solr特点三: defType(查询权重排序)

Solr的defType有dismax/edismax两种，这两种的区别，可参见：http://blog.csdn.net/duck_genuine/article/details/8060026

edismax支持boost函数与score相乘作为，而dismax只能使用bf作用效果是相加，所以在处理多个维度排序时，score其实也应该是其中一个维度，用相加的方式处理调整麻烦。

而dismax的实现代码逻辑比较简单，看起来比较易理解，edismax是它的加强版，其实是改变了不少。。比如在以下：

先看看dismax的解析主要实现思路：

首先取出搜索字段名qf

将最终解析成一个BooleanQuery

先解析主mainQuery:

用户主要是搜索串的解析
altQuery解析处理，看是否使用用户定义的后备搜索串
PhraseQuery解析组装

再解析bq查询，主要是额外加分的查询，不会影响搜索结果数，只会影响排序

再则是bf解析，函数搜索最后会以加的方式作用于文档评分

看主要代码更清晰：

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@Override
public Query parse() throws ParseException {
SolrParams solrParams = SolrParams.wrapDefaults(localParams, params);
queryFields = SolrPluginUtils.parseFieldBoosts(solrParams.getParams(DisMaxParams.QF));
if (0 == queryFields.size()) {
queryFields.put(req.getSchema().getDefaultSearchFieldName(), 1.0f);
}
/* the main query we will execute. we disable the coord because
* this query is an artificial construct
*/
BooleanQuery query = new BooleanQuery(true);
boolean notBlank = addMainQuery(query, solrParams);
if (!notBlank)
return null;
addBoostQuery(query, solrParams);
addBoostFunctions(query, solrParams);
return query;
}

edismax的主要实现思路跟dismax差不多，以下是一些主要差别之处：

edismax解析含有+,OR,NOT,-语法时，就会忽略掉使用MM。

以下是主要代码实现：

统计搜索串中+,OR ,NOT,-语法元个数

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// defer escaping and only do if lucene parsing fails, or we need phrases
// parsing fails. Need to sloppy phrase queries anyway though.
List<Clause> clauses = null;
int numPluses = 0;
int numMinuses = 0;
int numOR = 0;
int numNOT = 0;
clauses = splitIntoClauses(userQuery, false);
for (Clause clause : clauses) {
if (clause.must == '+') numPluses++;
if (clause.must == '-') numMinuses++;
if (clause.isBareWord()) {
String s = clause.val;
if ("OR".equals(s)) {
numOR++;
} else if ("NOT".equals(s)) {
numNOT++;
} else if (lowercaseOperators && "or".equals(s)) {
numOR++;
}
}
}

/////当搜索串里包含有+,OR ,NOT,-这四种时候，mm就会失效

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boolean doMinMatched = (numOR + numNOT + numPluses + numMinuses) == 0;
(parsedUserQuery != null && doMinMatched) {
String minShouldMatch = solrParams.get(DisMaxParams.MM, "100%");
if (parsedUserQuery instanceof BooleanQuery) {
SolrPluginUtils.setMinShouldMatch((BooleanQuery)parsedUserQuery, minShouldMatch);
}
}

短语查询，先找出普通的查询，原来就是短语查询的、或者属于“OR”,“AND”，“NOT”，’TO‘类型的都不要。由于 edismax支持解析符合lucene语法的搜索串，所以不像dismax那样，只需要简单的将搜索串去掉\“,然后加个“”括起来就行

// find non-field clauses

List<Clause>normalClauses =new ArrayList<Clause>(clauses.size());

for (Clauseclause :clauses) {

if (clause.field !=null ||clause.isPhrase)continue;

// check for keywords "AND,OR,TO"

if (clause.isBareWord()) {

String s =clause.val.toString();

// avoid putting explict operators in the phrase query

if ("OR".equals(s) ||"AND".equals(s) ||"NOT".equals(s) || "TO".equals(s))continue;

