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GC easy – Universal Java GC Log Analyser

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Java

Simulation und Fehlerbehebung von Deadlocks in Kotlin – Bahnbrechende Deadlocks

We appreciate Entwinkler.de JavaMagazin for translating and publishing our article ‘Simulating and troubleshooting deadlocks in Kotlin’ in German. It’s a privilege to see our work featured in a print magazine, specifically the December 2022 issue, under the title ‘Simulation und Fehlerbehebung von Deadlocks in Kotlin’.

Oracle Architect uses improves App performance

Prabhakar Jonnalagadda, a performance architect at Oracle, tackled an application's frequent crashes and poor performance by analyzing its GC log with GCeasy and optimizing JVM arguments. He emphasizes that tuning options are case-specific and encourages engineers to explore and adapt solutions, as there is no universal fix for performance issues.

This Is Garbage Talk. Don’t Attend! – ADDO Conference 2022

The ADDO conference, a major online DevOps community, featured architect Ram Lakshmanan in 2022 discussing wasteful enterprise spending on garbage collection. He emphasized that millions are squandered, yet optimization can improve customer experience and save costs. His talk urges a reevaluation of current garbage collection practices to enhance efficiency.

You might be wasting millions of dollars in garbage Collection – JAX London!

JAX London is an annual conference for Java and Software Architecture enthusiasts, taking place every October. In 2022, architect Ram Lakshmanan discussed the significant financial waste enterprises incur from ineffective garbage collection, emphasizing the importance of optimization for cost savings and enhanced customer experience.

Inspect the contents of the Java Metaspace region

The post outlines the regions of JVM memory, focusing on the Metaspace, which contains class metadata. It offers five methods to inspect loaded classes: using verbose flags for versions 8 and 9+, invoking jcmd, a programmatic approach, and performing Heap Dump analysis. Each method is described for practical usage.

Java String intern(): Performance impact

The java.lang.String#intern() method can significantly reduce memory usage by eliminating duplicate strings in Java applications. A comparison of two programs—one utilizing intern() and the other not—demonstrated that the intern() method reduced memory consumption from 1.08GB to 38.37MB at the cost of increased response time.

Java String intern(): Interesting Q & A

The intern() function in Java's String class optimizes memory usage by managing a pool of string objects in the JVM. When invoked, it checks for existing strings, reusing them if present to eliminate duplicates. While beneficial for memory efficiency, using intern() can negatively impact application response time compared to other methods like string deduplication.

In which region intern strings are stored?

The intern() function in Java's String class helps eliminate duplicate string objects, reducing memory usage by storing interned strings in the JVM's heap region. This post includes practical examples, performance observations from a sample program, and highlights the significance of enabling garbage collection logging for memory management insights.

Java Hashtable, HashMap, ConcurrentHashMap – Performance impact

This post compares the performance of HashMap, Hashtable, and ConcurrentHashMap through practical examples. It recommends ConcurrentHashMap for its thread-safe implementation, despite being marginally slower than HashMap. Testing showed HashMap performed best, but was not thread-safe, while Hashtable was significantly slower due to its synchronization constraints.

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