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初级

分析缓存命中率与优化建议

未完成
初级参考 完整示例代码供参考，建议自己理解后重新输入 
def solve():
    from pyodide.http import open_url
    from io import StringIO
    cache_log_csv = open_url("https://data.zuihe.com/dbd/ms-shop/state_07/cache_log.csv").read()
    import pandas as pd
    from io import StringIO
    log = pd.read_csv(StringIO(cache_log_csv))
    gets = log[log['operation']=='GET']
    sets = log[log['operation']=='SET']
    deletes = log[log['operation']=='DELETE']
    hits = gets[gets['hit']==1.0] if 'hit' in gets.columns else gets[gets['hit']==1]
    misses = gets[gets['hit']!=1.0] if 'hit' in gets.columns else gets[gets['hit']!=1]
    hit_rate = len(hits) / len(gets) if len(gets) > 0 else 0
    print(f"缓存操作统计:")
    print(f"  GET={len(gets)}, SET={len(sets)}, DELETE={len(deletes)}")
    print(f"  命中={len(hits)}, 未命中={len(misses)}")
    print(f"  命中率: {hit_rate:.1%}")
    key_miss = gets[gets['hit']!=1]['key'].value_counts().head(5)
    print(f"高频未命中Key:")
    for k, cnt in key_miss.items(): print(f"  {k}: {cnt}次miss")
    if hit_rate < 0.6: print("建议: 命中率低，考虑增大TTL或预热缓存")
    else: print("建议: 命中率良好")

示例

输入
solve()
期望输出
缓存操作统计:
  GET=8, SET=14, DELETE=8
  命中=4, 未命中=4
  命中率: 50.0%
高频未命中Key:
  product:7: 1次miss
  product:2: 1次miss
  product:11: 1次miss
  product:5: 1次miss
建议: 命中率低，考虑增大TTL或预热缓存
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