rdlc data matrix

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By default, you can update the partition key as long as the row remains in the same partition. Updates to the partition key that would cause the row to be moved to another partition will result in the following error: ORA-14402: updating partition key column would cause a partition change In Oracle 8.1.5 and above, you can enable movement of updated rows between partitions using the E A L R W M V M N clause: N BE O OE ET

For example, if user IGAMA has been deleted from the Oracle Internet Directory, which will also deprovision his accounts, the following command will remove his Real-Time Collaboration data from the database: delete_userpl -dbname orcl -rtc_app_user rtc_app -rtc_app_password oracle1 -user igama.

ALTER TABLE tl ENABLE ROW MOVEMENT;

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printfn "Result 'num': %A Result 'ident': %A" num ident The result of this example when compiled and run is as follows: Result 'num': Success: Val 3.1416 Result 'ident': Success: Ident "anIdent" The other interesting point to note about this example is you use the function many1Satisfy. This is a function that allows us to create a parser from a predicate function, which it accepts as a parameter. The FPrasec library contains a number of other similar functions that are summarized in Table 13-4. The input text is fed to the predicate function and if it returns true for one or more charters then the parser created by many1Satisfy is successful. The predicate function takes a character and must return a Boolean, which represents whether the character is one that the parser accepts. In this case, you use the predefined predicate function isLetter which will return true for any character that is a letter. This is a powerful and convenient way to create parsers. Our examples show CharParsers.many1SatisfyL CharParsers.isLetter "identifier", which matches a continuous chain of more than one letter, but

From a performance point of view, partitioned tables perform well for queries where the partition key is known Consider a range-partitioned table containing one partition for each month over the last five years If there are no suitable indexes, then a query will have to perform a full table scan of all rows in each of the 60 partitions However, if the query knows the partition key, it can use this information to eliminate unnecessary partitions and scan only a single partition Similarly, if part of the partition key is known, then a smaller range of partitions might be scanned Therefore, partitions have the potential to minimize the amount of I/O performed by the database You can create indexes against partitioned tables These indexes may be either nonpartitioned or partitioned If the index is partitioned, then it may be either local or global.

Locally partitioned indexes have the same number of partitions as the table that they index The columns of a locally partitioned index key must include all the columns in the partition key for the table When a new partition is added to the table, a corresponding partition will also be added to the local index From a performance point of view, local indexes can be highly efficient or highly inefficient, depending on how they are accessed In a partitioned local index, each partition contains a separate B-tree If, for example, the index contains one partition for each month in the last five years, there would be 60 partitions and 60 separate B-trees When the locally partitioned index is accessed, if the partition key is known, Oracle can identify the partition directly and scan a single B-tree index.

It is highly likely that the depth of each partitioned B-tree would be lower than the B-tree depth of an equivalent nonpartitioned index; therefore, using the locally partitioned index would be more efficient However, if the partition key is not known when the locally partitioned index is accessed, then Oracle will need to scan all 60 B-trees for the relevant partition Depending on the number of rows in each partition, the optimizer may still decide to use this index in an execution plan, as it may still be more efficient than performing a full-table scan It will, however, be significantly less efficient than using the equivalent nonpartitioned index Maintenance of local indexes is highly efficient For example, if you drop a table partition, the corresponding local index partition will also be dropped The remaining partitions of the local index will be unaffected and will continue to be available.

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