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advance (though not to strncmp), this complexity is unnecessary; we know the counts are right so checking for the \O wastes time Third, s t r c h r is also complex, since it must look for the character and also atch for the \O byte that terminates the message For a given call to isspam, the message is fixed, so time spent looking for the \O is wasted since we know where the message ends Finally, although strncmp, s t r c h r , and s t r l e n are all efficient in isolation, the overhead of calling these functions is comparable to the cost of the calculation they will perform It's more efficient to do all the work in a special, carefully written version of s t r s t r and avoid calling other functions altogether These sorts of problems are a common source of performance trouble-a routine or interface works well for the typical case, but performs poorly in an unusual case that happens to be central to the program at issue The existing s t r s t r was fine when both the pattern and the string were short and changed each call, but when the string is long and fixed, the overhead is prohibitive With this in mind, s t r s t r was rewritten to walk the pattern and message strings together looking for matches, without calling subroutines The resulting implementation has predictable behavior: it is slightly slower in some cases, but much faster in the spam filter and, most important, is never terrible To verify the new implementation's correctness and performance, a performance test suite was built This suite included not only simple examples like searching for a word in a sentence, but also pathological cases such as looking for a pattern of a single x in a string of a thousand e's and a pattern of a thousand x's in a string of a single e, both of which can be handled badly by naive implementations Such extreme cases are a key part of performance evaluation The library was updated with the new s t r s t r and the sparn filter ran about 30% faster, a good payoff for rewriting a single routine Unfortunately, it was still too slow When solving problems, it's important to ask the right question Up to now, we've been asking for the fastest way to search for a textual pattern in a string But the real problem is to search for a large, fixed set of textual patterns in a long, variable string Put that way, s t r s t r is not so obviously the right solution The most effective way to make a program faster is to use a better algorithm With a clearer idea of the problem, it's time to think about what algorithm would work best The basic loop, f o r ( i = 0 ; i < npat; i++) i f (strstr(mesg, p a t [ i ] ) != NULL) return 1; scans down the message npat independent times; assuming it doesn't find any matches, it examines each byte of the message npat times, for a total of s t r l en (mesg) m p a t comparisons.

Interface We decided on three basic operations: c h a r c-csvgetl ine(F1LE c - ) : read a new CSV line c h a r c - c s v f i e l d ( i n t n): return the n-th field of the current line i n t csvnf i e l d (voi d): return the number of fields on the current line What function value should c s v g e t l i ne return It is desirable to return as much useful information as convenient, which suggests returning the number of fields, as in the prototype But then the number of fields must be computed even if the fields aren't being used Another possible value is the input line length, which is affected by whether the trailing newline is preserved After several experiments, we decided that c s v g e t l i n e will return a pointer to the original line of input, or NULL if end of file has been reached We will remove the newline at the end of the line returned by c s v g e t l i ne, since it can easily be restored if necessary The definition of a field is complicated; we have tried to match what we observe empirically in spreadsheets and other programs A field is a sequence of zero or more characters Fields are separated by commas Leading and trailing blanks are preserved A field may be enclosed in double-quote characters, in which case it may contain commas A quoted field may contain double-quote characters, which are represented by a doubled double-quote; the CSV field " x " " y W defines the string x"y Fields may be empty; a field specified as "" is empty, and identical to one specified by adjacent commas Fields are numbered from zero What if the user asks for a non-existent field by calling s v f i e l d(-1) or c s v f i e l d (100000) We could return " " (the empty string) because this can be printed and compared; programs that process variable numbers of fields would not have to take special precautions to deal with non-existent ones But that choice provides no way to distinguish empty from non-existent A second choice would be to print an error message or even abort; we will discuss shortly why this is.

