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DomWilliams0 · DomWilliams0 · commit 011d2e2c56d1 · 2016-01-07T00:19:46.000Z
diff --git a/1-Beginner/Personal-Skills/08-How to Deal with IO Expense.md b/1-Beginner/Personal-Skills/08-How to Deal with IO Expense.md
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 # How to Deal with I/O Expense
 
-or a lot of problems, processors are fast compared to the cost of communicating with a hardware device. This cost is usually abbreviated I/O, and can include network cost, disk I/O, database queries, file I/O, and other use of some hardware not very close to the processor. Therefore building a fast system is often more a question of improving I/O than improving the code in some tight loop, or even improving an algorithm.
+For a lot of problems, processors are fast compared to the cost of communicating with a hardware device. This cost is usually abbreviated I/O, and can include network cost, disk I/O, database queries, file I/O, and other use of some hardware not very close to the processor. Therefore building a fast system is often more a question of improving I/O than improving the code in some tight loop, or even improving an algorithm.
 
 There are two very fundamental techniques to improving I/O: caching and representation. Caching is avoiding I/O (generally avoiding the reading of some abstract value) by storing a copy of that value locally so no I/O is performed to get the value. The first key to caching is to make it crystal clear which data is the master and which are copies. There is only one master - period. Caching brings with it the danger that the copy is sometimes can't reflect changes to the master instantaneously.
 
