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'DD-MM-YYYY')), 'DD-MM-YYYY')), 'DD-MM-YYYY')), 'DD-MM-YYYY')) );

There is no limit on the number of interval partitions in a table. In our example here, the database will continue to create a new interval partition for each new month.

Cmd+Shift+D (Mac). The butterflies will appear in the new Butterfly layers that appear under the Garden layer. Rename these layers Butterfly02 and Butterfly03, and move them, as shown in Figure 1-35, above the Butterly01 layer.



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Suppose the transaction data in the previous example were not evenly distributed among the quarters. What if, due to business and cyclical reasons, an overwhelming number of sales occurred in the last two quarters, with the earlier quarters contributing relatively negligible sales Range partitioning will be good only in theory, because the last two quarters could end up each having almost half of the original nonpartitioned table s data. In such cases, it s better to use the hash-partitioning scheme. All you have to do is decide on the number of partitions, and Oracle s hashing algorithms will assign a hash value to each row s partitioning key and place it in the appropriate partition. You don t have to know anything about the distribution of the data in the table, other than that the data doesn t fall into some easily determined ranges. All you need to do is provide a partition key, which in the hash-partitioning scheme shown next is the ticket_no column: SQL> 2 3 4 CREATE TABLE sales_data (ticket_no NUMBER, sale_year INT NOT NULL, sale_month INT NOT NULL,





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Figure 1-35. Multiple selections can be placed in their own layers using the Distribute to Layers command. The next technique is one that addresses a very common issue encountered by Flash designers: taking content from one layer and placing it in the exact same position in another layer. This is an issue because you can t drag content from one layer to another.

5 sale_day INT NOT NULL) 6 PARTITION BY HASH (ticket_no) 7 PARTITIONS 4 8* STORE IN (ts1,ts2,ts3,ts4); Table created. SQL> In the preceding example, four hash partitions are created in four tablespaces. We won t know in which partition the data for, say, June 10, 2008, is stored. Oracle determines the storage based on a hashing algorithm, and you have no control whatsoever over the row-to-partition mapping.

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There may be times when you ll want to partition the data not on the basis of a time range or evenly distributed hashing scheme, but rather by known values, such as city, territory, or some such attribute. List partitioning is preferable to range or hash partitioning when your data is distributed among a set number of discrete values. For example, you may want to group a company s sales data according to regions rather than quarters. List partitioning enables you to group your data on the same lines as real-world groupings of data, rather than arbitrary ranges of time or some such criterion. For example, when you re dealing with statewide totals in the United States, you ll be dealing with 50 different sets of data. It makes more sense in this situation to partition your data into four or five regions, rather than use the range method to partition the data alphabetically. Listing 7-6 shows how to use list partitioning to partition the ticket_sales table. The partitions are made up of groups of flight-originating cities, shown by the start_city column. Listing 7-6. Creating a List-Partitioned Table SQL> 2 3 4 5 6 7 8 9 10 11 12* CREATE TABLE sales_data (ticket_no NUMBER, sale_year INT NOT NULL, sale_month INT NOT NULL, sale_day INT NOT NULL, destination_city CHAR(3), start_city CHAR(3)) PARTITION BY LIST (start_city) (PARTITION northeast_sales values ('NYC','BOS','PEN') TABLESPACE ts1, PARTITION southwest_sales values ('DFW','ORL','HOU') TABLESPACE ts2, PARTITION pacificwest_sales values('SAN','LOS','WAS') TABLESPACE ts3, PARTITION southeast_sales values ('MIA','CHA','ATL') TABLESPACE ts4);

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