Memahami Kebocoran Memori di Jawa

Pengaturcaraan

1. Pengenalan

Salah satu kelebihan utama Java adalah pengurusan memori automatik dengan bantuan Pengumpul Sampah terbina dalam (atau GC secara ringkas). GC secara implisit mengurus peruntukan dan pembebasan memori dan dengan itu mampu menangani sebahagian besar masalah kebocoran memori.

Walaupun GC secara berkesan menangani sebahagian memori yang baik, ia tidak menjamin penyelesaian yang mudah untuk kebocoran memori. GC cukup pintar, tetapi tidak sempurna. Kebocoran memori masih boleh tersembunyi walaupun dalam aplikasi pemaju yang berhati-hati.

Masih mungkin ada situasi di mana aplikasi menghasilkan sejumlah besar objek berlebihan, sehingga menghabiskan sumber memori penting, kadang-kadang mengakibatkan kegagalan keseluruhan aplikasi.

Kebocoran memori adalah masalah sebenar di Jawa. Dalam tutorial ini, kita akan melihat apa kemungkinan penyebab kebocoran memori, bagaimana mengenalinya semasa menjalankan, dan bagaimana menghadapinya dalam aplikasi kita .

2. Apa itu Kebocoran Ingatan

Kebocoran Memori adalah keadaan apabila terdapat benda-benda di timbunan yang tidak lagi digunakan, tetapi pengumpul sampah tidak dapat mengeluarkannya dari memori dan, oleh itu, ia tidak perlu dijaga.

Kebocoran memori tidak baik kerana menyekat sumber memori dan menurunkan prestasi sistem dari masa ke masa . Dan jika tidak ditangani, aplikasi tersebut akhirnya akan menghabiskan sumbernya, akhirnya diakhiri dengan java.lang.OutOfMemoryError yang membawa maut .

Terdapat dua jenis objek yang terdapat di memori Heap - dirujuk dan tidak dirujuk. Objek yang dirujuk adalah mereka yang masih mempunyai rujukan aktif dalam aplikasi sedangkan objek yang tidak dirujuk tidak mempunyai rujukan aktif.

Pengutip sampah membuang objek yang tidak dirujuk secara berkala, tetapi tidak pernah mengumpulkan objek yang masih menjadi rujukan. Di sinilah kebocoran memori boleh berlaku:

Gejala Kebocoran Ingatan

  • Kemerosotan prestasi yang teruk ketika aplikasi terus berjalan untuk waktu yang lama
  • Kesalahan timbunan OutOfMemoryError dalam aplikasi
  • Kemalangan aplikasi spontan dan pelik
  • Aplikasi kadangkala kehabisan objek sambungan

Mari kita perhatikan lebih dekat beberapa senario ini dan bagaimana menanganinya.

3. Jenis-Jenis Kebocoran Memori di Jawa

Dalam aplikasi apa pun, kebocoran memori boleh berlaku kerana pelbagai sebab. Di bahagian ini, kita akan membincangkan yang paling biasa.

3.1. Kebocoran Memori Melalui Medan statik

Senario pertama yang boleh menyebabkan kebocoran memori berpotensi adalah penggunaan pemboleh ubah statik yang berat .

Di Jawa, bidang statik memiliki kehidupan yang biasanya sesuai dengan seumur hidup aplikasi yang sedang berjalan (kecuali ClassLoader memenuhi syarat untuk pengumpulan sampah).

Mari buat program Java sederhana yang mengisi Senarai statik :

public class StaticTest { public static List list = new ArrayList(); public void populateList() { for (int i = 0; i < 10000000; i++) { list.add(Math.random()); } Log.info("Debug Point 2"); } public static void main(String[] args) { Log.info("Debug Point 1"); new StaticTest().populateList(); Log.info("Debug Point 3"); } }

Sekarang jika kita menganalisis memori Heap semasa pelaksanaan program ini, maka kita akan melihat bahawa antara titik debug 1 dan 2, seperti yang diharapkan, memori timbunan meningkat.