}

normalClauses.add(clause);

}

// full phrase...

addShingledPhraseQueries(query, normalClauses, phraseFields, 0,

tiebreaker,pslop);

// shingles...

addShingledPhraseQueries(query, normalClauses, phraseFields2, 2,

tiebreaker,pslop);

addShingledPhraseQueries(query, normalClauses, phraseFields3, 3,

tiebreaker,pslop);

////下面是dismax获取短语查询的作法：

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protected Query getPhraseQuery(String userQuery, SolrPluginUtils.DisjunctionMaxQueryParser pp) throws ParseException {
String userPhraseQuery = userQuery.replace("\"", "");
return pp.parse("\"" + userPhraseQuery + "\"");
}

下面是edismax的作法：

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private void addShingledPhraseQueries(final BooleanQuery mainQuery,
final List<Clause> clauses,
final Map<String,Float> fields,
int shingleSize,
final float tiebreaker,
final int slop)
throws ParseException {
if (null == fields || fields.isEmpty() ||
null == clauses || clauses.size() <= shingleSize )
return;
if (0 == shingleSize) shingleSize = clauses.size()；
final int goat = shingleSize-1; // :TODO: better name for var?
StringBuilder userPhraseQuery = new StringBuilder();
for (int i=0; i < clauses.size() - goat; i++) {
userPhraseQuery.append('"');
for (int j=0; j <= goat; j++) {
userPhraseQuery.append(clauses.get(i + j).val);
userPhraseQuery.append(' ');
}
userPhraseQuery.append('"');
userPhraseQuery.append(' ');
}
ExtendedSolrQueryParser pp =
new ExtendedSolrQueryParser(this, IMPOSSIBLE_FIELD_NAME);
pp.addAlias(IMPOSSIBLE_FIELD_NAME, tiebreaker, fields);
pp.setPhraseSlop(slop);
pp.setRemoveStopFilter(true); // remove stop filter and keep stopwords
pp.makeDismax = true;
pp.minClauseSize = 2;
Query phrase = pp.parse(userPhraseQuery.toString());
if (phrase != null) {
mainQuery.add(phrase, BooleanClause.Occur.SHOULD);
}
}

edismax技术另一个重要的boost查询，

boost查询也是不会影响搜索结果数，但是影响排序，主要作用是将最后得分以相乘的方式作用于score,函数的解析跟bf差不多。

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//
// create a boosted query (scores multiplied by boosts)
//
Query topQuery = query;
multBoosts = solrParams.getParams("boost");
if (multBoosts!=null && multBoosts.length>0) {
List<ValueSource> boosts = new ArrayList<ValueSource>();
for (String boostStr : multBoosts) {
if (boostStr==null || boostStr.length()==0) continue;
Query boost = subQuery(boostStr, FunctionQParserPlugin.NAME).getQuery();
ValueSource vs;
if (boost instanceof FunctionQuery) {
vs = ((FunctionQuery)boost).getValueSource();
} else {
vs = new QueryValueSource(boost, 1.0f);
}
boosts.add(vs);
}
if (boosts.size()>1) {
ValueSource prod = new ProductFloatFunction(boosts.toArray(new ValueSource[boosts.size()]));
topQuery = new BoostedQuery(query, prod);
} else if (boosts.size() == 1) {
topQuery = new BoostedQuery(query, boosts.get(0));
}
}

可以看到最后不是一个BooleanQuery，而是一个BoostedQuery。

它就是简单处理子查询的分值再与函数查询的分值相乘返回：主要的score方法如下：

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public float score() throws IOException {
float score = qWeight * scorer.score() * vals.floatVal(scorer.docID());
return score>Float.NEGATIVE_INFINITY ? score : -Float.MAX_VALUE;
}

