大数据|Elasticsearch-mapper 基于注解方式生成mapping(2.0以上) java|git

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
【大数据|Elasticsearch-mapper 基于注解方式生成mapping(2.0以上)】git 地址：http://git.oschina.net/music_code_m/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 = "https://www.it610.com/article/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 = https://www.it610.com/article/@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; }

public class SalesArea { /*未分词String*/ @Field(type = FieldType.String, index = FieldIndex.not_analyzed) private String localtionName; /*分词String且禁用fielddata*/ @Field( type = FieldType.String, index = FieldIndex.analyzed, analyzer = "ik_max_word", fielddata = https://www.it610.com/article/@Fielddata(format = FielddataFormat.disabled) ) private String description; /*数值型*/ @Field(type = FieldType.Integer) private int openDays; }

转载于:https://www.cnblogs.com/chennanlcy/p/6591786.html