Database Journal
MS SQL Oracle DB2 Access MySQL PostgreSQL Sybase PHP SQL Etc SQL Scripts & Samples Tips Database Forum Rss Feed

» Database Journal Home
» Database Articles
» Database Tutorials
MS Access
SQL Scripts & Samples
» Database Forum
» Slideshows
Free Newsletters:

News Via RSS Feed

Rss Feed

Database Journal |DBA Support |SQLCourse |SQLCourse2

Featured Database Articles


Posted Apr 1, 2004

Working with VARRAYs in Oracle Part III

By James Koopmann

This article is the third and last in the three part series, that has explored the use of VARRAYs in Oracle. This part will look at the performance implications if you should choose to use VARRAYS.

In Part I&II of this series, we learned how to create the abstract data types and use them to our advantage for modeling purposes. They were pretty slick and could handle some interesting scenarios when moving data around. We also learned that we could easily hide the complexity of the abstract structures from our end users to make the abstract data types very easy to use. However, in this article we turn our focus to how these structures will behave when we actually use them. Will they improve the performance or bring our systems to their knees. Let's walk through a few different scenarios and show the effects of using VARRAYs.

The Players

1.      The table called GAS_LOG, defined with and without a VARRAY. See the first and second part of this series if need be.

2.      A non-unique b-tree index on GAS_LOG table for VIN number.

3.      A source table of 50,000 rows where each row is a unique VIN number. This table will be cycled through 20 times to simulate 20 different gas logs added for each VIN defined. This will amount to a 1 million-row table.

The Simple Test

For our test, we will be determining the response time, wait time, and a breakout of the CPU used. Table 1 shows the three test scenarios we will use and what they entail. The last two require a PL/SQL procedure which can be found in Listing 1.

Table 1
Test Scenarios




This is a simple insert into...select from statement and will be used as a baseline because it requires no processing and will produce the quickest response since there is not translation processing to be done.

PL/SQL Cursor

on Regular Table

This will open a cursor (20 times) on the source table and execute individual insert statements for a GAS_LOG table that does not have a VARRAY defined on it.

PL/SQL Cursor

on Table with VARRAY

This will open a cursor (20 times) on the source table and execute individual insert statements for a GAS_LOG table that DOES HAVE a VARRAY defined on it.

Definition Level Set

Before we go any further in this, I have provided a few quick definitions in Table 2 to give you insight into what we will be measuring. I have zeroed in only on these items because at a high level they are what matters to the end user and directly impact what the end user will see as response from the system. Please note that response time is the summation of the CPU times plus the Wait time. Also, note that parse time and recursive time are components of the total CPU used.

Table 2
Important Response Time Statistics

Response Time

The amount of time it took the application to finish. This is the summation of CPU Used and Wait Time.

CPU used by this session

Total amount of CPU Used for the application.

parse time CPU

Total amount of CPU used to parse the SQL Statements.

recursive CPU usage

Total amount of CPU used to update internal tables for the processing of the SQL Statements. This could be stuff like space allocation of updates to the data dictionary.

Wait Time

Total amount of time that resources were in a wait state.

Comparing Inserting Data

In the following scenarios, you will see the top level wait events along with the amount of CPU that was used to produce the inserts into the tables. While there were other wait events with some time associated to them, they were not very much and did not impact the results that I saw. Table 3 shows you a quick overview of the statistics and how the different scenarios compare to one another. A few gleaming insights can be noted:

1.      If it were not for the PL/SQL code doing recursive calls the cursor and inserting into the table without the VARRAY would almost be as quick as the straight inserts.

2.      For the VARRY object, all the times were much more than any operation on a normal table. Remember, if you want to look back at Part I&II of this series, that there is more PL/SQL code to handle the inserting into the VARRAY table and we must read the VARRAY into memory before we can change it and update it.

Table 3
Overview of Statistics Gathered



Response Time

CPU Used

Parse Time CPU

Recursive CPU Usage

Time Waited







PL/SQL Cursor on Regular Table






PL/SQL Cursor on Table with VARRAY






While performing the inserts, 50,000 at a time for 20 cycles, I decided to take a look at the segregation of the insert rate. As you can see from Table 4 there was not really any derogation for the straight insert or PL/SQL cursor methods. Unfortunately, the more entries we put in the VARRAY in our table, the more time it took. As you can also see, the very first insert we did had the best response time but still was not even close to what the other methods provided. Moreover, it just went downhill (upslope) from there.

Table 4
Graph of Response Time for each set of Inserts over time

Oracle Archives

Latest Forum Threads
Oracle Forum
Topic By Replies Updated
Oracle Data Mining: Classification jan.hasller 0 July 5th, 07:19 AM
Find duplicates - Unique IDs Lava 5 July 2nd, 08:30 AM
no matching unique or primary key rcanter 1 April 25th, 12:32 PM
Update values of one table based on condition of values in other table using Trigger Gladiator 3 February 29th, 06:01 PM