下面示例用于演示如下场景：

有一网站，在用户查询的结果中，需要按这样排序：

VIP的付费信息需要排在免费信息的前头
点击率越高越靠前
发布时间越晚的越靠前

这样的查询排序使用普通的查询结果的Order by是做不到的，必需使用solr的defType。

做法：

1、先看schema.xml的定义：

<?xml version="1.0" ?>
<schema name="sample5" version="1.1">

    <fieldtype name="string"  class="solr.StrField" sortMissingLast="true" omitNorms="true"/>
    <fieldType name="long" class="solr.TrieLongField" precisionStep="0" positionIncrementGap="0"/>
    <fieldType name="tdate" class="solr.TrieDateField" precisionStep="6" positionIncrementGap="0"/>
    <fieldType name="int" class="solr.TrieIntField" precisionStep="0" positionIncrementGap="0"/>
    <fieldType name="float" class="solr.TrieFloatField" precisionStep="0" positionIncrementGap="0"/>
    <fieldType name="double" class="solr.TrieDoubleField" precisionStep="0" positionIncrementGap="0"/>
    <fieldType name="boolean" class="solr.BoolField" sortMissingLast="true"/>
    <fieldtype name="binary" class="solr.BinaryField"/>
    <fieldType name="text_cn" class="solr.TextField">
        <analyzer type="index" class="org.wltea.analyzer.lucene.IKAnalyzer" useSmart="false" />
        <analyzer type="query" class="org.wltea.analyzer.lucene.IKAnalyzer" useSmart="true" />
        <analyzer>
            <tokenizer class="solr.KeywordTokenizerFactory"/>
            <filter class="solr.LowerCaseFilterFactory" ignoreCase="true"/>
        </analyzer>
    </fieldType>
    
    <!-- general -->
    <fields>
        <field name="id" type="long" indexed="true" stored="true" multiValued="false" required="true"/>
        <field name="subject" type="text_cn" indexed="true" stored="true" />
        <field name="content" type="text_cn" indexed="true" stored="true" />
        <field name="regionId" type="int" indexed="true" stored="true" />
        <field name="region" type="text_cn" indexed="true" stored="true" />
        <field name="categoryId" type="int" indexed="true" stored="true" />
        <field name="category" type="text_cn" indexed="true" stored="true" />
        <field name="price" type="float" indexed="true" stored="true" />
        <field name="createTime" type="tdate" indexed="true" stored="true" />
        <field name="point" type="long" indexed="true" stored="true" />
        <field name="vip" type="boolean" indexed="true" stored="true" />
        <field name="_version_" type="long" indexed="true" stored="true"/>
        <field name="searchText" type="text_cn" indexed="true" stored="false" multiValued="true" />
    </fields>
    
    <copyField source="subject" dest="searchText" />
    <copyField source="content" dest="searchText" />
    <copyField source="region" dest="searchText" />
    <copyField source="category" dest="searchText" />
    
     <!-- field to use to determine and enforce document uniqueness. -->
     <uniqueKey>id</uniqueKey>

     <!-- field for the QueryParser to use when an explicit fieldname is absent -->
     <defaultSearchField>searchText</defaultSearchField>

     <!-- SolrQueryParser configuration: defaultOperator="AND|OR" -->
     <solrQueryParser defaultOperator="AND"/>
</schema>

说明：

a)里头定义了一个copyField：searchText，此字段为：subject+content+region+category，并把这个字段设置为默认查询字段。意思是查询时，默认查询四个字段的内容。

b)把solrQueryParser设置为AND，事实上，大多情况下，我们是习惯使用AND为条件查询，而非OR

c)text_cn字段类型中的：useSmart

        <analyzer type="index" class="org.wltea.analyzer.lucene.IKAnalyzer" useSmart="false" />
        <analyzer type="query" class="org.wltea.analyzer.lucene.IKAnalyzer" useSmart="true" />

