ElasticSearch升级记录 ver.1.4.5→ver.5.2.0

前言

项目中的es由ver.1.4.5升级至ver.5.2.0。

安装elasticSearch

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#下载
wget https://artifacts.elastic.co/downloads/elasticsearch/elasticsearch-5.2.0.tar.gz
# 解压
tar zxvf elasticsearch-5.5.0.tar.gz

修改elasticsearch.yml

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$ES_HOME/config/elasticsearch.yml

在这里不详细展开elasticsearch.yml的各个配置项,附上链接。
配置es外部链接

安装elasticsearch-head

lasticsearch-head是一个很好的可视化前端框架,方便用可视化界面对es进行调用。elasticsearch-head在Github的地址如下:https://github.com/mobz/elasticsearch-head
安装也不复杂,由于它是一个前端的工具,因此需要我们预先安装了node和npm,之后执行下面的步骤:

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git clone git://github.com/mobz/elasticsearch-head.git
cd elasticsearch-head
npm install

安装完成后,运行命令npm run start就行。

调整弃用api的兼容问题

1.setting

1.4.5的org.elasticsearch.common.settings.ImmutableSettings已经弃用,生成配置对象setting的方式改成:

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Settings settings = Settings.builder().put("cluster.name", clusterName).put("client.transport.sniff", true).build();

2.InetSocketTransportAddress

org.elasticsearch.common.transport.InetSocketTransportAddress#InetSocketTransportAddress(java.lang.String, int)方法已经弃用,注入集群地址的方式改成:

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clusterNodeAddressList.add(new InetSocketTransportAddress(InetAddress.getByName(host), 9300));

3.TransportClient

org.elasticsearch.client.transport.TransportClient#TransportClient(org.elasticsearch.common.settings.Settings),该构造方法已经弃用,生成TransportClient实例的方式改成:

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transportClient = new PreBuiltTransportClient(settings);

4.ClusterHealthStatus

org.elasticsearch.action.admin.cluster.health.ClusterHealthStatus类已经弃用,相同功能由org.elasticsearch.cluster.health.ClusterHealthStatus继承

5.ScriptSortBuilder调整

原版写法:

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Map<Object, Integer> optionalSortMap = manualSortMapBuilder.put("other", sortIndex + 1).build();

String script = "paramsMap.containsKey(doc[\"%s\"].value) ? paramsMap.get(doc[\"%s\"].value) : paramsMap.get('other')";

script = String.format(script, sort.getFieldName(), sort.getFieldName());

sortBuilder = SortBuilders.scriptSort(script, "number").param("paramsMap", optionalSortMap).order(SortOrder.ASC).missing(optionalSortMap.get("other"));

调整为:

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Map<Object, Integer> optionalSortMap = manualSortMapBuilder.put("other", sortIndex + 1).build();

String script = "paramsMap.containsKey(doc[\"%s\"].value) ? paramsMap.get(doc[\"%s\"].value) : paramsMap.get('other')";

script = String.format(script, sort.getFieldName(), sort.getFieldName());
Map<String, Object> params = Maps.newConcurrentMap();

params.put("paramsMap", optionalSortMap);

Script scriptObject = new Script(Script.DEFAULT_SCRIPT_TYPE, Script.DEFAULT_SCRIPT_LANG, script, params);

sortBuilder = SortBuilders.scriptSort(scriptObject, ScriptSortBuilder.ScriptSortType.fromString("number")).order(SortOrder.ASC);

6.FilterBuilder调整

org.elasticsearch.index.query.FilterBuilder类已经弃用,基本上从2.x版本开始,Filter就已经弃用了(不包括bool查询内的filter),所有FilterBuilder全都要用QueryBuilder的各种子类来调整:

1.org.elasticsearch.index.query.BoolFilterBuilder

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BoolFilterBuilder boolFilterBuilder = FilterBuilders.boolFilter();

调整为:

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BoolQueryBuilder boolFilterBuilder = new BoolQueryBuilder();

2.org.elasticsearch.index.query.NestedFilterBuilder

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filterBuilder = FilterBuilders.nestedFilter(param.getPath(), boolFilterBuilder);

调整为:

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filterBuilder = new NestedQueryBuilder(param.getPath(), boolFilterBuilder, ScoreMode.None);

3.org.elasticsearch.index.query.MissingFilterBuilder

5.x版本中,missing关键字已经弃用,其功能由其逆运算exist继承。

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MissingFilterBuilder missingFilterBuilder = FilterBuilders.missingFilter(paramName);
if (param.getNvlType() == QueryFieldType.EXISTS) {
filterBuilder = FilterBuilders.boolFilter().mustNot(missingFilterBuilder);
}
if (param.getNvlType() == QueryFieldType.MISSING) {
filterBuilder = FilterBuilders.boolFilter().must(missingFilterBuilder);
}

