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physical address of the row it points to, the rowid. An IOT secondary index cannot do this; it must use some other way to address the row. This is because a row in an IOT can move around a lot, and it does not migrate in the way a row in a heap organized table would. A row in an IOT is expected to be at some position in the index structure, based on its primary key value; it will only be moving because the size and shape of the index itself is changing. (We ll cover more about how index structures are maintained in the next chapter, Indexes .) To accommodate this, Oracle introduced a logical rowid. These logical rowids are based on the IOT s primary key. They may also contain a guess as to the current location of the row, although this guess is almost always wrong because after a short while, data in an IOT tends to move. The guess is the physical address of the row in the IOT when it was first placed into the secondary index structure. If the row in the IOT has to move to another block, the guess in the secondary index becomes stale. Therefore, an index on an IOT is slightly less efficient than an index on a regular table. On a regular table, an index access typically requires the I/O to scan the index structure and then a single read to read the table data. With an IOT, typically two scans are performed: one on the secondary structure and the other on the IOT itself. That aside, indexes on IOTs provide fast and efficient access to the data in the IOT using columns other than the primary key.

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Getting the right mix of data on the index block versus data in the overflow segment is the most critical part of the IOT setup. Benchmark various scenarios with different overflow conditions, and see how they will affect your INSERTs, UPDATEs, DELETEs, and SELECTs. If you have a structure that is built once and read frequently, stuff as much of the data onto the index block as you can. If you frequently modify the structure, you will have to achieve some balance between having all of the data on the index block (great for retrieval) versus reorganizing data in the index frequently (bad for modifications). The FREELIST consideration you had for heap tables applies to IOTs as well. PCTFREE and PCTUSED play two roles in an IOT. PCTFREE is not nearly as important for an IOT as for a heap table, and PCTUSED doesn t come into play normally. When considering an OVERFLOW segment, however, PCTFREE and PCTUSED have the same interpretation as they do for a heap table; set them for an overflow segment using the same logic as you would for a heap table.

You saw earlier how to use the |> forward pipe operator to pipe values through a number of functions. This was a small example of the process of computing with functions, an essential and powerful programming technique in F#. In this section, we cover ways to compute new function values from existing ones using compositional techniques. First let s take a look at function composition. For example, consider the following code: let google = http "http://www.google.com" google |> getWords |> List.filter (fun s -> s = "href") |> List.length

I generally find people s understanding of what a cluster is in Oracle to be inaccurate Many people tend to confuse a cluster with a SQL Server or Sybase clustered index They are not the same A cluster is a way to store a group of tables that share some common column(s) in the same database blocks and to store related data together on the same block A clustered index in SQL Server forces the rows to be stored in sorted order according to the index key, similar to an IOT as just described With a cluster, a single block of data may contain data from many tables Conceptually, you are storing the data prejoined It can also be used with single tables where you are storing data together grouped by some column.