How to Use GCViewer to Analyze JVM Memory Behavior

GCViewer: Visualize Java Garbage Collection Logs EasilyGarbage collection (GC) is a core part of Java runtime behavior. For production services and local development alike, understanding how the JVM collects and manages memory is essential for diagnosing pauses, memory leaks, and throughput problems. GCViewer is a lightweight, focused tool that helps you transform raw JVM GC logs into visualizations and metrics you can act on quickly.

What is GCViewer?

GCViewer is an open-source utility that parses Java garbage collection logs and produces interactive charts and summarized metrics. It supports multiple GC log formats (from different JVM versions and GC algorithms) and provides a compact view of events such as pause durations, heap usage over time, and allocation rates. Instead of scanning text logs for patterns, GCViewer gives you visual signals that surface problematic behavior fast.

Why visualize GC logs?

• Humans read visuals faster: Graphs make trends and anomalies obvious at a glance.
• Correlation of events: Visual timelines reveal how pause times align with heap growth or allocation bursts.
• Faster triage: Spot long pauses, frequent small pauses, or sustained GC activity without manual parsing.
• Better decision-making: Use observed patterns to tune heap size, GC flags, or to identify code paths causing excessive allocation.

Supported GC log types

GCViewer accommodates many common GC log formats, including:

• Concurrent Mark-Sweep (CMS) logs
• Garbage-First (G1) GC logs
• Parallel/Throughput collector logs
• Legacy -XX:+PrintGC and -XX:+PrintGCDetails formats
• New unified logging format (JDK 9+) with proper parsing options

Note: Some log variants (especially highly customized formats or logs with non-standard timestamps) may require minor preprocessing or specifying the correct parsing mode.

Installing and running GCViewer

1. Download GCViewer JAR or a release package from the project’s repository.
2. Start the tool with Java:

   
   java -jar GCViewer-<version>.jar 

3. Open your GC log file via the UI (File → Open) or drag-and-drop the log into the window.
4. Select the appropriate parsing mode if prompted (e.g., PrintGCDetails, G1, Unified).

GCViewer runs on any platform with a compatible JRE and has a small memory footprint.

Key visualizations and metrics

GCViewer provides several panes and charts; the most useful include:

• Heap Usage Over Time: Shows used heap versus total heap, helping spot memory growth and post-GC recovery.
• Pause Times Timeline: Plots individual GC pause durations; long spikes are immediate red flags.
• Throughput and Application Time: Shows the percentage of time the application was running vs. GC activity.
• Generation-specific Views: When available, separate charts for young and old generation behavior.
• Histogram and Scatter Charts: Distribution of pause times and correlations (e.g., pause time vs. heap size).
• Summary Metrics: Totals and averages—total GC time, number of pauses, average pause, max pause, and allocation rate.

Typical workflows

• Triage long pauses: Open the log, switch to Pause Times Timeline, click the spike to inspect surrounding heap usage and GC event details.
• Identify allocation hotspots: Look for frequent young-gen collections with high survivor/eden churn.
• Verify tuning changes: Compare two GC logs (before/after) to measure improvements in pause time or throughput.
• Root-cause memory leaks: Observe steady upward drift in used heap that never returns to baseline after full GCs.

Interpreting common patterns

• Frequent, short young-gen collections: Often normal for allocation-heavy apps; consider tuning young generation size or improving object lifetime.
• Infrequent, long full GC pauses: Could indicate insufficient heap for working set, fragmentation (older collectors), or costly finalization.
• Rising baseline used heap between GCs: Suggests a memory leak or an increase in retained live data.
• Long concurrent phases with CMS/G1: Might show concurrent marking work impacting CPU; check concurrent settings and promotion rates.

Tips for accurate analysis

• Ensure GC logging is enabled with sufficient detail (-Xlog or -XX flags depending on JVM version).
• Use timestamps (absolute or relative) in logs to align with application traces or monitoring data.
• Keep GC logs per JVM instance; aggregated logs can confuse timelines.
• When using the new unified logging format (JDK 9+), include the GC subsystem logs and timestamps.

Alternatives and integrations

GCViewer is great for quick, local analysis. For large-scale automated monitoring or multi-instance correlation, consider complementing it with:

• Prometheus + Grafana dashboards (JVM exporters)
• Commercial APMs (for correlated traces and application-level context)
• Other log analysis tools like GCeasy or HPJmeter for different feature sets

Example: quick diagnosis in 5 minutes

1. Collect GC log: start app with logging flags and run workload.
2. Load log into GCViewer.
3. Scan Pause Times Timeline for spikes.
4. Click a spike to view heap usage before/after and event details.
5. Check summary metrics (max pause, average pause, total GC time) and tweak JVM flags or code accordingly.

Conclusion

GCViewer turns verbose GC logs into actionable visuals, making it faster to detect, diagnose, and verify fixes for JVM memory and GC problems. It’s ideal for developers and ops engineers who need a quick, local way to understand garbage collection behavior without heavy setup.