.NET/Java PDF, Tiff, Barcode SDK Library

You can also build strings using objects of the .NET type System.Text.StringBuilder. These objects are mutable buffers that you can use to accumulate and modify text, and they are more efficient than repeated uses of the + operator. Here s an example: > let buf = new System.Text.StringBuilder();; val buf : System.Text.StringBuilder > buf.Append("Humpty Dumpty");; > buf.Append(" sat on the wall");; > buf.ToString();; val it : string = "Humpty Dumpty sat on the wall"

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Earlier, in 1, we briefly looked at the parameter CURSOR_SHARING, which can work as a short-term crutch in this area The only real way to solve this issue, however, is to use reusable SQL in the first place Even on the largest of large systems, I find that there are typically at most 10,000 to 20,000 unique SQL statements Most systems execute only a few hundred unique queries The following real-world example demonstrates just how bad things can get if you use the shared pool poorly I was asked to work on a system where the standard operating procedure was to shut down the database every night, to wipe out the SGA and restart it clean.

The reason for doing this was that the system was having issues during the day whereby it was totally CPU-bound and, if the database were left to run for more than a day, performance really started to decline They were using a 1GB shared pool inside of a 11GB SGA This is true: 01GB dedicated to block buffer cache and other elements and 1GB dedicated to caching unique queries that would never be executed again The reason for the cold start was that if they left the system running for more than a day, they would run out of free memory in the shared pool At that point, the overhead of aging structures out (especially from a structure so large) was such that it overwhelmed the system and performance was massively degraded (not that performance was that great anyway, since they were managing a 1GB shared pool).

Note For compatibility with OCaml, the ^ operator can also be used for string concatenation, though it is

Furthermore, the people working on this system constantly wanted to add more and more CPUs to the machine, as hard-parsing SQL is so CPU-intensive By correcting the application and allowing it to use bind variables, not only did the physical machine requirements drop (they then had many times more CPU power than they needed), but also the allocation of memory to the various pools was reversed Instead of a 1GB shared pool, they had less than 100MB allocated and they never used it all over many weeks of continuous uptime One last comment about the shared pool and the parameter SHARED_POOL_SIZE In Oracle9i and before, there is no direct relationship between the outcome of the query.

DML locks are used to ensure that only one person at a time modifies a row and that no one can drop a table upon which you are working. Oracle will place these locks for you, more or less transparently, as you do work.

Some of the foundational data structures of F# coding are tuples, lists, and options. In the following sections, we discuss these and some related topics by example.

A TX lock is acquired when a transaction initiates its first change, and it is held until the transaction performs a COMMIT or ROLLBACK. It is used as a queuing mechanism so that other sessions can wait for the transaction to complete. Each and every row you modify or SELECT FOR UPDATE in a transaction will point to an associated TX lock for that transaction. While this sounds expensive, it is not. To understand why this is, you need a conceptual understanding of where locks live and how they are managed. In Oracle, locks are stored as an attribute of the data (see 10 Database Tables for an overview of the Oracle block format). Oracle does not have a traditional lock manager that keeps a long list of every row that is locked in the system. Many other databases do it that way because, for them, locks are a scarce resource, the use of which needs to be monitored. The more locks are in use, the more these systems have to manage, so it is a concern in these systems if too many locks are being used. In a database with a traditional memory-based lock manager, the process of locking a row would resemble the following: 1. 2. 3. Find the address of the row you want to lock. Get in line at the lock manager (which must be serialized, as it is a common inmemory structure). Lock the list.

4. 5. 6.