FlatBuffers相对于Protobuf的表现又如何呢?这里咱们用数听说话,对比一下FlatBuffers格式、JSON格式与Protobuf的表现。测试一样用fastjson做为JSON的编码解码工具。java
测试用的数据结构全部的数据结构,Protobuf相关的测试代码,及JSON的测试代码同在Android中使用Protocol Buffers 一文所述,FlatBuffers的测试代码如上面看到的 AddressBookFlatBuffers。json
经过以下的这段代码来执行测试:数组
private class ProtoTestTask extends AsyncTask<Void, Void, Void> { private static final int BUFFER_LEN = 8192; private void compress(InputStream is, OutputStream os) throws Exception { GZIPOutputStream gos = new GZIPOutputStream(os); int count; byte data[] = new byte[BUFFER_LEN]; while ((count = is.read(data, 0, BUFFER_LEN)) != -1) { gos.write(data, 0, count); } gos.finish(); gos.close(); } private int getCompressedDataLength(byte[] data) { ByteArrayInputStream bais =new ByteArrayInputStream(data); ByteArrayOutputStream baos = new ByteArrayOutputStream();try { compress(bais, baos); } catch (Exception e) { } return baos.toByteArray().length; } private void dumpDataLengthInfo(byte[] protobufData, String jsonData, byte[] flatbufData) { int compressedProtobufLength = getCompressedDataLength(protobufData); int compressedJSONLength = getCompressedDataLength(jsonData.getBytes()); int compressedFlatbufLength = getCompressedDataLength(flatbufData); Log.i(TAG, String.format("%-120s", "Data length")); Log.i(TAG, String.format("%-20s%-20s%-20s%-20s%-20s%-20s", "Protobuf", "Protobuf (GZIP)", "JSON", "JSON (GZIP)", "Flatbuf", "Flatbuf (GZIP)")); Log.i(TAG, String.format("%-20s%-20s%-20s%-20s%-20s%-20s", String.valueOf(protobufData.length), compressedProtobufLength, String.valueOf(jsonData.getBytes().length), compressedJSONLength, String.valueOf(flatbufData.length), compressedFlatbufLength)); } private void doEncodeTest(String[] names, int times) { long startTime = System.nanoTime(); byte[] protobufData = AddressBookProtobuf.encodeTest(names, times); long protobufTime = System.nanoTime(); protobufTime = protobufTime - startTime; startTime = System.nanoTime(); String jsonData = AddressBookJson.encodeTest(names, times); long jsonTime = System.nanoTime(); jsonTime = jsonTime - startTime; startTime = System.nanoTime(); byte[] flatbufData = AddressBookFlatBuffers.encodeTest(names, times); long flatbufTime = System.nanoTime(); flatbufTime = flatbufTime - startTime; dumpDataLengthInfo(protobufData, jsonData, flatbufData); Log.i(TAG, String.format("%-20s%-20s%-20s%-20s", "Encode Times", String.valueOf(times), "Names Length", String.valueOf(names.length))); Log.i(TAG, String.format("%-20s%-20s%-20s%-20s%-20s%-20s", "ProtobufTime", String.valueOf(protobufTime), "JsonTime", String.valueOf(jsonTime), "FlatbufTime", String.valueOf(flatbufTime))); } private void doEncodeTest10(int times) { doEncodeTest(TestUtils.sTestNames10, times); } private void doEncodeTest50(int times) { doEncodeTest(TestUtils.sTestNames50, times); } private void doEncodeTest100(int times) { doEncodeTest(TestUtils.sTestNames100, times); } private void doEncodeTest(int times) { doEncodeTest10(times); doEncodeTest50(times); doEncodeTest100(times); } private void doDecodeTest(String[] names, int