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A cost-based optimizer can go further Suppose the system catalog contains three additional pieces of information: (1) that there are 100 rows in Table1, (2) that there are two pages in Table1, and (3) that the value 55 appears 60 times in the index for column2 Those facts change everything The equals operation will match on 60% of the rows, so it's not a narrow search And he whole table can be scanned using two page reads, whereas an index lookup would take three page reads (one to lookup in the index, two more to fetch the data later) Therefore the cost-based optimizer makes a different plan: find matching rows using a table scan Notice that the cost-based optimizer is using volatile data (the row and column values that have been inserted) and an override (that the contents are more important than the fixed assumptions) In other words, a cost-based optimizer is a rule-based optimizer that has additional, volatile information available to it so that it can override the fixed assumptions that would otherwise govern its decisions The terminology causes an impression that one optimizer type is based on rules while the other is based on cost That's unfortunate because both optimizer types use rules and both optimizer types have the goal of calculating cost The reality is that cost-based is an extension of rule-based, and a better term would have been something like "rule-based++" Most vendors claim that their DBMSs have cost-based optimizers, as you can see from Table 17-1 The claims don't mean much by themselves What's important is whether the optimizer estimates cost correctly and how it acts on the estimate In this chapter, we'll look at the actions DBMSs take to fulfill their claims Table 17-1 Cost-Based Optimizers "Explains" the Access "Updates" Statistics for the Plan Optimizer EXPLAIN RUNSTATS SET EXPLAIN UPDATE STATISTICS EXECUTE QEP optimizedb utility SELECT PLAN SET STATISTICS EXPLAIN UPDATE STATISTICS EXPLAIN ANALYZE TABLE EXPLAIN PLAN FOR ANALYZE SET SHOWPLAN ON UPDATE STATISTICS.

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Because Walgreens had the money but not the materials or manpower to build new stores during the war, the company wisely salted away a portion of its earnings every year, earmarking the extra $15 million for expansion once the war had ended In a postwar issue of the Pepper Pod, Chuck Walgreen announced a new era of optimism when he declared, Extensive expansion is the keynote for 1946 4 But Walgreens did not expand the number of stores reatly under Chuck s reign only about a 20 percent increase during his three-decade run Instead, the company devoted its resources to refurbishing, replacing, and supersizing its existing outlets and to branching out into new areas, both physically and strategically Walgreens first dipped into its wartime nest egg to give its stores long overdue facelifts, from remodeling floor plans to installing fluorescent lighting By 1946, it was no longer possible to ignore that the company had finally outgrown its second headquarters on Bowen Avenue, despite four expansions over the previous 21 years Chuck and company started building a brand new corporate office at 4300 W Peterson Avenue on Chicago s northwest side Opened in 1949, the new headquarters 100,000 square feet of usable space was more than enough to house all 640 central employees, many of whom had been forced to work outside the old headquarters Like so many other US companies in the postwar era for whom diversification was the buzz word, Walgreens dived headfirst into the brave new world of mergers and acquisitions In the spring of 1946, Robert Knight received a call from Julio Lacaud, a prominent investment banker, the Kogans wrote, to see if Walgreens might be interested in buying a slice of Sanborns, a popular chain of department stores in Mexico5 The idea held more than a little appeal When Walgreens bought Sanborns in 1946, the Mexican chain consisted of just two links, with.

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Here, an integer program variable named seconds is displayed in hexadecimal You could as well display it as an ASCII character: (gdb) print /c seconds $6 = 42 '*' It's the same value (decimal 42, hex 2A) but displayed as its ASCII equivalent, which is the asterisk character (*) You can display a register or a variable in binary by using the t format code This is useful when you're interpreting a register value as a bitmap or as a set of flags: (gdb) print /t $ebx $7 = 1000000001001000010100010000 Note that when using the t format code, leading zeros in the display are suppressed, so you will not always get 32 ones or zeros (There are only 28 in the preceding value The four highest-order bits in the value are 0 and have been suppressed) A summary of all the format codes available to the print command is given in Table 121 Table 121: Format Codes for gdb's Print and x Commands CODE c d i o s t u x CMD Both Both x Both x Both Both Both DEFINITION Assume the data is a single byte, and display it as an ASCII character Assume ata is an integer, and display it in signed decimal Display the memory value as a machine instruction mnemonic Assume data is an integer, and display it in octal Assume data is a null-terminated string, and display it as a string Display data in binary (think: base 2) Assume the data is an integer, and display it in unsigned decimal Assume the data is an integer, and display it in hexadecimal.

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$8 = (<data variable, no debug info> *) 0x80496d5 This will also work for code labels, to determine the address at which a label exists The x command can dump memory for a specified number of bytes beginning at a specified address The two additional tricks (over and above the format code) are the repeat count and the unit size The repeat count is a number placed immediately after the slash in the x command, and it specifies the number of units o dump The format command comes next and indicates which way the data must be displayed Finally, the unit size specifies how large each displayed unit is For a traditional memory count, this is best done as a byte, for which the code is b The address may be specified as a literal address in hex, or as the address in a register, or as the address of a specific variable name or program label Here's an example of a memory dump of 64 bytes, each formatted in hex: (gdb) x /64xb 0x8049500: 0x8049508: 0x8049510: 0x8049518: 0x8049520: 0x8049528: 0x8049530: 0x8049538: (gdb) 0x8049500 0x55 0x89 0x90 0x90 0x55 0x89 0x00 0xe8 0x04 0xa3 0x97 0x04 0x83 0xc4 0x08 0xe8.

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possible (ie live ) before such events diminish, as in the Three Mile Island (TMI) incident mentioned by McGee (2004) In the instance, a lesson had been learned that the relief valve used in a nuclear reactor built by Company X had failed to function properly in one occasion and further action was needed The immediate event for reusing the lesson learned was at the TMI nuclear reactor where another relief valve built by Company X was being used However, the lesson learned from reactor A was not transferred to the TMI operator and hence was not being reused No action was taken by TMI operator which had subsequently led to the TMI incident when the valve failed All other similar type of relief valves would have been replaced after that, but the single most crucial event for reusing the lesson learned had been missed Similarly, in the context of the construction industry, it is possible for a construction organisation to have similar types of project running roughly parallel, such as the PFI projects Speci c knowledge captured from a particular type of project may only be valuable and reusable in similar projects In this instance, the live capture and reuse methodology can help to ensure that the speci c knowledge created or identi ed from one courthouse project is made available for sharing nd reuse in another courthouse project (or just another courthouse in the same project) so that the triggers for reuse are not missed In summary, the result of the review depicts that live capture and reuse of project methodology is crucial in addressing the aforementioned shortcomings of current practice, to better manage project knowledge and to enable the bene ts of knowledge captured to be fully exploited The live capture and reuse of project knowledge methodology facilitates the capture of project knowledge as soon as the knowledge is created or identi ed (ie live ) to avoid persistent knowledge loss problem of current practice due to time lapse and other constraints The importance of live methodology is further strengthened by the reduction of knowledge loss facilitated which helps to ensure that a more complete set of project knowledge is captured from construction project, and which allows the knowledge to be reused live to reap the most from the knowledge Having established the importance of the live capture and reuse of project knowledge in construction, the next chapter explores the potential types of reusable project knowledge in construction, the learning situations where most of the new learning is created, the current practice for the capture of knowledge focusing on the capability to facilitate live capture of project knowledge and the soft (organisational, cultural and human) issues that affect the knowledge capture and reuse.

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