Tetapi ketika kita meninggalkan kaedah populateList () pada titik debug 3, memori timbunan belum dikumpulkan sampah seperti yang kita lihat dalam respons VisualVM ini:

Walau bagaimanapun, dalam program di atas, pada baris ke-2, jika kita menggugurkan kata kunci secara statik , maka akan membawa perubahan drastik pada penggunaan memori, respons Visual VM ini menunjukkan:

Bahagian pertama sehingga titik debug hampir sama dengan apa yang kami peroleh sekiranya berlaku statik. Tetapi kali ini setelah kita meninggalkan kaedah populateList () , semua memori senarai adalah sampah yang dikumpulkan kerana kita tidak mempunyai rujukan kepadanya .

Oleh itu kita perlu memperhatikan penggunaan pemboleh ubah statik kita . Sekiranya koleksi atau objek besar dinyatakan sebagai statik , maka ia tetap berada dalam memori sepanjang hayat aplikasi, sehingga menyekat memori penting yang sebaliknya dapat digunakan di tempat lain.

Bagaimana Mencegahnya?

  • Meminimumkan penggunaan pemboleh ubah statik
  • Semasa menggunakan singlet, bergantung pada implementasi yang memuatkan objek dengan malas dan bukannya memuatkan dengan bersemangat

3.2. Melalui Sumber yang Tidak Ditutup

Setiap kali kita membuat sambungan baru atau membuka aliran, JVM memperuntukkan memori untuk sumber ini. Beberapa contoh merangkumi sambungan pangkalan data, aliran input, dan objek sesi.

Lupa untuk menutup sumber ini dapat menyekat memori, sehingga menjauhkannya dari jangkauan GC. Ini bahkan boleh berlaku sekiranya terdapat pengecualian yang menghalang pelaksanaan program mencapai pernyataan yang mengendalikan kod untuk menutup sumber ini.

Dalam kedua-dua kes tersebut, sambungan terbuka yang tersisa dari sumber daya menghabiskan memori , dan jika kita tidak menghadapinya , sambungan tersebut dapat merosot prestasi dan bahkan dapat mengakibatkan OutOfMemoryError .

Bagaimana Mencegahnya?

  • Sentiasa gunakan blok akhirnya untuk menutup sumber
  • Kod (walaupun pada blok akhirnya ) yang menutup sumber tidak boleh mempunyai pengecualian
  • Semasa menggunakan Java 7+, kita dapat menggunakan blok try -with-resources

3.3. Tidak wajar sama dengan () dan Kodcincang () Perlaksanaan

Semasa menentukan kelas baru, pengawasan yang sangat biasa adalah tidak menulis kaedah diganti yang betul untuk kaedah sama () dan hashCode () .

HashSet dan HashMap menggunakan kaedah ini dalam banyak operasi, dan jika mereka tidak diganti dengan betul, maka mereka boleh menjadi sumber masalah kebocoran memori yang berpotensi.

Mari kita ambil contoh kelas Person remeh dan menggunakannya sebagai kunci dalam HashMap :

public class Person { public String name; public Person(String name) { this.name = name; } }

Sekarang kita akan memasukkan objek Orang pendua ke dalam Peta yang menggunakan kunci ini.

Ingat bahawa Peta tidak boleh mengandungi kunci pendua:

@Test public void givenMap_whenEqualsAndHashCodeNotOverridden_thenMemoryLeak() { Map map = new HashMap(); for(int i=0; i<100; i++) { map.put(new Person("jon"), 1); } Assert.assertFalse(map.size() == 1); }

Here we're using Person as a key. Since Map doesn't allow duplicate keys, the numerous duplicate Person objects that we've inserted as a key shouldn't increase the memory.

But since we haven't defined proper equals() method, the duplicate objects pile up and increase the memory, that's why we see more than one object in the memory. The Heap Memory in VisualVM for this looks like:

However, if we had overridden the equals() and hashCode() methods properly, then there would only exist one Person object in this Map.

