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Stepping through the initializeStudent method, we first note that we re using a specialized InvalidStudentException to report any problems that we encounter while attempting to initialize the Student whose unique ID (actually, the student s ssn) is passed in as an argument to this method:

select a, b, max(c) from t ... group by a select a, b, max(c) from t ... group by a,b select a, count(b), min(c) from t ... group by a select count(c) from t ... group by a

By far the fastest, most efficient type of cache available to Django, Memcached is an entirely memory-based cache framework originally developed to handle high loads at LiveJournal (http://wwwlivejournalcom/) and subsequently open-sourced by Danga Interactive (http:// dangacom/) It s used by sites such as Slashdot and Wikipedia to reduce database access and dramatically increase site performance Memcached is available for free at http://dangacom/memcached/ It runs as a daemon and is allotted a specified amount of RAM Its primary feature is to provide an interface a superlightning-fast interface for adding, retrieving, and deleting arbitrary data in the cache All data is stored directly in memory, so there s no overhead of database or filesystem usage After installing Memcached itself, you ll need to install the Memcached Python bindings, which are not bundled with Django directly These bindings are in a single Python module, memcache.

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public static Student initializeStudent(String sId) throws InvalidStudentException { We begin by constructing a dummy Student object: Student s = new Student(" "); We then attempt to pull this Student s information from the appropriate data file nnn-nn-nnnn.dat by fabricating the file name on the fly based on the student ID number passed in as argument sId to this method: String line = null; BufferedReader bIn = null; // Formulate the file name. String pathToFile = sId + ".dat"; try { // Open the file. bIn = new BufferedReader(new FileReader(pathToFile)); If we successfully open the file, we ll attempt to read the primary/header record first, parsing it into four fields/tokens, using the data to populate the attributes of Student object s: // // // // The file consists of a primary/header record, containing the student's basic info. (ssn, name, etc.), and 0 or more subsequent records representing a list of the sections that he/she is currently registered for.

The examples in Table 8-3 illustrate the following two general rules: You do not need to select the column expression you group on (see the last example). Any column expression that is not part of the GROUP BY clause can occur only in the SELECT clause as an argument to a group function. That s why the first example is invalid.

line = bIn.readLine(); if (line == null) { // Signal the problem via a custom Exception. throw new InvalidStudentException("Improperly formatted " + "file: " + pathToFile); } // We're going to parse the primary record into // four attributes -- ssn, name, major, and degree. StringTokenizer st = new StringTokenizer(line, "\t"); // If record doesn't have four columns, report an error. if (st.countTokens() != 4) { // Signal the problem via a custom Exception. throw new InvalidStudentException("Improperly formatted " + "record |" + line + "| in file " + pathToFile); } // Populate the newly crafted Student object with the information // read from the file. s.setSsn(st.nextToken());

py, which is available at http://wwwtummycom/Community/software/python-memcached/ To use Memcached with Django, set CACHE_BACKEND to memcached://ip:port/, where ip is the IP address of the Memcached daemon and port is the port on which Memcached is running In this example, Memcached is running on localhost (127001) port 11211: CACHE_BACKEND = 'memcached://127001:11211/' One excellent feature of Memcached is its ability to share cache over multiple servers This means you can run Memcached daemons on multiple machines, and the program will treat the group of machines as a single cache, without the need to duplicate cache values on each machine To take advantage of this feature with Django, include all server addresses in CACHE_BACKEND, separated by semicolons In this example, the cache is shared over Memcached instances running on the IP addresses 1721926240 and 1721926.

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