Hadoop-Yarn-NodeManager如何计算Linux系统上的资源信息

本文主要是介绍Hadoop-Yarn-NodeManager如何计算Linux系统上的资源信息，希望对大家解决编程问题提供一定的参考价值，需要的开发者们随着小编来一起学习吧！

一、上下文

<Hadoop-Yarn-NodeManager都做了什么>中讲节点资源监控服务（NodeResourceMonitorImpl）时只是提了下SysInfoLinux，下面我们展开讲下

SysInfoLinux是用于计算Linux系统上的资源信息的插件

二、SysInfoLinux源码

package org.apache.hadoop.util;import java.io.BufferedReader;
import java.io.FileInputStream;
import java.io.FileNotFoundException;
import java.io.InputStreamReader;
import java.io.IOException;
import java.math.BigInteger;
import java.nio.charset.Charset;
import java.util.HashMap;
import java.util.HashSet;
import java.util.regex.Matcher;
import java.util.regex.Pattern;
import com.google.common.annotations.VisibleForTesting;
import org.apache.hadoop.classification.InterfaceAudience;
import org.apache.hadoop.classification.InterfaceStability;
import org.apache.hadoop.util.Shell.ShellCommandExecutor;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;/*** 用于计算Linux系统上的资源信息的插件*/
@InterfaceAudience.Private
@InterfaceStability.Evolving
public class SysInfoLinux extends SysInfo {private static final Logger LOG =LoggerFactory.getLogger(SysInfoLinux.class);/*** proc的meminfo虚拟文件具有以下格式的键值* "key:[ \t]*value[ \t]kB".*/private static final String PROCFS_MEMFILE = "/proc/meminfo";private static final Pattern PROCFS_MEMFILE_FORMAT =Pattern.compile("^([a-zA-Z_()]*):[ \t]*([0-9]*)[ \t]*(kB)?");//我们需要meminfo中以下键的值private static final String MEMTOTAL_STRING = "MemTotal";private static final String SWAPTOTAL_STRING = "SwapTotal";private static final String MEMFREE_STRING = "MemFree";private static final String SWAPFREE_STRING = "SwapFree";private static final String INACTIVE_STRING = "Inactive";private static final String INACTIVEFILE_STRING = "Inactive(file)";private static final String HARDWARECORRUPTED_STRING = "HardwareCorrupted";private static final String HUGEPAGESTOTAL_STRING = "HugePages_Total";private static final String HUGEPAGESIZE_STRING = "Hugepagesize";/*** 解析/proc/cpuinfo的样板*/private static final String PROCFS_CPUINFO = "/proc/cpuinfo";private static final Pattern PROCESSOR_FORMAT =Pattern.compile("^processor[ \t]:[ \t]*([0-9]*)");private static final Pattern FREQUENCY_FORMAT =Pattern.compile("^cpu MHz[ \t]*:[ \t]*([0-9.]*)");private static final Pattern PHYSICAL_ID_FORMAT =Pattern.compile("^physical id[ \t]*:[ \t]*([0-9]*)");private static final Pattern CORE_ID_FORMAT =Pattern.compile("^core id[ \t]*:[ \t]*([0-9]*)");/*** 解析/proc/stat的样板*/private static final String PROCFS_STAT = "/proc/stat";private static final Pattern CPU_TIME_FORMAT =Pattern.compile("^cpu[ \t]*([0-9]*)" +"[ \t]*([0-9]*)[ \t]*([0-9]*)[ \t].*");private CpuTimeTracker cpuTimeTracker;/*** 解析/proc/net/dev的样板*/private static final String PROCFS_NETFILE = "/proc/net/dev";private static final Pattern PROCFS_NETFILE_FORMAT =Pattern .compile("^[ \t]*([a-zA-Z]+[0-9]*):" +"[ \t]*([0-9]+)[ \t]*([0-9]+)[ \t]*([0-9]+)[ \t]*([0-9]+)" +"[ \t]*([0-9]+)[ \t]*([0-9]+)[ \t]*([0-9]+)[ \t]*([0-9]+)" +"[ \t]*([0-9]+)[ \t]*([0-9]+)[ \t]*([0-9]+)[ \t]*([0-9]+)" +"[ \t]*([0-9]+)[ \t]*([0-9]+)[ \t]*([0-9]+)[ \t]*([0-9]+).*");/*** 解析/proc/diskstats的样板*/private static final String PROCFS_DISKSFILE = "/proc/diskstats";private static final Pattern PROCFS_DISKSFILE_FORMAT =Pattern.compile("^[ \t]*([0-9]+)[ \t]*([0-9 ]+)" +"(?!([a-zA-Z]+[0-9]+))([a-zA-Z]+)" +"[ \t]*([0-9]+)[ \t]*([0-9]+)[ \t]*([0-9]+)[ \t]*([0-9]+)" +"[ \t]*([0-9]+)[ \t]*([0-9]+)[ \t]*([0-9]+)[ \t]*([0-9]+)" +"[ \t]*([0-9]+)[ \t]*([0-9]+)[ \t]*([0-9]+)");/*** 解析/sys/block/partition_name/queue/hw_sector_size的样板*/private static final Pattern PROCFS_DISKSECTORFILE_FORMAT =Pattern.compile("^([0-9]+)");private String procfsMemFile;private String procfsCpuFile;private String procfsStatFile;private String procfsNetFile;private String procfsDisksFile;private long jiffyLengthInMillis;private long ramSize = 0;private long swapSize = 0;private long ramSizeFree = 0;  // 机器上的可用 ram 磁盘空间 (kB)private long swapSizeFree = 0; // 机器上的可用 swap 空间 (kB)private long inactiveSize = 0; // 不活跃内存 (kB)private long inactiveFileSize = -1; // 非活动缓存，-1（如果不存在）private long hardwareCorruptSize = 0; // RAM已损坏且不可用大小private long hugePagesTotal = 0; // # 保留的标准大页private long hugePageSize = 0; // # 每个标准大页的大小/* 系统上的逻辑处理器数量. */private int numProcessors = 0;/* 系统上的物理核心数. */private int numCores = 0;private long cpuFrequency = 0L; // 系统上的CPU频率 (kHz)private long numNetBytesRead = 0L; // 从网络读取的聚合字节private long numNetBytesWritten = 0L; // 写入网络的聚合字节数private long numDisksBytesRead = 0L; // 从磁盘读取的聚合字节数private long numDisksBytesWritten = 0L; // 写入磁盘的聚合字节数private boolean readMemInfoFile = false;private boolean readCpuInfoFile = false;/* 为每个磁盘映射其扇区大小 */private HashMap<String, Integer> perDiskSectorSize = null;public static final long PAGE_SIZE = getConf("PAGESIZE");public static final long JIFFY_LENGTH_IN_MILLIS =Math.max(Math.round(1000D / getConf("CLK_TCK")), -1);private static long getConf(String attr) {if(Shell.LINUX) {try {ShellCommandExecutor shellExecutorClk = new ShellCommandExecutor(new String[] {"getconf", attr });shellExecutorClk.execute();return Long.parseLong(shellExecutorClk.getOutput().replace("\n", ""));} catch (IOException|NumberFormatException e) {return -1;}}return -1;}/*** 获取当前时间* @return Unix时间戳（毫秒）*/long getCurrentTime() {return System.currentTimeMillis();}public SysInfoLinux() {this(PROCFS_MEMFILE, PROCFS_CPUINFO, PROCFS_STAT,PROCFS_NETFILE, PROCFS_DISKSFILE, JIFFY_LENGTH_IN_MILLIS);}/*** 构造函数，它允许分配/proc/目录。这将仅用于单元测试* @param procfsMemFile fake file for /proc/meminfo* @param procfsCpuFile fake file for /proc/cpuinfo* @param procfsStatFile fake file for /proc/stat* @param procfsNetFile fake file for /proc/net/dev* @param procfsDisksFile fake file for /proc/diskstats* @param jiffyLengthInMillis fake jiffy length value*/@VisibleForTestingpublic SysInfoLinux(String procfsMemFile,String procfsCpuFile,String procfsStatFile,String procfsNetFile,String procfsDisksFile,long jiffyLengthInMillis) {this.procfsMemFile = procfsMemFile;this.procfsCpuFile = procfsCpuFile;this.procfsStatFile = procfsStatFile;this.procfsNetFile = procfsNetFile;this.procfsDisksFile = procfsDisksFile;this.jiffyLengthInMillis = jiffyLengthInMillis;this.cpuTimeTracker = new CpuTimeTracker(jiffyLengthInMillis);this.perDiskSectorSize = new HashMap<String, Integer>();}/*** 读 /proc/meminfo, 只解析和计算一次内存信息.*/private void readProcMemInfoFile() {readProcMemInfoFile(false);}/**** Long.parseLong（）的包装器，如果值无效则返回零。在某些情况下，* /proc/meminfo中的swapFree可能为负数，报告为非常大的十进制值。*/private long safeParseLong(String strVal) {long parsedVal;try {parsedVal = Long.parseLong(strVal);} catch (NumberFormatException nfe) {parsedVal = 0;}return parsedVal;}/*** 读 /proc/meminfo, 解析和计算内存信息.* @param readAgain if false, read only on the first time*/private void readProcMemInfoFile(boolean readAgain) {if (readMemInfoFile && !readAgain) {return;}// Read "/proc/memInfo" fileBufferedReader in;InputStreamReader fReader;try {fReader = new InputStreamReader(new FileInputStream(procfsMemFile), Charset.forName("UTF-8"));in = new BufferedReader(fReader);} catch (FileNotFoundException f) {// shouldn't happen....LOG.warn("Couldn't read " + procfsMemFile+ "; can't determine memory settings");return;}Matcher mat;try {String str = in.readLine();while (str != null) {mat = PROCFS_MEMFILE_FORMAT.matcher(str);if (mat.find()) {if (mat.group(1).equals(MEMTOTAL_STRING)) {ramSize = Long.parseLong(mat.group(2));} else if (mat.group(1).equals(SWAPTOTAL_STRING)) {swapSize = Long.parseLong(mat.group(2));} else if (mat.group(1).equals(MEMFREE_STRING)) {ramSizeFree = safeParseLong(mat.group(2));} else if (mat.group(1).equals(SWAPFREE_STRING)) {swapSizeFree = safeParseLong(mat.group(2));} else if (mat.group(1).equals(INACTIVE_STRING)) {inactiveSize = Long.parseLong(mat.group(2));} else if (mat.group(1).equals(INACTIVEFILE_STRING)) {inactiveFileSize = Long.parseLong(mat.group(2));} else if (mat.group(1).equals(HARDWARECORRUPTED_STRING)) {hardwareCorruptSize = Long.parseLong(mat.group(2));} else if (mat.group(1).equals(HUGEPAGESTOTAL_STRING)) {hugePagesTotal = Long.parseLong(mat.group(2));} else if (mat.group(1).equals(HUGEPAGESIZE_STRING)) {hugePageSize = Long.parseLong(mat.group(2));}}str = in.readLine();}} catch (IOException io) {LOG.warn("Error reading the stream " + io);} finally {//关闭流try {fReader.close();try {in.close();} catch (IOException i) {LOG.warn("Error closing the stream " + in);}} catch (IOException i) {LOG.warn("Error closing the stream " + fReader);}}readMemInfoFile = true;}/*** 读 /proc/cpuinfo, 解析和计算CPU信息.*/private void readProcCpuInfoFile() {// 此目录只需读取一次if (readCpuInfoFile) {return;}HashSet<String> coreIdSet = new HashSet<>();// Read "/proc/cpuinfo" fileBufferedReader in;InputStreamReader fReader;try {fReader = new InputStreamReader(new FileInputStream(procfsCpuFile), Charset.forName("UTF-8"));in = new BufferedReader(fReader);} catch (FileNotFoundException f) {// shouldn't happen....LOG.warn("Couldn't read " + procfsCpuFile + "; can't determine cpu info");return;}Matcher mat;try {numProcessors = 0;numCores = 1;String currentPhysicalId = "";String str = in.readLine();while (str != null) {mat = PROCESSOR_FORMAT.matcher(str);if (mat.find()) {numProcessors++;}mat = FREQUENCY_FORMAT.matcher(str);if (mat.find()) {cpuFrequency = (long)(Double.parseDouble(mat.group(1)) * 1000); // kHz}mat = PHYSICAL_ID_FORMAT.matcher(str);if (mat.find()) {currentPhysicalId = str;}mat = CORE_ID_FORMAT.matcher(str);if (mat.find()) {coreIdSet.add(currentPhysicalId + " " + str);numCores = coreIdSet.size();}str = in.readLine();}} catch (IOException io) {LOG.warn("Error reading the stream " + io);} finally {// Close the streamstry {fReader.close();try {in.close();} catch (IOException i) {LOG.warn("Error closing the stream " + in);}} catch (IOException i) {LOG.warn("Error closing the stream " + fReader);}}readCpuInfoFile = true;}/*** 读/proc/stat file, parse and calculate cumulative CPU.*/private void readProcStatFile() {// Read "/proc/stat" fileBufferedReader in;InputStreamReader fReader;try {fReader = new InputStreamReader(new FileInputStream(procfsStatFile), Charset.forName("UTF-8"));in = new BufferedReader(fReader);} catch (FileNotFoundException f) {// shouldn't happen....return;}Matcher mat;try {String str = in.readLine();while (str != null) {mat = CPU_TIME_FORMAT.matcher(str);if (mat.find()) {long uTime = Long.parseLong(mat.group(1));long nTime = Long.parseLong(mat.group(2));long sTime = Long.parseLong(mat.group(3));cpuTimeTracker.updateElapsedJiffies(BigInteger.valueOf(uTime + nTime + sTime),getCurrentTime());break;}str = in.readLine();}} catch (IOException io) {LOG.warn("Error reading the stream " + io);} finally {// Close the streamstry {fReader.close();try {in.close();} catch (IOException i) {LOG.warn("Error closing the stream " + in);}} catch (IOException i) {LOG.warn("Error closing the stream " + fReader);}}}/*** Read /proc/net/dev file, 解析并计算通过网络读取和写入的字节数。*/private void readProcNetInfoFile() {numNetBytesRead = 0L;numNetBytesWritten = 0L;// Read "/proc/net/dev" fileBufferedReader in;InputStreamReader fReader;try {fReader = new InputStreamReader(new FileInputStream(procfsNetFile), Charset.forName("UTF-8"));in = new BufferedReader(fReader);} catch (FileNotFoundException f) {return;}Matcher mat;try {String str = in.readLine();while (str != null) {mat = PROCFS_NETFILE_FORMAT.matcher(str);if (mat.find()) {assert mat.groupCount() >= 16;// 忽略环回接口if (mat.group(1).equals("lo")) {str = in.readLine();continue;}numNetBytesRead += Long.parseLong(mat.group(2));numNetBytesWritten += Long.parseLong(mat.group(10));}str = in.readLine();}} catch (IOException io) {LOG.warn("Error reading the stream " + io);} finally {// Close the streamstry {fReader.close();try {in.close();} catch (IOException i) {LOG.warn("Error closing the stream " + in);}} catch (IOException i) {LOG.warn("Error closing the stream " + fReader);}}}/*** Read /proc/diskstats file, 解析和计算从磁盘读取和写入磁盘的字节数。*/private void readProcDisksInfoFile() {numDisksBytesRead = 0L;numDisksBytesWritten = 0L;// Read "/proc/diskstats" fileBufferedReader in;try {in = new BufferedReader(new InputStreamReader(new FileInputStream(procfsDisksFile), Charset.forName("UTF-8")));} catch (FileNotFoundException f) {return;}Matcher mat;try {String str = in.readLine();while (str != null) {mat = PROCFS_DISKSFILE_FORMAT.matcher(str);if (mat.find()) {String diskName = mat.group(4);assert diskName != null;// 忽略循环或ram分区if (diskName.contains("loop") || diskName.contains("ram")) {str = in.readLine();continue;}Integer sectorSize;synchronized (perDiskSectorSize) {sectorSize = perDiskSectorSize.get(diskName);if (null == sectorSize) {// 检索扇区大小// 如果不可用或错误，假设512sectorSize = readDiskBlockInformation(diskName, 512);perDiskSectorSize.put(diskName, sectorSize);}}String sectorsRead = mat.group(7);String sectorsWritten = mat.group(11);if (null == sectorsRead || null == sectorsWritten) {return;}numDisksBytesRead += Long.parseLong(sectorsRead) * sectorSize;numDisksBytesWritten += Long.parseLong(sectorsWritten) * sectorSize;}str = in.readLine();}} catch (IOException e) {LOG.warn("Error reading the stream " + procfsDisksFile, e);} finally {// Close the streamstry {in.close();} catch (IOException e) {LOG.warn("Error closing the stream " + procfsDisksFile, e);}}}/*** Read /sys/block/diskName/queue/hw_sector_size file, 解析并计算特定磁盘的扇区大小* @return sector size of specified disk, or defSector*/int readDiskBlockInformation(String diskName, int defSector) {assert perDiskSectorSize != null && diskName != null;String procfsDiskSectorFile ="/sys/block/" + diskName + "/queue/hw_sector_size";BufferedReader in;try {in = new BufferedReader(new InputStreamReader(new FileInputStream(procfsDiskSectorFile),Charset.forName("UTF-8")));} catch (FileNotFoundException f) {return defSector;}Matcher mat;try {String str = in.readLine();while (str != null) {mat = PROCFS_DISKSECTORFILE_FORMAT.matcher(str);if (mat.find()) {String secSize = mat.group(1);if (secSize != null) {return Integer.parseInt(secSize);}}str = in.readLine();}return defSector;} catch (IOException|NumberFormatException e) {LOG.warn("Error reading the stream " + procfsDiskSectorFile, e);return defSector;} finally {// Close the streamstry {in.close();} catch (IOException e) {LOG.warn("Error closing the stream " + procfsDiskSectorFile, e);}}}/** {@inheritDoc} */@Overridepublic long getPhysicalMemorySize() {readProcMemInfoFile();return (ramSize- hardwareCorruptSize- (hugePagesTotal * hugePageSize)) * 1024;}/** {@inheritDoc} */@Overridepublic long getVirtualMemorySize() {return getPhysicalMemorySize() + (swapSize * 1024);}/** {@inheritDoc} */@Overridepublic long getAvailablePhysicalMemorySize() {readProcMemInfoFile(true);long inactive = inactiveFileSize != -1? inactiveFileSize: inactiveSize;return (ramSizeFree + inactive) * 1024;}/** {@inheritDoc} */@Overridepublic long getAvailableVirtualMemorySize() {return getAvailablePhysicalMemorySize() + (swapSizeFree * 1024);}/** {@inheritDoc} */@Overridepublic int getNumProcessors() {readProcCpuInfoFile();return numProcessors;}/** {@inheritDoc} */@Overridepublic int getNumCores() {readProcCpuInfoFile();return numCores;}/** {@inheritDoc} */@Overridepublic long getCpuFrequency() {readProcCpuInfoFile();return cpuFrequency;}/** {@inheritDoc} */@Overridepublic long getCumulativeCpuTime() {readProcStatFile();return cpuTimeTracker.getCumulativeCpuTime();}/** {@inheritDoc} */@Overridepublic float getCpuUsagePercentage() {readProcStatFile();float overallCpuUsage = cpuTimeTracker.getCpuTrackerUsagePercent();if (overallCpuUsage != CpuTimeTracker.UNAVAILABLE) {overallCpuUsage = overallCpuUsage / getNumProcessors();}return overallCpuUsage;}/** {@inheritDoc} */@Overridepublic float getNumVCoresUsed() {readProcStatFile();float overallVCoresUsage = cpuTimeTracker.getCpuTrackerUsagePercent();if (overallVCoresUsage != CpuTimeTracker.UNAVAILABLE) {overallVCoresUsage = overallVCoresUsage / 100F;}return overallVCoresUsage;}/** {@inheritDoc} */@Overridepublic long getNetworkBytesRead() {readProcNetInfoFile();return numNetBytesRead;}/** {@inheritDoc} */@Overridepublic long getNetworkBytesWritten() {readProcNetInfoFile();return numNetBytesWritten;}@Overridepublic long getStorageBytesRead() {readProcDisksInfoFile();return numDisksBytesRead;}@Overridepublic long getStorageBytesWritten() {readProcDisksInfoFile();return numDisksBytesWritten;}/*** 测试 {@link SysInfoLinux}.** @param args - arguments to this calculator test*/public static void main(String[] args) {SysInfoLinux plugin = new SysInfoLinux();System.out.println("Physical memory Size (bytes) : "+ plugin.getPhysicalMemorySize());System.out.println("Total Virtual memory Size (bytes) : "+ plugin.getVirtualMemorySize());System.out.println("Available Physical memory Size (bytes) : "+ plugin.getAvailablePhysicalMemorySize());System.out.println("Total Available Virtual memory Size (bytes) : "+ plugin.getAvailableVirtualMemorySize());System.out.println("Number of Processors : " + plugin.getNumProcessors());System.out.println("CPU frequency (kHz) : " + plugin.getCpuFrequency());System.out.println("Cumulative CPU time (ms) : " +plugin.getCumulativeCpuTime());System.out.println("Total network read (bytes) : "+ plugin.getNetworkBytesRead());System.out.println("Total network written (bytes) : "+ plugin.getNetworkBytesWritten());System.out.println("Total storage read (bytes) : "+ plugin.getStorageBytesRead());System.out.println("Total storage written (bytes) : "+ plugin.getStorageBytesWritten());try {// 睡眠，以便计算CPU使用量Thread.sleep(500L);} catch (InterruptedException e) {// do nothing}System.out.println("CPU usage % : " + plugin.getCpuUsagePercentage());}@VisibleForTestingvoid setReadCpuInfoFile(boolean readCpuInfoFileValue) {this.readCpuInfoFile = readCpuInfoFileValue;}public long getJiffyLengthInMillis() {return this.jiffyLengthInMillis;}
}

从源码中可以看到，linux上的资源信息是从各个文件中获取的：

/proc/meminfo   解析和计算内存信息
/proc/cpuinfo   解析和计算CPU信息
/proc/stat       获取CPU的运行数据
/proc/net/dev   解析并计算通过网络读取和写入的字节数。
/proc/diskstats   解析和计算从磁盘读取和写入磁盘的字节数
/sys/block/partition_name/queue/hw_sector_size 解析并计算特定磁盘的扇区大小

下面我们看下linux操作系统中的这些文件中都是什么内容

三、proc下各示例文件

1、/proc/meminfo

MemTotal: 131479404 kB
MemFree: 29109144 kB
MemAvailable: 109564132 kB
Buffers: 3922940 kB
Cached: 65545372 kB
SwapCached: 0 kB
Active: 9252304 kB
Inactive: 79107168 kB
Active(anon): 120256 kB
Inactive(anon): 18893260 kB
Active(file): 9132048 kB
Inactive(file): 60213908 kB
Unevictable: 0 kB
Mlocked: 0 kB
SwapTotal: 0 kB
SwapFree: 0 kB
Dirty: 123956 kB
Writeback: 0 kB
AnonPages: 18856940 kB
Mapped: 151268 kB
Shmem: 122260 kB
KReclaimable: 12166144 kB
Slab: 13454424 kB
SReclaimable: 12166144 kB
SUnreclaim: 1288280 kB
KernelStack: 29584 kB
PageTables: 88028 kB
NFS_Unstable: 0 kB
Bounce: 0 kB
WritebackTmp: 0 kB
CommitLimit: 65739700 kB
Committed_AS: 34508552 kB
VmallocTotal: 34359738367 kB
VmallocUsed: 168540 kB
VmallocChunk: 0 kB
Percpu: 210432 kB
HardwareCorrupted: 0 kB
AnonHugePages: 12728320 kB
ShmemHugePages: 0 kB
ShmemPmdMapped: 0 kB
FileHugePages: 0 kB
FilePmdMapped: 0 kB
DupText: 0 kB
HugePages_Total: 0
HugePages_Free: 0
HugePages_Rsvd: 0
HugePages_Surp: 0
Hugepagesize: 2048 kB
Hugetlb: 0 kB
DirectMap4k: 2277228 kB
DirectMap2M: 119357440 kB
DirectMap1G: 14680064 kB

/proc/meminfo是了解Linux系统内存使用状况的主要接口，我们最常用的”free”、”vmstat”等命令就是通过它获取数据的

MemTotal：系统从加电开始到引导完成，firmware/BIOS要保留一些内存，kernel本身要占用一些内存，最后剩下可供kernel支配的内存就是MemTotal。这个值在系统运行期间一般是固定不变的

MemFree：表示系统尚未使用的内存。[MemTotal-MemFree]就是已被用掉的内存

MemAvailable：有些应用程序会根据系统的可用内存大小自动调整内存申请的多少，所以需要一个记录当前可用内存数量的统计值，MemFree并不适用，因为MemFree不能代表全部可用的内存，系统中有些内存虽然已被使用但是可以回收的，比如cache/buffer、slab都有一部分可以回收，所以这部分可回收的内存加上MemFree才是系统可用的内存，即MemAvailable。/proc/meminfo中的MemAvailable是内核使用特定的算法估算出来的，要注意这是一个估计值，并不精确

Buffers：用于缓存数据的内存量

Cached：用于缓存文件系统数据的内存量

SwapCached：用于缓存交换分区数据的内存量

Active：活跃内存量，活跃指最近被访问过或正在使用中的内存

Inactive：非活跃内存量，非活跃指长时间没有被访问或已经释放但仍在缓冲区中的内存

Active(anon)：活跃的匿名内存

Inactive(anon)：不活跃的匿名内存

Active(file)：活跃的文件使用内存

Inactive(file)：不活跃的文件使用内存

Unevictable：不能被释放的内存页

Mlocked：系统调用 mlock 家族允许程序在物理内存上锁住它的部分或全部地址空间。这将阻止Linux 将这个内存页调度到交换空间（swap space），即使该程序已有一段时间没有访问这段空间

SwapTotal：交换分区总容量

SwapFree：交换分区剩余容量

Dirty：脏页面数量，脏页面是指已经被修改但还没有被写回磁盘的页面

Writeback：等待写回磁盘的页面数量

AnonPages：未映射页的内存大小

Mapped：设备和文件等映射的大小

Shmem：包含共享内存以及tmpfs文件系统占用的内存

KReclaimable：在SReclaimable的基础上加上MISC_RECLAIMABLE

Slab：Slab是Linux中用来管理小块内核对象分配和释放的一种内存管理机制，Slab = SReclaimable + SUnreclaim

SReclaimable：slab中可回收的部分

SUnreclaim：slab中不可回收的部分

KernelStack：内核消耗的内存

PageTables：管理内存分页的索引表的大小

NFS_Unstable：不稳定页表的大小

Bounce：在低端内存中分配一个临时buffer作为跳转，把位于高端内存的缓存数据复制到此处消耗的内存

WritebackTmp：FUSE用于临时写回缓冲区的内存

CommitLimit：系统实际可分配内存

Committed_AS：系统当前已分配的内存

VmallocTotal：预留的虚拟内存总量

VmallocUsed：已经被使用的虚拟内存

VmallocChunk：可分配的最大的逻辑连续的虚拟内存

Percpu：表示用于percpu分配的的内存大小，不包括metadata

HardwareCorrupted：当系统检测到内存的硬件故障时删除掉的内存页的总量

AnonHugePages：匿名大页缓存

ShmemHugePages：表示用于shared memory或tmpfs的透明大页

ShmemPmdMapped：表示用于用户态shared memory映射的透明大页

FileHugePages：

FilePmdMapped：

DupText：

HugePages_Total：预留的大页内存总量

HugePages_Free：空闲的大页内存

HugePages_Rsvd：已经被应用程序分配但尚未使用的大页内存

HugePages_Surp：初始大页数与修改配置后大页数的差值

Hugepagesize：单个大页内存的大小

Hugetlb：

DirectMap4k：映射TLB为4kB的内存数量

DirectMap2M：映射TLB为2M的内存数量

DirectMap1G：映射TLB为1G的内存数量

2、/proc/cpuinfo

processor : 0
vendor_id : GenuineIntel
cpu family : 6
model : 85
model name : Intel Xeon Processor (Skylake, IBRS)
stepping : 4
microcode : 0x1
cpu MHz : 2299.992
cache size : 16384 KB
physical id : 0
siblings : 12
core id : 0
cpu cores : 12
apicid : 0
initial apicid : 0
fpu : yes
fpu_exception : yes
cpuid level : 13
wp : yes
flags : fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ss ht syscall nx pdpe1gb rdtscp lm constant_tsc rep_good nopl xtopology c
puid tsc_known_freq pni pclmulqdq ssse3 fma cx16 pcid sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand hypervisor lahf_lm abm 3dnowprefetch cpuid_fault invpcid
_single ssbd ibrs ibpb stibp fsgsbase tsc_adjust bmi1 hle avx2 smep bmi2 erms invpcid rtm mpx avx512f avx512dq rdseed adx smap clflushopt clwb avx512cd avx512bw avx512vl xsaveopt xsavec xge
tbv1 xsaves arat umip pku ospke md_clear
bugs : cpu_meltdown spectre_v1 spectre_v2 spec_store_bypass l1tf mds swapgs taa itlb_multihit mmio_stale_data retbleed
bogomips : 4599.98
clflush size : 64
cache_alignment : 64
address sizes : 46 bits physical, 48 bits virtual
power management:

.................................省略...............................

processor : 23
vendor_id : GenuineIntel
cpu family : 6
model : 85
model name : Intel Xeon Processor (Skylake, IBRS)
stepping : 4
microcode : 0x1
cpu MHz : 2299.992
cache size : 16384 KB
physical id : 1
siblings : 12
core id : 11
cpu cores : 12
apicid : 27
initial apicid : 27
fpu : yes
fpu_exception : yes
cpuid level : 13
wp : yes
flags : fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ss ht syscall nx pdpe1gb rdtscp lm constant_tsc rep_good nopl xtopology cpuid tsc_known_freq pni pclmulqdq ssse3 fma cx16 pcid sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand hypervisor lahf_lm abm 3dnowprefetch cpuid_fault invpcid_single ssbd ibrs ibpb stibp fsgsbase tsc_adjust bmi1 hle avx2 smep bmi2 erms invpcid rtm mpx avx512f avx512dq rdseed adx smap clflushopt clwb avx512cd avx512bw avx512vl xsaveopt xsavec xgetbv1 xsaves arat umip pku ospke md_clear
bugs : cpu_meltdown spectre_v1 spectre_v2 spec_store_bypass l1tf mds swapgs taa itlb_multihit mmio_stale_data retbleed
bogomips : 4599.98
clflush size : 64
cache_alignment : 64
address sizes : 46 bits physical, 48 bits virtual
power management:

通过/proc/cpuinfo，可以查看系统中CPU的提供商和相关配置信息，例如我们想获取，有多少颗物理CPU，每个物理cpu核心数，以及超线程是否开启等信息，下面是每项参数的解释：

processor ：系统中逻辑处理核心数的编号，从0开始排序

vendor_id ：CPU制造商

cpu family ：CPU产品系列代号

model ：CPU属于其系列中的哪一代的代号

model name：CPU属于的名字及其编号、标称主频

stepping ：CPU属于制作更新版本

cpu MHz ：CPU的实际使用主频

cache size ：CPU二级缓存大小

physical id ：单个物理CPU的标号

siblings ：单个物理CPU的逻辑CPU数。siblings=cpu cores [*2]

core id ：当前物理核在其所处CPU中的编号，这个编号不一定连续

cpu cores ：该逻辑核所处CPU的物理核数。比如此处cpu cores 是4个，那么对应core id 可能是 1、3、4、5。

apicid ：用来区分不同逻辑核的编号，系统中每个逻辑核的此编号必然不同，此编号不一定连续

fpu ：是否具有浮点运算单元（Floating Point Unit）

fpu_exception ：是否支持浮点计算异常

cpuid level ：执行cpuid指令前，eax寄存器中的值，根据不同的值cpuid指令会返回不同的内容

wp ：表明当前CPU是否在内核态支持对用户空间的写保护（Write Protection）

flags ：当前CPU支持的功能

bugs ：保存内核检测到的硬件错误

bogomips：在系统内核启动时粗略测算的CPU速度（Million Instructions Per Second

clflush size ：每次刷新缓存的大小单位

cache_alignment ：缓存地址对齐单位

address sizes ：可访问地址空间位数

power management ：对能源管理的支持

3、/proc/stat

cpu 8736131408 5678 193273561 20516569092 64420147 202089758 24839900 736849109 0 0
cpu0 248135539 221 7727953 977102347 3547852 7843342 1836321 26959080 0 0
cpu1 288960610 208 7253118 939752913 3465875 6253758 983012 22610655 0 0
cpu2 331782665 173 6580943 898614791 3179773 5927649 705463 20377701 0 0
cpu3 357312958 119 6079401 873515056 3082820 5636253 675032 19192651 0 0
cpu4 416415379 134 4970987 817517624 2702326 5029001 461878 15707695 0 0
cpu5 431656991 49 4560783 803250964 2571613 4865074 410522 14757252 0 0
cpu6 435254195 169 4473639 799793313 2533305 4816086 391800 14568012 0 0
cpu7 430149966 193 5306474 799970897 2274711 5119291 4203530 15644401 0 0
cpu8 442943177 38 4245770 792483084 2429873 4720225 472371 14247201 0 0
cpu9 450045462 66 4306296 784947171 2410185 4660788 1014418 13736325 0 0
cpu10 451355787 39 4064980 784676208 2261500 4619102 396365 13709422 0 0
cpu11 457452811 64 3901559 778822656 2231050 4565301 393815 13362096 0 0
cpu12 308242715 360 10256742 887773491 2996516 16295533 1139546 52646450 0 0
cpu13 291977604 326 12356349 906520116 2948164 14127718 995623 49241553 0 0
cpu14 314799511 763 11789179 887439430 2724265 12548004 926359 45887607 0 0
cpu15 343893959 589 10565703 861975365 2476760 11234089 879714 42636791 0 0
cpu16 357686825 202 9889055 850148237 2299417 10596337 839523 40920853 0 0
cpu17 371250803 336 9230196 838222800 2170862 10053101 814107 39442271 0 0
cpu18 381559924 227 8684083 829076848 2133621 9640147 793837 38300080 0 0
cpu19 391204359 360 8217143 820527206 2044874 9294489 780223 37347635 0 0
cpu20 395787749 376 7934865 816504952 2030798 9101060 793620 36768582 0 0
cpu21 382765684 287 8586382 826536768 2751789 9517617 1313220 39011440 0 0
cpu22 403637541 284 7699240 808560612 3025058 8623423 868515 35789081 0 0
cpu23 51859181 83 24592711 1132836231 4127127 17002359 2751076 73984264 0 0
intr 41293626138 0 9 0 0 250 0 0 0 0 0 1257757 0 15 0 12281947 0 0 0 0 0 0 0 0 0 0 74418226 0 9915152 0 62205235 0 16892400 0 170973248 4915 0 3076909346 41960 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
ctxt 66125412027
btime 1695643289
processes 68123558
procs_running 20
procs_blocked 0
softirq 26896249797 0 1534546890 2296517 681491783 147607814 0 4570937 2751393260 9053148 290452968

/proc/stat记录的是系统进程整体的统计信息

cpu ~ cpu23 描述的指标如下：(单位都是jiffies，1jiffies=0.01秒)

name	user	nice	system	idle	iowait	irrq	softirq	steal	guest	guest_nice
cpu	8736131408	5678	193273561	20516569092	64420147	202089758	24839900	736849109	0	0
……	……	……	……	……	……	……	……	……	……	……
cpu23	51859181	83	24592711	1132836231	4127127	17002359	2751076	73984264	0	0

这部分统计了CPU时间消耗分布在哪些地方,是用户态任务,还是内核或者是中断、idle等等；第一行的第一个字段为"cpu"，没有指定CPU号，表示是其他各个CPU时间分布的汇总；而其他行有cpu编号表示特定编号的cpu时间消耗分布情况。

name：cpu汇总/cpu编号

user：到目前为止，CPU上nice值不大于0的用户态任务的运行时间

nice：到目前为止，CPU上nice值大于0的用户态任务的运行时间

system：到目前为止，CPU上内核态的运行时间。包括用户态任务系统调用、异常等陷入内核消耗时间，也包括内核线程消耗的时间；但是不包括中断和软中断的执行时间

idle：到目前为止，处于idle任务的时间。不包括CPU上因为任务IO阻塞导致CPU上没有任务可运行、处于idle状态的时间。

iowait：到目前为止，由于CPU上任务IO阻塞导致CPU无可运行任务、处于idle的时间。需要强调的是，iowait是在CPU处于idle状态下的一种特殊情况的时间，与上面的“idle”列互补构成CPU上真正处于idle的时间。

irrq：到目前为止，CPU进入到中断处理的时间(在没有使能CONFIG_IRQ_TIME_ACCOUNTING的情况下，大部分架构实际上无法记录到该项，见下面的分析)。

softirq：到目前为止，CPU处理软中断的时间，包括softirqd中处理软中断的时间。

steal：与虚拟化有关

guest：与虚拟化有关

guest_nice：与虚拟化有关

其他指标如下：

intr：系统启动以来的所有interrupts的次数情况

ctxt: 系统上下文切换次数

btime：启动时长(单位:秒)，从Epoch(即1970零时)开始到系统启动所经过的时长，每次启动会改变。此处指为1695643289，转换北京时间为2023-09-25 20:01:29

processes：系统启动后所创建过的进程数量。当短时间该值特别大，系统可能出现异常

procs_running：处于Runnable状态的进程个数

procs_blocked：处于被阻塞的进程个数

softirq：此行显示所有CPU的softirq总数，第一列是所有软件和每个软件的总数，后面的列是特定softirq的总数

4、/proc/net/dev

Inter-| Receive | Transmit
face |bytes packets errs drop fifo frame compressed multicast|bytes packets errs drop fifo colls carrier compressed
lo: 8262570189990 1009625458 0 1217 0 0 0 0 8262570189990 1009625458 0 0 0 0 0 0
eth0: 4725352845467 3727035213 0 0 0 0 0 0 12125473603784 322028286 0 0 0 0 0 0
eth1: 12250497813726 9789277543 0 1066 0 0 0 0 12066904463831 2712923220 0 0 0 0 0 0

/proc/net/dev提供了网络设备接口的统计信息，lo、eth0、eth1为网络社保接口的名称。下面是具体指标解释

bytes：接收或发送的总字节数。

packets：接收或发送的总数据包数量。

errs：在接收或发送过程中发生的错误数量。

drop：由于缓冲区溢出或其他原因而丢弃的数据包数量。

fifo：由于队列拥塞而丢弃的数据包数量。

frame：由于帧错误而丢弃的数据包数量。

compressed：压缩传输所节省的字节数量。

multicast：接收到多播数据包的数量。

5、/proc/diskstats

253 0 vda 978184 4128 81150594 20755299 73453182 4078455 1309816689 398292145 0 113223744 426791458 0 0 0 0 15585634 7744013 20200452 365556940 0
253 1 vda1 977999 4128 81131978 20753990 72102739 4078455 1309816681 396863176 0 112567056 417617166 0 0 0 0 0 0 20199145 365556938 0
253 16 vdb 10371383 566918 5197295816 186317736 4253043 5537854 2637106896 128050659 0 68754698 314653319 0 0 0 0 411815 284922 185895864 126318932 0
253 17 vdb1 10371274 566918 5197280288 186316863 4253012 5537854 2637106896 128050617 0 68754916 314367481 0 0 0 0 0 0 185894994 126318932 0
253 32 vdc 62355261 2902021 51036086962 4222776827 51209471 48829571 38641223240 1144000034 1 453445155 1073094954 0 0 0 0 1186448 1285388 4096018303 1082051035 0
11 0 sr0 352 0 3115 420 0 0 0 0 0 456 420 0 0 0 0 0 0 419 0 0

/proc/diskstatsv提供了磁盘信息的统计信息，含义从左到右依次如下

设备号编号设备读完成次数合并完成次数读扇区次数读操作花费毫秒数写完成次数合并写完成次数写扇区次数写操作花费的毫秒数正在处理的输入/输出请求数输入/输出操作花费的毫秒数输入/输出操作花费的加权毫秒数