如何将输出流转换为输入流？
我正处于开发阶段，我有两个模块，从一个模块中得到输出为 OutputStream，第二个模块只接受 InputStream。你知道如何将 OutputStream 转换为 InputStream （反之亦然，我的意思是这样）我将能够连接这两个部分吗？
谢谢
new YourOutputStream(thePipedOutputStream) 和 new YourInputStream(thePipedInputStream) 那样构造，这可能不是您的流的工作方式。所以我认为这不是解决方案。
似乎有很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 的优点是没有额外的内存消耗。 ByteArrayOutputStream.toByteArray() 返回原始缓冲区的副本，这意味着无论您在内存中拥有什么，现在都有两个副本。然后写入 InputStream 意味着您现在拥有三个数据副本。
使用 lambdas 的代码（评论中对@John Manko 的提示）：
PipedInputStream in = new PipedInputStream();
final PipedOutputStream out = new PipedOutputStream(in);
// in a background thread, write the given output stream to the
// PipedOutputStream for consumption
((Runnable)() -> {originalByteArrayOutputStream.writeTo(out);}).run();
@John Manko 指出的一件事是，在某些情况下，当您无法控制 OutputStream 的创建时，您最终可能会遇到创建者可能会清理 OutputStream 对象过早。如果您得到 ClosedPipeException，那么您应该尝试反转构造函数：
PipedInputStream in = new PipedInputStream(out);
((Runnable)() -> {originalByteArrayOutputStream.writeTo(out);}).run();
请注意，您也可以反转以下示例的构造函数。
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();
此代码假定 originalByteArrayOutputStream 是 ByteArrayOutputStream，因为它通常是唯一可用的输出流，除非您正在写入文件。我希望这有帮助！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，所以任何消耗你的输入流的东西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较小，您将有更少的延迟和更少的内存使用。
如果您没有 ByteArrayOutputStream，则必须使用 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()。
OutputStream 是您向其中写入数据的地方。如果某个模块公开了 OutputStream，则期望在另一端有读取内容。
另一方面，暴露 InputStream 的东西表明您将需要收听此流，并且会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 中的 copy() 方法可以让您做的事情。走另一条路是没有意义的……希望这是有道理的
更新：
当然，我想得越多，我就越能看到这实际上是一个要求。我知道有些评论提到了 Piped 输入/输出流，但还有另一种可能性。
如果公开的输出流是 ByteArrayOutputStream，那么您始终可以通过调用 toByteArray() 方法获取完整内容。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，但对我来说仍然很奇怪......
由于输入和输出流只是起点和终点，解决方案是将数据临时存储在字节数组中。因此，您必须创建中间 ByteArrayOutputStream，从中创建用作新 ByteArrayInputStream 输入的 byte[]。
public void doTwoThingsWithStream(InputStream inStream, OutputStream outStream){
//create temporary bayte array output stream
ByteArrayOutputStream baos = new ByteArrayOutputStream();
doFirstThing(inStream, baos);
//create input stream from baos
InputStream isFromFirstData = new ByteArrayInputStream(baos.toByteArray());
doSecondThing(isFromFirstData, outStream);
}
希望能帮助到你。
ByteArrayOutputStream buffer = (ByteArrayOutputStream) aOutputStream;
byte[] bytes = buffer.toByteArray();
InputStream inputStream = new ByteArrayInputStream(bytes);
toByteArray() 方法体就像返回一个新数组的 return Arrays.copyOf(buf, count);。
java.io.FileOutputStream cannot be cast to java.io.ByteArrayOutputStream
您将需要一个中间类来缓冲。每次调用 InputStream.read(byte[]...) 时，缓冲类将用从 OutputStream.write(byte[]...) 传入的下一个块填充传入的字节数组。由于块的大小可能不同，适配器类将需要存储一定量，直到它有足够的空间来填充读取缓冲区和/或能够存储任何缓冲区溢出。
本文对解决此问题的几种不同方法进行了很好的细分：
http://blog.ostermiller.org/convert-java-outputstream-inputstream
easystream 开源库直接支持将 OutputStream 转换为 InputStream：http://io-tools.sourceforge.net/easystream/tutorial/tutorial.html
// create conversion
final OutputStreamToInputStream<Void> out = new OutputStreamToInputStream<Void>() {
@Override
protected Void doRead(final InputStream in) throws Exception {
LibraryClass2.processDataFromInputStream(in);
return null;
}
};
try {
LibraryClass1.writeDataToTheOutputStream(out);
} finally {
// don't miss the close (or a thread would not terminate correctly).
out.close();
}
他们还列出了其他选项：http://io-tools.sourceforge.net/easystream/outputstream_to_inputstream/implementations.html
将数据写入内存缓冲区 (ByteArrayOutputStream) 获取 byteArray 并使用 ByteArrayInputStream 再次读取。如果您确定您的数据适合内存，这是最好的方法。
将您的数据复制到临时文件并读回。
使用管道：这是内存使用和速度的最佳方法（您可以充分利用多核处理器），也是 Sun 提供的标准解决方案。
使用 easystream 库中的 InputStreamFromOutputStream 和 OutputStreamToInputStream。
我在将 ByteArrayOutputStream 转换为 ByteArrayInputStream 时遇到了同样的问题，并通过使用来自 ByteArrayOutputStream 的派生类来解决它，该派生类能够返回使用 ByteArrayOutputStream 的内部缓冲区初始化的 ByteArrayInputStream。这种方式不使用额外的内存，并且“转换”非常快：
package info.whitebyte.utils;
import java.io.ByteArrayInputStream;
import java.io.ByteArrayOutputStream;
/**
* This class extends the ByteArrayOutputStream by
* providing a method that returns a new ByteArrayInputStream
* which uses the internal byte array buffer. This buffer
* is not copied, so no additional memory is used. After
* creating the ByteArrayInputStream the instance of the
* ByteArrayInOutStream can not be used anymore.
