Saturday, January 11, 2014

My Digital Toolbox

This is to keep a list of utilities that I use.


General Utilities

Development Utility:

  • JMeter
  • SoapUI


  • putty (Windows)
  • MobaXterm

Digital Content Utilities

Android Apps:

  • Juice Defender
  • GPS Status
  • Waze
  • Lux Free Dash
  • Prefixer
  • ConnectBot
  • EbookDroid
  • BSPlayer – Can browse samba share and play a lot video formats, including RMVB, KMV.
  • NYC Bus & Subway Maps
  • Google Pinyin (Not the best Chinese keyboard but balance of performance and feature)
  • Terminal Emulator
  • Ping & DNS

Tuesday, October 08, 2013

If/Else Statement vs. Ternary Operator

The question of which one is faster, the ternary operator or if/else statement, was asked again and again. The canned answer is: you don’t care, don’t even think about performance here, just choose the one that is most readable in the context you use.

But leave aside about the argument of which one is more readable. If I’m going to call it hundred millions of times, the performance difference might be matter to me, right? I was again asked about this question recently so I decided to find this out. Only test can tell the truth.

Test Setup

We define each run as repeatedly transmitting data from an array with 10 elements to another array multi-million times. When the data are transmitted from one array to another, we also transform the date. We used different methods to transform the data so we can compare the time difference between different methods. We also capture the baseline performance. A baseline does very same thing as the regular run but with not data transformation.

The code for every run is somewhat like below.

   1:          @Override
   2:          void run() {
   3:              int a[] = source;
   4:              int b[] = target;
   5:              for (int i = LOOP_COUNT; i > 0; i--) {
   6:                  for (int j = ELEMENT_END; j >= 0; j--) {
   7:                      // copy and transform the data from a to b
   8:                  }
   9:              }
  10:          }

We execute the run 20 times to warm up the system and run it another 100 times with time measured for each run.

   1:          // warn up
   2:          for (int j = 20; j > 0; j--) {
   3:              for (Fixture f : fixtures)
   4:        ;
   5:          }
   7:          // run and measure it
   8:          for (int j = 100; j > 0; j--) {
   9:              for (Fixture f : fixtures)
  10:                  f.runMeasured();
  11:          }

And the code to measure the performance.

   1:      void runMeasured() {
   2:          long start = System.nanoTime();
   3:          run();
   4:          histogram.update(System.nanoTime() - start);
   5:      }

You can find the source code on github.

And all the test run was on a Lenovo X220 Laptop with Core i5-2520M @ 2.5GHz, Running Windows 7 64bit and JRE 1.7 64bit.

Absolute Value Test

The first test is to transform the data in the source array into their absolute value and then store them in target array. The data in the source array were purposely set to be half positive and half negative.

The similar tests were done in two different ways. Both use a base class and have each derived class overrides a method. The difference is that, one have the loop logic common in base class and let the derived class only override the method that does the absolute value calculation, another repeats the loop logic in each derived class and have the absolute value calculation inlined inside the loop.

Using Overridden Methods

The test is captured in RunnerAbsOverride class. Below is the run logic

   1:          void run() {
   2:              int a[] = source;
   3:              int b[] = target;
   4:              for (int i = LOOP_COUNT; i > 0; i--) {
   5:                  for (int j = ELEMENT_END; j >= 0; j--) {
   6:                      int x = a[j];
   7:                      b[j] = abs(x);
   8:                  }
   9:              }
  10:          }

We compare the performance different by using different implementations of the abs methods.


The baseline implementation doesn’t really compute the absolute value. It simply returns itself without no data transformation.

            return x;
Using Math.abs

This method calls the JDK build in abs method in Math class to transform the date into absolute value.

            return Math.abs(x);
Using ternary operator

Here we use ternary operator to compute the absolute value of x.

            return x >= 0 ? x : -x;
Using if/else statement

At last, we use if/else statement to return x if it is positive and –x if x is negative.

            if (x >= 0) return x;
            else return -x;
Test Result

Below is the result of calculating absolute value in an overridden method of different implementations. Time is the nano seconds taken to transform and copy the array.

