java_lang_Memory_HeapMemoryUsage_used

这是Java中内存相关的一项指标，表示堆内存的已使用量。在Java中，内存分为堆内存和非堆内存两种类型。堆内存用于存储Java对象，是Java程序运行时的主要内存使用来源。其中，该指标表示堆内存已使用的内存量，即堆内存池中已经分配出去但还未被回收的内存大小。可以通过该指标了解堆内存使用情况，以及避免堆内存溢出等问题。同时，还可以通过调整堆内存大小等参数来优化JVM的性能和稳定性。

相关问题

open falcon java_open-falcon监控java详细配置

Java应用程序的监控可以通过Open-Falcon进行配置和实现。下面是一些详细的配置步骤：

1. 下载和安装Open-Falcon Agent

在Java应用程序所在服务器上下载和安装Open-Falcon Agent。

2. 配置Open-Falcon Agent

修改Open-Falcon Agent配置文件，添加如下配置项：

{
    "plugin": {
        "enabled": true,
        "dir": "/usr/local/open-falcon/agent/plugin"
    },
    "heartbeat": {
        "enabled": true,
        "addr": "127.0.0.1:6030",
        "interval": 60,
        "timeout": 1000
    },
    "transfer": {
        "enabled": true,
        "addrs": [
            "127.0.0.1:8433"
        ],
        "interval": 60,
        "timeout": 1000
    }
}

其中，`plugin.enabled`设置为`true`表示启用插件，`plugin.dir`设置插件所在目录。

3. 下载和安装Java插件

在Open-Falcon Agent所在服务器上下载和安装Java插件。

4. 配置Java插件

修改Java插件配置文件，添加如下配置项：

{
    "debug": true,
    "metric": {
        "step": 60,
        "prefix": "java."
    },
    "plugin": {
        "jvm": {
            "enabled": true,
            "bin": "/usr/local/java/bin/java",
            "option": "-classpath ${plugin_dir}/java-plugin.jar",
            "jmx_url": "service:jmx:rmi:///jndi/rmi://127.0.0.1:1099/jmxrmi",
            "metrics": [
                {
                    "name": "jvm.mem.heap_used",
                    "type": "GAUGE",
                    "mbean": "java.lang:type=Memory",
                    "attribute": "HeapMemoryUsage.used"
                },
                {
                    "name": "jvm.mem.heap_committed",
                    "type": "GAUGE",
                    "mbean": "java.lang:type=Memory",
                    "attribute": "HeapMemoryUsage.committed"
                },
                {
                    "name": "jvm.mem.heap_max",
                    "type": "GAUGE",
                    "mbean": "java.lang:type=Memory",
                    "attribute": "HeapMemoryUsage.max"
                },
                {
                    "name": "jvm.mem.non_heap_used",
                    "type": "GAUGE",
                    "mbean": "java.lang:type=Memory",
                    "attribute": "NonHeapMemoryUsage.used"
                },
                {
                    "name": "jvm.mem.non_heap_committed",
                    "type": "GAUGE",
                    "mbean": "java.lang:type=Memory",
                    "attribute": "NonHeapMemoryUsage.committed"
                },
                {
                    "name": "jvm.threads.count",
                    "type": "GAUGE",
                    "mbean": "java.lang:type=Threading",
                    "attribute": "ThreadCount"
                },
                {
                    "name": "jvm.threads.daemon_count",
                    "type": "GAUGE",
                    "mbean": "java.lang:type=Threading",
                    "attribute": "DaemonThreadCount"
                },
                {
                    "name": "jvm.threads.peak_count",
                    "type": "GAUGE",
                    "mbean": "java.lang:type=Threading",
                    "attribute": "PeakThreadCount"
                },
                {
                    "name": "jvm.gc.young_count",
                    "type": "COUNTER",
                    "mbean": "java.lang:type=GarbageCollector,name=PS Scavenge",
                    "attribute": "CollectionCount"
                },
                {
                    "name": "jvm.gc.young_time",
                    "type": "COUNTER",
                    "mbean": "java.lang:type=GarbageCollector,name=PS Scavenge",
                    "attribute": "CollectionTime"
                },
                {
                    "name": "jvm.gc.old_count",
                    "type": "COUNTER",
                    "mbean": "java.lang:type=GarbageCollector,name=PS MarkSweep",
                    "attribute": "CollectionCount"
                },
                {
                    "name": "jvm.gc.old_time",
                    "type": "COUNTER",
                    "mbean": "java.lang:type=GarbageCollector,name=PS MarkSweep",
                    "attribute": "CollectionTime"
                }
            ]
        }
    }
}

其中，`plugin.jvm.enabled`设置为`true`表示启用Java插件，`plugin.jvm.bin`设置Java程序所在路径，`plugin.jvm.option`设置Java插件所在路径，`plugin.jvm.jmx_url`设置JMX URL，`plugin.jvm.metrics`设置监控指标。

5. 重启Open-Falcon Agent

修改完Open-Falcon Agent和Java插件的配置文件后，需要重启Open-Falcon Agent。

6. 查看监控数据

在Open-Falcon Web界面上查看Java应用程序的监控数据。

java.lang.outofmemoryerror: wr

apped or Direct buffer memory

This error occurs when the Java Virtual Machine (JVM) runs out of memory allocated for direct buffers or mapped files. Direct buffers are a type of buffer that is allocated outside of the normal Java heap, and is used for I/O operations. Mapped files are a type of file that is mapped into memory.

To solve this issue, you can try the following:

1. Increase the memory allocated to the JVM using the -Xmx option. For example, you can set the maximum heap size to 4 GB by passing the following option to the JVM: -Xmx4g.

2. Reduce the amount of memory used by your application. You can do this by optimizing your code, using more efficient data structures, or reducing the size of your data.

3. Use a different I/O mechanism that does not rely on direct buffers or mapped files.

4. Use a profiling tool to identify memory leaks or other memory usage issues in your application.

5. If none of the above solutions work, consider upgrading your hardware to increase the amount of physical memory available to the JVM.