11.1.0.7

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Function-Based Indexes And CURSOR_SHARING = FORCE

In general it is known that Function-Based Indexes (FBIs) can no longer be used by the optimizer if the expression contains literals and CURSOR_SHARING = FORCE / SIMILAR (deprecated) turns those literals into bind variables.

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Video Tutorial: XPLAN_ASH Active Session History - Introduction

I finally got around preparing another part of the XPLAN_ASH video tutorial.

This part is about the main funcationality of XPLAN_ASH: SQL statement execution analysis using Active Session History and Real-Time SQL Monitoring.

In this video tutorial I'll explain what the output of XPLAN_ASH is supposed to mean when using the Active Session History functionality of the script. Before diving into the details of the script output using sample reports I provide some overview and introduction in this part that hopefully makes it simpler to understand how the output is organized and what it is supposed to mean.

This is the initial, general introduction part. More parts to follow.

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Unnecessary BUFFER SORT Operations - Parallel Concatenation Transformation

When using Parallel Execution, depending on the plan shape and the operations used, Oracle sometimes needs to turn non-blocking operations into blocking operations, which means in this case that the row source no longer passes its output data directly to the parent operation but buffers some data temporarily in PGA memory / TEMP. This is either accomplished via the special HASH JOIN BUFFERED operation, or simply by adding BUFFER SORT operations to the plan.The reason for such a behaviour in parallel plans is the limitation of Oracle Parallel Execution that allows only a single data redistribution to be active concurrently.

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View Data Volume Estimates

When the optimizer has to estimate the data volume (the BYTES column in the plan output), it usually bases this information on the column statistics, if applicable and available (think of complex expressions).However, whenever there is a VIEW operator in an execution plan, that represents an unmerged view, the optimizer obviously "loses" this information and starts applying defaults that are based on the column definition.Depending on the actual content of the columns this can lead to dramatic differences in data volume estimates.Both, under- and overestimates are possible, because for character based columns these defaults seem to be based on an assumed 50% fill grade, so a VARCHAR2(100 BYTE) column counts as 50 bytes data volume.For multi-byte character sets the same rule applies based on the maximum width of a column using the "char" semantics, so a VARCHAR2(1000 CHAR) column counts as 2000 byte

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TIMESTAMP WITH TIME ZONE Aggregation

The TIMESTAMP WITH TIME ZONE data type that got introduced a long time ago is known for some oddities, for example Tony Hasler has a nice summary of some of them here.Here is another oddity that shows up when trying to aggregate on such a data type. Have a look at the following simple example:


create table t
as
select
rownum as id
, date '2000-01-01' + rownum - 1 as some_date
, cast(date '2000-01-01' + rownum - 1 as timestamp) as some_timestamp
, cast(date '2000-01-01' + rownum - 1 as timestamp with local time zone) as some_timestamp_with_local_tz
, cast(date '2000-01-01' + rownum - 1 as timestamp with time zone) as some_timestamp_with_timezone
from
dual
connect by
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New Version Of XPLAN_ASH Tool - Video Tutorial

A new major release (version 3.0) of my XPLAN_ASH tool is available for download.

You can download the latest version here.

In addition to many changes to the way the information is presented and many other smaller changes to functionality there is one major new feature: XPLAN_ASH now also supports S-ASH, the free ASH implementation.

If you run XPLAN_ASH in a S-ASH repository owner schema, it will automatically detect that and adjust accordingly.

XPLAN_ASH was tested against the latest stable version of S-ASH (2.3). There are some minor changes required to that S-ASH release in order to function properly with XPLAN_ASH. Most of them will be included in the next S-ASH release as they really are only minor and don't influence the general S-ASH functionality at all.

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"Cost-free" joins - 1

Recently I came across some interesting edge cases regarding the costing of joins. They all have in common that they result in (at first sight) unexpected execution plans, but only some of them are actual threats to performance.

Outer Joins

The first one is about outer joins with an extreme data distribution. Consider the following data setup:


create table t1
as
select
rownum as id
, rpad('x', 100) as filler
, case when rownum > 1e6 then rownum end as null_fk
from
dual
connect by
level <= 1e6
;

exec dbms_stats.gather_table_stats(null, 't1')

create table t2
as
select
rownum as id
, rpad('x', 100) as filler
from
dual
connect by
level <= 1e6
;
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New Version Of XPLAN_ASH Utility

A new version 2.0 of the XPLAN_ASH utility introduced here is available for download.You can download the latest version here.The change log tracks the following changes:- Access check- Conditional compilation for different database versions- Additional activity summary- Concurrent activity information (what is/was going on at the same time)- Experimental stuff: Additional I/O summary- More pretty printing- Experimental stuff: I/O added to Average Active Session Graph (renamed to Activity Timeline)- Top Execution Plan Lines and Top Activities added to Activity Timeline- Activity Timeline is now also shown for serial execution when TIMELINE option is specified- From 11.2.0.2 on: We get the ACTUAL DOP from the undocumented PX_FLAGS colu

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Parallel Execution Analysis Using ASH - The XPLAN_ASH Tool

Preface

Note: This blog post actually serves three purposes:

  1. It introduces and describes my latest contribution to the Oracle Community,  the "XPLAN_ASH" tool

  • It accompanies a future OTN article on Parallel Execution that will be published some time in the future

  • It is supposed to act as a teaser for my upcoming "Parallel Execution Masterclass" that will be organized by Oracle University and can be booked later this year
  • Table Of Contents

    Introduction

    Real-Time SQL Monitoring Overview

    Real-Time SQL Monitoring Shortcomings

    randolf.geist's picture

    Table Functions And Join Cardinality Estimates

    If you consider the usage of Table Functions then you should be aware of some limitations to the optimizer calculations, in particular when considering a join between a Table Function and other row sources.

    As outlined in one of my previous posts you can and should help the optimizer to arrive at a reasonable cardinality estimate when dealing with table functions, however doing so doesn't provide all necessary inputs to the join cardinality calculation that are useful and available from the statistics when dealing with regular tables.

    Therefore even when following the recommended practice regarding the cardinality estimates it is possible to end up with some inaccuracies. This post will explain why.

    Join Cardinality Basics

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