JVM memory consists of various regions, including Young Generation, Old Generation, and Metaspace. 'java.lang.OutOfMemoryError: Metaspace' occurs when the Metaspace is full due to excessive metadata from dynamically created classes. Solutions include increasing Metaspace size or troubleshooting memory leaks. A sample program demonstrates this memory issue.
The java.lang.String#intern() function can significantly reduce memory consumption by eliminating duplicate strings. In a study comparing two programs, one using intern() and the other not, memory usage was 38.37MB versus 1.08GB, with a notable 97% memory waste in the latter. However, intern() showed slower response time due to additional processing overhead.
The intern() function in Java's String class helps reduce memory consumption by eliminating duplicate string objects, storing intern strings in the JVM heap memory. Earlier, intern strings were in the Perm Generation, but since Java 7, they reside in the Heap region. A practical experiment confirmed this memory behavior.
The intern() function in Java's String class helps eliminate duplicate string objects, reducing memory consumption. It checks if a string exists in the intern pool; if not, it adds it. Although it can improve memory efficiency, it may negatively impact application response time and CPU usage compared to other string deduplication methods.
The JVM memory consists of regions: Young Generation, Old Generation, and Metaspace. To inspect loaded classes in Metaspace, various methods can be used: -verbose:class (Java 8), -Xlog:class+load (Java 9+), jcmd GC.class_histogram, a programmatic approach, and Heap Dump analysis. Each method provides insights without significant application overhead.
The post discusses a 'java.lang.OutOfMemoryError: Metaspace' issue encountered in a Microservice application. It highlights the significance of the Metaspace memory region, outlines steps for diagnosing the error using garbage collection logs, and identifies a memory leak caused by an outdated third-party library. Upgrading the library resolved the issue.
The post discusses troubleshooting an intermittent HTTP 502 Bad Gateway error in an AWS Elastic Beanstalk application running on a Java Tomcat server. The error resulted from the Tomcat server being terminated due to insufficient RAM. Upgrading the EC2 instance's RAM from 1GB to 2GB resolved the issue.
The post discusses c1 and c2 compiler threads created by the Java virtual machine to enhance application performance. These threads can sometimes lead to high CPU usage. The article explains differences between the client and server compilers, explains term-related concepts, and offers potential solutions for addressing CPU consumption issues.
This post examines the performance characteristics of HashMap, Hashtable, and ConcurrentHashMap through practical examples. It finds that while HashMap is fastest, it is not thread-safe, risking infinite loops. ConcurrentHashMap offers comparable speed with thread safety. Hashtable, however, is significantly slower due to synchronization limiting thread access.
The java.lang.ClassLoader#loadClass() API is essential for loading Java classes but can degrade application performance due to thread contention. Frequent calls can cause threads to block, impacting responsiveness. To mitigate these issues, it's advised to load classes once at startup and reuse them, rather than repeatedly during execution.