我在开发阶段，在那里我有两个模块，从一个我得到输出作为一个OutputStream和第二个，它只接受InputStream。你知道如何将OutputStream转换为InputStream(反之亦然，我的意思是真的这样)，我将能够连接这两个部分吗?
谢谢
当前回答
输出流是将数据写入其中的流。如果某个模块公开了一个OutputStream，则期望在另一端有一些内容正在读取。
另一方面，公开InputStream的内容表明您将需要侦听此流，并且将有您可以读取的数据。
因此，可以将InputStream连接到OutputStream
InputStream----read——> intermediateBytes[n] ----write----> OutputStream
正如有人提到的，这就是IOUtils的copy()方法让您做的事情。相反的方向是没有意义的。希望这能让你们理解
更新:
当然，我越想这一点，就越能看出这实际上是一个要求。我知道有些评论提到了管道输入/输出流，但还有另一种可能性。
如果公开的输出流是bybyterayoutputstream，那么您总是可以通过调用toByteArray()方法来获得完整的内容。然后，您可以使用ByteArrayInputStream子类创建输入流包装器。这两个是伪流，它们基本上都只是包装一个字节数组。因此，以这种方式使用流在技术上是可行的，但对我来说还是很奇怪……
其他回答
From my point of view, java.io.PipedInputStream/java.io.PipedOutputStream is the best option to considere. In some situations you may want to use ByteArrayInputStream/ByteArrayOutputStream. The problem is that you need to duplicate the buffer to convert a ByteArrayOutputStream to a ByteArrayInputStream. Also ByteArrayOutpuStream/ByteArrayInputStream are limited to 2GB. Here is an OutpuStream/InputStream implementation I wrote to bypass ByteArrayOutputStream/ByteArrayInputStream limitations (Scala code, but easily understandable for java developpers):
import java.io.{IOException, InputStream, OutputStream}
import scala.annotation.tailrec
/** Acts as a replacement for ByteArrayOutputStream
*
*/
class HugeMemoryOutputStream(capacity: Long) extends OutputStream {
private val PAGE_SIZE: Int = 1024000
private val ALLOC_STEP: Int = 1024
/** Pages array
*
*/
private var streamBuffers: Array[Array[Byte]] = Array.empty[Array[Byte]]
/** Allocated pages count
*
*/
private var pageCount: Int = 0
/** Allocated bytes count
*
*/
private var allocatedBytes: Long = 0
/** Current position in stream
*
*/
private var position: Long = 0
/** Stream length
*
*/
private var length: Long = 0
allocSpaceIfNeeded(capacity)
/** Gets page count based on given length
*
* @param length Buffer length
* @return Page count to hold the specified amount of data
*/
private def getPageCount(length: Long) = {
var pageCount = (length / PAGE_SIZE).toInt + 1
if ((length % PAGE_SIZE) == 0) {
pageCount -= 1
}
pageCount
}
/** Extends pages array
*
*/
private def extendPages(): Unit = {
if (streamBuffers.isEmpty) {
streamBuffers = new Array[Array[Byte]](ALLOC_STEP)
}
else {
val newStreamBuffers = new Array[Array[Byte]](streamBuffers.length + ALLOC_STEP)
Array.copy(streamBuffers, 0, newStreamBuffers, 0, streamBuffers.length)
streamBuffers = newStreamBuffers
}
pageCount = streamBuffers.length
}
/** Ensures buffers are bug enough to hold specified amount of data
*
* @param value Amount of data
*/
private def allocSpaceIfNeeded(value: Long): Unit = {
@tailrec
def allocSpaceIfNeededIter(value: Long): Unit = {
val currentPageCount = getPageCount(allocatedBytes)
val neededPageCount = getPageCount(value)
if (currentPageCount < neededPageCount) {
if (currentPageCount == pageCount) extendPages()
streamBuffers(currentPageCount) = new Array[Byte](PAGE_SIZE)
allocatedBytes = (currentPageCount + 1).toLong * PAGE_SIZE
allocSpaceIfNeededIter(value)
}
}
if (value < 0) throw new Error("AllocSpaceIfNeeded < 0")
if (value > 0) {
allocSpaceIfNeededIter(value)
length = Math.max(value, length)
if (position > length) position = length
}
}
/**
* Writes the specified byte to this output stream. The general
* contract for <code>write</code> is that one byte is written
* to the output stream. The byte to be written is the eight
* low-order bits of the argument <code>b</code>. The 24
* high-order bits of <code>b</code> are ignored.
