Protostuff序列化分析

亦凉 2023-01-09 01:06 156阅读 0赞

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最近项目中需要将业务对象直接序列化，然后存数据库；考虑到序列化、反序列化的时间以及生产文件的大小觉得Protobuf是一个很好的选择，但是Protobuf有的问题就是需要有一个.proto的描述文件，而且由Protobuf生成的对象用来作为业务对象并不是特别友好，往往业务对象和Protobuf对象存在一个互相转换的过程；考虑到我们仅仅是将业务对象直接序列化到数据库，发现Protobuf在这种情况下并不是特别的好；

这时候发现了Protostuff，protostuff不需要依赖.proto文件，可以直接对普通的javabean进行序列化、反序列化的操作，而效率上甚至比protobuf还快，生成的二进制数据库格式和Protobuf完全相同的，可以说是一个基于Protobuf的序列化工具。

简单测试

1.先测试一下Protostuff

提供一个简单的javabean

public class Person {
    
    	private int id;
    	private String name;
    	private String email;
            
            // get/set方法省略
    }

测试类PbStuff

public class PbStuff {
    	
    	public static void main(String[] args) throws FileNotFoundException,
    			IOException {
    		Schema<Person> schema = RuntimeSchema.getSchema(Person.class);
    		Person person1 = new Person();
    		person1.setId(1);
    		person1.setName("zhaohui");
    		LinkedBuffer buffer = LinkedBuffer.allocate(1024);
    		byte[] data = ProtobufIOUtil.toByteArray(person1, schema, buffer);
    		System.out.println(data.length);
    	}
    }

序列化之后二进制的大小为29字节

2.测试Protobuf

proto文件

option java_package = "protobuf.clazz"; 
    option java_outer_classname = "PersonX";
    
    message Person {
      required int32 id = 1;
      required string name = 2;
      required string email = 3;
    }

PBTest类

public class PBTest {
    
    	public static void main(String[] args) {
    		PersonX.Person.Builder builder = PersonX.Person.newBuilder();
    		builder.setId(1);
    		builder.setName("zhaohui");
    		builder.setEmail("xxxxxxxx@126.com");
    
    		PersonX.Person p = builder.build();
    		byte[] result = p.toByteArray();
    		System.out.println(result.length);
    
    	}
    }

序列化之后二进制的大小同样也是29字节

经过简单的测试：发现Protobuf和Protostuff序列化相同的数据得到的结果是一样的

Protobuf的编码是尽其所能地将字段的元信息和字段的值压缩存储，并且字段的元信息中含有对这个字段描述的所有信息；既然Protostuff序列化之后的大小和Protobuf是一样的，那可以分析一下Protostuff的源码

源码分析

1.Schema

schema = RuntimeSchema.getSchema(Person.class); //获取业务对象Person的Schema

RuntimeSchema是一个包含业务对象所有信息的类，包括类信息、字段信息

/**
         * Gets the schema that was either registered or lazily initialized at runtime.
         * <p>
         * Method overload for backwards compatibility.
         */
        public static <T> Schema<T> getSchema(Class<T> typeClass)
        {
            return getSchema(typeClass, ID_STRATEGY);
        }
    
        /**
         * Gets the schema that was either registered or lazily initialized at runtime.
         */
        public static <T> Schema<T> getSchema(Class<T> typeClass,
                IdStrategy strategy)
        {
            return strategy.getSchemaWrapper(typeClass, true).getSchema();
        }

getSchema方法中指定了获取Schema的默认策略类ID\_STRATEGY，ID\_STRATEGY在类RuntimeEnv中进行了实例化：

ID_STRATEGY = new DefaultIdStrategy();

可以大致看一下DefaultIdStrategy类：

public final class DefaultIdStrategy extends IdStrategy
    {
    
        final ConcurrentHashMap<String, HasSchema<?>> pojoMapping = new ConcurrentHashMap<>();
    
        final ConcurrentHashMap<String, EnumIO<?>> enumMapping = new ConcurrentHashMap<>();
    
        final ConcurrentHashMap<String, CollectionSchema.MessageFactory> collectionMapping = new ConcurrentHashMap<>();
    
        final ConcurrentHashMap<String, MapSchema.MessageFactory> mapMapping = new ConcurrentHashMap<>();
    
        final ConcurrentHashMap<String, HasDelegate<?>> delegateMapping = new ConcurrentHashMap<>();
        ...
    }

可以发现DefaultIdStrategy内存缓存了很多Schema信息，不难理解既然要或者业务对象的类和字段信息，必然用到反射机制，这是一个很耗时的过程，进行缓存很有必要，这样下次遇到相同的类就可以不用进行反射了