Method,    Mean,   Min,   Max, Median,  75%
Baseline,  36.4,  35.6,  39.0,  36.2,  36.6
MathAbs ,  40.6,  39.6,  49.9,  40.2,  40.7
Ternary ,  40.3,  39.6,  42.2,  40.2,  40.6
IfElse  ,  40.4,  39.5,  43.9,  40.2,  40.7

We observed three things here

  1. Comparing to the baseline, computing the absolute value of an integer takes additional 11% more time on top of baseline’s looping and a method call.
  2. All three methods of calculating an absolute value has same performance.
  3. We didn’t see any difference of using the built in Math.abs. Which means the static method is inlined and nothing else special was done to this JDK method.

Inlining the Code

What if we inline the code directly in the loop? Let’s repeat the loop below in every implementation and replace the comment with the different methods of computing the absolute values. This test is captured in RunnerAbsInline class.

   1:          final void run() {
   2:              final int a[] = source;
   3:              final int b[] = target;
   4:              for (int i = LOOP_COUNT; i > 0; i--) {
   5:                  for (int j = ELEMENT_END; j >= 0; j--) {
   6:                     // compute absolute value of a[j] then assign it to b[j]
   7:                  }
   8:              }
   9:          }
                    b[j] = a[j];
Using Math.abs
                    b[j] = Math.abs(a[j]);
Using ternary operator
                    b[j] = a[j] >= 0 ? a[j] : -a[j];
Using if/else statement
                    if (a[j] >= 0) b[j] = a[j];
                    else b[j] = -a[j];
Using if statement without else

When it is inlined, it allow us to use a single if statement to get the absolute value.

                    int x = a[j];
                    if (x < 0) x = -x;
                    b[j] = x;
Test result

Below is the result of calculating absolute value inlined in the loop of different implementations. Time is the nano seconds taken to transform and copy the array.

Method,    Mean,   Min,   Max, Median,  75%
Baseline,   1.7,   1.6,   3.0,   1.7,   1.7
MathAbs ,   7.0,   6.7,   8.6,   6.9,   7.0
Ternary ,   7.0,   6.7,   8.4,   6.9,   7.0
IfElse  ,   8.6,   8.4,   9.6,   8.5,   8.6
IfOnly  ,   6.9,   6.7,   9.0,   6.9,   7.0

The numbers above tells us that

  1. Using if/else statement is 30% slower than other methods in average.
  2. We have added a if statement only implementation is at the same speed as Math.abs() and ternary operator.
  3. Again, we didn’t see the difference between using Math.abs vs. the ternary operation here.
  4. The overhead of method invocation is much higher than any of the method we used.

Number Ordering Test

The 2nd test is compare the numbers in the two adjacent elements of the source array, then store the two number to the target array in ascending order. The data in the source array were carefully set so that the opportunity is the same for the left element of the adjacent two being smaller or larger.

Again, like we did in the Absolute Value test, we’ll test in two different ways. One have the logic in its own method and another to have the logic inlined in the loop.

Using Overridden Methods

The test is captured in RunnerOrderingOverride class. Below is the run logic

   1:          void run() {
   2:              int a[] = source;
   3:              for (int i = LOOP_COUNT; i > 0; i--) {
   4:                  for (int j = ELEMENT_END; j >= 0; j--) {
   5:                      compareSet(a[j], a[j + 1], j);
   6:                  }
   7:              }
   8:          }

We compare the performance different by using different implementations of the compareSet methods.


