Garbage collection in Java is an automatic memory management process that identifies and removes objects that are no longer needed by the program, freeing up memory for reuse.

Techniques of Garbage Collection

Mark and Sweep

This is one of the fundamental algorithms used in garbage collection, not just in Java but in many programming languages.

The Mark and Sweep algorithm consists of two main phases:

1. Mark Phase

• The garbage collector starts from the “root set” of objects. These are objects that are directly accessible to the program, such as global variables, objects on the stack, or objects in CPU registers.

• It then recursively traverses all references from these root objects, marking each object it encounters as “alive”.

• This process continues until all reachable objects have been marked.

• Any objects that aren’t marked after this process are considered unreachable and thus eligible for garbage collection.

2. Sweep Phase

• The garbage collector iterates through the entire heap memory.

• For each object it encounters:
  • If the object is marked, it clears the mark for future collection cycles.
  • If the object is not marked, it’s considered garbage and its memory is freed.
• The freed memory is typically added to a list of available memory blocks that can be used for future allocations.

Additional details and considerations

• Stop-the-World: Traditional Mark and Sweep is a “stop-the-world” algorithm, meaning that the application threads must be paused during garbage collection to ensure consistency.

• Memory Fragmentation: One drawback of basic Mark and Sweep is that it can lead to memory fragmentation over time, as freed objects leave gaps in memory.

• Optimizations:
  • Bitmap marking: Instead of modifying objects to mark them, a separate bitmap can be used to track marked objects, which can be more efficient.
  • Lazy sweeping: The sweep phase can be done incrementally or lazily, cleaning up memory only when needed for new allocations.
• Tri-color marking: An optimization where objects are divided into three sets during marking:
  • White: Objects not yet discovered.
  • Gray: Discovered objects whose references haven’t been examined yet.
  • Black: Fully examined objects.

• Parallel Mark and Sweep: Modern implementations often parallelize both the mark and sweep phases to improve performance on multi-core systems.

• Concurrent Mark and Sweep: Some garbage collectors (like Java’s CMS) perform marking concurrently with the application to reduce pause times.

While the basic concept of Mark and Sweep remains the same, Java’s garbage collectors have evolved to use more sophisticated variants of this algorithm, often combining it with other techniques like copying or generational collection to optimize performance and reduce pause times.

Copying

The Copying technique is another important garbage collection algorithm, often used in combination with other methods. It’s particularly effective for managing the young generation in generational garbage collection systems. Here’s a detailed look at the Copying technique:

Basic Concept:

The Copying algorithm divides the available memory space into two equal halves: the “From” space and the “To” space (also sometimes called “Semi-spaces”).

Key Steps:

1. Allocation:
   • All new objects are allocated in the “From” space.
   • Allocation is typically done using a simple bump pointer, which is very fast.
2. Collection Process:
   • When the “From” space fills up, garbage collection is triggered.
   • The garbage collector identifies all live objects in the “From” space.
   • These live objects are copied to the “To” space.
   • After copying, the roles of the spaces are swapped - the “To” space becomes the new “From” space and vice versa.

Advantages:

1. Simplicity: The algorithm is relatively simple to implement.

2. Speed: Allocation is very fast, using a bump pointer.

3. No Fragmentation: By copying live objects to a new space, memory fragmentation is eliminated.

4. Implicit Compaction: As objects are copied, they are naturally compacted in memory.

5. Efficient for Short-lived Objects: It works well when most objects die young, as is often the case in many applications.

Disadvantages:

1. Space Overhead: It requires twice as much memory as the total live set of objects.

2. Inefficient for Long-lived Objects: If most objects survive, a lot of copying occurs, which can be time-consuming.

3. Cache Unfriendly: Copying objects can disrupt cache locality.

Implementation in Java:

• In Java’s generational garbage collection, a variant of the Copying algorithm is used for the young generation.

• The young generation is typically divided into one Eden space and two Survivor spaces (instead of just two spaces).

• New objects are allocated in Eden.

• During a minor collection, live objects from Eden are copied to one of the Survivor spaces.

• Objects that survive multiple minor collections are eventually promoted to the old generation.

Optimizations:

1. Age Tracking: Objects are given an “age” each time they survive a collection. This is used to determine when to promote objects to the old generation.

