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The following sample shows how to use these operators to encode 32-bit integers into 1, 2, or 5 bytes, represented by returning a list of integers. Integers in the range 0 to 127 return a list of length 1: let encode (n: int32) = if (n >= 0 && n <= 0x7F) then [ n ] elif (n >= 0x80 && n <= 0x3FFF) then [ (0x80 ||| (n >>> 8)) &&& 0xFF; (n &&& 0xFF) ] else [ 0xC0; ((n >>> 24) &&& 0xFF); ((n >>> 16) &&& 0xFF); ((n >>> 8) &&& 0xFF); (n &&& 0xFF) ] Here s an example of the function in action: > encode 32;; val it : int32 list = [32] > encode 320;; val it : int32 list = [129; 64] > encode 32000;; val it : int32 list = [192; 0; 0; 125; 0]

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This strategy is good when modifications cannot be made to the database in use Be sure to build only columns that could change into the where clause The disadvantage to this approach is the amount of code it takes and the amount of work that must be done at runtime, including marshaling of data across the wire and the complexity of the database queries..

In this section, we ll enable inserts on the object view. If we try to insert data without having created any instead of triggers, the insert operation fails as follows: benchmark@ORA10G> insert into components_or_view values 2 ( 3 3, 'component 3', 4 part_type_tab(part_type(3,6,'part 11', 'part 11 description')) 5 ); insert into components_or_view values * ERROR at line 1: ORA-01733: virtual column not allowed here For the preceding insert to work, we need to write an instead of insert trigger on the components_or_view itself as follows: benchmark@ORA10G> create or replace trigger components_or_view_io_insert 2 instead of insert on components_or_view 3 begin First, we insert into the parent relational table components_rel: 5 6 7 insert into components_rel( component_id, component_name ) values ( :new.component_id, :new.component_name );

Numeric types are not implicitly converted conversions between different numeric types must be made explicitly. You do this by using overloaded conversion operators. These work in the same way as overloaded infix operators such as + and *. Table 3-4 shows the primary conversion operators.

Then we insert into the child table parts_rel any new child records. Any duplicate records are filtered out based on the primary key of the child table (in this case, the primary key of the child table parts_rel is the column part_id): 9 10 11 12 13 14 15 insert into parts_rel select * from TABLE( cast( :new.parts as part_type_tab ) ) where part_id not in ( select part_id from parts_rel ); end; /

If you have no control over the database schema, but the overhead of the last approach is too much to bear, you can update and query on only those column values that have changed. Unfortunately, this approach requires dynamic generation of SQL statements, so it is generally frowned upon. For tables with high column counts, this approach may be worth the trade-off. There is another business rule that must be present before adopting this approach. When user A moves a change to "address" back to the database, it must be irrelevant if user B has changed "state" in the meantime. Using this approach, "address" will get updated with the new value from user A, but "state" will remain the value that user B set it to. While technically both changes were based on fresh data, the combination of values might be invalid. You could end up with an author from Green Bay, MN. (East coasters: Green Bay is in Wisconsin.) So, if your requirements can overlook all of the glaring deficiencies of this method, here s what it would look like (see Concurrency2.aspx in Web10). private bool UpdateAuthors(DataSet ds) { string sql = ""; string sqlBase = " update authors set {0} where au_id = '{1}'{2}"; string sqlUpdate = ""; string sqlWhere = "";

Convert/truncate to sbyte Convert/truncate to byte Convert/truncate to int16 Convert/truncate to uint16 Convert/truncate to int32 Convert/truncate to uint32 Convert/truncate to int64 Convert/truncate to uint64 Convert to float32/single Convert to float/double

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