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Understanding Data Flow

JFR collects data from the JVM (through internal APIs) and from the Java application (through the JFR APIs). This data is stored in small thread-local buffers that are flushed to a global in-memory buffer. Data in the global in-memory buffer is then written to disk. Disk write operations are expensive, so you should try to minimize them by carefully selecting the event data you enable for recording. The format of the binary recording files is very compact and efficient for applications to read and write.

There is no information overlap between the various buffers. A particular chunk of data is available either in memory or on disk, but never in both places. This has the following implications:

In some cases, the JVM drops the event order to ensure that it does not crash. Any data that cannot be written fast enough to disk is discarded. When this happens, the recording file will include information on which time period was affected. This information will also be logged to the logging facility of the JVM.

You can configure JFR to not write any data to disk. In this mode, the global buffer acts as a circular buffer and the oldest data is dropped when the buffer is full. This very low-overhead operating mode still collects all the vital data necessary for root-cause problem analysis. Because the most recent data is always available in the global buffer, it can be written to disk on demand whenever operations or surveillance systems detect a problem. However, in this mode, only the last few minutes of data is available, so it only contains the most recent events. If you need to get the full history of operation for a long period of time, use the default mode when events are written to disk regularly.