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Clustering Factor

Oracle 19c Automatic Indexing: Common Index Creation Trap (Rat Trap)

When I go to a customer site to resolve performance issues, one of the most common issues I encounter is in relation to inefficient SQL. And one of the most common causes for inefficient SQL I encounter is because of deficiencies the default manner by which the index Clustering Factor is calculated. When it comes […]

Oracle 19c Automatic Indexing: Mixing Manual and Automatic Indexes Part I (I Can’t Read)

In previous articles, I discussed how Automatic Indexing has the capability to add columns or reorder the column list of previously created Automatic Indexes. However, how does Automatic Indexing handle these types of scenarios with regard to existing manually created indexes? To investigate, let’s create a table identical to the table I created in my […]

Oracle Database 19c Automatic Indexing: Default Index Column Order Part II (Future Legend)

In Part I, we explored some options that Oracle might adopt when ordering the columns within an Automatic Index by default, in the absence of other factors where there is only the one SQL statement to be concerned with. A point worth making is that if all columns of an index are specified within SQL […]

Rebuilding Indexes: Danger With Clustering Factor Calculation (Chilly Down)

Let me start by saying if you don’t already following Jonathan Lewis’s excellent Oracle blog, do yourself a favour. In a recent article, Jonathan highlighted a danger with rebuilding indexes (or indeed creating an index) when used in relation to collecting index statistics with the TABLE_CACHED_BLOCKS preference. I’ve discussed the importance of the TABLE_CACHED_BLOCKS statistics […]

Answer: Anything Wrong With Query Performance? (Red Right Hand)

I of course attract a highly clever readership :). As some have commented, for a single table to require 1000+ consistent gets to retrieve 1000 rows implies that each row needs to be accessed from a different block. This in turn implies the Clustering Factor for this index to be relatively bad and the associated […]

Improve Data Clustering on Multiple Columns Concurrently (Two Suns in the Sunset)

I’ve had a couple of recent discussions around clustering and how if you attempt to improve the clustering of a table based on a column, you thereby ruin the current clustering that might exist for a different column. The common wisdom being you can only order the data one way and if you change the […]

12.2 Online Conversion of a Non-Partitioned Table to a Partitioned Table (A Small Plot Of Land)

In my previous post, I discussed how you can now move heap tables online with Oracle Database 12.2 and how this can be very beneficial in helping to address issues with the Clustering Factor of key indexes. A problem with this technique is that is requires the entire table to be effectively reorganised when most of […]

12.1.0.2 Introduction to Attribute Clustering (The Division Bell)

One of the really cool new features introduced in 12.1.0.2 is Attribute Clustering. This new table based attribute allows you to very easily cluster data in close physical proximity based on the content of specific columns. As I’ve discussed many times, indexes love table data that is physically clustered in a similar manner to the index … … Continue reading

Clustering Factor Calculation Improvement Part III (Too Much Rope)

In my previous post, I discussed how for larger tables that really do have randomised data, not even setting the new TABLE_CACHED_BLOCKS to its 255 maximum value is going to make any real difference to the resultant Clustering Factor (CF) of an index. The 255 maximum value here protects us somewhat from abusing this capability […]

Clustering Factor Calculation Improvement Part II (Blocks On Blocks)

My previous post on the new TABLE_CACHED_BLOCKS statistics gathering preference certainly generated some interest My blog hits for the week have gone off the charts !! One of the concerns raised by this new capability was that setting such a preference might result in really unrealistic and inaccurate Clustering Factor (CF) values, especially for those […]