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![Inefficiency in Collections
List<User> users = new ArrayList<>();
users.add(user);
2 54 6 7 8 1093
wasted
11
ArrayList underlyingly maintains
Object[]
initial capacity = 10](https://image.slidesharecdn.com/howtowritememoryefficientcode-190321123322/85/How-to-write-memory-efficient-code-16-320.jpg)
![Inefficiency in Collections
List<User> users = new ArrayList<>();
users.add(user);
2 54 6 7 8 1093
wasted
11
ArrayList underlyingly maintains
Object[]
initial capacity = 10](https://image.slidesharecdn.com/howtowritememoryefficientcode-190321123322/75/How-to-write-memory-efficient-code-16-2048.jpg)
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Similar to How to write memory efficient code?
How to write memory efficient code?
- 1. How to memoryefficient Code? Ram Lakshmanan Architect – GCeasy.io, fastThread.io, HeapHero.io Confoo 2019
- 2. Do I needto care about memory? It’s very cheap! 1970s 1 Byte = 1 $ 2019 FRACTION OF COST
- 3. Here is mycase: Memory is not cheap! Memory saturates first. Other resources are partially/under utilized. 3. Storage 4. Network 1. CPU 2. Memory
- 4. Do you knowhow much memory applications wastes? 30 – 90%
- 5. You can't optimize,what you can't measure A famous saying
- 6. How to measurewasted memory? Step 1: Capture Heap dumps in production* https://blog.heaphero.io/2017/10/13/how-to-capture-java-heap-dumps-7-options/ Step 2: Analyze with HeapHero: https://heaphero.io Reports amount of memory wasted, code triggering it, recommendations to fix. * - if possible
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- 9. What is duplicateString? String s1 = new String("Hello World"); String s2 = new String("Hello World"); System.out.println(s1.equals(s2)); // prints 'true' System.out.println((s1 == s2)); // prints 'false'
- 10. Solution 1: intern() Strings1 = new String("Hello World").intern(); String s2 = new String("Hello World").intern(); System.out.println(s1.equals(s2)); // prints 'true' System.out.println((s1 == s2)); // prints 'true' >>> s1 = intern(’Hello World') Java Python
- 11. How intern() works? “HelloWorld” s1 s2 String pool String s1 = new String("Hello World").intern(); String s2 = new String("Hello World").intern();
- 12. Solution 2: UseStringDeduplication •-XX:+UseStringDeduplication • Works only with • G1 GC algorithm • Java 8 update 20 • Real life case study: https://blog.gceasy.io/2018/07/17/disappointing-story-on-memory- optimization/ Long lived objects (-XX:StringDeduplicationAgeThreshold=3) • Check GC pause time impact
- 13. Solution 3: UseString literals public static final String HELLO_WORLD = “Hello World”;
- 14. Solution 4: Avoidcreating strings In DB store data as primitive types: user id Name …. country 1 Joe Libson …. Canada 2 Nathan Ray …. Canada 3 Chris Mang …. USA 4 Erik Pilz …. USA 5 Lakshmi Singh …. India user id Name …. country 1 Joe Libson …. 2 2 Nathan Ray …. 2 3 Chris Mang …. 1 4 Erik Pilz …. 1 5 Lakshmi Singh …. 124
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- 16. Inefficiency in Collections List<User>users = new ArrayList<>(); users.add(user); 2 54 6 7 8 1093 wasted 11 ArrayList underlyingly maintains Object[] initial capacity = 10
- 17. 1 2 546 7 8 1093 Inefficiency in Collections wasted List<User> users = new ArrayList<>(); for (int counter = 1; counter <= 11; ++counter) { users.add(user); } 1 2 54 6 7 8 1093 11 12 1514 17 18 201913 16 1 2 54 6 7 8 93 11 12 1514 17 18 201913 16 21 22 2524 26 27 28 2923 31 32 3534 37 38 403933 3630 wasted 10 for (int counter = 1; counter <= 21; ++counter) { users.add(user); }
- 18. Recommendation 1: usecapacity new ArrayList<>(3); new ArrayList<>();
- 19. Recommendation 2: lazyinitialization private List<User> users = new ArrayList<>(); public void addUser(User user) { users.add(user); } private List<User> users; public void addUser(User user) { if (users == null) { users = new ArrayList<>(); } users.add(user); }
- 20. Recommendation 3: avoidclear() List<User> users = new ArrayList<>(); users = null; List<User> users = new ArrayList<>(); users.clear();
- 21. Let’s understand overheadof an Object
- 22. Object overhead public classUser { private String name; private int age; private float weight; } new User(); Object Header name age weight 12 bytes 4 bytes 4 bytes 4 bytes Fixed overhead 1. Virtual method invocation 2. ‘synchronized’ object lock 3. Garbage collection 4. Object book keeping 24 bytes
- 23. Boxed numbers: java.lang.Integer •int: 4 bytes • java.lang.Integer: 16 bytes Data is 4 bytes, object overhead is 12 bytes
- 24. Yesterday’s key note:2 instance variables/class public class User { private int field1; private int field2; private int field3; : private int field10; } public class User { private Object1 obj1; private Object2 obj2; } public class Object1 { private int field1; private Object3 obj3; } public class Object2 { private int field2; private Object4 obj4; } public class Object3 { private int field3; private Object5 obj5; } public class Object4 { private int field4; private Object6 obj6; }52 bytes i.e. 12 bytes header + (10 ints* 4 bytes) public class Object5 { private int field5; private Object6 obj7; } public class Object6 { private int field6; private Object3 obj8; } public class Object7 { private int field7; private Object4 obj9; } public class Object8 { private int field8; private int field9; } public class Object9 { private int field10; } 196 bytes (~4x more needed) = 10 object headers * 12 + (10 ints * 4 bytes) + (9 object references * 4)
- 25. How all memoryis wasted? 1. Duplicate Strings: https://heaphero.io/heap-recommendations/duplicate-strings.html 2. Wrong memory size settings 3. Inefficient Collections: http://heaphero.io/heap-recommendations/inefficient-collections.html 4. Duplicate Objects: https://heaphero.io/heap-recommendations/duplicate-objects.html 5. Duplicate arrays: https://heaphero.io/heap-recommendations/duplicate-primitive-arrays.html 6. Inefficient arrays: https://heaphero.io/heap-recommendations/inefficient-primitive-arrays.html 7. Objects waiting for finalization: https://heaphero.io/heap-recommendations/objects-waiting- finalization.html 8. Boxed numbers: https://heaphero.io/heap-recommendations/boxed-numbers.html 9. Object Headers: https://heaphero.io/heap-recommendations/object-headers.html
- 26. Reduce computing cost BetterResponse time Reduce Garbage Collection Pause Time Optimizing memory
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- 28. Thank you!! ram@tier1app.com Ram Lakshmanan @tier1app https://www.linkedin.com/company/gceasy AnyQuestions Deck will be published in: http://blog.heaphero.io
Editor's Notes
- #8 https://heaphero.io/my-heap-report.jsp?p=YXJjaGl2ZWQvMjAxOS8wMy8xNC8tLVRQQkUxLWhlYXBkdW1wLTE3XzA4XzE3XzEwXzMwLmJpbi5nei0zLTQ0LTE1Lmpzb24tLQ== https://heaphero.io/my-heap-report.jsp?p=YXJjaGl2ZWQvMjAxOS8wMy8xNC8tLVRQU1AxLWhlYXBkdW1wLTE3XzA4XzE3XzEwXzMwLmJpbi5nei0zLTI1LTI3Lmpzb24tLQ==