* <p>
* The ByteArrayInputStream can be retrieved using <code>getInputStream()</code>.
* @author Nick Russler
*/
public class ByteArrayInOutStream extends ByteArrayOutputStream {
/**
* Creates a new ByteArrayInOutStream. The buffer capacity is
* initially 32 bytes, though its size increases if necessary.
*/
public ByteArrayInOutStream() {
super();
}
/**
* Creates a new ByteArrayInOutStream, with a buffer capacity of
* the specified size, in bytes.
*
* @param size the initial size.
* @exception IllegalArgumentException if size is negative.
*/
public ByteArrayInOutStream(int size) {
super(size);
}
/**
* Creates a new ByteArrayInputStream that uses the internal byte array buffer
* of this ByteArrayInOutStream instance as its buffer array. The initial value
* of pos is set to zero and the initial value of count is the number of bytes
* that can be read from the byte array. The buffer array is not copied. This
* instance of ByteArrayInOutStream can not be used anymore after calling this
* method.
* @return the ByteArrayInputStream instance
*/
public ByteArrayInputStream getInputStream() {
// create new ByteArrayInputStream that respects the current count
ByteArrayInputStream in = new ByteArrayInputStream(this.buf, 0, this.count);
// set the buffer of the ByteArrayOutputStream
// to null so it can't be altered anymore
this.buf = null;
return in;
}
}
我把东西放在github上：https://github.com/nickrussler/ByteArrayInOutStream
库 io-extras 可能有用。例如，如果您想使用 GZIPOutputStream 压缩 InputStream 并且希望它同步发生（使用默认缓冲区大小 8192）：
InputStream is = ...
InputStream gz = IOUtil.pipe(is, o -> new GZIPOutputStream(o));
请注意，该库具有 100% 的单元测试覆盖率（当然值得！）并且位于 Maven Central 上。 Maven依赖是：
<dependency>
<groupId>com.github.davidmoten</groupId>
<artifactId>io-extras</artifactId>
<version>0.1</version>
</dependency>
请务必检查更高版本。
从我的角度来看，java.io.PipedInputStream/java.io.PipedOutputStream 是考虑的最佳选择。在某些情况下，您可能想要使用 ByteArrayInputStream/ByteArrayOutputStream。问题是您需要复制缓冲区才能将 ByteArrayOutputStream 转换为 ByteArrayInputStream。 ByteArrayOutpuStream/ByteArrayInputStream 也限制为 2GB。这是我为绕过 ByteArrayOutputStream/ByteArrayInputStream 限制而编写的 OutpuStream/InputStream 实现（Scala 代码，但对于 java 开发人员来说很容易理解）：
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
}
}
}
}
易于使用，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(...)
...
如果您想从 InputStream 制作 OutputStream ，则存在一个基本问题。写入 OutputStream 的方法会阻塞，直到完成。所以写完方法后就可以得到结果了。这有两个后果：
如果只使用一个线程，则需要等到所有内容都写入（因此您需要将流的数据存储在内存或磁盘中）。如果要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来实现。变体 1 可以使用 pipies 实现（直接或使用额外的抽象 - 例如 RingBuffer 或其他评论中的 google lib）。
事实上，对于标准 java，没有其他方法可以解决这个问题。每个解决方案都是其中之一的实现。
有一个概念称为“延续”（有关详细信息，请参阅 wikipedia）。在这种情况下，基本上这意味着：
有一个特殊的输出流，它需要一定量的数据
如果达到数量，则流将控制权交给它的对应物，这是一个特殊的输入流
输入流使数据量在被读取之前可用，之后，它将控制权传递回输出流
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，来自 apache 的“commons-javaflow”为 java 实现了此类。缺点是这需要在构建时进行一些特殊的字节码修改。因此，将所有东西放在一个带有自定义构建脚本的额外库中是有意义的。
旧帖子但可能对其他人有所帮助，请使用这种方式：
OutputStream out = new ByteArrayOutputStream();
...
out.write();
...
ObjectInputStream ois = new ObjectInputStream(new ByteArrayInputStream(out.toString().getBytes()));
toString().getBytes() *不会返回流的内容。
尽管您无法将 OutputStream 转换为 InputStream，但 java 提供了一种使用 PipedOutputStream 和 PipedInputStream 的方法，您可以将数据写入 PipedOutputStream 以通过关联的 PipedInputStream 变得可用。
有时，在处理需要将 InputStream 实例而不是 OutputStream 实例传递给它们的第三方库时，我遇到了类似的情况。
我解决此问题的方法是使用 PipedInputStream 和 PipedOutputStream。
顺便说一句，它们使用起来很棘手，您必须使用多线程来实现您想要的。我最近在 github 上发布了一个你可以使用的实现。
这里是 link 。您可以通过 wiki 了解如何使用它。
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out传递给in的构造函数，否则由于竞争条件（我经历过），您可能会在in上得到一个封闭的管道异常。使用 Java 8 Lambda：PipedInputStream in = new PipedInputStream(out); ((Runnable)() -> {originalOutputStream.writeTo(out);}).run(); return in;PipedInputStreamJavadocs 中看到：如果向连接的管道输出流提供数据字节的线程不再活动，则称该管道已损坏。 所以我怀疑如果您使用上面的示例，线程在Jax-RS使用输入流之前完成。同时，我查看了 MongoDB Javadocs。GridFSDBFile有一个输入流，那么为什么不直接将它传递给 Jax-RS？