Java Programming with Oracle JDBC: Oracle and Java Programming
496
Java Programming with Oracle JDBC: Oracle and Java Programming
496Paperback
-
PICK UP IN STORECheck Availability at Nearby Stores
Available within 2 business hours
Related collections and offers
Overview
You begin by learning the all-important mysteries of establishing database connections. This can be one of the most frustrating areas for programmers new to JDBC, and Donald covers it well with detailed information and examples showing how to make database connections from applications, applets, Servlets, and even from Java programs running within the database itself.
Next comes thorough coverage of JDBC's relational SQL features. You'll learn how to issue SQL statements and get results back from the database, how to read and write data from large, streaming data types such as BLOBs, CLOBs, and BFILEs, and you'll learn how to interface with Oracle's other built-in programming language, PL/SQL.
If you're taking advantage of the Oracle's relatively new ability to create object tables and column objects based on user-defined datatypes, you'll be pleased with Don's thorough treatment of this subject. Don shows you how to use JPublisher and JDBC to work seamlessly with Oracle database objects from within Java programs. You'll also learn how to access nested tables and arrays using JDBC.
Donald concludes the book with a discussion of transaction management, locking, concurrency, and performance—topics that every professional JDBC programmer must be familiar with. If you write Java programs to run against an Oracle database, this book is a must-have.
Product Details
| ISBN-13: | 9780596000882 |
|---|---|
| Publisher: | O'Reilly Media, Incorporated |
| Publication date: | 12/28/2001 |
| Pages: | 496 |
| Product dimensions: | 7.00(w) x 9.19(h) x 1.14(d) |
About the Author
Read an Excerpt
Chapter 19: Performance
Performance is usually considered an issue at the end of a development cycle when it should really be considered from the start. Often, a task called "performance tuning" is done after the coding is complete, and the end user of a program complains about how long it takes the program to complete a particular task. The net result of waiting until the end of the development cycle to consider performance includes the expense of the additional time required to recode a program to improve its performance. It's my opinion that performance is something that is best considered at the start of a project.
When it comes to performance issues concerning JDBC programming there are two major factors to consider. The first is the performance of the database structure and the SQL statements used against it. The second is the relative efficiency of the different ways you can use the JDBC interfaces to manipulate a database.
In terms of the database's efficiency, you can use the EXPLAIN PLAN facility to explain how the database's optimizer plans to execute your SQL statements. Armed with this knowledge, you may determine that additional indexes are needed, or that you require an alternative means of selecting the data you desire.
On the other hand, when it comes to using JDBC, you need to know ahead
of time the relative strengths and weaknesses of using auto-commit, SQL92
syntax, and a Statement versus a
PreparedStatement versus a CallableStatement
object. In this chapter, we'll examine the relative performance of various
JDBC objects using example programs that report the amount of time it takes
to accomplish a given task. We'll first look at auto-commit. Next, we'll
look at the impact of the SQL92 syntax parser. Then we'll start a series of
comparisons of the Statement object versus the
PreparedStatement object versus the
CallableStatement object. At the same time we'll also examine
the performance of the OCI versus the Thin driver in each situation to see
if, as Oracle's claims, there is a significant enough performance gain with
the OCI driver that you should use it instead of the Thin driver. For the
most part, our discussions will be based on timing data for 1,000 inserts
into the test performance table TESTXXXPERF. There are separate programs
for performing these 1,000 inserts using the OCI driver and the Thin
driver.
The performance test programs themselves are very simple and are available online with the rest of the examples in this book. However, for brevity, I'll not show the code for the examples in this chapter. I'll only talk about them. Although the actual timing values change from system to system, their relative values, or ratios from one system to another, remain consistent. The timings used in this chapter were gathered using Windows 2000. Using objective data from these programs allows us to come to factual conclusions on which factors improve performance, rather than relying on hearsay.
I'm sure you'll be surprised at the reality of performance for these objects, and I hope you'll use this knowledge to your advantage. Let's get started with a look at the testing framework used in this chapter.
A Testing Framework
For the most part, the test programs in this chapter report the timings for inserting data into a table. I picked an INSERT statement because it eliminates the performance gain of the database block buffers that may skew timings for an UPDATE, DELETE, or SELECT statement.
The test table used in the example programs in this chapter is a simple relational table. I wanted it to have a NUMBER, a small VARCHAR2, a large VARCHAR2, and a DATE column. Table TESTXXXPERF is defined as:
create table TestXXXPerf (id number,code varchar2(30),descr varchar2(80),insert_user varchar2(30),insert_date date )tablespace users pctfree 20storage( initial 1 M next 1 M pctincrease 0 );alter table TestXXXPerfadd constraint TestXXXPerf_Pkprimary key ( id )using indextablespace users pctfree 20storage( initial 1 M next 1 M pctincrease 0 );
The initial extent size used for the table makes it unlikely that the database will need to take the time to allocate another extent during the execution of one of the test programs. Therefore, extent allocation will not impact the timings. Given this background, you should have a context to understand what is done in each section by each test program.