* <p>
* Subclasses of <code>OutputStream</code> must provide an
* implementation for this method.
*
* @param b the <code>byte</code>.
*/
@throws[IOException]
override def write(b: Int): Unit = {
val buffer: Array[Byte] = new Array[Byte](1)
buffer(0) = b.toByte
write(buffer)
}
/**
* Writes <code>len</code> bytes from the specified byte array
* starting at offset <code>off</code> to this output stream.
* The general contract for <code>write(b, off, len)</code> is that
* some of the bytes in the array <code>b</code> are written to the
* output stream in order; element <code>b[off]</code> is the first
* byte written and <code>b[off+len-1]</code> is the last byte written
* by this operation.
* <p>
* The <code>write</code> method of <code>OutputStream</code> calls
* the write method of one argument on each of the bytes to be
* written out. Subclasses are encouraged to override this method and
* provide a more efficient implementation.
* <p>
* If <code>b</code> is <code>null</code>, a
* <code>NullPointerException</code> is thrown.
* <p>
* If <code>off</code> is negative, or <code>len</code> is negative, or
* <code>off+len</code> is greater than the length of the array
* <code>b</code>, then an <tt>IndexOutOfBoundsException</tt> is thrown.
*
* @param b the data.
* @param off the start offset in the data.
* @param len the number of bytes to write.
*/
@throws[IOException]
override def write(b: Array[Byte], off: Int, len: Int): Unit = {
@tailrec
def writeIter(b: Array[Byte], off: Int, len: Int): Unit = {
val currentPage: Int = (position / PAGE_SIZE).toInt
val currentOffset: Int = (position % PAGE_SIZE).toInt
if (len != 0) {
val currentLength: Int = Math.min(PAGE_SIZE - currentOffset, len)
Array.copy(b, off, streamBuffers(currentPage), currentOffset, currentLength)
position += currentLength
writeIter(b, off + currentLength, len - currentLength)
}
}
allocSpaceIfNeeded(position + len)
writeIter(b, off, len)
}
/** Gets an InputStream that points to HugeMemoryOutputStream buffer
*
* @return InputStream
*/
def asInputStream(): InputStream = {
new HugeMemoryInputStream(streamBuffers, length)
}
private class HugeMemoryInputStream(streamBuffers: Array[Array[Byte]], val length: Long) extends InputStream {
/** Current position in stream
*
*/
private var position: Long = 0
/**
* Reads the next byte of data from the input stream. The value byte is
* returned as an <code>int</code> in the range <code>0</code> to
* <code>255</code>. If no byte is available because the end of the stream
* has been reached, the value <code>-1</code> is returned. This method
* blocks until input data is available, the end of the stream is detected,
* or an exception is thrown.
*
* <p> A subclass must provide an implementation of this method.
*
* @return the next byte of data, or <code>-1</code> if the end of the
* stream is reached.
*/
@throws[IOException]
def read: Int = {
val buffer: Array[Byte] = new Array[Byte](1)
if (read(buffer) == 0) throw new Error("End of stream")
else buffer(0)
}
/**
* Reads up to <code>len</code> bytes of data from the input stream into
* an array of bytes. An attempt is made to read as many as
* <code>len</code> bytes, but a smaller number may be read.
* The number of bytes actually read is returned as an integer.
*
* <p> This method blocks until input data is available, end of file is
* detected, or an exception is thrown.
*
* <p> If <code>len</code> is zero, then no bytes are read and
* <code>0</code> is returned; otherwise, there is an attempt to read at
* least one byte. If no byte is available because the stream is at end of
* file, the value <code>-1</code> is returned; otherwise, at least one
* byte is read and stored into <code>b</code>.
*
* <p> The first byte read is stored into element <code>b[off]</code>, the
* next one into <code>b[off+1]</code>, and so on. The number of bytes read
* is, at most, equal to <code>len</code>. Let <i>k</i> be the number of
* bytes actually read; these bytes will be stored in elements
* <code>b[off]</code> through <code>b[off+</code><i>k</i><code>-1]</code>,
* leaving elements <code>b[off+</code><i>k</i><code>]</code> through
* <code>b[off+len-1]</code> unaffected.
*
* <p> In every case, elements <code>b[0]</code> through
* <code>b[off]</code> and elements <code>b[off+len]</code> through
* <code>b[b.length-1]</code> are unaffected.
