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In this chapter you have been introduced to the fundamentals of I/O and performance characteristics of disk drives and RAID. Because I/O performance is so important to SQL Server, you must carefully plan and design the SQL Server System. This has been briefly covered here and will be covered in future chapters as well. It is important that the I/O subsystem be monitored and tuned as necessary. In 6, you will see how to monitor and benchmark the storage system to plan for the future. This chapter provided the fundamentals and basics of I/O performance. The chapter started with the fundamentals of disk drive performance. These fundamentals are important since the disk drive is the basic building block of most I/O subsystems. By exceeding the capacity of these components, the response time or latency of the I/O subsystem will increase. This will cascade into poor SQL Server performance, potential blocking, or even deadlocks. In addition to disk drives, the RAID level that you select can also adversely influence the performance of your I/O subsystem. Careful design and planning can help alleviate some of these problems. Determining how much hardware you actually need is the act of sizing and is discussed in 6. A properly sized system will provide for good performance and flexibility for changes over time. Remember the fundamentals, and add capacity as necessary.

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In this project Adobe PDF Reader COM Component is used and wrapped as WPF control. Background: The application uses WPF PDF Viewer control to display  ...

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means there are 606 x 17 x 1,158, or 11,929,716 possible combinations, which means there could theoretically be 11,929,716 rows in the fact table In reality, products and employees were introduced gradually over time, and each product isn t sold every day by every employee, so only 60,858 combinations actually appear as rows in the FactResellerSales table Even though the fact table contains only 60,858 detail values, the cube can display up to 11,929,716 detail level cells most of which would be empty In addition, because a cube appears to contain every possible summarized value at every possible level of detail for every dimension, the cube must appear to contain not only the 11,929,716 possible detail combinations, but also all possible summary values Counting all the members in each attribute hierarchy of these three dimensions, the SSAS Step by Step DW warehouse database has a lot of possible combinations.

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In the Product dimension, there are 647 members comprising the 606 members in the Product attribute hierarchy, 37 members in the Subcategory attribute hierarchy, and four members in the Category attribute hierarchy There are 296 members in the Employee dimension In the Time dimension, there are 1,186 members, which include the 1,158 members in the Date attribute hierarchy, 12 members in the Month attribute hierarchy, four members in the Calendar Quarter attribute hierarchy, four members in the Fiscal Quarter attribute hierarchy, four members in the Calendar Year attribute hierarchy, and four members in the Fiscal Year attribute hierarchy Finally, there are the two measures for the Reseller Sales measure group The cube must therefore appear to contain 647 x 296 x 1,186 x 2, or 454,266,464 values, just for this one measure group.

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In this small sample database, the cube appears to contain over 7,464 times as many values as the fact table contains rows! This is called data explosion, which was explained in 2 Data explosion is a major issue with OLAP cubes, and all OLAP products must deal with it in some way The simplest way to avoid data explosion is to avoid storing aggregations altogether and, instead, calculate them on demand But when you have a large data warehouse, this option quickly takes its toll on performance because requesting a single high-level summarized value from the cube would require retrieving and summing hundreds or thousands of values from the source data The challenge of OLAP is to make queries as fast as possible while avoiding data explosion.

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Microsoft SQL Server 2005 Analysis Services provides several features that allow the database administrator to control and fine-tune the relationship between the physical size of the cube and the speed of the queries In fact, Analysis Services provides options in many cases that allow both compact data files and responsive queries Aggregations are precalculated summaries of detailed data that enable the Analysis server to answer queries quickly While you can easily create a cube without aggregations none of the cubes used previously in this book have any aggregations aggregations can make a tremendous difference in query time for a large cube Regardless of how many aggregations you design, the cube always appears to contain every possible aggregated value When you request a value from a cube, Analysis Services uses whatever aggregations are available to retrieve the value as quickly as possible..

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NET WPF Viewer control supports viewing and converting PDF , DOCX, DOC, BMP, ... With the PDF Viewer control, you can display PDF files directly in your ...

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Another option is to use the WebBrowser control in your GUI. It's going to use the browser to render the PDF, but I'd do that route rather than ...

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