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Some Batch Processing Using the CSV Library require "csv" file_name = ARGV[0] fail "no existing file specified" unless Fileexist (file_name) records = [] CSVopen(file_name, "r") do |record| records << recordvalues_at(0, 1, 3) records << recordvalues_at(2, 4, 5) end # some global data-checking here, perhaps CSVopen("#{file_name}new", "w") do |output| recordseach { |record| output << record } end Briefly, this listing includes the CSV library, checks for a supplied filename, and reads in each record from the file specified, breaking that record s six fields into two groups (by index) and shoving those groups onto the end of an array (records) The final operation is to write out a second CSV file that encodes the structure of that array The operation described by Listing 7-3 is largely incidental.

This example provided a first-hand taste of socket programming in the .NET world, and you implemented it using UDP. Although in reality UDP comes into action only in a specific scenario, most of the time applications are designed using TCP. UDP undoubtedly is the fastest delivery transport protocol, but it has some serious drawbacks: Unreliable: UDP provides no guarantee that data will ever reach its destination; this means in the previous example the market data information published may or may not reach the market data consumer. If you are looking for this kind of reliability feature, then you have no other choice but to hand-roll custom logic at the application level. Unordered sequence: Consider an example where market data is continuously pumped by the market data producer service, and in such cases the consumer will face a huge surge of data. If you look at the pattern of information published, you will find a case where a price of a stock is sent, and immediately an updated price for the same stock is delivered. In such cases UDP does not guarantee that the updated price information will be delivered only after the old price information is delivered. On the receiving end, you can imagine the impact on the application and its downstream components when it first receives the updated price and when afterward it receives the stale price.

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@In(value="user", required=false) private User mUser;

Custom sink layer: Compared to its predecessor, the remoting architecture provides a mind-blowing level of extensibility The custom sink layer allows developers to plug their custom logic Such custom logic provides the means to introduce additional features, be it business features or infrastructure-related features One of the most commonly used features is securing the message by applying a strong encryption technique A mind-numbing way to implement this feature is to change both the proxy and the remote objects and inject additional security code into every method A much smarter way to achieve this is with the help of a custom sink that is transparently plugged, and then every message is passed through this custom sink layer, thus providing complete liberty to sinks to further change the characteristics of the message Channel layer: The channel layer is the backbone for message delivery within the remoting framework.

The important point is that the CSV library abstracts away the nature of the data formatting and presents the records of fields as an array of arrays, which is a much nicer representation The bundled library used in Listing 7-3 is formally correct; it should parse any valid CSV file no matter how convoluted However, it can be a little slow due to all the work it s doing and a fairly liberal approach to things likes row endings A more recent alternative exists in the form of the FasterCSV gem, which is faster and works with every file I ve ever thrown at it As usual, more detail on gems can be found in 10..

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