*
* <p> The <code>read(b,</code> <code>off,</code> <code>len)</code> method
* for class <code>InputStream</code> simply calls the method
* <code>read()</code> repeatedly. If the first such call results in an
* <code>IOException</code>, that exception is returned from the call to
* the <code>read(b,</code> <code>off,</code> <code>len)</code> method. If
* any subsequent call to <code>read()</code> results in a
* <code>IOException</code>, the exception is caught and treated as if it
* were end of file; the bytes read up to that point are stored into
* <code>b</code> and the number of bytes read before the exception
* occurred is returned. The default implementation of this method blocks
* until the requested amount of input data <code>len</code> has been read,
* end of file is detected, or an exception is thrown. Subclasses are encouraged
* to provide a more efficient implementation of this method.
*
* @param b the buffer into which the data is read.
* @param off the start offset in array <code>b</code>
* at which the data is written.
* @param len the maximum number of bytes to read.
* @return the total number of bytes read into the buffer, or
* <code>-1</code> if there is no more data because the end of
* the stream has been reached.
* @see java.io.InputStream#read()
*/
@throws[IOException]
override def read(b: Array[Byte], off: Int, len: Int): Int = {
@tailrec
def readIter(acc: Int, b: Array[Byte], off: Int, len: Int): Int = {
val currentPage: Int = (position / PAGE_SIZE).toInt
val currentOffset: Int = (position % PAGE_SIZE).toInt
val count: Int = Math.min(len, length - position).toInt
if (count == 0 || position >= length) acc
else {
val currentLength = Math.min(PAGE_SIZE - currentOffset, count)
Array.copy(streamBuffers(currentPage), currentOffset, b, off, currentLength)
position += currentLength
readIter(acc + currentLength, b, off + currentLength, len - currentLength)
}
}
readIter(0, b, off, len)
}
/**
* Skips over and discards <code>n</code> bytes of data from this input
* stream. The <code>skip</code> method may, for a variety of reasons, end
* up skipping over some smaller number of bytes, possibly <code>0</code>.
* This may result from any of a number of conditions; reaching end of file
* before <code>n</code> bytes have been skipped is only one possibility.
* The actual number of bytes skipped is returned. If <code>n</code> is
* negative, the <code>skip</code> method for class <code>InputStream</code> always
* returns 0, and no bytes are skipped. Subclasses may handle the negative
* value differently.
*
* The <code>skip</code> method of this class creates a
* byte array and then repeatedly reads into it until <code>n</code> bytes
* have been read or the end of the stream has been reached. Subclasses are
* encouraged to provide a more efficient implementation of this method.
* For instance, the implementation may depend on the ability to seek.
*
* @param n the number of bytes to be skipped.
* @return the actual number of bytes skipped.
*/
@throws[IOException]
override def skip(n: Long): Long = {
if (n < 0) 0
else {
position = Math.min(position + n, length)
length - position
}
}
}
}
使用方便，无缓冲区重复，无2GB内存限制
val out: HugeMemoryOutputStream = new HugeMemoryOutputStream(initialCapacity /*may be 0*/)
out.write(...)
...
val in1: InputStream = out.asInputStream()
in1.read(...)
...
val in2: InputStream = out.asInputStream()
in2.read(...)
...
