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Processing stores in a round-robin fashion is a simple strategy, but more complex strategies can be implemented, such as processing stores based on the volatility of the underlying stock This ensures that messages of highly volatile stocks are first pushed on the network before all other stocks Broadcast pipe: The broadcast pipe is formed by chaining individual discrete components The first component in this chain is the rule engine The rule engine allows subscribers to express the subscription rule Based on this rule, the rule engine examines an individual market data message If it finds a subscriber that satisfies the rules, then it forwards the message to the serializer component in the chain The serializer converts the message to a byte array that is then passed to the transport The transport is the final component in the chain, and it transmits data to its recipients.

In the following sections, we ll cover the code that more or less illustrates these concepts The only component that is not covered is the rule engine..

Just as a += b is short for a = a + b, so a ||= b is really a = a || b It s worth noting that standard Ruby logic rules apply, so everything I ve just described for a variable with value nil will work equally well for one with value false..

. . . @End public String listGadgets() { setActiveGadget(null); return "success"; } . . .

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ConsoleWriteLine(elements[ctr]); } } } Similarly, to locate items in an array, the NET Framework provides a binary search algorithm The only prerequisite required for this search algorithm is that the array must be sorted So, the first step is to apply a quick sort to ensure that the arrays are sorted either in ascending order or in descending order With the incredible increase in the processing power of computers, a search conducted on 1,000 elements using either sequential search or binary search would make no difference to the overall performance of an application However, the binary search technique would easily outperform the sequential search when the underlying array contains an extremely large number of items.

The following code demonstrates how to use the built-in binary search algorithm to locate a specific item in an array: using System; class BinarySearch { static void Main(string[] args) { //elements arranged in unsorted order int[] elements = {12,98,95,1,6,4,101}; //sort element using quick sort ArraySort(elements,0,elementsLength); //find element using binary search //ie find 95 int elementPos = ArrayBinarySearch(elements,0,elementsLength,95); //if exact match found if ( elementPos >= 0 ) { ConsoleWriteLine("Exact Match Found : " +elementPos); } else //nearest match found { //bitwise complement operator elementPos = ~elementPos; ConsoleWriteLine("Nearest Match : " +elementPos); } } } The search is initiated by calling the ArrayBinarySearch static method If this method returns a positive value, then it is a success indicator and represents the index of the searched item.

With the improvements made, we save a whole bunch of memory. Of course, we ve also made adding an embezzlement amount slightly slower, as there s now an extra conditional check every time embezzle is called. It is possible to shortcut this disadvantage with a feat of lunatic daring called a self-destructing method, but this is so beautifully abstract that I m going to save it for the next chapter. Before moving on, I ll draw your attention to another bit of laziness in our code. The total amount embezzled is calculated live, on demand. This bit of lazy evaluation could also be pivotal as a design choice. If embezzled_total were to be called frequently, it would be well worth caching the pertinent amount rather than calculating it each time. This approach is codified in Listing 3-12. Listing 3-12. Exchanging Memory for Performance by Caching the Embezzlement Total def embezzle(amount) (@embezzled ||= []) << amount (@embezzled_total ||= 0) += amount end def embezzled_total (@embezzled_total || 0) end In practice, nobody would write embezzled_total in full as shown in the listing. After all, it s very close to being the same as attr_reader :embezzled_total. Also, it may be overkill to lazy-instantiate @embezzled_total, as Ruby really doesn t have a lot of overhead for storing integers (particularly small ones). Taken together, these points mean that you would likely instantiate @embezzled_total in Employee.initialize and use the attribute reader macro to provide access to it.

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