2Fplugins%2Fplugin-chart-table%2Fsrc%2FtransformProps.ts%0A%2A%2ALine%3A%2A%2A%20248%3A250%0A%2A%2AComment%3A%2A%2A%0A%09%2APerformance%3A%20This%20does%20a%20linear%20search%20through%20all%20datasource%20columns%20for%20every%20result%20column%2C%20creating%20O%28n%C2%B2%29%20work%20during%20prop%20transformation.%20With%20wider%20tables%20this%20becomes%20noticeably%20expensive%3B%20build%20a%20one-time%20lookup%20map%20keyed%20by%20column%20name%20and%20read%20filterability%20in%20O%281%29.%0A%0AValidate%20the%20correctness%20of%20the%20flagged%20issue.%20If%20correct%2C%20How%20can%20I%20resolve%20this%3F%20If%20you%20propose%20a%20fix%2C%20implement%20it%20and%20please%20make%20it%20concise.%0AOnce%20fix%20is%20implemented%2C%20also%20check%20other%20comments%20on%20the%20same%20PR%2C%20and%20ask%20user
%20if%20the%20user%20wants%20to%20fix%20the%20rest%20of%20the%20comments%20as%20well.%20if%20said%20yes%2C%20then%20fetch%20all%20the%20comments%20validate%20the%20correctness%20and%20implement%20a%20minimal%20fix%0A)
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Claude](https://app.codeant.ai/fix-in-ide?tool=vscode-claude&prompt=This%20is%20a%20comment%20left%20during%20a%20code%20review.%0A%0A%2A%2APath%3A%2A%2A%20superset-frontend%2Fplugins%2Fplugin-chart-table%2Fsrc%2FtransformProps.ts%0A%2A%2ALine%3A%2A%2A%20248%3A250%0A%2A%2AComment%3A%2A%2A%0A%09%2APerformance%3A%20This%20does%20a%20linear%20search%20through%20all%20datasource%20columns%20for%20every%20result%20column%2C%20creating%20O%28n%C2%B2%29%20work%20during%20prop%20transformation.%20With%20wider%20tables%20this%20becomes%20noticeably%20expensive%3B%20build%20a%20one-time%20lookup%20map%20keyed%20by%20column%20name%20and%20read%20filterability%20in%20O%281%29.%0A%0AValidate%20the%20correctness%20of%20the%20flagged%20issue.%20If%20correct%2C%20How%
20can%20I%20resolve%20this%3F%20If%20you%20propose%20a%20fix%2C%20implement%20it%20and%20please%20make%20it%20concise.%0AOnce%20fix%20is%20implemented%2C%20also%20check%20other%20comments%20on%20the%20same%20PR%2C%20and%20ask%20user%20if%20the%20user%20wants%20to%20fix%20the%20rest%20of%20the%20comments%20as%20well.%20if%20said%20yes%2C%20then%20fetch%20all%20the%20comments%20validate%20the%20correctness%20and%20implement%20a%20minimal%20fix%0A)
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<details>
<summary><b>Prompt for AI Agent đ¤ </b></summary>
```mdx
This is a comment left during a code review.
**Path:** superset-frontend/plugins/plugin-chart-table/src/transformProps.ts
**Line:** 248:250
**Comment:**
*Performance: This does a linear search through all datasource columns
for every result column, creating O(n²) work during prop transformation. With
wider tables this becomes noticeably expensive; build a one-time lookup map
keyed by column name and read filterability in O(1).
Validate the correctness of the flagged issue. If correct, How can I resolve
this? If you propose a fix, implement it and please make it concise.
Once fix is implemented, also check other comments on the same PR, and ask
user if the user wants to fix the rest of the comments as well. if said yes,
then fetch all the comments validate the correctness and implement a minimal fix
```
</details>
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