The baseline implementation doesn’t really compare the value. It simply sets the value in the original order.

            int b[] = target;
            b[index++] = x;
            b[index] = y;
Using Math.abs

This try to avoid the if statement by computing the difference and sum of the two number, and then derive the smaller one and larger from the sum and different. The difference is obtained by subtracting one from another and then taking the absolute value.

            int b[] = target;
            int diff = Math.abs(x - y);
            int sum = x + y;
            b[index++] = sum - diff;
            b[index] = sum + diff;
Using ternary operator

This is very similar to Math.abs, except that the ternary operator is used instead of Math.abs.

            int b[] = target;
            int diff = x >= y ? x - y : y - x;
            int sum = x + y;
            b[index++] = sum - diff;
            b[index] = sum + diff;
Using if/else statement

This uses straightforward if/else statement.

            int b[] = target;
            if (x >= y) {
                b[index++] = y;
                b[index] = x;
            } else {
                b[index++] = x;
                b[index] = y;
Test Result

Below is the result of ordering the numbers in an overridden method of different implementations. The unit is nano second.

Method,    Mean,   Min,   Max, Median,  75%
Baseline,  54.3,  52.6,  66.4,  53.9,  54.7
MathAbs ,  66.3,  64.2,  79.2,  65.6,  66.3
Ternary ,  62.2,  60.2,  79.1,  61.2,  62.0
IfElse  ,  58.9,  56.3,  78.6,  58.0,  58.6

It turned out that the straightforward if/else statement is the fastest. The attempt of replacing it with ternary operator plus multiple steps of integer computation doesn’t really outperform if/else statement. It is actually much slower.

This time, Ternary is faster than Match.abs because it eliminated the negate operation in the Math.abs when x < y.

Inlining the Code

Again, let’s re-test the logic by inlining them in the loop. We repeat the loop below in every implementation and replace the comment with the different methods of ordering the number. This test is captured in RunnerOrderingInline class.

   1:          final void run() {
   2:              int a[] = source;
   3:              int b[] = target;
   4:              for (int i = LOOP_COUNT; i > 0; i--) {
   5:                  for (int j = ELEMENT_END; j >= 0; j--) {
   6:                      final int x = a[j];
   7:                      final int y = a[j + 1];
   8:                      // set the smaller one of x and y to b[j] and the larger one to b[j+1]
   9:                  }
  10:              }
  11:          }
  12:      }

Baseline simply assigns the value without ordering them.

                    b[j] = x;
                    b[j + 1] = y;
Using Math.abs
                    int diff = Math.abs(x - y);
                    final int sum = x + y;
                    b[j] = sum - diff;
                    b[j + 1] = sum + diff;
Using ternary operator
                    final int diff = x >= y ? x - y : y - x;
                    final int sum = x + y;
                    b[j] = sum - diff;
                    b[j + 1] = sum + diff;
Using if/else statement
                    if (x >= y) {
                        b[j] = x;
                        b[j + 1] = y;
                    } else {
                        b[j] = y;
                        b[j + 1] = x;
Test result

Below is the result of ordering the numbers inlined in the loop of different implementations. Unit is nano seconds.

Method,    Mean,   Min,   Max, Median,  75%
Baseline,   3.8,   3.5,   4.9,   3.6,   3.7
MathAbs ,  18.3,  17.3,  22.6,  17.9,  18.5
Ternary ,  13.9,  13.0,  19.0,  13.5,  14.0
IfElse  ,  11.1,  10.6,  13.6,  11.0,  11.2

The result is same as the override method test except it is overall faster because of the inlined code. So method invocation is much more expensive than any of those.


  1. There are no fundamental difference between ternary and if/else.
  2. Ternary is faster then if/else as long as no additional computation is required to convert the logic to us ternary. When it is a simply ternary operation, it has better readability as well.
  3. If only statement is faster than if/else, so if the logic doesn’t require an else statement, do use it.
  4. Don’t try to outsmart. Adding additional operations to replace if/else with ternary lead you to the conversed result. In this case, use straightforward if/else gets you better performance and readability.
  5. JDK doesn’t do native optimization to Math.abs other than inlined the static method call almost everywhere. It is not like others suggested that JDK does native optimization for built in functions.
  6. Comparing the different between if/else and ternary, method invocation is every expensive.