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"In theory there is no difference between theory and practice But, in practice, there is" Jan LA van de Snepscheut You don't have to specialize to find useful ideas in this book Over and over again, we have found that basic matters that are true for DBMS #1 are also true for DBMS #2, DBMS #3, and so on, across the board For example, we can say that "DBMSs store data in fixed-size pages and the size is a power of two" But isn't that a bold generalization Let's be honest We have not checked this statement on every DBMS that exists, we know it's not a law of nature, and in fact we know of at least two DBMSs for which the statement is false But, in this book, when we make a claim or "all DBMSs" or just "DBMSs" we're not being vague or general we mean, very specifically, eight particular DBMSs that we have actually tested and for which we guarantee that the statement is true at time of writing We call these DBMSs "the Big Eight" not a standard term, but a convenient way to direct your memory to this introductory explanation We chose the Big Eight according to the following criteria:.

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dictionary sorts and BYTE columns to test binary sorts Ingres doesn't provide SQL Standardcompliant CHARACTER SET or COLLATE options For InterBase, these criteria meant that the InterBase database was created with DEFAULT CHARACTER SET WIN1252 We used NCHAR columns with COLLATE EN_US to test dictionary sorts and NCHAR columns with no COLLATE clause to test binary sorts We also used NCHAR columns with (a) COLLATE DA_DA to test Danish/Norwegian sorts, (b) COLLATE DE_DE to test German sorts, (c) COLLATE IS_IS to test Icelandic sorts, (d) COLLATE EN_UK to test Irish sorts, (e) COLLATE ES_ES to test Spanish sorts, and (f) COLLATE FI_FI and COLLATE SV_SV to test Swedish/Finnish sorts For Microsoft, these criteria meant that SQL Server was installed with the default "1252/ISO" Character Set and the default "Dictionary Order, case insensitive" Sort Order for CHAR columns, and a nondefault "Binary" Unicode Collation We used CHAR columns with no COLLATE clause to test dictionary sorts and CHAR columns with COLLATE SQL_Latin1_General_BIN to test binary sorts We also used CHAR columns with (a) COLLATE SQL_Danish to test Danish/Norwegian sorts, (b) COLLATE German_PhoneBook to test German phone book sorts, (c) COLLATE SQL_Icelandic to test Icelandic sorts, (d) COLLATE Mexican_Trad_Spanish and COLLATE Modern_Spanish to test Spanish sorts, and (e) COLLATE SQL_SwedishStd to test Swedish/Finnish sorts (Note: Where applicable, PREF was always indicated, the code page was 1252, case sensitivity was CI, and accent sensitivity was AS) For MySQL, these criteria meant that MySQL was installed with the default "Latin1" (aka iso_1) character set We used CHAR columns to test dictionary sorts and CHAR BINARY columns to test binary sorts MySQL doesn't provide SQL Standard-compliant CHARACTER SET or COLLATE options For Oracle, these criteria meant that Oracle was installed with the default "WIN1252" character set We used CHAR columns with NLS_SORT=XWEST_EUROPEAN to test dictionary sorts and CHAR columns with NLS_SORT=BINARY to test binary sorts We also used CHAR columns with (a) NLS_SORT=DANISH and NLS_SORT=NORWEGIAN to test Danish/Norwegian sorts, (b) NLS_SORT=XGERMAN to test German dictionary sorts, (c) NLS_SORT=GERMAN_DIN to test German phone book sorts, (d) NLS_SORT=ICELANDIC to test Icelandic sorts, (e) NLS_SORT=XWEST_EUROPEAN to test Irish sorts, (f) NLS_SORT=XSPANISH to test Spanish Traditional sorts, (g) NLS_SORT=SPANISH to test Spanish Modern sorts, and (h) NLS_SORT=FINNISH to test Swedish/Finnish sorts For Sybase, these criteria meant that Sybase was installed with the nondefault "Character Set = iso_1" and nondefault "Sort Order = Dictionary" We used CHAR columns to test dictionary sorts and BINARY columns to test binary sorts Sybase doesn't provide SQL Standard-compliant CHARACTER SET or OLLATE options.

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