/×××××××××××××××××××××××××××××××××××××××××/
Author：xxx0624
HomePage：http://www.cnblogs.com/xxx0624/
/×××××××××××××××××××××××××××××××××××××××××/
原英文文档:http://www.elasticsearch.org/guide/en/elasticsearch/client/java-api/index.html (各个版本的api)
这里有一个简单的使用search的官方文档：http://www.elastic.co/guide/en/elasticsearch/client/java-api/current/search.html#java-search-template
这是另外一个作者有关es api的翻译：http://blog.csdn.net/woshiyexinjie/article/details/41088705
Search部分:
查询有两种方法:query Java API和filter Java API
首先看一个例子:
import org.elasticsearch.action.search.SearchResponse;
import org.elasticsearch.action.search.SearchType;
import org.elasticsearch.index.query.FilterBuilders.*;
import org.elasticsearch.index.query.QueryBuilders.*;SearchResponse response = client.prepareSearch("index1", "index2")
//设置要查询的索引(index)
.setTypes("type1", "type2")
//设置type, 这个在建立索引的时候同时设置了, 或者可以使用head工具查看
.setSearchType(SearchType.DFS_QUERY_THEN_FETCH)
.setQuery(QueryBuilders.termQuery("multi", "test"))
// Query 查询之一. 对于QueryBuilders接下来会解释. 在这里"multi"是要查询的field,"test"是要查询的内容
.setFilter(FilterBuilders.rangeFilter("age").from().to())
// Filter 查询之二, FilterBuilders接下来会解释. 在这里"age"是要查询的field, 后面的数字是查询的条件范围
.setFrom().setSize().setExplain(true)
//0-60 表示显示数量
.execute()
.actionGet();
提示:以上所有参数都是可选的.
最小的查询如下所示:
// MatchAll on the whole cluster with all default options
SearchResponse response = client.prepareSearch().execute().actionGet();
为了使用QueryBuilders必须先import下面的类:
import org.elasticsearch.index.query.QueryBuilders.*;
第一种:Match Query (链接内有详细解释)
QueryBuilder qb = QueryBuilders.matchQuery("name", "kimchy elasticsearch");
//name是field,kimchy elasticsearch是要查询的字符串
第二种:MultiMatch Query (链接内有详细解释)
QueryBuilder qb = QueryBuilders.multiMatchQuery(
"kimchy elasticsearch", // Text you are looking for
//kimchy elasticsearch是要查询的字符串
"user", "message" // Fields you query on
//user 和 message都是field
);
第三种: Boolean Query (链接内有详细解释)
QueryBuilder qb = QueryBuilders
.boolQuery()
.must(termQuery("content", "test1"))
.must(termQuery("content", "test4"))
.mustNot(termQuery("content", "test2"))
.should(termQuery("content", "test3"));
//content为field,test为查询内容.
//其中must表示必须满足,mustNot表示必须不满足,should表示可有可无
如果bool查询语句中不存在must,则必须至少有一个should查询,同时可以通过minimum_should_match参数来设置至少需要满足的should个数.
略…
QueryBuilders.idsQuery().ids("1", "2");
//通过id来查询
略…
略…
略…
略…
QueryBuilders.fieldQuery("name", "+kimchy -dadoonet");// Note that you can write the same query using queryString query.
QueryBuilders.queryString("+kimchy -dadoonet").field("name");
//+表示必须有的 -表示一定没有的 name表示查询的filed
Fuzzy Like This Query * Fuzzy Like This Field Query
略….不懂…..
QueryBuilder qb = QueryBuilders.fuzzyQuery("name", "kimzhy");
//根据提供的字符串作为前缀进行查询
略….不懂…..
QueryBuilder qb = QueryBuilders.matchAllQuery();
//显示所有的记录
* More Like This Query * More Like This Field Query
略…不懂……
QueryBuilders.prefixQuery("brand", "heine");
//brand是field, heine是前缀查询字符串
QueryBuilder qb = QueryBuilders.queryString("+kimchy -elasticsearch");
略….不懂…..
QueryBuilder qb = QueryBuilders
.rangeQuery("price")
.from(5)
.to(10)
.includeLower(true)
.includeUpper(false);
//price是field, 数字代表范围.除了from to还有lt gt等等...
* Span First Query * Span Near Query * Span Not Query * Span Or Query * Span Term Quer// Span First
QueryBuilders.spanFirstQuery(
QueryBuilders.spanTermQuery("user", "kimchy"), // Query
3 // Max End position
);
//只匹配在Field开头出现的, 数字表示从开头起的几个单词内查询, 则此查询意思是:user中的开头3个单词内,kimchy是否能查询到// Span Near
QueryBuilders.spanNearQuery()
.clause(QueryBuilders.spanTermQuery("field","value1")) // Span Term Queries
.clause(QueryBuilders.spanTermQuery("field","value2"))
.clause(QueryBuilders.spanTermQuery("field","value3"))
.slop(12) // Slop factor
.inOrder(false)
.collectPayloads(false);
//匹配距离相近的, inOrder表示:true表示按照value1/2/3的顺序来计算距离(两个单词中间夹一个单词 距离为1). 举例: a b c d. {a,b,c}中a,c的距离为1.
