ElasticSearch的JAVA客户端操作
一、java操作ES有两种客户端：
1、TransportClient：轻量级的Client，使用Netty线程池，Socket连接到ES集群。本身不加入到集群，只作为请求的处理。
2、Node Client：客户端节点本身也是ES节点，加入到集群，和其他ElasticSearch节点一样。频繁的开启和关闭这类Node Clients会在集群中产生“噪音”。
二、TransportClient的基本使用
1、创建Client
public ElasticSearchService(String ipAddress, int port) {
client = new TransportClient()
.addTransportAddress(new InetSocketTransportAddress(ipAddress,
port));
}
2、创建/删除Index和Type信息
// 创建索引
public void createIndex() {
client.admin().indices().create(new CreateIndexRequest(IndexName))
.actionGet();
}
// 清除所有索引
public void deleteIndex() {
IndicesExistsResponse indicesExistsResponse = client.admin().indices()
.exists(new IndicesExistsRequest(new String[] { IndexName }))
.actionGet();
if (indicesExistsResponse.isExists()) {
client.admin().indices().delete(new DeleteIndexRequest(IndexName))
.actionGet();
}
}
// 删除Index下的某个Type
public void deleteType(){
client.prepareDelete().setIndex(IndexName).setType(TypeName).execute().actionGet();
}
// 定义索引的映射类型
public void defineIndexTypeMapping() {
try {
XContentBuilder mapBuilder = XContentFactory.jsonBuilder();
mapBuilder.startObject()
.startObject(TypeName)
.startObject("properties")
.startObject(IDFieldName).field("type", "long").field("store", "yes").endObject()
.startObject(SeqNumFieldName).field("type", "long").field("store", "yes").endObject()
.startObject(IMSIFieldName).field("type", "string").field("index", "not_analyzed").field("store", "yes").endObject()
.startObject(IMEIFieldName).field("type", "string").field("index", "not_analyzed").field("store", "yes").endObject()
.startObject(DeviceIDFieldName).field("type", "string").field("index", "not_analyzed").field("store", "yes").endObject()
.startObject(OwnAreaFieldName).field("type", "string").field("index", "not_analyzed").field("store", "yes").endObject()
.startObject(TeleOperFieldName).field("type", "string").field("index", "not_analyzed").field("store", "yes").endObject()
.startObject(TimeFieldName).field("type", "date").field("store", "yes").endObject()
.endObject()
.endObject()
.endObject();
PutMappingRequest putMappingRequest = Requests
.putMappingRequest(IndexName).type(TypeName)
.source(mapBuilder);
client.admin().indices().putMapping(putMappingRequest).actionGet();
} catch (IOException e) {
log.error(e.toString());
}
}
这里自定义了某个Type的索引映射（Mapping），默认ES会自动处理数据类型的映射：针对整型映射为long，浮点数为double，字符串映射为string，时间为date，true或false为boolean。
注意：针对字符串，ES默认会做“analyzed”处理，即先做分词、去掉stop words等处理再index。如果你需要把一个字符串做为整体被索引到，需要把这个字段这样设置：field("index", "not_analyzed")。
详情参考：https://www.elastic.co/guide/en/elasticsearch/guide/current/mapping-intro.html
3、索引数据
// 批量索引数据
public void indexHotSpotDataList(List
if (dataList != null) {
int size = dataList.size();
if (size > 0) {
BulkRequestBuilder bulkRequest = client.prepareBulk();
for (int i = 0; i < size; ++i) {
Hotspotdata data = dataList.get(i);
String jsonSource = getIndexDataFromHotspotData(data);
if (jsonSource != null) {
bulkRequest.add(client
.prepareIndex(IndexName, TypeName,
data.getId().toString())
.setRefresh(true).setSource(jsonSource));
}
}
BulkResponse bulkResponse = bulkRequest.execute().actionGet();
if (bulkResponse.hasFailures()) {
Iterator
while (iter.hasNext()) {
