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2 Apr 2016 ... Also, this scanner only reads 1-D barcodes, which hold a small amount of data. 2-D barcodes (sometimes known as QR codes ) are now common, which can hold a lot more data. There's several . NET solutions available to allow us to read barcodes from an image- the one I'm going to look at today is ZXing . NET .

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This chapter described the basic elements of the SQL language. The basic structure of SQL can be summarized as follows: I The SQL language that is in common use includes about 30 statements, each consisting of a verb and one or more clauses. Each statement performs a single, specific function. I SQL-based databases can store various types of data, including text, integers, decimal numbers, floating point numbers, and usually many more vendorspecific data types. I SQL statements can include expressions that combine column names, constants, and built-in functions, using arithmetic and other vendor-specific operators. I Variations in data types, constants, and built-in functions make portability of SQL statements more difficult than it may seem at first. I NULL values provide a systematic way of handling missing or inapplicable data in the SQL language.

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The emergence of an Internet-centric architecture is exposing enterprise data processing infrastructures to new peak-load demands that dwarf the workloads of just a few years ago. When databases primarily supported in-house applications used by a few dozen employees at a time, database performance issues may have produced employee frustration, but they did not really impact customers. The advent of call centers and other customer support applications produced a closer coupling between data management and customer satisfaction, but applications were still limited to at most hundreds of concurrent users (the people manning the phones in the call center). With the Internet, the connection between a customer and the company s databases becomes a direct one. Database performance problems translate directly into slow customer response times. Database unavailability translates directly into lost sales. Furthermore, databases and other parts of the data processing infrastructure are no longer buffered from peak-load transaction rates. If a financial services firm offers online trading or portfolio management, it will need to prepare for peak-load volumes on days of heavy stock price movement that may be 10 or 20 times the average daily volume. Similarly, an online retailer must gear up to support the heaviest end-of-year selling season, not just mid-March transaction rates.

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Our demand for hot water is fairly constant throughout the year. We use more or less the same amount of hot water for washing and cleaning in the winter as we do in the summer.

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The demands of e-commerce and real-time Internet information access are already producing peak-load transaction rates from the most popular Internet services that are one or two orders of magnitude higher than the fastest conventional disk-based RDBMS systems. To cope with these demands, companies will increasingly turn to distributed and replicated databases. They will pull hot data forward and cache it closer to the customer interaction within the network. To meet peak-load demands, they will use in-memory databases. This will, in turn, require new database support for deciding which data to cache, and which levels of synchronization and replication are appropriate. At first, these issues will apply only to the largest and highest-volume sites, but just as web page caching has become an accepted and then an essential technique for maintaining adequate web browser performance, hot data caching will become a mainstream Internet data management architecture as volumes grow.

SELECT 'Valuable Customer ' || PERSON_GIVEN_NAME || ' ' || PERSON_FAMILY_NAME AS CUSTOMER_SALUTATION FROM PERSON;

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In the Internet era, database management will increasingly become just one more network service, and one that must be tightly integrated with other services, such as messaging, transaction services, and network management In some of these areas, standards are well established, such as the XA standard for distributed transaction management In others, standards are in their infancy or are just emerging, such as the SOAP standard for sending XML data over the Internet s HTTP protocol and the UDDI standards for finding services in a distributed network environment The multitier architecture that is dominating Internet-centric applications also poses new questions about which roles should be played by the database manager and by other components of the overall information system For example, when network transactions are viewed from the point of distributed databases, a two-phase commit protocol, implemented in a proprietary way by a DBMS vendor, may provide a solution.

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