Let's take a look at proper implementations of equals() and hashCode() for our Person class:

public class Person { public String name; public Person(String name) { this.name = name; } @Override public boolean equals(Object o) { if (o == this) return true; if (!(o instanceof Person)) { return false; } Person person = (Person) o; return person.name.equals(name); } @Override public int hashCode() { int result = 17; result = 31 * result + name.hashCode(); return result; } }

And in this case, the following assertions would be true:

@Test public void givenMap_whenEqualsAndHashCodeNotOverridden_thenMemoryLeak() { Map map = new HashMap(); for(int i=0; i<2; i++) { map.put(new Person("jon"), 1); } Assert.assertTrue(map.size() == 1); }

After properly overriding equals() and hashCode(), the Heap Memory for the same program looks like:

Another example is of using an ORM tool like Hibernate, which uses equals() and hashCode() methods to analyze the objects and saves them in the cache.

The chances of memory leak are quite high if these methods are not overridden because Hibernate then wouldn't be able to compare objects and would fill its cache with duplicate objects.

How to Prevent It?

  • As a rule of thumb, when defining new entities, always override equals() and hashCode() methods
  • It's not just enough to override, but these methods must be overridden in an optimal way as well

For more information, visit our tutorials Generate equals() and hashCode() with Eclipse and Guide to hashCode() in Java.

3.4. Inner Classes That Reference Outer Classes

This happens in the case of non-static inner classes (anonymous classes). For initialization, these inner classes always require an instance of the enclosing class.

Every non-static Inner Class has, by default, an implicit reference to its containing class. If we use this inner class' object in our application, then even after our containing class' object goes out of scope, it will not be garbage collected.

Consider a class that holds the reference to lots of bulky objects and has a non-static inner class. Now when we create an object of just the inner class, the memory model looks like:

However, if we just declare the inner class as static, then the same memory model looks like this:

This happens because the inner class object implicitly holds a reference to the outer class object, thereby making it an invalid candidate for garbage collection. The same happens in the case of anonymous classes.

How to Prevent It?

  • If the inner class doesn't need access to the containing class members, consider turning it into a static class

3.5. Through finalize() Methods

Use of finalizers is yet another source of potential memory leak issues. Whenever a class' finalize() method is overridden, then objects of that class aren't instantly garbage collected. Instead, the GC queues them for finalization, which occurs at a later point in time.

Additionally, if the code written in finalize() method is not optimal and if the finalizer queue cannot keep up with the Java garbage collector, then sooner or later, our application is destined to meet an OutOfMemoryError.

To demonstrate this, let's consider that we have a class for which we have overridden the finalize() method and that the method takes a little bit of time to execute. When a large number of objects of this class gets garbage collected, then in VisualVM, it looks like:

However, if we just remove the overridden finalize() method, then the same program gives the following response:

How to Prevent It?

  • We should always avoid finalizers

For more detail about finalize(), read section 3 (Avoiding Finalizers) in our Guide to the finalize Method in Java.

3.6. Interned Strings

The Java String pool had gone through a major change in Java 7 when it was transferred from PermGen to HeapSpace. But for applications operating on version 6 and below, we should be more attentive when working with large Strings.

If we read a huge massive String object, and call intern() on that object, then it goes to the string pool, which is located in PermGen (permanent memory) and will stay there as long as our application runs. This blocks the memory and creates a major memory leak in our application.

The PermGen for this case in JVM 1.6 looks like this in VisualVM:

In contrast to this, in a method, if we just read a string from a file and do not intern it, then the PermGen looks like:

How to Prevent It?

  • The simplest way to resolve this issue is by upgrading to latest Java version as String pool is moved to HeapSpace from Java version 7 onwards
  • If working on large Strings, increase the size of the PermGen space to avoid any potential OutOfMemoryErrors: 
    -XX:MaxPermSize=512m

3.7. Using ThreadLocals

ThreadLocal (discussed in detail in Introduction to ThreadLocal in Java tutorial) is a construct that gives us the ability to isolate state to a particular thread and thus allows us to achieve thread safety.

When using this construct, each thread will hold an implicit reference to its copy of a ThreadLocal variable and will maintain its own copy, instead of sharing the resource across multiple threads, as long as the thread is alive.

Despite its advantages, the use of ThreadLocal variables is controversial, as they are infamous for introducing memory leaks if not used properly. Joshua Bloch once commented on thread local usage:

“Sloppy use of thread pools in combination with sloppy use of thread locals can cause unintended object retention, as has been noted in many places. But placing the blame on thread locals is unwarranted.”

