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This property is upheld by the database s concurrency control mechanisms, as you ll see in the following sections Although concurrent access is a hallmark of the relational database, isolation techniques make it appear as though users are executing transactions serially, one after another This chapter discusses how Oracle implements concurrency control the assurance of atomicity and isolation of individual transactions in a concurrently accessed database Durability: The last ACID property, durability, ensures that the database saves commit transactions permanently Once a transaction completes, the database should ensure that the transaction s changes are not lost This property is enforced by the database recovery mechanisms, which make sure that all committed transactions are retrieved As you saw in 5, Oracle uses the write-ahead protocol, which ensures that all changes are first written to the redo logs on disk before they re transferred to the database files on disk..



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Users can name a transaction to make it easier to monitor it, and there are several advantages to giving a meaningful name to a long-running transaction. For example, using the LogMiner utility, you can look for details of the specific transaction you re interested in. 16 shows how to use the LogMiner utility to help undo DML changes. Assigning names to transactions also makes it easier for the user to query the transaction details using the name column of the V$TRANSACTION view.

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In place of gets(), you can use a function that does check the length of the user input. The following is a function called safe_gets() that does the trick: #define EOLN '\n' void safe_gets (char *input, int max_chars) { int count = 0; char next_char; do { next_char = getchar(); if (next_char != EOLN) input[count++] = next_char; } while ((count < max_chars-1) && (next_char != EOLN)); input[count]=0; } The safe_gets() function is called differently than gets(). The gets() function only takes a buffer as input. The safe_gets() function takes two parameters: a buffer called input, and max_chars, an integer that specifies the maximum number of characters that the function should put into the buffer. As safe_gets() adds characters into the input buffer, it continuously checks to make sure it is not writing more characters than the input buffer can hold. The safe_gets() function has two local variables. The first is count, the current number of characters that have been input. The other is next_char, a one-byte character that stores the next character of input. Using a function called getchar(),5 safe_gets() accepts one character of input at a time, so long as count is less than the maximum number of characters it is allowed to accept and the user input has not ended yet. The getchar() function returns EOLN (for end of line) when there is no more user input to accept. When the do...while loop starts executing, count is less than max_chars-1, and it is safe to put next_char into the input buffer because you are not going to overrun or overflow the

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To ensure data consistency, each user must see a consistent set of data that includes all changes made by that user s transactions as well as all the other users transactions. In a single-user database, it s a trivial matter to achieve data consistency. However, real-life databases need to allow simultaneous operations by numerous users, a requirement that s known as data concurrency. Improper interactions among transactions can cause data to become inconsistent. Transaction concurrency is achieved by managing various users simultaneous transactions without permitting any interference among them. If you re the only user of the database, you don t need to worry about concurrency control of transactions. However, in most cases, databases enable thousands of users to perform simultaneous select, update, insert, and delete transactions against the same table. One solution to concurrency control is to lock the entire table for the duration of each operation, so one user s transactions do not impact another s. Thus, each user would be operating in isolation, thereby sacrificing data concurrency. However, this would mean that access to the table would be severely reduced. As you ll see, Oracle does use locking mechanisms to keep the data consistent, but the locking is done in the least restrictive fashion, with the goal of maintaining the maximum amount of concurrency. Concurrency no doubt increases the throughput of an RDBMS, but it brings along its own special set of problems, which we ll look at next.

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