1. Performance metrics and measurement
Welcome to our video on performance metrics and measurement!
2. Beyond time measurements
In the previous videos, we learned about how to measure time taken for operations such as CPU-intensive code, network calls, and other operations. We also learned about memory management in the JVM.
While time measurements are useful, they don't tell the whole story. Now, we'll explore other critical performance metrics beyond timing - specifically, memory usage and CPU utilization.
These metrics provide deeper insights into how our application uses system resources and can help us identify bottlenecks that timing alone might not reveal.
3. Memory metrics with runtime
Let's start with measuring memory usage. The Java `Runtime` class provides methods to monitor memory consumption in our application.
We can access these metrics through the `Runtime.getRuntime()` method.
The `totalMemory()` method returns the total amount of memory currently allocated to the JVM, while `freeMemory()` tells us how much of that allocated memory is unused. Finally, the `maxMemory()` method shows the maximum amount of memory the JVM will attempt to use.
All those methods return `long` numbers that represent bytes.
4. Understanding memory metrics
Let's clarify the difference between the memory metrics.
`maxMemory()` represents the upper limit of memory the JVM can use, typically set by the -Xmx JVM argument.
`totalMemory()` represents how much memory is currently allocated to the JVM from the operating system. This can grow or shrink over time but will never exceed `maxMemory()`.
`freeMemory()` is the portion of total memory that isn't currently being used. The actual memory used by our application is calculated by subtracting `freeMemory()` from `totalMemory()`.
Understanding these distinctions is important because the JVM doesn't immediately allocate all the memory it might eventually need - it dynamically adjusts the `totalMemory` value as our application runs.
5. Memory metrics in practice
Let's see how this works with a practical example. We'll first create a helper method called `getUsedMemoryMB()` that calculates the current memory usage in megabytes for more readable output. This simple pattern allows us to track how our operations affect memory consumption.
6. CPU utilization measurement
Now let's look at measuring CPU utilization. While timing measurements tell us how long an operation took, CPU utilization with `ThreadMXBean` only counts when our code is actually running on the CPU.
First, we check if CPU time measurement is supported on the current JVM. CPU may not be supported in some older JVM versions or restricted environments. If it's not supported, we should fall back to `System.nanoTime()`.
If it is, we enable CPU time measurement and then get the ID of the current thread. The `getThreadCpuTime` method returns the total CPU time consumed by the specified thread in nanoseconds.
7. Java profiling tools
While the methods we've covered are great for targeted measurements, Java offers sophisticated tools for comprehensive analysis.
JVisualVM provides a visual interface for monitoring memory, CPU, and more, whereas for command-line analysis, jmap analyzes heap memory.
These tools go beyond the simple metrics we've discussed and provide deeper insights into our application's performance characteristics. They can help identify complex issues that might not be apparent from basic measurements.
8. Let's practice!
Ready to move beyond simple timing measurements? Let's practice!