Join methods in oracle

Hello,
I understand what a nested loop, merge sort and hash join does in oracle. Can someone tell me which scenerio the optimizer will choose the above join method.
can someone explain me which context this join methods will be used with a small eg?
I would appreciate your great help in this...

Not really.
Lets assume that a table is "properly indexed" when it has indexes that give us the optimal balance of DML performance and query performance, i.e. there are enough indexes to answer our questions without index maintenance overburdening inserts, updates or deletes.
That said, whether or not an index is used is depends on a number of details, important details.
The fundamental question is: can the optimizer retrieve the data you want with more or less I/O via an index or via a full table scan? As I stated initially, a table comprised of 1 or 2 blocks should always see a full table scan. After that, the proportion of data you are retrieving from the table is the most important factor. A not unreasonable starting point is 10%, if you are retrieving less than 10% of the data in a table then an index may be of use and if you are retrieving more than 10% of the data then an index may well not be of use. From there you want to consider factors such as:
1. The selectivity of an index varies depending on the value(s) we are selecting. We create histograms exactly because we expect the utility of an index to vary with respect to the values selected.
2. The physical distribution or clustering of data matters a great deal. An index on order lines will typically have very poor clustering with respect to the inventory items ordered because the order lines for a given type of tennis shoe are scattered semi-uniformly across the table. In comparison, an index on order number will typically have very good clustering because the relevant order lines were inserted at roughly the same time and are probably quite close to one another physically.
3. Scads of other details that aren't coming to mind right now.
Cheers,
Scott

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