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Last but not least, the JavaScript s native String object has been extended in the xyz to include a handful of useful additions to once again make it somewhat more similar to the String class in the .NET Framework. These additions can be very useful because string processing in one form or another is done quite often in most applications. Other than two formatting methods (similar to those found in the Date and Number extensions), the String extension includes a few trimming methods among others as shown in Table 4-8.

cpu elapsed disk query current -------- ---------- ---------- ---------- ---------0.00 0.00 0 0 0 0.18 0.19 0 0 0 0.00 0.00 0 35 0 -------- ---------- ---------- ---------- ---------0.18 0.19 0 35 0

rows ---------0 0 5 ---------5

Returns a boolean value indicating whether or not the end of the String object matches the specified string Formats a string by replacing placeholders with provided values

Misses in library cache during parse: 1

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The first thing to note is how the tag was retained by the SQL statement, thus enabling us to clearly see the profile of the statement separately. The tkprof output itself reveals the following: There were a total of five parses, which implies that the statement was parsed in every iteration of the loop. The 1 after the label Misses in library cache during parse indicates that the very first parse did not find the statement in the shared pool; hence, it was a hard parse. The remaining four parses were soft parses. Looking at the tkprof output for our second loop, we see the following: select /*+ prepareStatement() outside loop */ empno, job from emp where ename = :1

Formats a string by replacing placeholders with provided values with locale specificity Returns a boolean value indicating whether or not the start of the String object matches the specified string Removes leading and trailing spaces from a String object Removes trailing spaces from a String object Removes leading white spaces from a String object

cpu elapsed disk query current -------- ---------- ---------- ---------- ---------0.00 0.00 0 0 0 0.01 0.00 0 0 0 0.00 0.00 0 35 0 -------- ---------- ---------- ---------- ---------0.01 0.00 0 35 0

rows ---------0 0 5 ---------5

The following small script illustrates usage of some of the main methods of the String extension:

Misses in library cache during parse: 1 We can see that in case 2, Oracle needed to parse only once (a hard parse, as indicated by the misses in library cache being 1) for all five iterations. We can conclude that whenever possible, we should prepare a statement only once, and bind or execute it many times to reduce the number of soft parses and the associated overhead. However, there are situations where this may not be straightforward. For example, I work in an environment where there are around 500 other developers all over the world working on the same product with different components. With each request, statements and result sets are created and closed using a centralized piece of code that implements connection pooling (connection pooling is covered in the next chapter). If I wanted to implement statement caching in such a scenario, I would have to implement and maintain my own centralized cache associated with a connection object, through which all code would need to be channeled. The closing of statements and cursors would also need to go through this piece of code, requiring a disciplined approach from all the developers. We would also have to manage the cache (aging out statements and so on). Fortunately, with JDBC 3.0, this functionality (called statement caching) is now available as part of JDBC, wherein this cache is created and managed transparently by the driver. Before we look at statement caching, we will look at the related concept of session cursor caching, which is a mechanism Oracle provides to cache the cursors automatically in the session on the server side, to reduce the impact of soft parsing. We will then examine PL/SQL cursor caching, after which we will discuss JDBC statement caching.

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