ASP.NET Web PDF Document Viewer/Editor Control Library

With an IOT, the space overhead of the primary key index is removed, as the index is the data, and the data is the index The fact is that an index is a complex data structure that requires a lot of work to manage and maintain, and the maintenance requirements increase as the width of the row to store increases A heap, on the other hand, is trivial to manage by comparison There are efficiencies in a heap organized table over an IOT That said, IOTs have some definite advantages over their heap counterparts For example, I once built an inverted list index on some textual data (this predated the introduction of interMedia and related technologies) I had a table full of documents, and I would parse the documents and find words within them.

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int32 '<StartupCode>'.Hw::i@3

My table looked like this: create table keywords ( word varchar2(50), position int, doc_id int, primary key(word,position,doc_id) ); Here I had a table that consisted solely of columns of the primary key I had over 100 percent overhead; the size of my table and primary key index were comparable (actually, the primary key index was larger since it physically stored the rowid of the row it pointed to, whereas a rowid is not stored in the table it is inferred) I only used this table with a WHERE clause on the WORD or WORD and POSITION columns That is, I never used the table I used only the index on the table The table itself was no more than overhead I wanted to find all documents containing a given word (or near another word, and so on).

The KEYWORDS heap table was useless, and it just slowed down the application during maintenance of the KEYWORDS table and doubled the storage requirements This is a perfect application for an IOT Another implementation that begs for an IOT is a code lookup table Here you might have ZIP_CODE to STATE lookup, for example You can now do away with the heap table and just use an IOT itself Anytime you have a table that you access via its primary key exclusively, it is a possible candidate for an IOT..

// do Console.WriteLine("Input a number:");; IL_0006: ldstr "Input a number:" IL_000b: call void [mscorlib]System.Console::WriteLine(string) IL_0010: ldnull // let v = Int32.Parse(Console.ReadLine());; IL_0011: stsfld class [fslib]Microsoft.FSharp.Core.Unit '<StartupCode>'.Hw::_doval@6@6 IL_0016: call string [mscorlib]System.Console::ReadLine() IL_001b: call int32 [mscorlib]System.Int32::Parse(string) IL_0020: stsfld int32 '<StartupCode>'.Hw::v@8 // do Console.WriteLine(i * v);; IL_0025: ldc.i4.2 IL_0026: call int32 Hw::get_v() IL_002b: mul IL_002c: call void [mscorlib]System.Console::WriteLine(int32)

When you want to enforce co-location of data or you want data to be physically stored in a specific order, the IOT is the structure for you For users of Sybase and SQL Server, this is where you would have used a clustered index, but IOTs go one better A clustered index in those databases may have up to a 110 percent overhead (similar to the previous KEYWORDS table example) Here, we have a 0 percent overhead since the data is stored only once A classic example of when you might want this physically co-located data would be in a parent/child relationship Let s say the EMP table had a child table containing addresses You might have a home address entered into the system when the employee is initially sent an offer letter for a job Later, he adds his work address.

Over time, he moves and changes the home address to a previous address and adds a new home address Then he has a school address he added when he went back for a degree, and so on That is, the employee has three or four (or more) detail records, but these details arrive randomly over time In a normal heap based table, they just go anywhere The odds that two or more of the address records would be on the same database block in the heap table are very near zero However, when you query an employee s information, you always pull the address detail records as well The rows that arrive over time are always retrieved together.

IL_0031: ldnull IL_0032: stsfld class [fslib]Microsoft.FSharp.Core.Unit '<StartupCode>'.Hw::_doval@11@11 IL_0037: ret } // end of method Hw::_main The ldxxx instructions are used to load values onto the operand s stack of the abstract machine, and the stxxx instructions store values from that stack in locations (locals, arguments, or class fields). In this example, variables are declared as top level, and the compiler introduces static fields into the Hw class. The first assignment requires the value 2 to be loaded onto the stack using the ldc instruction, and the stfld instruction stores the value in the static variable that represents i in the compiled program. For method invocations, arguments are loaded on the stack, and a call operation is used to invoke the method. The JIT compiler is responsible for generating the binary code that will run on the actual processor. The code generated by the JIT interacts with all the elements of the runtime, including external code loaded dynamically in the form of DLLs or COM components.