Index Organized Tables – the Basics.

..>IOT2 – Examples and proofs
….>IOT3 – Greatly reducing IO with IOTs
……>IOT4 – Boosting Buffer Cache Efficiency
……..>IOT5 – Primary Key issues
……….>IOT6a – Slowing Down Insert
…………>IOT6(B) – OLTP Inserts

I think Index Organized Tables(IOTs) are a much under-used and yet very useful feature of Oracle. Over the next few postings I’m going to cover some aspect of Index Organised Tables, both good and not-so-good. I am going to cover some benefits of IOTs that I think many people are unaware of. In this first post I am just going to run through the basics of IOTs.

The idea behind an IOT is simple. You hold all the data for the table in the ordered structure of an index. Why would you want to do that? Let us consider a very common requirement, accessing a row in a “large” table via a known, unique key.

Traditionally you have a heap table holding the data you want to access and a standard index to support access to that table. See the first diagram below. The 4-layer triangle represents the index, with a root block, two levels of branch blocks and then the leaf blocks at the “bottom”. The blue rectangle represents the table with the squares being individual rows. Of course, in a large table there would be thousands or millions of “squares”, this is just a simple diagram to show the idea.

When you issue a SQL statement to select the row via the indexed column(s) then oracle will read the root block (1), find the relevent block in the first level of branch blocks (2), then the relevant block in the second level of branch blocks (3) and finally (as far as the index is concerned) the relevant Leaf Block for the unique key. The leaf block holds the indexed column(s) and also the rowid. The rowid is the fastest way to look up a record, it states the file, block and row offset for the row. This allows oracle to go straight to the block and get the row. That is read number (5).
The number of branch blocks {and thus the number of blocks that need to be read to find a row} will vary depending on how much data is indexed, the number and size of the columns in the index, how efficiently the space has been used in the blocks and one or two other factors. In my experience most indexes for tables with thousands or millions of rows have one, two or three levels of branch blocks.

The second diagram shows a representation of the Index Organized Table. The table has in effect disappeared as a distinct object and the information has been moved into the leaf blocks of the index {part of me feels Index Organized Tables should really be called Table Organized Indexes or Table Containing Indexes as that would better indicate what is physically done}:

So with the IOT oracle reads the root block (1), the two branch level blocks (2 and 3) and finally the leaf block (4). The leaf block does not hold the rowid but rather the rest of the columns for the table {this can be changed, a more advanced feature allows you to store some or all the extra columns in an overflow segment}. Thus to access the same data, Oracle has to read only 4 blocks, not 5. Using an IOT saves one block read per unique lookup.

This saving of block reads is probably the main feature that IOTs are known for, but there are others which I will cover in later posts. Two things I will mention now is that, firstly, the use of IOTs is potentially saving disc space. An index is in effect duplication of data held in the table. When you create an index no new information is created but space is used up holding some of the table information in a structure suitable for fast lookup. Secondly, the index and table have to be maintained whenever a change is made to the columns that are indexed. IOTs reduce this maintenance overhead as there is only one thing to maintain.

Now for some drawbacks.

• The IOT has to be indexed on the primary key. There is no option to create an IOT based on other indexes. As such you have to either be accessing the table via the primary key to get the benefit – or you have to be a little cunning.
• The index is going to be larger than it was and very often larger than the original table. This can slow down range scans or full scans of the index and a “full table scan” will now be a full index scan on this large object, so that can also negatively impact performance. However, if a range scan would then have resulted in access to the table to get extra columns, the IOT gives a similar benefit in reducing IO to that for single row lookups.
• I just want to highlight that you now have no rowid for the rows.
• Secondary indexes are supported but will potentially be less efficient due to this lack of rowid.

So, a brief summary is that Index Organised Tables effectively move the table data into the Primary Key index, reduce the number of block lookups needed to select one row, can save some disc space. But you can only organize the table via the Primary Key and it can make full or partial table scans and lookups via other indexes slower.

There are several more important benefits to IOTs {in my opinion} which I will come to over the next week or two.