BulkItemResponse itemResponse = iter.next();
if (itemResponse.isFailed()) {
log.error(itemResponse.getFailureMessage());
}
}
}
}
}
}
// 索引数据
public boolean indexHotspotData(Hotspotdata data) {
String jsonSource = getIndexDataFromHotspotData(data);
if (jsonSource != null) {
IndexRequestBuilder requestBuilder = client.prepareIndex(IndexName,
TypeName).setRefresh(true);
requestBuilder.setSource(jsonSource)
.execute().actionGet();
return true;
}
return false;
}
// 得到索引字符串
public String getIndexDataFromHotspotData(Hotspotdata data) {
String jsonString = null;
if (data != null) {
try {
XContentBuilder jsonBuilder = XContentFactory.jsonBuilder();
jsonBuilder.startObject().field(IDFieldName, data.getId())
.field(SeqNumFieldName, data.getSeqNum())
.field(IMSIFieldName, data.getImsi())
.field(IMEIFieldName, data.getImei())
.field(DeviceIDFieldName, data.getDeviceID())
.field(OwnAreaFieldName, data.getOwnArea())
.field(TeleOperFieldName, data.getTeleOper())
.field(TimeFieldName, data.getCollectTime())
.endObject();
jsonString = jsonBuilder.string();
} catch (IOException e) {
log.equals(e);
}
}
return jsonString;
}
ES支持批量和单个数据索引。
4、查询获取数据
// 获取少量数据100个
private List
List
SearchResponse searchResponse = client.prepareSearch(IndexName)
.setTypes(TypeName).setQuery(queryBuilder).setSize(100)
.execute().actionGet();
SearchHits searchHits = searchResponse.getHits();
for (SearchHit searchHit : searchHits) {
Integer id = (Integer) searchHit.getSource().get("id");
ids.add(id);
}
return ids;
}
// 获取大量数据
private List
List
// 一次获取100000数据
SearchResponse scrollResp = client.prepareSearch(IndexName)
.setSearchType(SearchType.SCAN).setScroll(new TimeValue(60000))
.setQuery(queryBuilder).setSize(100000).execute().actionGet();
while (true) {
for (SearchHit searchHit : scrollResp.getHits().getHits()) {
Integer id = (Integer) searchHit.getSource().get(IDFieldName);
ids.add(id);
}
scrollResp = client.prepareSearchScroll(scrollResp.getScrollId())
.setScroll(new TimeValue(600000)).execute().actionGet();
if (scrollResp.getHits().getHits().length == 0) {
break;
}
}
return ids;
}
这里的QueryBuilder是一个查询条件，ES支持分页查询获取数据，也可以一次性获取大量数据，需要使用Scroll Search。
5、聚合（Aggregation Facet）查询
// 得到某段时间内设备列表上每个设备的数据分布情况<设备ID，数量>
public Map
String endTime, List
Map
QueryBuilder deviceQueryBuilder = getDeviceQueryBuilder(deviceList);
QueryBuilder rangeBuilder = getDateRangeQueryBuilder(startTime, endTime);
QueryBuilder queryBuilder = QueryBuilders.boolQuery()
.must(deviceQueryBuilder).must(rangeBuilder);
TermsBuilder termsBuilder = AggregationBuilders.terms("DeviceIDAgg").size(Integer.MAX_VALUE)
.field(DeviceIDFieldName);
SearchResponse searchResponse = client.prepareSearch(IndexName)
.setQuery(queryBuilder).addAggregation(termsBuilder)
.execute().actionGet();
Terms terms = searchResponse.getAggregations().get("DeviceIDAgg");
if (terms != null) {
for (Terms.Bucket entry : terms.getBuckets()) {
resultsMap.put(entry.getKey(),
String.valueOf(entry.getDocCount()));
}
}
return resultsMap;
}
Aggregation查询可以查询类似统计分析这样的功能：如某个月的数据分布情况，某类数据的最大、最小、总和、平均值等。
详情参考：https://www.elastic.co/guide/en/elasticsearch/client/java-api/current/java-aggs.html
本文参考：http://www.cnblogs.com/luxiaoxun/p/4869509.html
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