Auto-Commit
By default, JDBC's auto-commit feature is on, which means that each SQL statement is committed as it is executed. If more than one SQL statement is executed by your program, then a small performance increase can be achieved by turning off auto-commit.
Let's take a look at some numbers. Table 19-1 shows
the average time, in milliseconds, needed to insert 1,000 rows into the
TESTXXXPERF table using a Statement object. The timings
represent the average from three runs of the program. Both drivers
experience approximately a one-second loss as overhead for committing
between each SQL statement. When you divide that one second by 1,000
inserts, you can see that turning off auto-commit saves approximately 0.001
seconds (1 millisecond) per SQL statement. While that's not interesting
enough to write home about, it does demonstrate how auto-commit can impact
performance.
|
Auto-commit |
OCI |
Thin |
|---|---|---|
|
On |
3,712 |
3,675 |
|
Off |
2,613 |
2,594 |
Clearly, it's more important to turn off auto-commit for managing multistep transactions than for gaining performance. But on a heavily loaded system where many users are committing transactions, the amount of time it takes to perform commits can become quite significant. So my recommendation is to turn off auto-commit and manage your transactions manually. The rest of the tests in this chapter are performed with auto-commit turned off....
SQL92 Token Parsing
Like auto-commit, SQL92 escape syntax token parsing is on by default. In case you don't recall, SQL92 token parsing allows you to embed SQL92 escape syntax in your SQL statements (see "Oracle and SQL92 Escape Syntax" in Chapter 9). These standards-based snippets of syntax are parsed by a JDBC driver transforming the SQL statement into its native syntax for the target database. SQL92 escape syntax allows you to make your code more portable--but does this portability come with a cost in terms of performance?
Table 19-2 shows the number of milliseconds needed to insert 1,000 rows into the TESTXXXPERF table. Timings are shown with the SQL92 escape syntax parser on and off for both the OCI and Thin drivers. As before, these timings represent the result of three program runs averaged together.
|
SQL92 parser |
OCI |
Thin |
|---|---|---|
|
On |
2,567 |
2,514 |
|
Off |
2,744 |
2,550 |
Notice from Table 19-2 that with the OCI driver we lose 177 milliseconds when escape syntax parsing is turned off, and we lose only 37 milliseconds when the parser is turned off with the Thin driver. These results are the opposite of what you might intuitively expect. It appears that both drivers have been optimized for SQL92 parsing, so you should leave it on for best performance.
Now that you know you never have to worry about turning the SQL92 parser off, let's move on to something that has some potential for providing a substantial performance improvement.
Statement Versus PreparedStatement
There's a popular belief that using a PreparedStatement
object is faster than using a Statement object. After all, a
prepared statement has to verify its metadata against the database only
once, while a statement has to do it every time. So how could it be any
other way? Well, the truth of the matter is that it takes about 65
iterations of a prepared statement before its total time for execution
catches up with a statement. This has performance implications for your
application, and exploring these issues is what this section is all about.
When it comes to which SQL statement object performs better under
typical use, a Statement or a PreparedStatement,
the truth is that the Statement object yields the best
performance. When you consider how SQL statements are typically used in an
application--1 or 2 here, maybe 10-20 (rarely more) per transaction--you
realize that a Statement object will perform them in less time
than a PreparedStatement object. In the next two sections,
we'll look at this performance issue with respect to both the OCI driver
and the Thin driver.
The OCI Driver
Table 19-3 shows the timings in milliseconds for 1
insert and 1,000 inserts in the TESTXXXPERF table. The inserts are done
first using a Statement object and then a
PreparedStatement object. If you look at the results for 1,000
inserts, you may think that a prepared statement performs better. After
all, at 1,000 inserts, the PreparedStatement object is almost
twice as fast as the Statement object, but if you examine Figure 19-1, you'll see a different story.
|
Inserts |
Statement |
PreparedStatement |
|---|---|---|
|
1 |
10 |
113 |
|
1,000 |
2,804 |
1,412 |
Figure 19-1 is a graph of the timings needed to
insert varying numbers of rows using both a Statement object
and a PreparedStatement object. The number of inserts begins
at 1 and climbs in intervals of 10 up to a maximum of 150 inserts. For this
graph and for those that follow, the lines themselves are polynomial trend
lines with a factor of 2. I chose polynomial lines instead of straight
trend lines so you can better see a change in the performance as the number
of inserts increases. I chose a factor of 2 so the lines have only one
curve in them. The important thing to notice about the graph is that it's
not until about 65 inserts that the PreparedStatement object
outperforms the Statement object. 65 inserts! Clearly, the
Statement object is more efficient under typical use when
using the OCI driver.
The Thin Driver
If you examine Table 19-4 (which shows the same
timings as for Table 19-3, but for the Thin driver)
and Figure 19-2 (which shows the data incrementally),
you'll see that the Thin driver follows the same behavior as the OCI
driver. However, since the Statement object starts out
performing better than the PreparedStatement object, it takes
about 125 inserts for the PreparedStatement to outperform
Statement....