Thursday, August 15, 2013

Words for Versioning

It's always been difficult to come up with good names for versioning or naming of the Agile sprints. Here are idea we used.

Last Name of top scientists

Mainly from this page 100 Scientists Who Shaped World History. But I cannot find a last name starts with Q, U or X. It is also confirmed from the page Alphabetized List by Scientist's Name. Hence, I used word Quantum, Universe and X-ray, which you can find on the page and related to science.
Archimedes Kepler Universe
Bohr Lavoisier Virchow
Copernicus Maxwell Watson
Darwin Newton X-ray
Einstein Onnes Yalow
Freud Pasteur Zhang
Galilei Quantum
Heisenberg Rutherford
Ibn-e-Sina Schrodinger
Jenner Thomson

Name of cars

From, we picked those names are rarely used in software documentation so the can be searched easily.
Axiom Kodiak Uplander
Boxter Lanos Vitara
Cougar Murano Windstar
Durango Nubira Xantia
Envoy Optima Yaris
Fiero Paseo Zephyr
Galant Quattro
Hombre Reatta
Impala Sorento
Jetta Tredia


Here you can find all superheros names

Mountains of the World

Monday, June 17, 2013

VBA Routine To Set Excel Cell Color By Value

I though some one must have already done this, but I cannot find the ready to use code. So I had to write one myself:

Private Sub Worksheet_Change(ByVal Target As Range)
    Dim Column
    Dim Row
    Dim Red
    Dim Green
    Dim heat
    For Each c In Target
        Column = c.Column
        Row = c.Row
        Rem # Define the range of the cells to change color, keep this to minimal for better performance
        If Column > 1 And Column <= 12 And Row > 1 And Row < 40 Then
            If c.Value = "" Then
                c.Interior.ColorIndex = -4142
                Rem # Calculate the heat. You can times c.Value by a factor to control the range
                heat = c.Value - 255
                If (heat > 255) Then heat = 255
                If (heat < -255) Then heat = -255
                Rem # Set back color of the cell
                If (heat > 0) Then
                    Green = 256 - heat
                    Red = 255
                    Green = 255
                    Red = 255 + heat
                End If
                c.Interior.Color = RGB(Red, Green, 0)
                Rem # Set fore color of the cell
                If (heat > 100) Then
                    c.Font.Color = vbWhite
                    c.Font.Color = vbBlack
                End If
            End If
        End If
End Sub

Tuesday, June 04, 2013

Change Drive Label and Icon in Windows 7

I can use registry to do this. Here is an example.

Windows Registry Editor Version 5.00
@="Source Code"

Sunday, April 07, 2013

Integrate Java and GraphicsMagick – gm4java Performance


In the last two posts of this series, we enhanced GraphicsMagick (GM hereafter) to support interactive or batch mode, and we developed the Java library, gm4java, to integrate with GM. Now it’s time to give it a run!


This is the same web application that we tested the performance of sole im4java implementation. And we also use identical test environment and test setup for an apple to apple comparison. For the completeness, I’ll repeat the test application, environment and setup here.

The web application dynamically resize the source images that is 700x700 or less to a smaller dimension. An HTTP request come in with the individual image and the target size specified, the web application locates the source image and resize it to the target size, then streams the image back to the requester, typically a browser.

The application still use the same GM’s convert command,  “convert <source> –scale <width>x<height> <target>”, to scale down an image. The difference this time is that, instead of completely depending on im4java, we use gm4java to start 32 GM processes in interactive mode, they are pooled by gm4java to executed the convert commands coming in. That effectively eliminates the overhead of starting, and then shutting down, a new GM process for every request.

In order to avoid problems caused by any potential memory leak, each GM process was recycled after 1000 execution of commands. (Info: we have also tested with recycling disabled, that improved the performance by 1-2% and we also did not observe any memory leakage. But in the end we decided to keep the recycling enabled)

Test Environment

We also use exact same test environment that we tested the im4java integration. Again, repeated below:



CPU: 32 cores - 4 AMD Opteron(TM) Processor 6274 (8 cores)

Test Tool

JMeter is used to execute the test. The machine runs the JMeter has identical hardware as the test machine. There is high speed network connection between them and we have confirmed that there is no other factor being bottleneck.

