rahul37wallst-sudo commented on code in PR #21699:
URL: https://github.com/apache/echarts/pull/21699#discussion_r3631600352
##########
src/data/Source.ts:
##########
@@ -401,12 +401,23 @@ function determineSourceDimensions(
}
function objectRowsCollectDimensions(data: OptionSourceDataObjectRows):
DimensionDefinitionLoose[] {
- let firstIndex = 0;
- let obj;
- while (firstIndex < data.length && !(obj = data[firstIndex++])) {} //
jshint ignore: line
- if (obj) {
- return keys(obj);
+ const dimensionNameMap = createHashMap<true, DimensionName>();
+ const dimensionsDefine: DimensionDefinitionLoose[] = [];
+
+ for (let i = 0; i < data.length; i++) {
+ const obj = data[i];
+ if (!obj) {
+ continue;
+ }
+ each(keys(obj), function (name) {
+ if (!dimensionNameMap.get(name)) {
+ dimensionNameMap.set(name, true);
+ dimensionsDefine.push(name);
+ }
+ });
}
Review Comment:
Thanks for the suggestion. I ran a local benchmark with 100k object rows on
Windows / Node 22.18.0, using two warmups and nine measured runs.
Median source-creation times:
- Stable shape: previous-like first-row path 0.07 ms; full scan 4.92 ms;
explicit `dataset.dimensions` 0.02 ms.
- Sparse shape with a key appearing only in the final row: previous-like
path 0.02 ms; full scan 5.25 ms; explicit dimensions 0.01 ms.
I also isolated the collector implementation:
- `keys(obj)` plus callback: 38.47 ms stable / 34.86 ms sparse.
- `for...in` plus `hasOwn`: 3.10 ms stable / 3.67 ms sparse.
I updated the implementation to the allocation-free `for...in` loop in
commit `b6ace83a5`. The full scan remains O(total object keys), as required to
discover late sparse fields, but the measured source-initialization overhead
was about 5 ms for 100k three-field rows. Supplying `dataset.dimensions`
continues to bypass the scan.
The focused regression tests, `npm run lint`, `npm run checktype`, and `git
diff --check` all pass.
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