Elasticsearch-mapper 基于注解方式生成mapping(2.0以上)

Elasticsearch生成mapping的方式上有多种方式，我们可以把mapping做成配置文件，也可以用spring-data-elasticsearch基于注解生成。

在基于注解生成这种方式上spring-data的注解还是不错的，但是如果想深度定制化一些参数spring-data却是不支持的，比如针对分词的string类型字段的fielddata加载设置。

又如果项目中不想引入spring但又想使用基于注解方式生成mapping，这时spring-data就不行了，这里有另一种选择：elasticsearch-mapper。

elasticsearch-mapper支持绝大部分数据类型和相关参数的设置，使用是请参考官网对各种数据类型和相关参数：ES2.x官网mapping设置

下面是使用示例：

@Document(type = "book", _timestamp = true, _ttl = @TTL(enabled = true, _default = "5m"))  
public class Book {  
    /*ID,只能是Long或者String类型*/  
    @Id  
    private Long id;  
  
    /*数值类型*/  
    @Field(type = FieldType.Double, ignoreMalformed = true)  
    private Double price;  
  
    /*数值类型*/  
    @Field(type = FieldType.Integer)  
    private Integer pageCount;  
  
    /*未分词String型*/  
    @Field(type = FieldType.String, index = FieldIndex.not_analyzed)  
    private String isnNo;  
  
    /*bool型*/  
    @Field(type = FieldType.Boolean, nullValue = "false")  
    private Boolean isValid;  
  
    /*日期类型*/  
    @Field(type = FieldType.Date, format = DateFormat.basic_time_no_millis)  
    private Date publishDate;  
  
    /*分词String类型,并设置fielddata加载限制(当然也可不设置用默认)*/  
    @Field(  
            type = FieldType.String,  
            index = FieldIndex.analyzed,  
            analyzer = "ik_max_word",  
            searchAnalyzer = "ik_smart",  
            termVector = TermVector.with_positions_offsets,  
            fielddata = @Fielddata(  
                    format = FielddataFormat.paged_bytes,  
                    frequency = @FielddataFrequencyFilter(  
                            enable = true,  
                            min = 0.001,  
                            max = 1.2,  
                            minSegmentSize = 500  
                    ),  
                    loading = FielddataLoading.eager_global_ordinals  
            )  
  
    )  
    private String author;  
  
    /*multi field 类型(用于多字段搜索)*/  
    @MultiField(  
            mainField = @Field(type = FieldType.String, index = FieldIndex.analyzed, analyzer = "ik_max_word", searchAnalyzer = "ik_smart"),  
            otherFields = {  
                    @MultiNestedField(dotSuffix = "pinyin", nestedField = @Field(  
                            type = FieldType.String,  
                            index = FieldIndex.analyzed,  
                            analyzer = "lc_index",  
                            searchAnalyzer = "lc_search")  
                    ),  
                    @MultiNestedField(dotSuffix = "english", nestedField = @Field(  
                            type = FieldType.String,  
                            index = FieldIndex.analyzed,  
                            analyzer = "standard")  
                    )  
            }  
    )  
    private String title;  
  
    /*Completion Context Suggester配置(如果不配置CompletionContext则是Completion Suggester)*/  
    @CompletionField(analyzer = "ik", payloads = true, context = {  
            @CompletionContext(name = "bookType", type = CompletionContextType.category, defaultVal = {"algorithm"}),  
            @CompletionContext(name = "bookColor", type = CompletionContextType.category, defaultVal = {"red"})  
    })  
    private String suggestContextField;  
  
    /*二进制类型*/  
    @Field(type = FieldType.Binary)  
    private byte[] pdf;  
  
    /*内嵌类型*/  
    @NestedObject(clazz = SalesArea.class)  
    private SalesArea salesArea;  
      
}

[Reference]

[1] http://blog.csdn.net/chennanymy/article/details/52663589