Test Setup

We used 200K unique sample image and each image are being request twice, one converts to 260x420 and another converts to 114x166.

On thread group is used to run multiple threads in parallel. Each thread represent one concurrent user. We run the test multiple times, with different number of concurrent users. Each thread will request image one after another, there is no delay whatsoever.

We measure the throughput in terms of total number of images resized within a second by the server.

Test Result

Table below listed the total throughput under different load, side by side with the test result from our im4java implementation test.

Concurrent users Total Throughput (images/second)
im4java gm4java
50 278 Didn’t test
500 109 1447
5000 19 1490
20000 4 1452

The throughput is significantly higher comparing to the im4java implementation, and it stays high under high load as expected.

Disclaimer:this is NOT an comparison between im4java and gm4java, it is a comparison between the traditional integration mechanism im4java uses to integrate with GM, and the new interactive mechanism that is implemented by gm4java. gm4java does not compete with im4java, rather they complement each other.


The test result proves that using gm4java and GM’s new interactive/batch mode feature can provide a reliable and scalable mean to integrate Java and GM. We have successfully implemented our proposed solution, and concluded that is the solution we need.

Other Posts in the “Integrate Java and GraphicsMagick” Series

  1. Conception
  2. im4java Performance
  3. Interactive or Batch Mode
  4. gm4java
  5. gm4java Performance

Saturday, March 23, 2013

Integrate Java and GraphicsMagick – gm4java


Now we added interactive or batch mode support to GraphicsMagick (GM hereafter), we need to enable the Java side of the integration to complete the implementation of the proposed solution. Hence the gm4java library is born.

In this post, we’ll briefly discuss how gm4java is implemented, then put more focus on its features and API.

Update (3/30): gm4java is available from central maven repository|692293610


The implementation of gm4java that we are going to discuss sounds to be complicated but the good news is you don’t have to deal with that because gm4java encapsulates the complexity and does the heavy lifting for you. If you are not interested in the detail, you can skip right to “Feature and API” section. But I believe having some understanding of what’s under the hood always makes me a better driver.

Source code of gm4java can be found at (update 4/15: moved to

Interacting with GM Process

gm4java uses Java ProcessBuilder to spawn GM process in interactive mode. Code below illustrate how the GM process is started

   1:  process = new ProcessBuilder().command(command).redirectErrorStream(true).start();
   2:  outputStream = process.getOutputStream();
   3:  inputStream = process.getInputStream();

Note that a pair of the input and output stream are obtained from the process. gm4java uses them to communicate with the GM process, by sending commands to, and receiving feedback from it.

gm4java uses below GM batch options to start GM batch process.

        gm batch -escape windows -feedback on -pass OK -fail NG -prompt off
  • gm4java always use Windows style escape for the compatibility across the platforms
  • prompt is turned off because it is just noise in the machine communication.
  • feedback is turned on because that is how gm4java come to know
    • If GM had completed the execution of the command.
    • The result of the command, whether it was failed or succeeded.
  • gm4java choose OK/NG for pass/fail feedback text, as it is unlikely that the output of any command will produce such text alone in one line.

You now understood that gm4java relies on the proper batch option to operate correctly. Hence, you should never use “set” command directly in gm4java.

GM Process Pooling

Using one single GM batch process in a highly concurrent environment is obviously not enough. Managing multiple GM batch processes is a difficulty task to say the least. gm4java solves this problem by maintaining a pool of GM batch processes for you. It internally uses Apache Commons Pool but hides the complex detail from you so you don’t need to know the Commons Pool in order to use gm4java’s GM process pooling service.

Code Quality

gm4java has nearly 100% code coverage excluding simple getter and setters.

