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I installed some free barcode font, and created a template on Excel (just some simple formulas to create consecutive values) and printed normally. Then I sticked ...

hen Oracle first launched the Oracle Exadata Database Machine, it was aimed only at the broad solution area defined as data warehousing The reason why the initial focus was on data warehousing was simple Predesigned hardware configurations are well accepted in the data warehousing market and were available from many of Oracle s competitors Over the past decade, they have evolved from providing merely balanced server and storage configurations containing fast interconnects to delivering hardware-specific optimizations for typical data warehousing workloads Although Oracle s entry into this arena of providing integrated hardware and software solutions is relatively recent, Oracle is not new to providing data warehousing solutions In fact, information technology analysts generally agree that Oracle has provided the leading database for data warehousing for many years Oracle began to introduce key optimization techniques for data warehousing in its database more than 20 years ago For many organizations, these database optimization techniques provided solutions to their business needs while delivering the solutions on a familiar database engine that was also deployed elsewhere in their organization for transaction-processing applications However, growing data volumes and workload demands would sometimes tax the capabilities of Oracle-based data warehousing solutions designed around optimization provided by just the database software Even more challenging, many data warehouses were deployed without careful consideration of the impact of storage throughput needed to deliver the required query response time at the server(s) In this chapter, we ll give you a complete view of data warehousing considerations when deploying the Oracle Exadata Database Machine We ll start with a basic definition of data warehousing and a description of common topologies We ll then review some of the key features in the Oracle database that enable better reporting and ad hoc query performance, some of which were covered in more detail in 2 Since another desired capability of data warehousing is analytics, including trending and forecasting and predictive analysis through data mining, we ll also cover how the Oracle database supports those workloads After covering generic Oracle data warehousing topics, we ll discuss specific capabilities that are unique to the Oracle Exadata Database Machine and Exadata Storage Servers We ll cover unique optimization techniques and the role of Hybrid Columnar Compression We ll then describe how the generic features and special features for this platform work.

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Note that f is a speci c force with units of acceleration In the presence of a gravitational eld, the accelerometer dynamic equation is b k (1110) p = pc pc + G m m where G represents the position dependent gravitational acceleration It can be shown by manipulations similar to those shown above that f = f + p G(p) (1111)

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When the acceleration signal p(t) is within the sensor bandwidth, the speci c force output f is f = p G(p) (1112) Eqn (1112) represents the accelerometer output equation (neglecting bandwidth e ects) The equation does not make any assumptions about the accelerometer trajectory, but does recognize that the gravitational acceleration is location dependent The above discussion states that an accelerometer measures speci c force or the relative acceleration between the case and the mass m It does not detect accelerations that a ect the case and mass m identically It is useful to consider a few special cases

7:

Double helix A Adenine purine T Thymine pyrimidine (DNA only) G Guanine purine C Cytosine pyrimidine U Uracil pyrimidine (RNA only) AT/GC base pairs Antiparallel strands Major groove minor groove A-, B-, and Z-DNA

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The two complementary strands of the DNA double helix run in antiparallel directions (Fig 4-1) The phosphodiester connection between individual deoxynucleotides is directional It connects the 5 -hydroxyl group of one nucleotide with the 3 -hydroxyl group of the next nucleotide Think of it as an arrow If the top strand sequence is written with the 5 end on the left (this is the conventional way), the bottom strand will have a complementary sequence, and the phosphate backbone will run in the opposite direction; the 3 end will be on the left The antiparallel direc35

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together to provide great performance in solving a query We ll also point out some of the best practices for data loading, partitioning, and backing up data specific to data warehousing Finally, we ll cover surrounding business intelligence tools, data models, security considerations, and how to justify purchase of the Oracle Exadata Database Machine for your data warehousing project

Figure 4-1

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Parallel execution, or parallelism, has been a part of the Oracle database for more than a decade This long-time feature has become even more important in the context of the Exadata Database Machine, where multiple nodes, CPUs, and intelligence in the storage systems can increase the speed of individual parallel tasks as well as handle more of these tasks at the same time

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