所以可以看到DefaultIdStrategy中有很多这种模式的方法：

public <T> HasSchema<T> getSchemaWrapper(Class<T> typeClass, boolean create)
        {
            HasSchema<T> hs = (HasSchema<T>) pojoMapping.get(typeClass.getName());
            if (hs == null && create)
            {
                hs = new Lazy<>(typeClass, this);
                final HasSchema<T> last = (HasSchema<T>) pojoMapping.putIfAbsent(
                        typeClass.getName(), hs);
                if (last != null)
                    hs = last;
            }
    
            return hs;
        }

先get，如果为null，就putIfAbsent

当业务对象的Schema还没被缓存，这时候就会去create，RuntimeSchema提供了createFrom方法：

public static <T> RuntimeSchema<T> createFrom(Class<T> typeClass,
                Set<String> exclusions, IdStrategy strategy)
        {
            final Map<String, java.lang.reflect.Field> fieldMap = findInstanceFields(typeClass);
            ...省略
            final Field<T> field = RuntimeFieldFactory.getFieldFactory(
                            f.getType(), strategy).create(fieldMapping, name, f,
                            strategy);
                    fields.add(field);
                }
            }
    
            return new RuntimeSchema<>(typeClass, fields, RuntimeEnv.newInstantiator(typeClass));
         }

主要就是对typeClass进行反射，然后进行封装；将字段类型封装成了RuntimeFieldFactory，最后通过RuntimeFieldFactory的create方法封装进入Field类中，RuntimeFieldFactory列举了所有支持的类型：

static final RuntimeFieldFactory<BigDecimal> BIGDECIMAL;
        static final RuntimeFieldFactory<BigInteger> BIGINTEGER;
        static final RuntimeFieldFactory<Boolean> BOOL;
        static final RuntimeFieldFactory<Byte> BYTE;
        static final RuntimeFieldFactory<ByteString> BYTES;
        static final RuntimeFieldFactory<byte[]> BYTE_ARRAY;
        static final RuntimeFieldFactory<Character> CHAR;
        static final RuntimeFieldFactory<Date> DATE;
        static final RuntimeFieldFactory<Double> DOUBLE;
        static final RuntimeFieldFactory<Float> FLOAT;
        static final RuntimeFieldFactory<Integer> INT32;
        static final RuntimeFieldFactory<Long> INT64;
        static final RuntimeFieldFactory<Short> SHORT;
        static final RuntimeFieldFactory<String> STRING;
    
        static final RuntimeFieldFactory<Integer> ENUM;
        static final RuntimeFieldFactory<Object> OBJECT;
        static final RuntimeFieldFactory<Object> POJO;
        static final RuntimeFieldFactory<Object> POLYMORPHIC_POJO;
    
        static final RuntimeFieldFactory<Collection<?>> COLLECTION = 
                new RuntimeFieldFactory<Collection<?>>(ID_COLLECTION)

当然还有常用的Map类型，在RuntimeMapFieldFactory中定义了

2.LinkedBuffer buffer = LinkedBuffer.allocate(1024);

开辟了1024字节缓存，用来存放业务对象序列化之后存放的地方，当然你可能会担心这个大小如果不够怎么办，后面的代码中可以看到，如果空间不足，会自动扩展的，所有这个大小要设置一个合适的值，设置大了浪费空间，设置小了会自动扩展浪费时间。

3.byte\[\] data = ProtobufIOUtil.toByteArray(person1, schema, buffer);

ProtobufIOUtil提供的就是以Protobuf编码的格式来序列化业务对象

public static <T> byte[] toByteArray(T message, Schema<T> schema, LinkedBuffer buffer)
        {
            if (buffer.start != buffer.offset)
                throw new IllegalArgumentException("Buffer previously used and had not been reset.");
    
            final ProtobufOutput output = new ProtobufOutput(buffer);
            try
            {
                schema.writeTo(output, message);
            }
            catch (IOException e)
            {
            }
    
            return output.toByteArray();
        }

schema中调用writeTo方法，将message中的消息保存到ProtobufOutput中

public final void writeTo(Output output, T message) throws IOException
        {
            for (Field<T> f : getFields())
                f.writeTo(output, message);
        }

第一步中将业务对象的字段信息都封装到了Field中了，可以看一下Field类提供的几个方法：

/**
         * Writes the value of a field to the {@code output}.
         */
        protected abstract void writeTo(Output output, T message)
                throws IOException;
    
        /**
         * Reads the field value into the {@code message}.
         */
        protected abstract void mergeFrom(Input input, T message)
                throws IOException;
    
