Jackson Tutorial - 1

1. Jackson tutorial(http://wiki.fasterxml.com/JacksonInFiveMinutes)
2. 차례
   • JSON Three Ways
   • Examples
     • Full Data Binding (POJO) Example
     • Simple Data Binding Example
     • Data Binding with Generics
     • Three Model Example
     • Streaming API Example

    

3. JSON Three Ways
   • Jackson은 JSON 데이터를 처리하기 위한 세가지 방법을 제공한다.
   • Streaming API(aka Incremental Processing, or Token Streams)
     • http://wiki.fasterxml.com/JacksonStreamingApi
     • Streaming API는 JSON 데이터를 처리하는데 가장 효과적인 방법이다.
     • 어플리케이션 보다는 주로 미들웨어나 프레임워크와 같이 성능이 중요한 곳에서 사용된다.
     • 장점 : Lowest memory and processing overhead
     • 단점
       • 모든 데이터는 순차적으로 처리된다. Random Access 불가.
       • 매우 기본적인 데이터 타입만 제공한다.(String, byte[] for base64-encoded binary content)
     • org.codehaus.jackson.JsonParser reads, org.codehaus.jackson.JsonGenerator writes.
       • Creating Parsers
         • Paraser는 JSON Content에서 각각의 데이터를 분리한다.
         • JSON Content에 대한 Low-level access.
         • org.codehaus.jackson.JsonFactory has extensive set of methods to construct parsers
         • Example

   JsonFactory jsonFactory = new JsonFactory();                     // or, for data binding, org.codehaus.jackson.mapper.MappingJsonFactory JsonParser jp = jsonFactory.createJsonParser(file); // or URL, Stream, Reader, String, byte[]

   • Creating Generators
     • JSON Cotent를 JSON 각각의 데이터로 분리해준다.
     • Example

   JsonFactory jsonFactory = new JsonFactory();                           // or, for data binding, org.codehaus.jackson.mapper.MappingJsonFactory JsonGenerator jg = jsonFactory.createJsonGenerator(file, JsonEncoding.UTF8); // or Stream, Reader

   • Configuring
     • JsonParser.Features
       • http://wiki.fasterxml.com/JacksonFeaturesParser
       • AUTO_CLOSE_SOURCE, INTERN_FIELD_NAMES, CANONICALIZE_FIELD_NAMES
       • ALLOW_COMMENTS, ALLOW_UNQUOTED_FIELD_NAMES, ALLOW_SINGLE_QUOTES, ALLOW_UNQUOTED_CONTROL_CHARS
     • JsonGenerator.Feature
       • http://wiki.fasterxml.com/JacksonFeaturesGenerator
       • AUTO_CLOSE_TARGET, AUTO_CLOSE_JSON_CONTENT, QUOTE_NON_NUMERIC_NUMBERS, WRITE_NUMBERS_AS_STRINGS
       • QUOTE_FIELD_NAMES
   • Tree Model
     • http://wiki.fasterxml.com/JacksonTreeModel
     • Constructing Trees From JSON Content
       • ObjectMapper를 이용하며, 두가지 방법이있다.
       • Example

   <<첫번째 방법>>  // general method, same as with data binding   ObjectMapper mapper = new ObjectMapper();   // (note: can also use more specific type, like ArrayNode or ObjectNode!)   JsonNode rootNode = mapper.readValue(src, JsonNode.class); // src can be a File, URL, InputStream etc     <<두번째 방법>>   // or, with dedicated method; requires a JsonParser instance   JsonParser jp = ...; // construct using JsonFactory (can get one using ObjectMapper.getJsonFactory)   rootNode = mapper.readTree(jp);   // (most useful when binding sub-trees)

    

   • Constructing Tree Model instances from Scratch

   ObjectMapper mapper = new ObjectMapper();   JsonNode rootNode = mapper.createObjectNode(); // will be of type ObjectNode   ((ObjectNode) rootNode).put("name", "Tatu");   // ... and so forth

   • Writing Trees as JSON

   mapper.writeValue(dst, myBean); // dst can be File, OutputStream, Writer etc

   • Converting to Token Stream

   JsonParser jp = node.traverse();   // or:   JsonParser jp = mapper.treeAsTokens(node);

   • Converting to Java Objects

   MyBean bean = mapper.treeToValue(node, MyBean.class);

    

   • Data Binding
     • http://wiki.fasterxml.com/JacksonDataBinding
     • converts JSON to and from POJOs based either on property accessor conventions or annotations.
     • 두 가지 방법
       • Simple data binding means converting to and from Java Maps, Lists, Strings, Numbers, Booleans and nulls
       • Full data binding means converting to and from any Java bean type (as well as "simple" types mentioned above)
     • org.codehaus.jackson.map.ObjectMapper performs the marshalling and unmarshalling for both variants.
     • Serialization

   ObjectMapper mapper = new ObjectMapper(); mapper.writeValue(dst, myBean); // where 'dst' can be File, OutputStream or Writer

   • Full Data Binding

   MyBean value = mapper.readValue(src, MyBean.class); // 'src' can be File, InputStream, Reader, String

    

   • Generic Types: TypeReference Object를 사용한다.

   MyType<String> genValue = mapper.readValue(src, new TypeReference<MyType<String>>() { });

   • "Simple" Data Binding

   Object root = mapper.readValue(src, Object.class); Map<?,?> rootAsMap = mapper.readValue(src, Map.class);

    

   • 사용 가능한 Type

   JSON Type	Java Type
   object	LinkedHashMap<String,Object>
   array	ArrayList<Object>
   string	String
   number (no fraction)	Integer, Long or BigInteger (smallest applicable)
   number (fraction)	Double (configurable to use BigDecimal)
   true|false	Boolean
   null	null

    

   • Configuring
     • SerializationConfig.Feature
       • http://wiki.fasterxml.com/JacksonFeaturesSerialization
       • AUTO_DETECT_GETTERS, AUTO_DETECT_FIELDS, CAN_OVERRIDE_ACCESS_MODIFIERS,
       • USE_STATIC_TYPING, WRITE_DATES_AS_TIMESTAMPS, WRITE_DATES_AS_TIMESTAMPS,
       • USE_ANNOTATIONS, FAIL_ON_EMPTY_BEANS, DEFAULT_VIEW_INCLUSION
     • DeserializationConfig.Feature
       • http://wiki.fasterxml.com/JacksonFeaturesDeserialization
       • USE_ANNOTATIONS, AUTO_DETECT_SETTERS, AUTO_DETECT_CREATORS, AUTO_DETECT_FIELDS,
       • USE_GETTERS_AS_SETTERS, CAN_OVERRIDE_ACCESS_MODIFIERS, USE_BIG_DECIMAL_FOR_FLOATS,
       • USE_BIG_INTEGER_FOR_INTS, USE_BIG_INTEGER_FOR_INTS

    

• 정리하면,
• Streaming API는 성능이 가장 좋고, Data Binding은 가장 사용하기 편하며, Tree Model은 가장 유연하다.
• 특별한 사유가 아니라면 Data Binding을 쓰겠지?;;;

출처 : http://youreme.blog.me/110082668135