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For example, to look up the California county that contains the city of Marina del Rey, we ask a question What county is Marina del Rey located in and obtain an answer Los Angeles Table 4-1 shows this information in a sample cache of cities and counties The keys and values in a cache can be more complex objects and are not limited to strings; the only requirement is that the key object support some sort of equality test so that we can successfully test its membership when we query the cache

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Caches typically hold much less information than that in the originating source For example, there may be thousands (or hundreds of thousands) of city/county pairs, even though only a fraction of them are contained in the cache There are a variety of techniques to determine what information should be retained in the cache and what should be eliminated or "flushed" Generally speaking, when information not in the cache is requested, the system fetches it from its original source, returns it to the requestor, and adds it to the cache Of course, a cache has limited size and eventually it must be decided which information to flush Obviously, it's desirable to keep those pieces of information that will be the most frequently queried because that will provide the best system speedup Keep in mind, however, that I just said "will be the most frequently queried" Since there's no way to predict the future with 100 percent accuracy, part of the challenge in designing a caching system is identifying a good cache flush policy One example of such a policy is least recently used (LRU), which keeps only the most recently queried information For example, consider the sample city cache and assume that it can store only six key/value pairs, as shown Also, assume that the table shows the order of information access thus, Garden Grove was the last city queried Now, if the county for San Ramon is queried, the system fetches the answer (Alameda) from the originating source and replaces the least-recentlyused pair Pleasanton / Alameda from the cache

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1 Cash method A Recognize income when received; recognize expenses when paid B Include all items of income constructively received; deduct all bills paid C Expenses paid in advance are deducted when they apply D Use with service-oriented businesses and businesses with little or no inventory 2 Accrual method A Recognize income when earned; recognize expenses when incurred B Match income and expenses in the correct year C Items of income are included when they are earned, even though payment may be received in another tax year D All events that x the individual s right to receive the income must have happened, and the individual must be able to gure the amount with reasonable accuracy E Only the accrual method may be used for purchase and sales of inventory 3 Hybrid method A Any combination of the cash method and the accrual method may be used if the combination clearly shows income B Applies to businesses with both service and inventory 4 Long-term contracts building, installation, construction, or manufacturing contracts that are not completed in the tax year in which they are entered into (ie, manufacturing contract, machinery contract) 5 Installment sale A Installment sale treatment occurs when payments are received in a year other than the year of sale B Each payment usually consists of three parts: (1) interest, (2) gain on sale, and (3) recovery of basis C Interest must be charged at a rate at least equal to the IRS minimum The amount of interest is subtracted from the total of payments made, and the remainder is split between gain on sale and recovery of basis D The following sales are not reported under the installment method: (1) Sale resulting in loss (2) Sale of inventory in the ordinary course of a trade or business (3) Sale by a dealer of personal or real property, except for certain farm or time-share dispositions (4) Publicly traded stocks or bonds (5) Sale of a personal residence when the gain has been excluded under $250,000/$500,000 limits (6) Portion of a sale resulting in ordinary income due to depreciation recapture.

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Table 4-2 City/County Cache with Access Counts City Pleasanton Santa Clara Livermore Palo Alto Marina del Rey Garden Grove Alameda Santa Clara Alameda Santa Clara Los Angeles Orange County 100 1 1 1 1 1 Accessed

Although there are many cases where LRU ends up being the best or close-enough-to-the-best policy, this is not always the case For example, suppose that we also keep track of how many times information is accessed Our table might be amended as shown in Table 4-2 As you can see, even though Pleasanton was queried 100 times, it wasn't the object of the last five queries Then, when San Ramon was queried, LRU forced out Pleasanton because it hadn't been requested recently Since the cost of accessing information from its originating source can be very high, it can be better in the long term if things like access counts are taken into consideration Using caches to duplicate information can improve performance if the cache is more physically proximate, naturally quicker to access, or both The speed of light guarantees that a more proximate structure is always quicker to contact than a remote source That's just a rule of physics, and there is no getting around it Network optimizations aside, if I'm in San Francisco and I have to access my e-mail, it's going to take longer if the e-mail database is in New York than if it's in San Francisco On your computer, a CPU maintains a cache so that a memory request doesn't need to travel along the system bus to the actual static RAM chips Similarly, Web browsers maintain a cache so that they don't have to send a request over a network and withstand network latencies for a reply from the originating source Figure 4-1 illustrates this similarity In both cases, the reasoning is the same: It's physically faster to query a more proximate source

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