2. Adaptive Sizing: The sizes of Eden and Survivor spaces can be dynamically adjusted based on application behavior.

3. Thread-Local Allocation Buffers (TLABs): Each thread gets its own small allocation buffer in Eden, reducing contention for the shared allocation pointer.

4. Parallel Copying: Multiple threads can be used to copy objects concurrently, speeding up the process on multi-core systems.

The Copying technique is particularly effective for managing short-lived objects, which is why it’s commonly used for the young generation in Java’s garbage collectors. However, due to its space overhead, it’s typically not used for the entire heap in production systems.

Generational Collection

Generational Collection is a widely used garbage collection technique in Java and other languages. It’s based on the empirical observation known as the “weak generational hypothesis,” which states that most objects die young. Here’s a detailed look at Generational Collection:

Key Concept:

The heap is divided into multiple generations, typically a young generation and an old generation. Some implementations also include a third permanent generation (though this was removed in Java 8 in favor of metaspace).

Structure:

1. Young Generation:
   • Further divided into Eden space and two Survivor spaces (often called S0 and S1).
   • Most new objects are allocated here.
   • Typically small and collected frequently.
2. Old Generation (Tenured Space):
   • Holds long-lived objects.
   • Larger and collected less frequently.

Process:

1. Object Allocation:
   • New objects are typically allocated in Eden space.
   • When Eden fills up, a minor garbage collection is triggered.
2. Minor Garbage Collection (Young Generation):
   • Uses a copying algorithm.
   • Live objects in Eden are copied to one of the Survivor spaces.
   • Live objects in the current “from” Survivor space are copied to the “to” Survivor space.
   • Survivor spaces switch roles after each collection.
   • Objects that survive multiple minor collections are promoted to the Old Generation.
3. Major Garbage Collection (Full GC):
   • Collects both Young and Old Generations.
   • Usually uses a mark-sweep-compact algorithm.
   • Typically causes longer pause times.

Advantages:

1. Efficiency: Most collections are minor and only deal with a small portion of the heap.
2. Short Pause Times: Minor collections are usually quick.
3. Optimized for Common Case: Efficient for applications where most objects die young.

Challenges and Optimizations:

1. Premature Promotion: Objects may be promoted to Old Generation too soon, leading to unnecessary major collections.
   • Solution: Adaptive promotion thresholds.
2. Intergenerational References: Old objects may reference young objects.
   • Solution: Card marking and remembered sets to track these references.
3. Large Objects: Allocating large objects in Eden can be inefficient.
   • Solution: Directly allocate large objects in Old Generation.
4. Pause Times: Major collections can still cause noticeable pauses.
   • Solutions: Concurrent and incremental collection algorithms (like CMS and G1).

Java’s Implementations:

1. Serial GC: Simple, single-threaded collector.
2. Parallel GC: Uses multiple threads for minor collections.
3. Concurrent Mark Sweep (CMS): Performs most major collection work concurrently.
4. G1 (Garbage First): Divides heap into regions, can be seen as a more flexible generational collector.
5. ZGC and Shenandoah: Low-latency collectors that blur the lines between generations.

Tuning Parameters:

• -Xmn: Sets the size of the Young Generation.
• -XX:NewRatio: Ratio of Old to Young Generation sizes.
• -XX:SurvivorRatio: Ratio of Eden to Survivor space size.
• -XX:MaxTenuringThreshold: Maximum number of minor collections an object can survive before promotion.

Monitoring:

• Use -verbose:gc to print GC details.
• Tools like jstat, jconsole, and VisualVM can provide real-time GC statistics.

Generational Collection has proven to be very effective for a wide range of applications, which is why it’s the default strategy in many JVM implementations. However, as applications become more diverse and as requirements for low-latency increase, newer garbage collection algorithms are being developed that may deviate from the traditional generational model.

Concurrent and Parallel Collection

Concurrent and Parallel Collection techniques are advanced garbage collection strategies designed to improve performance and reduce pause times, especially for large-scale applications. Let’s explore both in detail:

Parallel Collection:

1. Basic Concept:
   • Uses multiple threads to perform garbage collection tasks simultaneously.
   • Aims to reduce overall GC time by leveraging multi-core processors.
2. Key Features:
   • “Stop-the-world” events still occur, but they’re shorter due to parallelism.
   • Typically used for both minor and major collections.
3. Advantages:
   • Significantly reduces collection time on multi-core systems.
   • Improves throughput for applications with large heaps.
4. Java Implementation:
   • Parallel Scavenge (for young generation)
   • Parallel Old (for old generation)
5. Tuning Parameters:
   • -XX:ParallelGCThreads: Sets the number of GC threads.
   • -XX:+UseParallelGC: Enables parallel collection.