调整为:

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ExistsQueryBuilder existsQueryBuilder = new ExistsQueryBuilder(paramName);
if (param.getNvlType() == QueryFieldType.EXISTS) {
filterBuilder = new BoolQueryBuilder().must(existsQueryBuilder);
}
if (param.getNvlType() == QueryFieldType.MISSING) {
filterBuilder = new BoolQueryBuilder().mustNot(existsQueryBuilder);
}

4.org.elasticsearch.index.query.TermFilterBuilder

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filterBuilder = FilterBuilders.termFilter(paramName, param.getEqValue());

调整为:

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filterBuilder = new TermQueryBuilder(paramName, param.getEqValue());

5.org.elasticsearch.index.query.TermsFilterBuilder

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filterBuilder = FilterBuilders.inFilter(paramName, param.getInValues());

调整为:

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filterBuilder = new TermsQueryBuilder(paramName, param.getInValues());

6.org.elasticsearch.index.query.RangeFilterBuilder

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//gte
if (null != param.getGteValue()) {
filterBuilder = FilterBuilders.rangeFilter(paramName).gte(param.getGteValue());
}
//gt
if (null != param.getGtValue()) {
filterBuilder = FilterBuilders.rangeFilter(paramName).gt(param.getGtValue());
}
//lte
if (null != param.getLteValue()) {
filterBuilder = FilterBuilders.rangeFilter(paramName).lte(param.getLteValue());
}
//lt
if (null != param.getLtValue()) {
filterBuilder = FilterBuilders.rangeFilter(paramName).lt(param.getLtValue());
}

调整为:

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//gte
if (null != param.getGteValue()) {
filterBuilder = new RangeQueryBuilder(paramName).gte(param.getGteValue());
}
//gt
if (null != param.getGtValue()) {
filterBuilder = new RangeQueryBuilder(paramName).gt(param.getGtValue());
}
//lte
if (null != param.getLteValue()) {
filterBuilder = new RangeQueryBuilder(paramName).lte(param.getLteValue());
}
//lt
if (null != param.getLtValue()) {
filterBuilder = new RangeQueryBuilder(paramName).lt(param.getLtValue());
}

7.search_type=count

原来我们想要计算文档的需要用到search_type=count,现在5.0已经将该API移除,取而代之你只需将size置于0即可:

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GET /my_index/_search?search_type=count
{
"aggs": {
"my_terms": {
"terms": {
"field": "foo"
}
}
}
}

调整为:

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#5.0以后
GET /my_index/_search
{
"size": 0,
"aggs": {
"my_terms": {
"terms": {
"field": "foo"
}
}
}
}

8.RangeBuilder

org.elasticsearch.search.aggregations.bucket.range.RangeBuilder已经弃用,相应功能由org.elasticsearch.search.aggregations.bucket.range.RangeAggregationBuilder实现,直接替换即可。

9.TopHitsAggregationBuilder

org.elasticsearch.search.aggregations.metrics.tophits.TopHitsBuilder已经弃用,相应功能由org.elasticsearch.search.aggregations.metrics.tophits.TopHitsAggregationBuilder实现,直接替换即可。

10.FiltersAggregationBuilder

org.elasticsearch.search.aggregations.bucket.filters.FiltersAggregationBuilder构造报文调整

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FiltersAggregationBuilder filtersAggregationBuilder = AggregationBuilders.filters(aggregationField.getAggName());
LufaxSearchConditionBuilder tmpConditionBuilder = new LufaxSearchConditionBuilder();
for (String key : aggregationField.getFiltersMap().keySet()) {
LufaxFilterCondition tmpLufaxFilterCondition = aggregationField.getFiltersMap().get(key);
FilterBuilder tmpFilterBuilder = tmpConditionBuilder.constructFilterBuilder(tmpLufaxFilterCondition.getAndParams(),tmpLufaxFilterCondition.getOrParams(),tmpLufaxFilterCondition.getNotParams());
filtersAggregationBuilder.filter(key, tmpFilterBuilder);
}

调整成:

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List<FiltersAggregator.KeyedFilter> keyedFilters = new LinkedList<FiltersAggregator.KeyedFilter>();
LufaxSearchConditionBuilder tmpConditionBuilder = new LufaxSearchConditionBuilder();
for (String key : aggregationField.getFiltersMap().keySet()) {
LufaxFilterCondition tmpLufaxFilterCondition = aggregationField.getFiltersMap().get(key);
QueryBuilder tmpFilterBuilder = tmpConditionBuilder.constructFilterBuilder(tmpLufaxFilterCondition.getAndParams(),tmpLufaxFilterCondition.getOrParams(),tmpLufaxFilterCondition.getNotParams());
keyedFilters.add(new FiltersAggregator.KeyedFilter(key, tmpFilterBuilder));
}
FiltersAggregationBuilder filtersAggregationBuilder = AggregationBuilders.filters(aggregationField.getAggName(), keyedFilters.toArray(new FiltersAggregator.KeyedFilter[]{}));

11.HighlightBuilder;

org.elasticsearch.search.highlight.HighlightBuilder弃用,相关功能由org.elasticsearch.search.fetch.subphase.highlight.HighlightBuilder实现。

12.OptimizeRequestBuilder

org.elasticsearch.action.admin.indices.optimize.OptimizeRequestBuilder 已经弃用,聚合索引的功能由org.elasticsearch.action.admin.indices.forcemerge.ForceMergeRequestBuilder来实现。

13.IndicesAliasesRequestBuilder

1.newAddAliasAction

旧版删除了AliasAction类的newAddAliasAction方法,故而IndicesAliasesRequestBuilder添加AliasActions应该:

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requestBuilder.addAliasAction(AliasAction.newAddAliasAction(toIndex, indexAlias));

调整成

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requestBuilder.addAliasAction(IndicesAliasesRequest.AliasActions.add().index(toIndex).alias(indexAlias));

2.newRemoveAliasAction

旧版删除了AliasAction类的newRemoveAliasAction方法,故而IndicesAliasesRequestBuilder删除AliasActions应该:

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requestBuilder.addAliasAction(AliasAction.newRemoveAliasAction(fromIdx, indexAlias));

调整成

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requestBuilder.addAliasAction(IndicesAliasesRequest.AliasActions.remove().index(fromIdx).alias(indexAlias));

14.AbstractAggregationBuilder的子类变更

1.org.elasticsearch.search.aggregations.bucket.terms.TermsBuilder

org.elasticsearch.search.aggregations.bucket.terms.TermsBuilder更名为
org.elasticsearch.search.aggregations.bucket.terms.TermsAggregationBuilder

2.org.elasticsearch.search.aggregations.bucket.range.date.DateRangeBuilder

org.elasticsearch.search.aggregations.bucket.range.date.DateRangeBuilder更名为
org.elasticsearch.search.aggregations.bucket.range.date.DateRangeAggregationBuilder

3.org.elasticsearch.search.aggregations.metrics.tophits.TopHitsBuilder

org.elasticsearch.search.aggregations.metrics.tophits.TopHitsBuilder更名为
org.elasticsearch.search.aggregations.metrics.tophits.TopHitsAggregationBuilder

15.SearchHit类

org.elasticsearch.search.SearchHit#isSourceEmpty方法改为org.elasticsearch.search.SearchHit#hasSource方法,反向替换。

16.DeleteByQueryResponse

org.elasticsearch.action.deletebyquery.DeleteByQueryResponse已经弃用,

调整关键字等结构性问题

1. String数据类型弃用

在 ES2.x 版本字符串数据是没有 keyword 和 text 类型的,只有string类型,ES更新到5版本后,取消了 string 数据类型,代替它的是 keyword 和 text 数据类型。区别在于:

text类型定义的文本会被分析,在建立索引前会将这些文本进行分词,转化为词的组合,建立索引。允许 ES来检索这些词语。text 数据类型不能用来排序和聚合。

keyWord类型表示精确查找的文本,不需要进行分词。可以被用来检索过滤、排序和聚合。keyword 类型字段只能用本身来进行检索。

在没有显性定义时,es默认为“text”类型。

2. multi_field关键字弃用

相关mapping方式改为:

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#对需要设置的字段,在'type'属性后增加"fields": 
#其中的"raw"为自定义的名称,想象它是city的一个分身。
PUT /my_index
{
"mappings": {
"my_type": {
"properties": {
"city": {
"type": "text",
"fields": {
"raw": {
"type": "keyword"
}
}
}
}
}
}
}

查询raw字段时,使用city.raw表示

3. analyzer

1.改版后,设置了search_analyzer的情况下,analyzer也要设置,否则会报:

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analyzer on field [name] must be set when search_analyzer is set。

2.改版后,index_analyzer设置被弃用,如果设置,会报

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MapperParsingException[Mapping definition for [fields] has unsupported parameters:  [index_analyzer : ik_max_word]];