Features and API

The API of gm4java was elaborately designed to be simply. The public interface is very well documented by Javadoc. I’ll cover the basics of the API but I refer you to the API documentation (javadoc) for further reading.

The use of gm4java is very much like using JDBC connection and connection pooling, which most of Java developers are very familiar with.

The primary interface of gm4java is GMConnection.

GMConnection Interface

Just like each JDBC Connection object represent a physical connection to database server, each GMConnection instance represent an interactive session with a GM process running in interactive mode until the connection is closed by invoking its close() method.

   1:  public interface GMConnection {
   2:      String execute(String command, String... arguments) throws GMException, GMServiceException;
   3:      String execute(List<String> command) throws GMException, GMServiceException;
   4:      void close() throws GMServiceException;
   5:  }

GMConnection has two overloaded execute methods, those are the methods you would use to execute GM commands. Each command passed to the execute methods is send to the interactive GM process for execution. The output of the command is then return as a String if it was executed successfully. Otherwise a GMException is thrown and the exception message contains the output of the GM command.

The two execute methods are essentially identical, having two of them is to give you the convenience of passing the command in one way or another.

In simply uses case, you can use varargs version for simplicity. e.g.

    String result = connection.execute("identify", "a.jpg");

But if you need to construct the command conditionally and dynamically, you’ll find the List version is more convenient.

You can use execute methods to run any GM command supported in interactive mode except “set” command. Currently gm4java doesn’t prevent you from doing it but the result is undetermined, mostly failure of all subsequent commands but can also hung. In future, gm4java will try to prevent you from being able to send “set” command.

You must call close() method after you are done with GMConnection, this is again similar to database connection, failure to do so can cause connection leaking. The close() method can effectively end the associated GM process, or just returns the GM process to the pool depends on the implementation of the GMConnection.

Below is the typical usage pattern to ensure connection is closed.

   1:  final GMConnection connection = ...
   2:  try {
   3:      // use connection to run one or many GM commands
   4:  } finally {
   5:      connection.close();
   6:  }

All three methods may throw GMServiceException. It doesn’t like GMException, which is only relevant to the specific GM command being executed, GMServiceException from these methods is usually a permanent condition. It indicates a communication error between gm4java and the interactive GM process, for example, you get this exception if the GM process crashed.

Lastly, please be warned that like JDBC Connection, GMConnection is NOT thread safe!

So far all sounds simple and easy, but GMConnection is an interface, where can we get a real instance of it? That’s is GMService.

GMService Interface

Continue the JDBC analog, GMService is like DataSource. GMService defines three methods, but the important one is the getConnection() method,

   1:  public interface GMService {
   2:      String execute(String command, String... arguments) throws GMException, GMServiceException;
   3:      String execute(List<String> command) throws GMException, GMServiceException;
   4:      GMConnection getConnection() throws GMServiceException;
   5:  }

The getConnection() method returns a GMConnection object associated to either a newly started GM interactive process, or one retrieved from a pool. Whether former or later depends on the actual implementations that we’ll cover in the following sections.

The two execute methods are convenient methods to execute one GM command. Both internally calls the getConnection() method to obtain a connection, execute the given GM command and immediately close the connection. Please see the Java API document for more detail on this.

All methods in GMService are guaranteed to be thread safe.

Although, GMService methods also throw GMServiceException, but it is not necessary, and usually is not, a permanent condition. This is because every time, it deals with a difference instance of GMConnection, hence a different GM process.

GMService is an interface, gm4java provides two concrete implementations of it.


SimpleGMService, telling by its name, is a simple implementation of GMService, Its getConnection method always starts a new GM interactive process and return an instance of GMConnection that is associated with that GM process. Closing of that GMConnection effectively stops the associated GM process. Because of this nature, applications use SimpleGMService to create GMConnection should make max use of the connection before closing it. Below is a typical usage pattern.

