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Oracle will take a lock at the lowest level possible (i.e., the least restrictive lock possible) and convert that lock to a more restrictive level if necessary. For example, if you select a row from a table with the FOR UPDATE clause, two locks will be created. One lock is placed on the row(s) you selected (and this will be an exclusive lock; no one else can lock that specific row in exclusive mode). The other lock, a ROW SHARE TABLE lock, is placed on the table itself. This will prevent other sessions from placing an exclusive lock on the table and thus prevent them from altering the structure of the table, for example. Another session can modify any other row in this table without conflict. As many commands as possible that could execute successfully given there is a locked row in the table will be permitted. Lock escalation is not a database feature. It is not a desired attribute. The fact that a database supports lock escalation implies there is some inherent overhead in its locking mechanism and significant work is performed to manage hundreds of locks. In Oracle, the overhead to have 1 lock or 1 million locks is the same: none.

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Values of type Async<'a> are usually run using the functions listed in Table 13-4. Async<'a> values can be built by using functions and members in the F# libraries.

The three general classes of locks in Oracle are as follows: DML locks: DML stands for Data Manipulation Language. In general this means SELECT, INSERT, UPDATE, MERGE, and DELETE statements. DML locks are the mechanism that allows for concurrent data modifications. DML locks will be, for example, locks on a specific row of data or a lock at the table level that locks every row in the table. DDL locks: DDL stands for Data Definition Language, (CREATE and ALTER statements, and so on). DDL locks protect the definition of the structure of objects. Internal locks and latches: Oracle uses these locks to protect its internal data structures. For example, when Oracle parses a query and generates an optimized query plan, it will latch the library cache to put that plan in there for other sessions to use. A latch is a lightweight, low-level serialization device employed by Oracle, similar in function to a lock. Do not confuse or be misled by the term lightweight; latches are a common cause of contention in the database, as you will see. They are lightweight in their implementation, but not their effect.

We will now take a more detailed look at the specific types of locks within each of these general classes and the implications of their use. There are more lock types than I can cover here. The ones I cover in the sections that follow are the most common and are held for a long duration. The other types of locks are generally held for very short periods of time.

Async.Run: Async<'a> -> 'a Async.Spawn: Async<unit> -> unit Async.SpawnChild: Async<unit> -> Async<unit>

One of the most perplexing things for a DBA can be setting the individual parameters, especially parameters such as SORT|HASH_AREA_SIZE and so on I often see systems running with incredibly small values for these parameters values so small that system performance is massively impacted in a negative way This is probably a result of the fact that the default values are very small themselves: 64KB for sorting and 128KB for hashing There s a lot of confusion over how big or small these values should be Not only that, but the values you should use for them might vary over time, as the day goes by At 8:00 am, with two users, a 50MB sort area size might be reasonable for the two users logged in However, at 12:00 pm with 500 users, 50MB might not be appropriate.

This is where the WORKAREA_SIZE_POLICY = AUTO setting and the corresponding PGA_AGGREGATE_TARGET come in handy Setting the PGA_AGGREGATE_TARGET, the amount of memory you would like Oracle to feel free to use to sort and hash, is conceptually easier than trying to figure out the perfect SORT|HASH_AREA_SIZE, especially since there isn't a perfect value for these parameters; the perfect value varies by workload Historically, DBAs configured the amount of memory Oracle would use by setting the size of the SGA (the buffer cache; the log buffer; and the shared, large, and Java pools) The remaining memory on the machine would then be used by the dedicated or shared servers in the PGA region The DBA had little control over how much of this memory would or would not be used.

Runs an operation in the thread pool and waits for its result. Queues the asynchronous computation as an operation in the thread pool. Queues the asynchronous computation, initially as a work item in the thread pool, but inherits the cancellation handle from the current asynchronous computation.