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Let's say you're designing a system that stores an incoming feed of real-time stock pricing information so that other applications can access it Relational databases aren't really built for this kind of real-time system, so you're going to build something that sits on its own, digesting the feed as it comes in, storing prices internally in memory, and spitting them out to other applications on request In addition, you want to track historical data You want to be able to save the high, low, and closing price each day after the closing bell, which sounds like a job for a relational database The tricky bit is that the real-time feed you're getting sends you only the current price First, let's examine the requirements:
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The system must consume a real-time feed of stock prices and store them internally The system must make pricing information (for example, the current price, the 52-week high, the 52-week low, and yesterday's closing price) available to other (external) applications upon request
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Now let's take a quick look at our data model A stock quote must have the following data fields:
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Stock symbol Current price 52-week high 52-week low Yesterday's close Date stamp (so we know how fresh the information is)
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This isn't a complex data model, but a few interesting technical problems come to mind First of all, we don't know the nature of these external applications that will be built as consumers of the stock price information Second, an RDBMS isn't terribly good at being a real-time storage system for information that constantly updates, second-to-second Finally, the feed itself doesn't contain historical information One solution to these problems would be to support interoperability with external applications by implementing a Web service and to store only historical data in the RDBMS When another application wants a stock quote, it will ask the feed decoder system, which will respond with a stream of XML that might look like this:
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<STOCK_QUOTE> <SYMBOL SYMBOL="XYZ"/> <DATESTAMP DATE="2000-02-18T20:21:07,0"/>
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<CURRENT_PRICE PRICE="10263"/> <YESTERDAY_CLOSE PRICE="10372"/> <FIFTYTWO_HIGH PRICE="11771"/> <FIFTYTWO_LOW PRICE="8764"/> </STOCK_QUOTE>
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However, your relational database schema might look something like this:
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CREATE TABLE stock_pricing ( stock datestamp high low close );
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This table gets updated only once per day per stock, after the market closes and final pricing is in While markets are open and active pricing is coming in over your feed, you're storing the pricing data in a big hash table somewhere in memory When a request from another program comes in for pricing information, you can grab the current price from memory and get all the historical data from the relational schema Again, the power of the relational database is put to use at what it's good at toring and aggregating large amounts of information If you want to do historical research about when a particular stock hit its high or use the data to create graphs, the information is all there in the RDBMS In this stock quote example, XML is used for one of the things it's good at ransmitting in a standard, generic manner information that can be understood by multiple applications Your applications on the front end can consume this easy-to-understand XML snippet and display the information in any way they want without having to understand where it came from This kind of modular application design also has implications for how the application is developed, enabling geographically separate developers to work together more easily If you specify what the XML is supposed to look like, you can get one developer working on the feed application and another developer working independently on the system that uses it One of them can be working in India, the other in Indianapolis
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NUMBER(16) TIMEDATE FLOAT(16) FLOAT(16) FLOAT(16)
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