   1:  GMService service = new SimpleGMService();
   3:  public void bar() {
   4:      GMConnection connection = service.getConnection();
   5:      try {
   6:          // use connection to run a lot of GM commands 
   7:      } finally {
   8:          connection.close();
   9:      }
  10:  }

The two execute methods in the SimpleGMService are provided for the purpose of completeness and should not be used in general. The implementation starts a new GM interactive process, run the given command and stop the GM process. That is actually slower than simply running the GM in the old single command mode.

SimpleGMService also has a property called gmPath. You’ll need to set this to full path of GM executable if it is not already in the command search path.


PooledGMService is the real star in gm4java. Analog to a JDBC connection pool, PooledGMService is able to manage a pool of GM interactive process and distribute the GM commands across them. Hence it is capable of delivering high performance and scalability in a heavily concurrent environment.

Since it internally uses Apache Commons Pool, it can support all pooling features brought in by Commons Pool which is a highly configurable object pool implementation. PooledGMService must be constructed with an instance of GMConnectionPoolConfig object, which contains a list of properties to configure the pool.

The getConnection() method in PooledGMService returns an instance of GMConnection that is associated with a pooled GM interactive process. The close() methods of the returned GMConnection effectively returns the GM interactive process back to the pool for reuse.

For the applications that run many concurrent threads and each thread is just to run one GM command, the PooledGMService is especially helpful. Its two execute() methods become very useful now. Not only they simplify the code to be written, but also optimize internally to perform better. e.g., code below

   1:  final GMConnection connection = service.getConnection();
   2:  try {
   3:      return connection.execute(command, arguments);
   4:  } finally {
   5:      connection.close();
   6:  }

can be simplified to

    return service.execute(command, arguments);

and the later is more efficient.

im4java Integration

So far, gm4java gives a new way to communicating with GM process to get the work done efficiently. It requires you to know the GM command very well and pass each command and its parameters to the execute methods. For people who are not familiar with native GM commands, there can be a steep learning curve.

Thankfully, im4java did a great job of providing a Java friendly interface to construct the GM commands. So gm4java doesn’t need reinvent the wheel. We’ll let you use your familiar im4java interface to construct operations, then give it to gm4java to executed it efficiently.

GMBatchCommand is the bridge between im4java and gm4java. The usage of it is best illustrated by a few sample programs.

Execute a convert command

   1:  GMService service = ...;
   3:  public void foo() {
   4:      GMBatchCommand command = new GMBatchCommand(service, "convert");
   6:      // create the operation, add images and operators/options
   7:      IMOperation op = new IMOperation();
   8:      op.addImage("input.jpg");
   9:      op.resize(800, 600);
  10:      op.addImage("output.jpg");
  12:      // execute the operation
  14:  }

Execute the identify command

   1:  GMService service = ...;
   3:  public List<String> foo() {
   4:      GMBatchCommand command = new GMBatchCommand(service, "identify");
   6:      IMOperation op = new IMOperation();
   8:      final String format = "%m\n%W\n%H\n%g\n%z";
   9:      op.format(format);
  10:      op.addImage();
  11:      ArrayListOutputConsumer output = new ArrayListOutputConsumer();
  12:      command.setOutputConsumer(output);
  16:      ArrayList<String> cmdOutput = output.getOutput();
  17:      return cmdOutput;
  18:  }

Please note that there are limitations of GMBatchCommand, at this time it doesn’t support im4java asynchronous mode and doesn’t support BufferedImage as output.

We do recognize the integration between im4java and gm4java is still weak. But we also believe there exists strong synergy between im4java and gm4java. Together, we can provide next level of integration between Java and GM.


While gm4java works fine being an independent library, it make perfect sense to have it merged with the im4java project for the reasons mentioned above. We have started the conversation and hopefully we can make it happen.

In next post of this series, I’ll present the new test result of the same web application that we have tested before. This time it uses gm4java.

Other Posts in the “Integrate Java and GraphicsMagick” Series

  1. Conception
  2. im4java Performance
  3. Interactive or Batch Mode
  4. gm4java
  5. gm4java Performance