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⚡ Optimize redundant array allocation in Heatmap component#7

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perf/heatmap-maxfreq-17136021111186621730
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⚡ Optimize redundant array allocation in Heatmap component#7
artosien wants to merge 1 commit intomainfrom
perf/heatmap-maxfreq-17136021111186621730

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@artosien
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💡 What: Replaced the array map + spread operator usage with a single reduce() operation when calculating maxFreq in the Heatmap component.
🎯 Why: The previous approach (Math.max(...numbers.map(...))) creates an intermediate array containing only the frequencies, which wastes memory and adds garbage collection overhead. Further, using the spread operator on a large array can potentially cause a call stack size exceeded error. The reduce() implementation computes the maximum in a single pass without extra allocations.
📊 Measured Improvement:
Using a standalone benchmark node script doing 1,000,000 iterations over an array of 58 objects:

  • Baseline (map + max): 882.84ms
  • Optimized (reduce): 152.64ms
  • Improvement: ~82.7% reduction in execution time (approx 5.8x speedup)

PR created automatically by Jules for task 17136021111186621730 started by @artosien

Replaced `Math.max(...numbers.map())` with `.reduce()` to eliminate redundant array allocation and improve performance. This avoids O(N) array allocation overhead.

Co-authored-by: artosien <65523959+artosien@users.noreply.github.com>
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