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Normally, objects are created in a LOGGING fashion, meaning all operations performed against them that can generate redo will generate it. NOLOGGING allows certain operations to be performed against that object without the generation of redo; we covered this in the 9 Redo and Undo in some detail. NOLOGGING affects only a few specific operations, such as the initial creation of the object, direct path loads using SQL*Loader, or rebuilds (see the SQL Language Reference Manual for the database object you are working with to see which operations apply). This option does not disable redo log generation for the object in general only for very specific operations. For example, if I create a table as SELECT NOLOGGING and then INSERT INTO THAT_TABLE VALUES ( 1 ), the INSERT will be logged, but the table creation might not have been (the DBA can force logging at the database or tablespace level).

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Each block in a segment has a block header. Part of this block header is a transaction table. Entries will be made in the transaction table to describe which transactions have what rows/elements on the block locked. The initial size of this transaction table is specified by the INITRANS setting for the object. For tables, this defaults to 2 (indexes default to 2 as well). This transaction table will grow dynamically as needed up to MAXTRANS entries in size (given sufficient free space on the block, that is). Each allocated transaction entry consumes 23 to 24 bytes of storage in the block header. Note that as of Oracle 10g, MAXTRANS is ignored all segments have a MAXTRANS of 255.

st = = int (byteU st) = int (byteU st) = int (byteU st) = int (byteU st) (b1 <<< 8) ||| (b2 <<< 16) ||| (b3 <<< 24)

A heap organized table is probably used 99 percent (or more) of the time in applications. A heap organized table is the type of table you get by default when you issue the CREATE TABLE statement. If you want any other type of table structure, you need to specify that in the CREATE statement itself. A heap is a classic data structure studied in computer science. It is basically a big area of space, disk, or memory (disk in the case of a database table, of course) that is managed in an apparently random

fashion Data will be placed where it fits best, rather than in any specific sort of order Many people expect data to come back out of a table in the same order it was put into it, but with a heap, this is definitely not assured In fact, rather the opposite is guaranteed: the rows will come out in a wholly unpredictable order This is quite easy to demonstrate In this example, I will set up a table such that in my database I can fit one full row per block (I am using an 8KB block size) You do not need to have the case where you only have one row per block I am just taking advantage of this to demonstrate a predictable sequence of events.

These functions have the following types: val val val val val val byteP byteU boolP boolU int32P int32U : : : : : : byte pickler byte unpickler bool pickler bool unpickler int pickler int unpickler

The following sort of behavior (that rows have no order) will be observed on tables of all sizes, in databases with any block size: ops$tkyte%ORA11GR2> create table t 2 ( a int, 3 b varchar2(4000) default rpad('*',4000,'*'), 4 c varchar2(3000) default rpad('*',3000,'*') 5 ) 6 / Table created ops$tkyte%ORA11GR2> insert into t (a) values ( 1); 1 row created ops$tkyte%ORA11GR2> insert into t (a) values ( 2); 1 row created ops$tkyte%ORA11GR2> insert into t (a) values ( 3); 1 row created ops$tkyte%ORA11GR2> delete from t where a = 2 ; 1 row deleted ops$tkyte%ORA11GR2> insert into t (a) values ( 4); 1 row created ops$tkyte%ORA11GR2> select a from t; A ---------1 4 3 Adjust columns B and C to be appropriate for your block size if you would like to reproduce this.

For example, if you have a 2KB block size, you do not need column C, and column B should be a VARCHAR2(1500) with a default of 1,500 asterisks Since data is managed in a heap in a table like this, as space becomes available, it will be reused..

So far, so simple. One real advantage of this approach comes as you write combinators that put these together in useful ways. For example for tuples: let tup2P p1 p2 (a, b) (st: outstate) = (p1 a st : unit) (p2 b st : unit) let tup3P (p1 a (p2 b (p3 c p1 st st st p2 p3 (a, b, c) (st: outstate) = : unit) : unit) : unit)