Memory leaks with ThreadLocals

ThreadLocals are supposed to be garbage collected once the holding thread is no longer alive. But the problem arises when ThreadLocals are used along with modern application servers.

Modern application servers use a pool of threads to process requests instead of creating new ones (for example the Executor in case of Apache Tomcat). Moreover, they also use a separate classloader.

Since Thread Pools in application servers work on the concept of thread reuse, they are never garbage collected — instead, they're reused to serve another request.

Now, if any class creates a ThreadLocal variable but doesn't explicitly remove it, then a copy of that object will remain with the worker Thread even after the web application is stopped, thus preventing the object from being garbage collected.

How to Prevent It?

  • It's a good practice to clean-up ThreadLocals when they're no longer used — ThreadLocals provide the remove() method, which removes the current thread's value for this variable
  • Do not use ThreadLocal.set(null) to clear the value — it doesn't actually clear the value but will instead look up the Map associated with the current thread and set the key-value pair as the current thread and null respectively
  • It's even better to consider ThreadLocal as a resource that needs to be closed in a finally block just to make sure that it is always closed, even in the case of an exception: 
    try { threadLocal.set(System.nanoTime()); //... further processing } finally { threadLocal.remove(); }

4. Other Strategies for Dealing With Memory Leaks

Although there is no one-size-fits-all solution when dealing with memory leaks, there are some ways by which we can minimize these leaks.

4.1. Enable Profiling

Java profilers are tools that monitor and diagnose the memory leaks through the application. They analyze what's going on internally in our application — for example, how memory is allocated.

Using profilers, we can compare different approaches and find areas where we can optimally use our resources.

We have used Java VisualVM throughout section 3 of this tutorial. Please check out our Guide to Java Profilers to learn about different types of profilers, like Mission Control, JProfiler, YourKit, Java VisualVM, and the Netbeans Profiler.

4.2. Verbose Garbage Collection

By enabling verbose garbage collection, we're tracking detailed trace of the GC. To enable this, we need to add the following to our JVM configuration:

-verbose:gc

By adding this parameter, we can see the details of what's happening inside GC:

4.3. Use Reference Objects to Avoid Memory Leaks

We can also resort to reference objects in Java that comes in-built with java.lang.ref package to deal with memory leaks. Using java.lang.ref package, instead of directly referencing objects, we use special references to objects that allow them to be easily garbage collected.

Reference queues are designed for making us aware of actions performed by the Garbage Collector. For more information, read Soft References in Java Baeldung tutorial, specifically section 4.

4.4. Eclipse Memory Leak Warnings

For projects on JDK 1.5 and above, Eclipse shows warnings and errors whenever it encounters obvious cases of memory leaks. So when developing in Eclipse, we can regularly visit the “Problems” tab and be more vigilant about memory leak warnings (if any):

4.5. Benchmarking

We can measure and analyze the Java code's performance by executing benchmarks. This way, we can compare the performance of alternative approaches to do the same task. This can help us choose a better approach and may help us to conserve memory.

For more information about benchmarking, please head over to our Microbenchmarking with Java tutorial.

4.6. Code Reviews

Finally, we always have the classic, old-school way of doing a simple code walk-through.

In some cases, even this trivial looking method can help in eliminating some common memory leak problems.

5. Conclusion

In layman's terms, we can think of memory leak as a disease that degrades our application's performance by blocking vital memory resources. And like all other diseases, if not cured, it can result in fatal application crashes over time.

Kebocoran memori sukar untuk diselesaikan dan mencarinya memerlukan penguasaan dan perintah yang rumit terhadap bahasa Java. Semasa menangani kebocoran memori, tidak ada solusi yang sesuai dengan semua ukuran, kerana kebocoran dapat terjadi melalui berbagai peristiwa yang beragam.

Walau bagaimanapun, jika kita menggunakan amalan terbaik dan secara berkala melakukan panduan kod dan profil yang ketat, maka kita dapat meminimumkan risiko kebocoran memori dalam aplikasi kita.

Seperti biasa, coretan kod yang digunakan untuk menghasilkan respons VisualVM yang digambarkan dalam tutorial ini terdapat di GitHub.