输出流是将数据写入其中的流。如果某个模块公开了一个OutputStream，则期望在另一端有一些内容正在读取。
另一方面，公开InputStream的内容表明您将需要侦听此流，并且将有您可以读取的数据。
因此，可以将InputStream连接到OutputStream
InputStream----read——> intermediateBytes[n] ----write----> OutputStream
正如有人提到的，这就是IOUtils的copy()方法让您做的事情。相反的方向是没有意义的。希望这能让你们理解
更新:
当然，我越想这一点，就越能看出这实际上是一个要求。我知道有些评论提到了管道输入/输出流，但还有另一种可能性。
如果公开的输出流是bybyterayoutputstream，那么您总是可以通过调用toByteArray()方法来获得完整的内容。然后，您可以使用ByteArrayInputStream子类创建输入流包装器。这两个是伪流，它们基本上都只是包装一个字节数组。因此，以这种方式使用流在技术上是可行的，但对我来说还是很奇怪……
如果你想从一个InputStream生成一个OutputStream，有一个基本的问题。写入OutputStream的方法会阻塞，直到完成为止。因此，当编写方法完成时，结果是可用的。这有两个后果:
如果只使用一个线程，则需要等待所有内容写入(因此需要将流数据存储在内存或磁盘中)。 如果希望在数据完成之前访问数据，则需要第二个线程。
变体1可以使用字节数组或字段实现。 变体1可以使用pipies实现(直接或额外的抽象-例如RingBuffer或来自其他注释的谷歌库)。
事实上，在标准java中，没有其他方法可以解决这个问题。每个解决方案都是其中一个的实现。
有一个概念叫做“延续”(详见维基百科)。在这种情况下，这基本上意味着:
有一个特殊的输出流，它需要一定数量的数据 如果达到数量，则流将控制权交给对应的特殊输入流 输入流在读取数据之前提供可用的数据量，在读取之后，它将控制传递回输出流
虽然有些语言内置了这个概念，但对于java，您需要一些“魔法”。例如apache中的“commons-javaflow”实现了这样的java。缺点是这需要在构建时进行一些特殊的字节码修改。因此，将所有的东西都放在一个带有自定义构建脚本的额外库中是有意义的。
似乎有许多链接和其他类似的东西，但没有使用管道的实际代码。使用java.io.PipedInputStream和java.io.PipedOutputStream的优点是不会额外消耗内存。ByteArrayOutputStream.toByteArray()返回原始缓冲区的副本，因此这意味着无论内存中有什么，现在都有它的两个副本。然后写入InputStream意味着现在有了数据的三个副本。
使用lambdas的代码(从评论中向@John Manko致敬):
PipedInputStream in = new PipedInputStream();
final PipedOutputStream out = new PipedOutputStream(in);
// in a background thread, write the given output stream to the
// PipedOutputStream for consumption
new Thread(() -> {originalOutputStream.writeTo(out);}).start();
@John Manko注意到的一件事是，在某些情况下，当您无法控制OutputStream的创建时，您可能会在创建者过早地清理OutputStream对象的情况下结束。如果你正在获取ClosedPipeException，那么你应该尝试反向构造函数:
PipedInputStream in = new PipedInputStream(out);
new Thread(() -> {originalOutputStream.writeTo(out);}).start();
注意，您也可以为下面的示例反转构造函数。
也感谢@AlexK纠正我开始一个线程，而不是仅仅启动一个Runnable。
使用try-with-resources的代码:
// take the copy of the stream and re-write it to an InputStream
PipedInputStream in = new PipedInputStream();
new Thread(new Runnable() {
public void run () {
// try-with-resources here
// putting the try block outside the Thread will cause the
// PipedOutputStream resource to close before the Runnable finishes
try (final PipedOutputStream out = new PipedOutputStream(in)) {
// write the original OutputStream to the PipedOutputStream
// note that in order for the below method to work, you need
// to ensure that the data has finished writing to the
// ByteArrayOutputStream
originalByteArrayOutputStream.writeTo(out);
}
catch (IOException e) {
// logging and exception handling should go here
}
}
}).start();
我写的原始代码:
// take the copy of the stream and re-write it to an InputStream
PipedInputStream in = new PipedInputStream();
final PipedOutputStream out = new PipedOutputStream(in);
new Thread(new Runnable() {
public void run () {
try {
// write the original OutputStream to the PipedOutputStream
// note that in order for the below method to work, you need
// to ensure that the data has finished writing to the
// ByteArrayOutputStream
originalByteArrayOutputStream.writeTo(out);
}
catch (IOException e) {
// logging and exception handling should go here
}
finally {
// close the PipedOutputStream here because we're done writing data
// once this thread has completed its run
if (out != null) {
// close the PipedOutputStream cleanly
out.close();
}
}
}
}).start();
这段代码假设原始ByteArrayOutputStream是一个ByteArrayOutputStream，因为它通常是唯一可用的输出流，除非您正在写入文件。这样做的好处是，因为它在一个单独的线程中，所以它也是并行工作的，所以无论消耗你的输入流的是什么，它也会从你的旧输出流中流出。这是有益的，因为缓冲区可以保持更小，您将有更少的延迟和内存使用。
如果你没有ByteArrayOutputStream，那么你将不得不使用java.io.OutputStream类中的write()方法之一或子类中可用的其他方法之一，而不是使用writeTo()。
ByteArrayOutputStream buffer = (ByteArrayOutputStream) aOutputStream;
byte[] bytes = buffer.toByteArray();
InputStream inputStream = new ByteArrayInputStream(bytes);
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