        /**
         * Transfer the input field to the output field.
         */
        protected abstract void transfer(Pipe pipe, Input input, Output output,
                boolean repeated) throws IOException;

提供了三个抽象方法，分别是写数据，读数据和转移数据

下面已int类型为实例，看看实现：

public static final RuntimeFieldFactory<Integer> INT32 = new RuntimeFieldFactory<Integer>(
                ID_INT32)
        {
            @Override
            public <T> Field<T> create(int number, java.lang.String name,
                    final java.lang.reflect.Field f, IdStrategy strategy)
            {
                final boolean primitive = f.getType().isPrimitive();
                final long offset = us.objectFieldOffset(f);
                return new Field<T>(FieldType.INT32, number, name,
                        f.getAnnotation(Tag.class))
                {
                    @Override
                    public void mergeFrom(Input input, T message)
                            throws IOException
                    {
                        if (primitive)
                            us.putInt(message, offset, input.readInt32());
                        else
                            us.putObject(message, offset,
                                    Integer.valueOf(input.readInt32()));
                    }
    
                    @Override
                    public void writeTo(Output output, T message)
                            throws IOException
                    {
                        if (primitive)
                            output.writeInt32(number, us.getInt(message, offset),
                                    false);
                        else
                        {
                            Integer value = (Integer) us.getObject(message, offset);
                            if (value != null)
                                output.writeInt32(number, value.intValue(), false);
                        }
                    }
                    ...
                };
            }

上面这段代码可以在RuntimeUnsafeFieldFactory中找到，基本的数据类型都在此类中能找到，collection和map分别在RuntimeRepeatedFieldFactory和RuntimeMapFieldFactory中，writeTo方法调用了ProtobufOutput中的writeInt32方法：

public void writeInt32(int fieldNumber, int value, boolean repeated) throws IOException
        {
             ...
             tail = writeTagAndRawVarInt32(
                      makeTag(fieldNumber, WIRETYPE_VARINT),
                      value,
                      this,
                      tail);
              ...
        }

写入field的Tag已经Value，Protobuf也是这种形式存放的，如下图所示：

![284b0b0137deb165c59a23cc055bd59b.png][]

public static LinkedBuffer writeTagAndRawVarInt32(int tag, int value,
                final WriteSession session, LinkedBuffer lb)
        {
            final int tagSize = computeRawVarint32Size(tag);
            final int size = computeRawVarint32Size(value);
            final int totalSize = tagSize + size;
    
            if (lb.offset + totalSize > lb.buffer.length)
                lb = new LinkedBuffer(session.nextBufferSize, lb);
    
            final byte[] buffer = lb.buffer;
            int offset = lb.offset;
            lb.offset += totalSize;
            session.size += totalSize;
    
            if (tagSize == 1)
                buffer[offset++] = (byte) tag;
            else
            {
                for (int i = 0, last = tagSize - 1; i < last; i++, tag >>>= 7)
                    buffer[offset++] = (byte) ((tag & 0x7F) | 0x80);
    
                buffer[offset++] = (byte) tag;
            }
    
            if (size == 1)
                buffer[offset] = (byte) value;
            else
            {
                for (int i = 0, last = size - 1; i < last; i++, value >>>= 7)
                    buffer[offset++] = (byte) ((value & 0x7F) | 0x80);
    
                buffer[offset] = (byte) value;
            }
    
            return lb;
        }

tag是通过makeTag方法创建的：

public static int makeTag(final int fieldNumber, final int wireType)
        {
            return (fieldNumber << TAG_TYPE_BITS) | wireType;
        }

fieldNumber每个字段的标号，wire\_type是该字段的数据类型，所有如果我们改变了业务对象类中字段的顺序，或者改变了字段的类型，都会出现反序列化失败；

前面提到的数据压缩在方法computeRawVarint32Size中体现出来了：

public static int computeRawVarint32Size(final int value)
        {
            if ((value & (0xffffffff << 7)) == 0)
                return 1;
            if ((value & (0xffffffff << 14)) == 0)
                return 2;
            if ((value & (0xffffffff << 21)) == 0)
                return 3;
            if ((value & (0xffffffff << 28)) == 0)
                return 4;
            return 5;
        }

根据value值的范围，返回不同的字节数；接下来的代码也可以看到检查LinkedBuffer的空间是否足够，不够进行扩充；接下来的代码就是用压缩的方式将tag和Value存入缓存中。

总结

大致了解了Protostuff对业务对象序列化的过程，不管是简单的测试还是通过查看源码，都可以发现Protostuff的序列化方式是完全借鉴Protobuf来实现的。

[284b0b0137deb165c59a23cc055bd59b.png]: /images/20221119/d37a895672e242049a0b3b38d8a28932.png