这里扩展一下,在原来的版本中,index_analyzer负责建立索引时的分词器定义,search_analyzer负责搜索时的分词器定义。

索引期间查找解析器的完整顺序是这样的:

  • 定义在字段映射中的index_analyzer
  • 定义在字段映射中的analyzer
  • 定义在文档_analyzer字段中的解析器
  • type的默认index_analyzer
  • type的默认analyzer
  • 索引设置中default_index对应的解析器
  • 索引设置中default对应的解析器
  • 节点上default_index对应的解析器
  • 节点上default对应的解析器
  • standard解析器

而查询期间的完整顺序则是:

  • 直接定义在查询中的analyzer
  • 定义在字段映射中的search_analyzer
  • 定义在字段映射中的analyzer
  • type的默认search_analyzer
  • type的默认analyzer
  • 索引设置中的default_search对应的解析器
  • 索引设置中的default对应的解析器
  • 节点上default_search对应的解析器
  • 节点上default对应的解析器
  • standard解析器

现在新版删除index_analyzer,具体功能由analyzer关键字承担,analyzer关键字生效与index时和search时(除非search_analyzer已经被显性定义)。

3. _timestamp在2.0弃用

_timestamp官方建议自定义一个字段,自己赋值用来表示时间戳。

4. 嵌套字段排序时字段名称调整

对于如下的数据:

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PUT /my_index/blogpost/2
{
"title": "Investment secrets",
"body": "What they don't tell you ...",
"tags": [ "shares", "equities" ],
"comments": [
{
"name": "Mary Brown",
"comment": "Lies, lies, lies",
"age": 42,
"stars": 1,
"date": "2014-10-18"
},
{
"name": "John Smith",
"comment": "You're making it up!",
"age": 28,
"stars": 2,
"date": "2014-10-16"
}
]
}

老版本中,对stars字段进行排序时,直接可以

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"sort" : [
{
"stars" : {
"order" : "desc",
"mode" : "min",
"nested_path" : "comments"
}
]

但在新版中,上述报文会报

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No mapping found for [stars] in order to sort on

需要改成:

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"sort" : [
{
"comments.stars" : {
"order" : "desc",
"mode" : "min"
}
]

5. _script脚本参数名变更

老版中,_script可以这样定义

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"sort" : [
{
"_script" : {
"script" : {
"inline" : "paramsMap.containsKey(doc[\"id\"].value) ? params.paramsMap.get(doc[\"id\"].value) : params.paramsMap.get('other')",
"lang" : "painless",
"params" : {
"paramsMap" : {
"1" : 1,
"2" : 1,
"3" : 2,
"other" : 3
}
}
},
"type" : "number",
"order" : "asc"
}
}
]

新版中,对于params的参数paramsMap必须用params.paramsMap

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"sort" : [
{
"_script" : {
"script" : {
"inline" : "params.paramsMap.containsKey(doc[\"productCategory\"].value) ? params.paramsMap.get(doc[\"productCategory\"].value) : params.paramsMap.get('other')",
"lang" : "painless",
"params" : {
"paramsMap" : {
"901" : 1,
"902" : 1,
"701" : 2,
"other" : 3
}
}
},
"type" : "number",
"order" : "asc"
}
}
]

注意:es 5.2.0默认禁用了动态语言,所以lang为painless之外的语言,默认情况下会报

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ScriptException[scripts of type [inline], operation [update] and lang [groovy] are disabled];

需要在yml文件中添加配置(如groovy):

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script.engine.groovy.inline:true 
script.engine.groovy.stored.search:true
script.engine.groovy.stored.aggs:true

6 .获取特定字段返回

在旧版本中,获取特定文档特定字段返回,可以使用stored_fields:

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{
"from" : 0,
"size" : 1,
"query" : {},
"stored_fields" : "timestamp",
"sort" : [
{
"timestamp" : {
"order" : "desc"
}
}
]
}

新版本中,引入了更为强大的_source过滤器

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{
"from" : 0,
"size" : 1,
"query" : {},
"_source" : "timestamp",
"sort" : [
{
"timestamp" : {
"order" : "desc"
}
}
]
}

或者

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{
"from" : 0,
"size" : 1,
"query" : {},
"_source" : {
"includes" : [ "timestamp" ],
"excludes" : [ "" ]
},
"sort" : [
{
"timestamp" : {
"order" : "desc"
}
}
]
}

java的api主要调用SearchRequestBuilder的setFetchSource方法

7. date字段的format定义

改版后,date字段最好再mapping时定义好format信息,以防止在请求前后因为格式转换问题报错:

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ElasticsearchParseException[failed to parse date field [Thu Jun 18 00:00:00 CST 2015] with format [strict_date_optional_time||epoch_millis]]; nested: IllegalArgumentException[Parse failure at index [0] of [Thu Jun 18 00:00:00 CST 2015]]; }

[strict_date_optional_time||epoch_millis]是es默认的date字段解析格式

8. UncategorizedExecutionException

改版前,transport client发送数据之前将java代码中的字段序列化成了json然后进行传输和请求,而在5.x以后,es改用使用的内部的transport protocol,这时候,如果定义一个比如bigDecimal类型,es不支持bigDecimal,数据类型不匹配会抛错误。

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UncategorizedExecutionException[Failed execution]; nested: IOException[can not write type [class java.math.BigDecimal]];

es支持的格式如下

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static {
Map<Class<?>, Writer> writers = new HashMap<>();
writers.put(String.class, (o, v) -> {
o.writeByte((byte) 0);
o.writeString((String) v);
});
writers.put(Integer.class, (o, v) -> {
o.writeByte((byte) 1);
o.writeInt((Integer) v);
});
writers.put(Long.class, (o, v) -> {
o.writeByte((byte) 2);
o.writeLong((Long) v);
});
writers.put(Float.class, (o, v) -> {
o.writeByte((byte) 3);
o.writeFloat((float) v);
});
writers.put(Double.class, (o, v) -> {
o.writeByte((byte) 4);
o.writeDouble((double) v);
});
writers.put(Boolean.class, (o, v) -> {
o.writeByte((byte) 5);
o.writeBoolean((boolean) v);
});
writers.put(byte[].class, (o, v) -> {
o.writeByte((byte) 6);
final byte[] bytes = (byte[]) v;
o.writeVInt(bytes.length);
o.writeBytes(bytes);
});
writers.put(List.class, (o, v) -> {
o.writeByte((byte) 7);
final List list = (List) v;
o.writeVInt(list.size());
for (Object item : list) {
o.writeGenericValue(item);
}
});
writers.put(Object[].class, (o, v) -> {
o.writeByte((byte) 8);
final Object[] list = (Object[]) v;
o.writeVInt(list.length);
for (Object item : list) {
o.writeGenericValue(item);
}
});
writers.put(Map.class, (o, v) -> {
if (v instanceof LinkedHashMap) {
o.writeByte((byte) 9);
} else {
o.writeByte((byte) 10);
}
@SuppressWarnings("unchecked")
final Map<String, Object> map = (Map<String, Object>) v;
o.writeVInt(map.size());
for (Map.Entry<String, Object> entry : map.entrySet()) {
o.writeString(entry.getKey());
o.writeGenericValue(entry.getValue());
}
});
writers.put(Byte.class, (o, v) -> {
o.writeByte((byte) 11);
o.writeByte((Byte) v);
});
writers.put(Date.class, (o, v) -> {
o.writeByte((byte) 12);
o.writeLong(((Date) v).getTime());
});
writers.put(ReadableInstant.class, (o, v) -> {
o.writeByte((byte) 13);
final ReadableInstant instant = (ReadableInstant) v;
o.writeString(instant.getZone().getID());
o.writeLong(instant.getMillis());
});
writers.put(BytesReference.class, (o, v) -> {
o.writeByte((byte) 14);
o.writeBytesReference((BytesReference) v);
});
writers.put(Text.class, (o, v) -> {
o.writeByte((byte) 15);
o.writeText((Text) v);
});
writers.put(Short.class, (o, v) -> {
o.writeByte((byte) 16);
o.writeShort((Short) v);
});
writers.put(int[].class, (o, v) -> {
o.writeByte((byte) 17);
o.writeIntArray((int[]) v);
});
writers.put(long[].class, (o, v) -> {
o.writeByte((byte) 18);
o.writeLongArray((long[]) v);
});
writers.put(float[].class, (o, v) -> {
o.writeByte((byte) 19);
o.writeFloatArray((float[]) v);
});
writers.put(double[].class, (o, v) -> {
o.writeByte((byte) 20);
o.writeDoubleArray((double[]) v);
});
writers.put(BytesRef.class, (o, v) -> {
o.writeByte((byte) 21);
o.writeBytesRef((BytesRef) v);
});
writers.put(GeoPoint.class, (o, v) -> {
o.writeByte((byte) 22);
o.writeGeoPoint((GeoPoint) v);
});
WRITERS = Collections.unmodifiableMap(writers);
}
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