TAILIEUCHUNG - OCA /OCP Oracle Database 11g A ll-in-One Exam Guide- P33

OCA /OCP Oracle Database 11g A ll-in-One Exam Guide- P33:There is an ever increasing demand for staff with IT industry certification. The benefits to employers are significant—they can be certain that staff have a certain level of competence—and the benefits to the individuals, in terms of demand for their services, are equally great. Many employers are now requiring technical staff to have certifications, and many IT purchasers will not buy from firms that do not have certified staff. | OCA OCP Oracle Database 11g All-in-One Exam Guide 276 of the table in order to find the relevant rows. If the table has billions of rows this can take hours. If there is an index on the relevant column s Oracle can search the index instead. An index is a sorted list of key values structured in a manner that makes the search very efficient. With each key value is a pointer to the row in the table. Locating relevant rows via an index lookup is far faster than using a full table scan if the table is over a certain size and the proportion of the rows to be retrieved is below a certain value. For small tables or for a WHERE clause that will retrieve a large fraction of the table s rows a full table scan will be quicker you can usually trust Oracle to make the correct decision regarding whether to use an index based on statistical information the database gathers about the tables and the rows within them. A second circumstance where indexes can be used is for sorting. A SELECT statement that includes the ORDER BY GROUP BY or UNION keyword and a few others must sort the rows into order unless there is an index which can return the rows in the correct order without needing to sort them first. A third circumstance when indexes can improve performance is when tables are joined but again Oracle has a choice depending on the size of the tables and the memory resources available it may be quicker to scan tables into memory and join them there rather than use indexes. The nested loop join technique passes through one table using an index on the other table to locate the matching rows this is usually a disk-intensive operation. A hash join technique reads the entire table into memory converts it into a hash table and uses a hashing algorithm to locate matching rows this is more memory and CPU intensive. A sort merge join sorts the tables on the join column and then merges them together this is often a compromise among disk memory and CPU resources. If there are no indexes then .

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