times) { byte[] protobufBytes = AddressBookProtobuf.encodeTest(names); ByteArrayInputStream bais = new ByteArrayInputStream(protobufBytes); long startTime = System.nanoTime(); AddressBookProtobuf.decodeTest(bais, times); long protobufTime = System.nanoTime(); protobufTime = protobufTime - startTime; String jsonStr = AddressBookJson.encodeTest(names); startTime = System.nanoTime(); AddressBookJson.decodeTest(jsonStr, times); long jsonTime = System.nanoTime(); jsonTime = jsonTime - startTime; byte[] flatbufData = AddressBookFlatBuffers.encodeTest(names); startTime = System.nanoTime(); AddressBookFlatBuffers.decodeTest(flatbufData, times); long flatbufTime = System.nanoTime(); flatbufTime = flatbufTime - startTime; Log.i(TAG, String.format("%-20s%-20s%-20s%-20s", "Decode Times", String.valueOf(times), "Names Length", String.valueOf(names.length))); Log.i(TAG, String.format("%-20s%-20s%-20s%-20s%-20s%-20s", "ProtobufTime", String.valueOf(protobufTime), "JsonTime", String.valueOf(jsonTime), "FlatbufTime", String.valueOf(flatbufTime))); } private void doDecodeTest10(int times) { doDecodeTest(TestUtils.sTestNames10, times); } private void doDecodeTest50(int times) { doDecodeTest(TestUtils.sTestNames50, times); } private void doDecodeTest100(int times) { doDecodeTest(TestUtils.sTestNames100, times); } private void doDecodeTest(int times) { doDecodeTest10(times); doDecodeTest50(times); doDecodeTest100(times); } @Override protected Void doInBackground(Void... params) { TestUtils.initTest(); doEncodeTest(5000); doDecodeTest(5000); return null; } @Override protected void onPostExecute(Void aVoid) { super.onPostExecute(aVoid); } }
这里咱们执行3组编码测试及3组解码测试。对于编码测试,第一组的单个数据中包含10个Person,第二组的包含50个,第三组的包含100个,而后对每一个数据分别执行5000次的编码操做。数据结构
对于解码测试,三组中单个数据一样包含10个Person、50个及100个,而后对每一个数据分别执行5000次的解码码操做。ide
在Galaxy Nexus的Android 4.4.4 CM平台上执行上述测试,最终获得以下结果:工具
Person个数 | Protobuf | Protobuf(GZIP) | JSON | JSON(GZIP) | Flatbuf | Flatbuf(GZIP) |
---|---|---|---|---|---|---|
10 | 860 | 288 | 1703 | 343 | 1532 | 513 |
50 | 4300 | 986 | 8463 | 1048 | 7452 | 1814 |
100 | 8600 | 1841 | 16913 | 1918 | 14852 | 3416 |
相同的数据,通过编码,在压缩前JSON的数据最长,FlatBuffers的数据长度与JSON的短大概10 %,而Protobuf的数据长度则大概只有JSON的一半。而在用GZIP压缩后,Protobuf的数据长度与JSON的接近,FlatBuffers的数据长度则接近二者的两倍。性能
Person个数 | Protobuf | JSON | FlatBuffers |
---|---|---|---|
10 | 6.000 | 8.952 | 12.464 |
50 | 26.847 | 45.782 | 56.752 |
100 | 50.602 | 73.688 | 108.426 |
编码性能Protobuf相对于JSON有较大幅度的提升,而FlatBuffers则有较大幅度的下降。测试
Person个数 | Protobuf | JSON | FlatBuffers |
---|---|---|---|
10 | 0.255 | 10.766 | 0.014 |
50 | 0.245 | 51.134 | 0.014 |
100 | 0.323 | 101.070 | 0.006 |
解码性能方面,Protobuf相对于JSON,有着惊人的提高。Protobuf的解码时间几乎不随着数据长度的增加而有太大的增加,而JSON则随着数据长度的增长,解码所须要的时间也愈来愈长。而FlatBuffers则因为无需解码,在性能方面相对于前二者更有着很是大的提高。ui
FlatBuffers的Java库只提供了以下的4个类:this
./com/google/flatbuffers/Constants.java ./com/google/flatbuffers/FlatBufferBuilder.java ./com/google/flatbuffers/Struct.java ./com/google/flatbuffers/Table.java
Constants 类定义FlatBuffers中可用的基本原始数据类型的长度:
public class Constants { // Java doesn't seem to have these. /** The number of bytes in an `byte`. */ static final int SIZEOF_BYTE = 1; /** The number of bytes in a `short`. */ static final int SIZEOF_SHORT = 2; /** The number of bytes in an `int`. */ static final int SIZEOF_INT = 4; /** The number of bytes in an `float`. */ static final int SIZEOF_FLOAT = 4; /** The number of bytes in an `long`. */ static final int SIZEOF_LONG = 8; /** The number of bytes in an `double`. */ static final int SIZEOF_DOUBLE = 8; /** The number of bytes in a file identifier. */ static final int FILE_IDENTIFIER_LENGTH = 4; }
FlatBufferBuilder 用于FlatBuffers编码,它会将咱们的结构化数据序列化为字节数组。咱们借助于 FlatBufferBuilder 在 ByteBuffer 中放置基本数据类型的数据、数组、字符串及对象。ByteBuffer 用于处理字节序,在序列化时,它将数据按适当的字节序进行序列化,在发序列化时,它将多个字节转换为适当的数据类型。在 .fbs 文件中定义的 table 和 struct,为它们生成的Java 类会继承 Table 和 Struct。
在反序列化时,输入的ByteBuffer数据被看成字节数组,Table提供了针对字节数组的操做,生成的Java类负责对这些数据进行解释。对于FlatBuffers编码的数据,无需进行解码,只需进行解释。在编译 .fbs 文件时,每一个字段在这段数据中的位置将被肯定。每一个字段的类型及长度将被硬编码进生成的Java类。
Struct 类的代码也比较简洁:
package com.google.flatbuffers; import java.nio.ByteBuffer; /// @cond FLATBUFFERS_INTERNAL /** * All structs in the generated code derive from this class, and add their own accessors. */ public class Struct { /** Used to hold the position of the `bb` buffer. */ protected int bb_pos; /** The underlying ByteBuffer to hold the data of the Struct. */ protected ByteBuffer bb; }
总体的结构以下图:
在序列化结构化数据时,咱们首先须要建立一个 FlatBufferBuilder ,在这个对象的建立过程当中会分配或从调用者那里获取 ByteBuffer,序列化的数据将保存在这个 ByteBuffer中:
/** * Start with a buffer of size `initial_size`, then grow as required. * * @param initial_size The initial size of the internal buffer to use. */ public FlatBufferBuilder(int initial_size) { if (initial_size <= 0) initial_size = 1; space = initial_size; bb = newByteBuffer(initial_size); } /** * Start with a buffer of 1KiB, then grow as required. */ public FlatBufferBuilder() { this(1024); } /** * Alternative constructor allowing reuse of {@link ByteBuffer}s. The builder * can still grow the buffer as necessary. User classes should make sure * to call {@link #dataBuffer()} to obtain the resulting encoded message. * * @param existing_bb The byte buffer to reuse. */ public FlatBufferBuilder(ByteBuffer existing_bb) { init(existing_bb); } /** * Alternative initializer that allows reusing this object on an existing * `ByteBuffer`. This method resets the builder's internal state, but keeps * objects that have been allocated for temporary storage. * * @param existing_bb The byte buffer to reuse. * @return Returns `this`. */ public FlatBufferBuilder init(ByteBuffer existing_bb){ bb = existing_bb; bb.clear(); bb.order(ByteOrder.LITTLE_ENDIAN); minalign = 1; space = bb.capacity(); vtable_in_use = 0; nested = false; finished = false; object_start = 0; num_vtables = 0; vector_num_elems = 0; return this; } static ByteBuffer newByteBuffer(int capacity) { ByteBuffer newbb = ByteBuffer.allocate(capacity); newbb.order(ByteOrder.LITTLE_ENDIAN); return newbb; }
下面咱们更详细地分析基本数据类型数据、数组及对象的序列化过程。ByteBuffer 为小尾端的。
FlatBuffer 的基本数据类型主要包括以下这些:
Boolean Byte Short Int Long Float Double
FlatBufferBuilder 提供了三组方法用于操做这些数据:
public void putBoolean(boolean x); public void putByte (byte x); public void putShort (short x); public void putInt (int x); public void putLong (long x); public void putFloat (float x); public void putDouble (double x); public void addBoolean(boolean x); public void addByte (byte x); public void addShort (short x); public void addInt (int x); public void addLong (long x); public void addFloat (float x); public void addDouble (double x); public void addBoolean(int o, boolean x, boolean d); public void addByte(int o, byte x, int d); public void addShort(int o, short x, int d); public void addInt (int o, int x, int d); public void addLong (int o, long x, long d); public void addFloat (int o, float x, double d); public void addDouble (int o, double x, double d);
putXXX 那一组,直接地将一个数据放入 ByteBuffer 中,它们的实现基本以下面这样:
public void putBoolean(boolean x) { bb.put(space -= Constants.SIZEOF_BYTE, (byte) (x ? 1 : 0)); } public void putByte(byte x) { bb.put(space -= Constants.SIZEOF_BYTE, x); } public void putShort(short x) { bb.putShort(space -= Constants.SIZEOF_SHORT, x); }
Boolean值会被先转为byte类型再放入 ByteBuffer。另一点值得注意的是,数据是从 ByteBuffer 的结尾处开始放置的,space用于记录最近放入的数据的位置及剩余的空间。
addXXX(XXX x) 那一组在放入数据以前会先作对齐处理,并在须要时扩展 ByteBuffer 的容量:
static ByteBuffer growByteBuffer(ByteBuffer bb) { int old_buf_size = bb.capacity(); if ((old_buf_size & 0xC0000000) != 0) // Ensure we don't grow beyond what fits in an int. throw new AssertionError("FlatBuffers: cannot grow buffer beyond 2 gigabytes."); int new_buf_size = old_buf_size << 1; bb.position(0); ByteBuffer nbb = newByteBuffer(new_buf_size); nbb.position(new_buf_size - old_buf_size); nbb.put(bb); return nbb; } public void pad(int byte_size) { for (int i = 0; i < byte_size; i++) bb.put(--space, (byte) 0); } public void prep(int size, int additional_bytes) { // Track the biggest thing we've ever aligned to. if (size > minalign) minalign = size; // Find the amount of alignment needed such that `size` is properly // aligned after `additional_bytes` int align_size = ((~(bb.capacity() - space + additional_bytes)) + 1) & (size - 1); // Reallocate the buffer if needed. while (space < align_size + size + additional_bytes) { int old_buf_size = bb.capacity(); bb = growByteBuffer(bb); space += bb.capacity() - old_buf_size; } pad(align_size); } public void addBoolean(boolean x) { prep(Constants.SIZEOF_BYTE, 0); putBoolean(x); } public void addInt(int x) { prep(Constants.SIZEOF_INT, 0); putInt(x); }
对齐是数据存放的起始位置相对于ByteBuffer的结束位置的对齐,additional bytes被认为是不须要对齐的,且在必要的时候会在ByteBuffer可用空间的结尾处填充值为0的字节。在扩展 ByteBuffer 的空间时,老的ByteBuffer被放在新ByteBuffer的结尾处。
addXXX(int o, XXX x, YYY y) 这一组方法在放入数据以后,会将 vtable 中对应位置的值更新为最近放入的数据的offset。
public void addShort(int o, short x, int d) { if (force_defaults || x != d) { addShort(x); slot(o); } } public void slot(int voffset) { vtable[voffset] = offset(); }
后面咱们在分析编码对象时再来详细地了解vtable。
基本上,在咱们的应用程序代码中不要直接调用这些方法,它们主要在构造对象时用于存储对象的基本数据类型字段。
相关阅读:
网易云新用户大礼包:https://www.163yun.com/gift
本文来自网易云社区,经做者韩鹏飞受权发布。