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CBO

Lost Concatenation

This note models one feature of a problem that came up at a client site recently from a system running 12.1.0.2 – a possible bug in the way the optimizer handles a multi-column in-list that can lead to extremely bad cardinality estimates.

The original query was a simple three table join which produced a bad plan with extremely bad cardinality estimates; there was, however, a type-mismatch in one of the predicates (of the form “varchar_col = numeric”), and when this design flaw was addressed the plan changed dramatically and produced good cardinality estimates. The analysis of the plan, 10053 trace, and 10046 trace files done in-house suggested that the problem might relate in some way to an error in the handling of SQL Plan Directives to estimate cardinalities.

Invisible Bug

At this Wednesday’s Oracle Midlands event someone asked me if Oracle would use the statistics on invisible indexes for the index sanity check. I answered that there had been a bug in the very early days of invisible indexes when the distinct_key statistic on the index could be used even though the index itself would not be considered as a candidate in the plan (and the invisible index is still used to avoid foreign key locking – even in 12c – it’s only supposed to be invisible to the optimizer).

Index Sanity

By popular demand (well, one person emailed me to ask for it) I’m going to publish the source code for a little demo I’ve been giving since the beginning of the millennium – it concerns indexes and the potential side effects that you can get when you drop an index that you’re “not using”. I think I’ve mentioned the effect several times in the history of this blog, but I can’t find an explicit piece of demo code, so here it is – starting at the conclusion – as a cut and paste from an SQL*Plus session running against an 11g instance:

Cardinality trick

In the absence of a virtual column or function-based index, the optimizer uses a basic selectivity guess of 1% for a predicate of the form: “function(column) = constant”; but there is (at least) one special case where it gets clever; simple type conversion:

Storing Date Values As Numbers (The Numbers)

In my last couple of posts, I’ve been discussing how storing date data in a character based column is a really really bad idea. In a follow-up question, I was asked if storing dates in NUMBER format was a better option. The answer is that it’s probably an improvement from storing dates as strings but it’s […]

Storing Date Values As Characters Part II (A Better Future)

In the previous post, I discussed how storing date values within a character data type is a really really bad idea and illustrated how the CBO can easily get its costings totally wrong as a result. A function-based date index helped the CBO get the correct costings and protect the integrity of the date data. During […]

CBO++

While browsing the web recently for articles on the HyperLogLog algorithm that Oracle uses for some of its approximate functions, I came upon a blog post written in Jan 2014 with the title Use Subqueries to Count Distinct 50X Faster. There are various ways that subqueries can be used to rewrite queries for improved performance, but when the title caught my eye I couldn’t think of a way in which they could improve “count distinct”.  It turned out that the word “subquery” was being used (quite correctly) in the sense of “inline view” while my mind had immediately turned to subqueries in the select list or where clause.

Virtual Partitions

Here’s a story of (my) failure prompted by a recent OTN posting.

The OP wants to use composite partitioning based on two different date columns – the table should be partitioned by range on the first date and subpartitioned by month on the second date. Here’s the (slightly modified) table creation script he supplied:

Debugging

The OTN database forum supplied a little puzzle a few days ago – starting with the old, old, question: “Why is the plan with the higher cost taking less time to run?”

The standard (usually correct) answer to this question is that the optimizer doesn’t know all it needs to know to predict what’s going to happen, and even if it had perfect information about your data the model used isn’t perfect anyway. This was the correct answer in this case, but with a little twist in the tail that made it a little more entertaining. Here’s the query, with the two execution plans and the execution statistics from autotrace:

Set Operations

A recent post on the OTN database forum highlights a couple of important points ideas for optimising SQL. There are: (a) is there a logically equivalent way of stating the SQL and (b) is there a different “natural language” way of posing the problem.

The posting starts with a query, part of an execution plan, and a request to “get rid of the tablescan”. I guessed originally that the query came from an 11g instance, and the OP gave us some code to create the tables and indexes, so I’ve modelled the tables to get the indicated plan (then filled in the original numbers). This is the query, and my cosmetically adjusted version of the plan output that the OP probably got: