摘要：緩沖輸入流從被稱為緩沖區的存儲器區域讀出數據僅當緩沖區是空時，本地輸入才被調用。同樣，緩沖輸出流，將數據寫入到緩存區，只有當緩沖區已滿才調用本機輸出。

：https://segmentfault.com/blog...

前陣子休息天日常在尋找項目里不好的代碼,看到了這樣的一段代碼:

    private Result sshSameExec(Session session, String cmd) {
        if (log.isDebugEnabled()) {
            log.debug("shell command: {}", cmd);
        }
        UserInfo ui = getUserInfo();
        session.setUserInfo(ui);
        int exitStatus = 0;
        StringBuilder builder = new StringBuilder();
        ChannelExec channel;
        InputStream in;
        InputStream err;
        try {
            session.connect(connectTimeout);
            channel = (ChannelExec) session.openChannel("exec");
            channel.setCommand(cmd);
            in = channel.getInputStream();
            err = channel.getErrStream();
            channel.connect();
        } catch (Exception e) {
            throw new CloudRuntimeException(e);
        }

        try {
            long lastRead = Long.MAX_VALUE;
            byte[] tmp = new byte[1024];
            while (true) {
                while (in.available() > 0 || err.available() > 0) {
                    int i = 0;
                    if (in.available() > 0) {
                        i = in.read(tmp, 0, 1024);
                    } else if (err.available() > 0) {
                        i = err.read(tmp, 0, 1024);
                    }
                    if (i < 0) {
                        break;
                    }
                    lastRead = System.currentTimeMillis();
                    builder.append(new String(tmp, 0, i));
                }
                if (channel.isClosed()) {
                    if (in.available() > 0) {
                        continue;
                    }
                    exitStatus = channel.getExitStatus();
                    break;
                }
                if (System.currentTimeMillis() - lastRead > exeTimeout) {
                    break;
                }
            }
        } catch (IOException e) {
            throw new CloudRuntimeException(e);
        } finally {
            channel.disconnect();
            session.disconnect();
        }

        if (0 != exitStatus) {
            return Result.createByError(ErrorData.builder()
                    .errorCode(ResultCode.EXECUTE_SSH_FAIL.getCode())
                    .detail(builder.toString())
                    .title(ResultCode.EXECUTE_SSH_FAIL.toString())
                    .build());
        } else {
            return Result.createBySuccess(builder.toString());
        }
    }

簡單解釋一下這段代碼——即通過ssh到一臺機器上,然后執行一些命令.對命令輸出的東西,開了一個循環,每一次讀一定的位置,然后以字節流的形式讀回來.

這段代碼有點丑,于是我聞到了學習的味道.

首先是對兩個Stream的消費,很顯然,在多核環境下,我們同時也只能夠消費其中一個Stream.其次,這代碼太挫了,自己定義一個tmp,然后1024、1024這樣的去取出來.

在改良之前,我們先來回顧一下JavaIO的接口定義.

這里有同學可能問了,為啥叫它低抽象接口呢?因為它離底層太近了,計算機本來就是處理二進制的,而這兩個接口正是用來處理二進制數據流的.

先簡單看一眼這兩個接口:

InputStream

**
 * This abstract class is the superclass of all classes representing
 * an input stream of bytes.
 *
 * 
 Applications that need to define a subclass of InputStream
 * must always provide a method that returns the next byte of input.
 *
 * @author  Arthur van Hoff
 * @see     java.io.BufferedInputStream
 * @see     java.io.ByteArrayInputStream
 * @see     java.io.DataInputStream
 * @see     java.io.FilterInputStream
 * @see     java.io.InputStream#read()
 * @see     java.io.OutputStream
 * @see     java.io.PushbackInputStream
 * @since   JDK1.0
 */
public abstract class InputStream implements Closeable {.....}

OutputStream

/**
 * This abstract class is the superclass of all classes representing
 * an output stream of bytes. An output stream accepts output bytes
 * and sends them to some sink.
 * 

 * Applications that need to define a subclass of
 * OutputStream must always provide at least a method
 * that writes one byte of output.
 *
 * @author  Arthur van Hoff
 * @see     java.io.BufferedOutputStream
 * @see     java.io.ByteArrayOutputStream
 * @see     java.io.DataOutputStream
 * @see     java.io.FilterOutputStream
 * @see     java.io.InputStream
 * @see     java.io.OutputStream#write(int)
 * @since   JDK1.0
 */
public abstract class OutputStream implements Closeable, Flushable {...}

我們可以發現,它們都實現了Closeable的接口.因此大家在使用這些原生類時,要注意在結束時調用Close方法哦.

這兩個接口的常用實現類有:
-?FileInputStream和FileOutputStream

DataInputStream和DataOutputStream

?ObjectInputStream和ObjectOutputStream

為啥說它是高級抽象接口呢?我們先來看看它們的注釋:

Writer

/**
 * Abstract class for writing to character streams.  The only methods that a
 * subclass must implement are write(char[], int, int), flush(), and close().
 * Most subclasses, however, will override some of the methods defined here in
 * order to provide higher efficiency, additional functionality, or both.
 *
 * @see Writer
 * @see   BufferedWriter
 * @see   CharArrayWriter
 * @see   FilterWriter
 * @see   OutputStreamWriter
 * @see     FileWriter
 * @see   PipedWriter
 * @see   PrintWriter
 * @see   StringWriter
 * @see Reader
 *
 * @author      Mark Reinhold
 * @since       JDK1.1
 */

public abstract class Writer implements Appendable, Closeable, Flushable {

Reader

/**
 * Abstract class for reading character streams.  The only methods that a
 * subclass must implement are read(char[], int, int) and close().  Most
 * subclasses, however, will override some of the methods defined here in order
 * to provide higher efficiency, additional functionality, or both.
 *
 *
 * @see BufferedReader
 * @see   LineNumberReader
 * @see CharArrayReader
 * @see InputStreamReader
 * @see   FileReader
 * @see FilterReader
 * @see   PushbackReader
 * @see PipedReader
 * @see StringReader
 * @see Writer
 *
 * @author      Mark Reinhold
 * @since       JDK1.1
 */

public abstract class Reader implements Readable, Closeable {

我們可以看到,這個抽象類是用來面向character的,也就是字符.字符的抽象等級必然比字節高,因為字符靠近上層,即人類.

如果我們直接使用上述實現類去打開一個文件(如FileWriter 、FileReader 、FileInputStream 、FileOutputStream ),對其對象調用read、write、readLine等,每個請求都是由基礎OS直接處理的,這會使一個程序效率低得多——因為它們都會引發磁盤訪問or網絡請求等.

為了減少這種開銷，Java 平臺實現緩沖 I/O 流。緩沖輸入流從被稱為緩沖區（buffer）的存儲器區域讀出數據;僅當緩沖區是空時，本地輸入 API 才被調用。同樣，緩沖輸出流，將數據寫入到緩存區，只有當緩沖區已滿才調用本機輸出 API。

用于包裝非緩存流的緩沖流類有4個：BufferedInputStream和BufferedOutputStream·用于創建字節緩沖字節流,?BufferedReader和BufferedWriter`用于創建字符緩沖字節流.

之前,我們提到了這段代碼寫得搓的地方:

首先是對兩個Stream的消費,很顯然,在多核環境下,我們同時也只能夠消費其中一個Stream.

其次,這代碼太挫了,自己定義一個tmp,然后1024、1024這樣的去取出來.

故此,我們可以考慮對每個Stream都進行包裝,支持用線程去消費,其次我們可以用高級抽象分接口去適配Byte,然后去裝飾成Buffer.

接下來,我們來看一段ZStack里的工具類ShellUtils,為了節省篇幅,我們僅僅截出它在IDE里的
概覽:

run方法的核心:

        public ShellResult run() {
            StopWatch watch = new StopWatch();
            watch.start();
            try {
                if (withSudo) {
                    command = String.format("sudo %s", command);
                }

                ProcessBuilder pb = new ProcessBuilder(Arrays.asList("/bin/bash", "-c", command));
                if (baseDir == null) {
                    baseDir = System.getProperty("user.home");
                }
                pb.directory(new File(baseDir));

                process = pb.start();
                if (!suppressTraceLog && logger.isTraceEnabled()) {
                    logger.debug(String.format("exec shell command[%s]", command));
                }

                Writer stdout;
                int stdoutLog = stdoutLogStrategy();
                if (stdoutLog == LOG_TO_FILE) {
                    stdout = new BufferedWriter(new FileWriter(stdoutFile));
                } else if (stdoutLog == LOG_TO_SCREEN) {
                    stdout = new BufferedWriter(new OutputStreamWriter(System.out));
                } else {
                    stdout = new StringWriter();
                }

                Writer stderr;
                int stderrLog = stderrLogStrategy();
                if (stderrLog == LOG_TO_FILE) {
                    stderr = new BufferedWriter(new FileWriter(stderrFile));
                } else if (stderrLog == LOG_TO_SCREEN) {
                    stderr = new BufferedWriter(new OutputStreamWriter(System.err));
                } else {
                    stderr = new StringWriter();
                }

                StreamConsumer stdoutConsumer = new StreamConsumer(process.getInputStream(), new PrintWriter(stdout, true), stdoutLog != LOG_TO_FILE);
                StreamConsumer stderrConsumer = new StreamConsumer(process.getErrorStream(), new PrintWriter(stderr, true), stderrLog != LOG_TO_FILE);

                stderrConsumer.start();
                stdoutConsumer.start();
                process.waitFor();
                stderrConsumer.join(TimeUnit.SECONDS.toMillis(30));
                stdoutConsumer.join(TimeUnit.SECONDS.toMillis(30));

                ShellResult ret = new ShellResult();
                ret.setCommand(command);
                ret.setRetCode(process.exitValue());
                if (stderrLog == LOG_TO_STRING) {
                    ret.setStderr(stderr.toString());
                } else if (stderrLog == LOG_TO_FILE) {
                    stderr.close();
                }
                if (stdoutLog == LOG_TO_STRING) {
                    ret.setStdout(stdout.toString());
                } else if (stdoutLog == LOG_TO_FILE) {
                    stdout.close();
                }

                return ret;
            } catch (Exception e) {
                StringBuilder sb = new StringBuilder();
                sb.append("Shell command failed:
");
                sb.append(command);
                throw new ShellException(sb.toString(), e);
            } finally {
                if (process != null) {
                    process.destroy();
                }
                watch.stop();
                if (!suppressTraceLog && logger.isTraceEnabled()) {
                    logger.trace(String.format("shell command[%s] costs %sms to finish", command, watch.getTime()));
                }
            }
        }
    }

我們可以看到StreamConsumer這個類,我們來看一下它的代碼:

    private static class StreamConsumer extends Thread {
        final InputStream in;
        final PrintWriter out;
        final boolean flush;

        StreamConsumer(InputStream in, PrintWriter out, boolean flushEveryWrite) {
            this.in = in;
            this.out = out;
            flush = flushEveryWrite;
        }

        @Override
        public void run() {
            BufferedReader br = null;
            try {
                br = new BufferedReader(new InputStreamReader(in));
                String line;
                while ( (line = br.readLine()) != null) {
                    out.println(line);
                    if (flush) {
                        out.flush();
                    }
                }
            } catch (Exception e) {
                logger.warn(e.getMessage(), e);
            } finally {
                try {
                    if (br != null) {
                        br.close();
                    }
                } catch (IOException e) {
                    logger.warn(e.getMessage(), e);
                }
            }
        }
    }

這段代碼已經達到了我們的理想狀態:線程消費,高級抽象.

閑話不多說,先貼代碼為敬:

import java.io.InputStream
import java.io.InputStreamReader

class StreamGobbler(private val inputStream: InputStream, private var result: StringBuilder) : Runnable {

    override fun run() {
        InputStreamReader(inputStream).buffered().use {
            it.lines().forEach { r -> result.append(r) }
        }
    }
}

還是一樣熟悉的配方,我們逐行來解讀:

定義一個類,并且要求構造函數必須傳入InputStream和一個StringBuilder.且實現了Runnable接口,這意味著它可以被線程消費.

覆寫run方法.我們可以看到InputStream被適配成了InputStreamReader,這意味著它可以輸出字符流了,然后我們使用了Kotlin的接口將其裝飾成了Buffer.

讀每一行buffer,并appned到result這個StringBuilder里去.

讀完就可以告辭了,close.(use會將其關閉)

先看一下上面的圖,我們都知道內核態線程是由OS調度的,但當一個線程拿到時間片時,卻調到了阻塞IO,那么只能等在那邊,浪費時間.

而協程則可以解決這個問題,當一個Jobhang住的時候,可以去做別的事情,繞開阻塞.更好的利用時間片.

最后,我們來看一下成品代碼:

    override fun sshExecWithCoroutine(session: Session, cmd: String): SimpleResult {
        val ui = InnerUserInfo()
        session.userInfo = ui
        val exitStatus: Int
        var channel = ChannelExec()
        val inputBuilder = StringBuilder()
        val errorBuilder = StringBuilder()
        try {
            session.connect(connectTimeout)
            channel = session.openChannel("exec") as ChannelExec
            channel.setCommand(cmd)
            channel.connect()
            val inputStream = StreamGobbler(channel.inputStream, inputBuilder)
            val errStream = StreamGobbler(channel.errStream, errorBuilder)

            val customJob = GlobalScope.launch {
                customStream(inputStream, errStream)
            }

            while (!customJob.isCompleted) {
                // wait job be done
            }

            exitStatus = channel.exitStatus
        } catch (e: IOException) {
            throw java.lang.RuntimeException(e)
        } finally {
            if (channel.isConnected) {
                channel.disconnect()
            }
            if (session.isConnected) {
                session.disconnect()
            }
        }

        return if (0 != exitStatus) {
            return SimpleResult.createByError(ErrorData.Builder()
                    .errorCode(ResultCode.EXECUTE_SSH_FAIL.value)
                    .detail(errorBuilder.toString())
                    .title(ResultCode.EXECUTE_SSH_FAIL.toString())
                    .build())

        } else {
            SimpleResult.createBySuccess(inputBuilder.toString())
        }
    }


    private suspend fun customStream(inputStream: StreamGobbler, errorStream: StreamGobbler) {
        val inputDeferred = GlobalScope.async {
            inputStream.run()
        }
        val errorDeferred = GlobalScope.async {
            errorStream.run()
        }

        inputDeferred.join()
        errorDeferred.join()
    }