Concurrent Collection:

1. Basic Concept:
   • Performs much of the GC work concurrently with the application threads.
   • Aims to minimize pause times by doing GC work while the application is running.
2. Key Features:
   • Typically involves short “stop-the-world” pauses for certain phases.
   • Often used for major collections in the old generation.
3. Advantages:
   • Significantly reduces pause times, improving application responsiveness.
   • Better suited for applications requiring low latency.
4. Challenges:
   • Slightly lower throughput due to overhead of concurrent operations.
   • Needs to handle concurrent modifications by the application.
5. Java Implementations:
   • Concurrent Mark Sweep (CMS)
   • G1 Garbage Collector (which is both concurrent and parallel)
6. Phases (using CMS as an example):
   • Initial Mark (brief pause)
   • Concurrent Mark
   • Concurrent Preclean
   • Remark (brief pause)
   • Concurrent Sweep
   • Concurrent Reset
7. Tuning Parameters:
   • -XX:+UseConcMarkSweepGC: Enables CMS
   • -XX:CMSInitiatingOccupancyFraction: When to start a CMS collection cycle

Combined Approaches:

Many modern garbage collectors combine both parallel and concurrent techniques:

1. G1 (Garbage-First) Collector:
   • Uses both concurrent and parallel collection strategies.
   • Divides heap into regions, allowing for incremental collection.
   • Aims to provide both low pause times and high throughput.
2. ZGC (Z Garbage Collector):
   • Concurrent collector designed for very large heaps.
   • Uses colored pointers and load barriers for concurrent operations.
   • Aims for sub-millisecond pause times.
3. Shenandoah:
   • Another concurrent collector focusing on low pause times.
   • Uses Brooks pointers for concurrent compaction.

Considerations for Choosing and Tuning:

1. Application Characteristics:
   • Parallel collectors are better for batch processing or applications prioritizing throughput.
   • Concurrent collectors are preferable for interactive applications needing low latency.
2. Hardware Resources:
   • Parallel collectors benefit more from additional CPU cores.
   • Concurrent collectors may require more total CPU time but distribute it better.
3. Heap Size:
   • Larger heaps often benefit more from concurrent collection to manage pause times.
4. Monitoring and Tuning:
   • Use tools like jstat, jconsole, or VisualVM to monitor GC behavior.
   • Adjust collector-specific parameters based on observed performance.

Both Concurrent and Parallel Collection techniques represent significant advancements in garbage collection, allowing Java applications to scale to larger heap sizes and more demanding performance requirements. The choice and tuning of these collectors can have a substantial impact on application performance and user experience.

Tuning Garbage Collection

1. Choosing the right GC algorithm:
   • Use -XX:+UseSerialGC for small applications.
   • Use -XX:+UseParallelGC for multi-core systems prioritizing throughput.
   • Use -XX:+UseConcMarkSweepGC or -XX:+UseG1GC for large heaps and low pause times.
2. Adjusting heap size:
   • Set initial heap size with -Xms.
   • Set maximum heap size with -Xmx.
3. Tuning generation sizes:
   • Adjust young generation size with -Xmn.
   • Set ratio of eden to survivor spaces with -XX:SurvivorRatio.
4. Adjusting GC frequency:
   • Increase -XX:MaxTenuringThreshold to keep objects in young generation longer.
   • Adjust -XX:TargetSurvivorRatio to control promotion to old generation.
5. Monitoring and profiling:
   • Use tools like jstat, jconsole, or VisualVM to monitor GC behavior.
   • Analyze GC logs with -XX:+PrintGCDetails and -XX:+PrintGCTimeStamps.

Summary

Java’s garbage collection employs diverse techniques to manage memory efficiently, freeing developers from manual memory management. Mark and Sweep removes unused objects, Copying combats fragmentation, and Generational Collection optimizes for short-lived objects. Parallel Collection speeds up GC using multiple threads, while Concurrent Collection reduces pause times. These methods automate memory reclamation, prevent memory leaks, and enhance application stability. Modern collectors like G1 often combine approaches, balancing performance and responsiveness. By automating complex memory management tasks, GC allows developers to focus on core application logic, leading to faster development cycles and more reliable software.