Android NDK: How to Reduce Binaries Size – The Algolia Blog

When we started Algolia Development for Android, binary size optimization was not one of our main concerns. In fact we even started to develop in JAVA before switching to C/C++ for reasons of performance.

We were reminded of the importance of binary size by Cyril Mottier who informed us that it would be difficult to integrate our lib in AVelov Android Application because its size. AVelov is 638KB and Algolia was 850KB, which would mean that AVelov would more than double in size with Algolia Search embedded.

To address this problem we managed to reduce Algolia binary size from 850KB to 307KB. In this post we share how we did it.

Do not use Exceptions and RTTI

We actually do not use exceptions in our native lib, but for the sake of completeness, I’ll cover this point too.

C++ exceptions and RTTI are disabled by default but you can enable them via APP_CPPFLAGS in your file and use a compatible STL, for example:

APP_CPPFLAGS += -fexceptions -frtti
APP_STL := stlport_shared

Whilst using exceptions and RTTI can help you to use existing code, it will obviously increase your binary size. If you have a way to remove them, go for it! Actually, there’s another reason to avoid using C++ exceptions: their support is still far from perfect. For example if was impossible for us to catch a C++ exception and launch a Java exception in JNI. The following code results in a crash (will probably be fixed in a future release of the Android NDK toolchain):

try {
} catch (std::exception& e) {
    env->ThrowNew(env->FindClass("java/lang/Exception"), "Error occured");

Do not use iostream

When starting to investigate our library size following Cyril’s feedback, we discovered that Algolia binaries had vastly increased in size since our last release (from 850KB to 1.35MB)! We first suspected the Android NDK toolchain since we upgraded it and tested different toolchains, but we only observed minor changes.

By dichotomy search in our commits, we discovered that a single line of code was responsible for the inflation:

std::cerr << .... << std::endl;

As incredible as it may sound, using iostream increases a lot the binary size. Our tests shown that it adds a least 300KB per architecture! You must be very careful with iostream and prefer to use __android_log_print method:

#include <android/log.h>
#define APPNAME "MyApp"

__android_log_print(ANDROID_LOG_VERBOSE, APPNAME, "The value of 1 + 1 is %d", 1+1);

Make sure you also link against the logging library, in your file:


Use -fvisibility=hidden

An efficient way to reduce binary size is to use the visibility feature of gcc. This feature lets you control which functions will be exported in the symbols table. Hopefully, JNI comes with a JNIEXPORT macro that flags JNI functions as public. You just have to check that all functions used by JNI are prefixed by JNIEXPORT, like this one:

JNIEXPORT void JNICALL Java_ClassName_MethodName
(JNIEnv *env, jobject obj, jstring javaString)

Then you have just to add -fvisibility=hidden for C and C++ files in file:

LOCAL_CPPFLAGS += -fvisibility=hidden
LOCAL_CFLAGS += -fvisibility=hidden

In our case the binaries were down to 809KB (-5%) but remember the gains may be very different for your project. Make your own measures!

Discard Unused Functions with gc-sections

Another interesting approach is to remove unused code in the binary. It can drastically reduce its size if for example part of your code is only used for tests.
To enable this feature, you just have to change the C and C++ compilation flags and the linker flags in
LOCAL_CPPFLAGS += -ffunction-sections -fdata-sections
LOCAL_CFLAGS += -ffunction-sections -fdata-sections 
LOCAL_LDFLAGS += -Wl,--gc-sections

Of course you can combine this feature with the visibility one:

LOCAL_CPPFLAGS += -ffunction-sections -fdata-sections -fvisibility=hidden
LOCAL_CPPFLAGS += -ffunction-sections -fdata-sections -fvisibility=hidden
LOCAL_CFLAGS += -ffunction-sections -fdata-sections  LOCAL_LDFLAGS += -Wl,--gc-sections

This optim only got us a 1% gain, but once combined with the previous visibility one, we were down to 691KB (-18.7%).

Remove Duplicated Code

You can remove duplicated code with the –icf=safe option of the linker. Be careful, this option will probably remove your code inlining, you must check that this flag does not impact performance.

This option is not yet available on the mips architecture so you need to add an architecture check in

ifneq ($(TARGET_ARCH),mips)
  LOCAL_LDFLAGS += -Wl,--icf=safe
And if you want to combine this option with gc-sections:
ifeq ($(TARGET_ARCH),mips)
  LOCAL_LDFLAGS += -Wl,--gc-sections
  LOCAL_LDFLAGS += -Wl,--gc-sections,--icf=safe

We actually only obtained a 0.8% gain in size with this one. All previous optimizations combined, we were now at 687KB (-19.2%).

Change the Default Flags of the Toolchain

If you want to go even further, you can change the default compilation flags of the toolchain. Flags are not identical accross architectures, for example:

  • inline-limit is set to 64 for arm and set to 300 for x86 and mips
  • Optimization flag is set to -Os (optimize for size) for arm and set to -O2 (optimize for performance) for x86 and mips

As arm is used by the large majority of devices, we have applied arm settings for other architectures. Here is the patch we applied on the toolchain (version r8d):

--- android-ndk-r8d/toolchains/mipsel-linux-android-4.6/
@@ -41,12 +41,12 @@

-TARGET_mips_release_CFLAGS := -O2 
+TARGET_mips_release_CFLAGS := -Os 
-                              -finline-limit=300
+                              -finline-limit=64

 TARGET_mips_debug_CFLAGS := -O0 
--- android-ndk-r8d/toolchains/x86-4.6/
@@ -39,13 +39,13 @@

 TARGET_CFLAGS += -fstack-protector

-TARGET_x86_release_CFLAGS := -O2 
+TARGET_x86_release_CFLAGS := -Os 
-                             -finline-limit=300
+                             -finline-limit=64

 # When building for debug, compile everything as x86.
 TARGET_x86_debug_CFLAGS := $(TARGET_x86_release_CFLAGS)

We were good for a 8.5% gain with these new flags. Once combined with previous optimizations, we were now at 613KB (-27.9%).

Limit the Number of Architectures

Our final suggestion is to limit the number of architectures. Supporting armeabi-v7a is mandory for performance if you have a lot of floating point computation, but armeabi will provide a similar result if you do not need a FPU. As for mips processors… well they just are not in use on the market today.

And if binary size is really important to you, you can just limit your support to armeabi and x86 architectures in

APP_ABI := armeabi x86

Obviously, this optim was the killer one. Dropping two out of four architectures halved the binaries size. Overall we obtained a size of 307KB, a 64% gain from the initial 850KB (not counting the bump at 1.35MB due to iostream).


I hope this post will help you to reduce the size of your native libraries on Android since default flags are far from optimal. Don’t expect to obtain the same size reductions, they will highly depend on your specific usage. And if you know other methods to reduce binary size, please share in the comments!


About the authorJulien Lemoine

Julien Lemoine

Co-founder & former CTO at Algolia

Recommended Articles

Powered by Algolia AI Recommendations

InstantSearch Android: Optimized Search Components for Android

InstantSearch Android: Optimized Search Components for Android

Paul-Louis Nech

Paul-Louis Nech

Senior ML Engineer
Algolia's top 10 tips to achieve highly relevant search results

Algolia's top 10 tips to achieve highly relevant search results

Julien Lemoine

Julien Lemoine

Co-founder & former CTO at Algolia
Inside the Engine Part 8: Handling Advanced Search Use Cases

Inside the Engine Part 8: Handling Advanced Search Use Cases

Julien Lemoine

Julien Lemoine

Co-founder & former CTO at Algolia