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l neighboring patches Nh (v) = {hl (v + x ), hl (v x ), hl (v + y ), hl (v y )}. Also, hg (v) is another neighboring node in the Markov network. Therefore, the optimal local feature hl can be de ned by l hl = arg max p hl (v)|Nh (v), hg (v) . hl

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As you can see, we take a fairly minimalist approach to initial indexing; then we let analysis tools suggest the rest. Nine times out of ten, this technique gives us the best possible performance for our databases. The remaining ten percent of the time, indexing is just a matter of observing and tweaking.

One final note: Regularly rebuild your indexes to maintain database performance. Failure to do so can make you wish that you d never heard of indexes in the first place. Indexes are typically rebuilt by first dropping and then recreating them. For example, the following code snippet rebuilds the IDX_ContactName index from scratch:

(12.23)

DROP INDEX IDX_ContactName CREATE NONCLUSTERED INDEX IDX_ContactName ON Customer(Lastname,Firstname,Middlename)

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0.35 0.3 80.00% 0.25 Frequency 0.2 0.15 0.1 0.05 10.00% 0 0.25 0.5 0.75 1 1.25 1.5 1.75 2 2.25 2.5 2.75 3 3.25 3.5 3.75 4 4.25 More .00% 70.00% 60.00% 50.00% 40.00% 30.00% 20.00% 100.00% 90.00%

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As data is inserted, updated, and deleted, two things happen. First, holes appear in your indexes where data is deleted or key values are updated and, therefore, move to different positions in the index. Second, if you insert new index entries into an index s data page that is already full, that data page must split into two separate data pages to make room for the new entry, and the whole index B-tree structure must be rebalanced. This splitting and rebalancing operation is very costly so much so that if your indexes get old enough before rebuilding them, you can actually hear the disk laboring more and more as new mass inserts are performed. Be careful in rebuilding indexes on key values; you can t just drop these indexes and rebuild them, because they are central to table definitions. Consult your database platform s documentation for instructions on rebuilding indexes in place without dropping them first. We are not covering myriad details about indexes here, because they are outside the scope of this book; index design and maintenance can easily fill a book by itself. If you are really serious about scalable database design, you should read further on the subject of index design and maintenance.

By introducing the Gibbs potential function EG ( ), it is described how likely a l patch hl (v) connects to hg (v) and Nh (v).

Data Description Language (DDL)

l l p hl (v)|Nh (v), hg (v) exp EG hl (v), Nh (v), hg (v)

When you execute a select, insert, update, or delete, you are employing Data Manipulation Language, or DML. When you do something to the structure of the database itself, you are employing Data Description Language or DDL. Listing 8-1 contains the DDL that builds the database shown in the physical data model in Figure 8-16. Listing 8-2 contains the DDL that builds the database shown in the physical data model in Figure 8-17. Carefully study the details and apply the same techniques to your own database designs.

CREATE TABLE Category( CategoryCode varchar(4) NOT NULL CHECK (DataLength(RTrim(CategoryCode)) > 0), CategoryName varchar(20) NOT NULL CHECK (DataLength(RTrim(CategoryName)) > 0), CONSTRAINT PK_Category PRIMARY KEY NONCLUSTERED (CategoryCode)

(12.24)

Figure 18.6 Empirical calibration data for the PDLT energy method of predicting the axial capacity of driven piles (Stenersen 2001).

) go CREATE TABLE CategoryInventoryItem( CategoryCode varchar(4) NOT NULL, ItemNumber varchar(15) NOT NULL, CONSTRAINT PK_CategoryInventoryItem PRIMARY KEY NONCLUSTERED (CategoryCode,ItemNumber) ) go CREATE TABLE Customer( CustomerNumber varchar(12) NOT NULL CHECK (DataLength(RTrim(CustomerNumber)) > 0), CustomerTypeCode char(3) NOT NULL, CompanyName varchar(30) NOT NULL CHECK (DataLength(RTrim(CompanyName)) > 0), Lastname varchar(20) NULL, Firstname varchar(20) NULL, Middlename varchar(20) NULL, CONSTRAINT PK_Customer PRIMARY KEY NONCLUSTERED (CustomerNumber) ) go CREATE TABLE CustomerType( CustomerTypeCode char(3) NOT NULL CHECK (DataLength(RTrim(CustomerTypeCode)) > 0), CustomerTypeName varchar(20) NOT NULL CHECK (DataLength(RTrim(CustomerTypeName)) > 0), CONSTRAINT PK_CustomerType PRIMARY KEY NONCLUSTERED (CustomerTypeCode) ) go CREATE TABLE InventoryItem( ItemNumber varchar(15) NOT NULL CHECK (DataLength(RTrim(ItemNumber)) > 0), ParentItemNumber varchar(15) NULL, Description varchar(40) NOT NULL CHECK (DataLength(RTrim(Description)) > 0), UnitPrice numeric(12, 2) NOT NULL CHECK (UnitPrice > 0), CONSTRAINT PK_InventoryItem PRIMARY KEY NONCLUSTERED (ItemNumber) ) go CREATE TABLE Newsletter( NewsletterCode char(6) NOT NULL CHECK (DataLength(RTrim(NewsletterCode)) > 0), NewsletterName varchar(30) NOT NULL

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