//则此查询的意思是:在field中,如果value1/2/3的距离是在12以内的,那么可以查询到.反之不能.// Span Not
QueryBuilders.spanNotQuery()
.include(QueryBuilders.spanTermQuery("field","value1"))
.exclude(QueryBuilders.spanTermQuery("field","value2"));
//匹配不重叠的,即除那些两个SpanQuery相互重叠的结果
//例如有两个Document：”the quick brown fox jump over a lazy dog”和”the quick red fox jumps over the sleepy cat”
//SpanNearQuery quick_fox =new SpanNearQuery(new SpanQuery[]{quick, fox}, 1, true); //基础的SpanQuery，默认匹配2个Document
//匹配的这两个结果的中间重叠部分为：red/brown
//SpanNotQuery quick_fox_dog = new SpanNotQuery(quick_fox, dog);//因为dog不是red或者brown，所以仍为两个
//SpanNotQuery no_quick_red_fox = new SpanNotQuery(quick_fox, red); //现在只剩下brown那个doc了
//这种Query经常用于连接的时候。// Span Or
QueryBuilders.spanOrQuery()
.clause(QueryBuilders.spanTermQuery("field","value1"))
.clause(QueryBuilders.spanTermQuery("field","value2"))
.clause(QueryBuilders.spanTermQuery("field","value3"));
//SpanQuery的合集// Span Term
QueryBuilders.spanTermQuery("user","kimchy");//该部分详见:http://www.coder4.com/archives/774
略…
略…
略…
略…
略…
略…
略…
略…
附上一个自己写的小型Test, 简单易懂.
import java.io.IOException; import org.elasticsearch.action.index.IndexResponse;
import org.elasticsearch.action.search.SearchResponse;
import org.elasticsearch.action.search.SearchType;
import org.elasticsearch.client.Client;
import org.elasticsearch.client.transport.TransportClient;
import org.elasticsearch.common.transport.InetSocketTransportAddress;
import org.elasticsearch.common.xcontent.XContentBuilder;
import org.elasticsearch.common.xcontent.XContentFactory;
import org.elasticsearch.index.query.FilterBuilders;
import org.elasticsearch.index.query.QueryBuilder;
import org.elasticsearch.index.query.QueryBuilders;
import org.elasticsearch.search.SearchHits; import user.User; public class First_ES_Test { private Client client; public void init()
{
//ip可以在http://localhost:9200/_plugin/head/中自行查询
client = new TransportClient().addTransportAddress(new InetSocketTransportAddress("192.168.1.103", 9300));
} public void close()
{
client.close();
} /*
* create index
**/
public void createIndex() {
for (int i = 0; i < 1000; i++) {
User user = new User();
user.setId(new Long(i));
user.setName("xxx0624 " + i);
user.setAge(i % 100);
System.out.println("ok:"+i);
client.prepareIndex("users", "user").setSource(generateJson(user))
.execute().actionGet();
}
} /*
* 转换成json对象
*
* @param user
* @return json(String)
**/
private String generateJson(User user) {
String json = "";
try {
XContentBuilder contentBuilder = XContentFactory.jsonBuilder()
.startObject();
contentBuilder.field("id", user.getId() + "");
contentBuilder.field("name", user.getName());
contentBuilder.field("age", user.getAge() + "");
json = contentBuilder.endObject().string();
} catch (IOException e) {
e.printStackTrace();
}
return json;
} public void search() {
QueryBuilder qb = QueryBuilders
.boolQuery()
.must(QueryBuilders.termQuery("age", "0"))
.should(QueryBuilders.termQuery("id", "0"))
//.mustNot(QueryBuilders.termQuery("content", "test2"))
//.should(QueryBuilders.termQuery("content", "test3"))
; SearchResponse response = client.prepareSearch("users")
.setTypes("user")
.setSearchType(SearchType.DFS_QUERY_THEN_FETCH)
.setQuery(qb) // Query
//.setFilter(FilterBuilders.rangeFilter("age").from(0).to(100)) // Filter
.setFrom(0).setSize(100).setExplain(true)
.execute().actionGet();
SearchHits hits = response.getHits();
System.out.println(hits.getTotalHits());
for (int i = 0; i < hits.getHits().length; i++) {
System.out.println(hits.getHits()[i].getSourceAsString());
}
} public static void main(String[] args) { First_ES_Test client = new First_ES_Test();
client.init();
client.createIndex();
client.search();
client.close(); } public void print(String output)
{
System.out.print(output);
}
public void println(String output)
{
System.out.println(output);
} }
待续…
