在Docker中为自容器.Net Core应用程序指定运行时(Specify runtime for self container .Net Core app in Docker)

 当我对你的问题发表评论时，我没有时间详细说明，所以这是一个尝试回答的问题。 代码已经改变了，我不确定我会像现在这样将代码添加到代码中。 
 
 然而，使我添加该评论的根本原因仍然存在： 除非您测量并发现相关代码确实对性能产生了显着的负面影响， 否则不要尝试进行优化 。 相反，努力使您的代码尽可能可读 。 
 
 我非常怀疑在将数据从磁盘复制到内存后，复制内存中的数据会对性能产生重大影响。 但是，由于您提供的代码无论如何都会对内存中的struct布局做出假设，因此直接读入struct不会真正降低代码的可读性（或者更不容易对该布局进行更改）： 
 
COUPLE titanic;
FILE *f = fopen("myfile", "rb");
fread(&titanic, sizeof(titanic), 1, f);
 
 或者，如果您确实有一个数组，请直接读入数组： 
 
COUPLE titanic[SIZE];
FILE *f = fopen("myfile", "rb");
fread(&titanic, sizeof(titanic), SIZE, f);
 
 取决于SIZE ，后者确实可以在性能上产生潜在的巨大差异。 对于较大的块，访问磁盘以获得更大的块通常更快。 （尽管磁盘缓存可能会减轻这种情况。） 

When made my comment to your question, I didn't have the time to elaborate, so here's an attempt to answer. The code has changed since, and I'm not sure I would add that comment to the code as it is now. 
 
Nevertheless, the underlying reason that made me add that comment still stands: Unless you measured and found that the code in question does indeed have a significant negative impact on performance, don't attempt to optimize. Instead, strive to make your code as readable as possible. 
 
I seriously doubt that copying the data in memory will have a significant performance impact after copying them from the disk into memory. However, since your code as provided makes assumptions about the struct's layout in memory anyway, directly reading into the struct wouldn't really make the code less readable (or less vulnerable to changes to that layout): 
 
COUPLE titanic;
FILE *f = fopen("myfile", "rb");
fread(&titanic, sizeof(titanic), 1, f);
 
Or, if you indeed have an array, read into the array directly: 
 
COUPLE titanic[SIZE];
FILE *f = fopen("myfile", "rb");
fread(&titanic, sizeof(titanic), SIZE, f);
 
Depending on SIZE, the latter could indeed make a potentially huge difference in performance. Accessing the disk for bigger chunks is, in general, faster that doing it for smaller chunks. (Although disk caching might alleviate that.)