意思是：useSmart =true ，分词器使用智能切分策略， =false则使用细粒度切分。详细，可下载IK分词器的源码看看。

2、加入一个查询Handler到solrconfig.xml的<config/>当中：

    <requestHandler name="/browse" class="solr.SearchHandler" default="true" >
        <lst name="defaults">
            <str name="defType">edismax</str>
            <str name="bf">
                sum(linear(vip,1000,0),linear(sqrt(log(linear(point,1,2))),100,0),sqrt(log(ms(createTime))))
            </str>
            <!--<str name="pf">
            searchText
            </str>
            <str name="qf">
            subject^1 content^0.8
            </str>-->
        </lst>
    </requestHandler>

说明：

a)上面的default="true"意思为设置为默认的查询handler（记得把原standard中的default="true"删除掉）

b)见已经被注释的这段：

            <!--<str name="pf">
            searchText
            </str>
            <str name="qf">
            subject^1 content^0.8
            </str>-->

这是简单的不使用bf的排序加权方式，可以用于应付简单的排序，具体pf/qf的使用，可以上网上搜搜应用。这里演示的功能相对“复杂”，不适用它。

c)见这句公式：

sum(linear(vip,1000,0),linear(sqrt(log(linear(point,1,2))),100,0),sqrt(log(ms(createTime))))

公式中的函数定义和意思，可以参考：

官方文档：

http://wiki.apache.org/solr/FunctionQuery

中文说明：

http://mxsfengg.iteye.com/blog/352191

这里的函数意思是：

如果是vip信息=值+1000，非vip信息=值+0
点击率(point)的值范围为：50~500之间
发布时间(createTime)值范围为：50以内

以上三个值相加得出最统权重分从高到低排序

3、Java bean:

package com.my.entity;

import java.util.Date;

import org.apache.solr.client.solrj.beans.Field;

public class Item {
    @Field
    private long id;
    @Field
    private String subject;
    @Field
    private String content;
    @Field
    private int regionId;
    @Field
    private int categoryId;
    @Field
    private float price;
    @Field
    private Date createTime;
    @Field
    private long point;
    @Field
    private boolean vip;
    
    public long getId() {
        return id;
    }
    public void setId(long id) {
        this.id = id;
    }
    public String getSubject() {
        return subject;
    }
    public void setSubject(String subject) {
        this.subject = subject;
    }
    public String getContent() {
        return content;
    }
    public void setContent(String content) {
        this.content = content;
    }
    public int getRegionId() {
        return regionId;
    }
    public void setRegionId(int regionId) {
        this.regionId = regionId;
    }
    public int getCategoryId() {
        return categoryId;
    }
    public void setCategoryId(int categoryId) {
        this.categoryId = categoryId;
    }
    public float getPrice() {
        return price;
    }
    public void setPrice(float price) {
        this.price = price;
    }
    public Date getCreateTime() {
        return createTime;
    }
    public void setCreateTime(Date createTime) {
        this.createTime = createTime;
    }
    public long getPoint() {
        return point;
    }
    public void setPoint(long point) {
        this.point = point;
    }
    public boolean isVip() {
        return vip;
    }
    public void setVip(boolean vip) {
        this.vip = vip;
    }
}

4、Java测试代码：

package com.my.solr;

import java.io.IOException;
import java.util.ArrayList;
import java.util.Calendar;
import java.util.Date;
import java.util.HashMap;
import java.util.Iterator;
import java.util.List;

import org.apache.solr.client.solrj.SolrQuery;
import org.apache.solr.client.solrj.SolrQuery.ORDER;
import org.apache.solr.client.solrj.SolrQuery.SortClause;
import org.apache.solr.client.solrj.SolrServerException;
import org.apache.solr.client.solrj.impl.HttpSolrServer;
import org.apache.solr.client.solrj.impl.XMLResponseParser;
import org.apache.solr.client.solrj.response.FacetField;
import org.apache.solr.client.solrj.response.FacetField.Count;
import org.apache.solr.client.solrj.response.QueryResponse;
import org.apache.solr.common.params.AnalysisParams;
import org.apache.solr.common.params.CommonParams;
import org.apache.solr.common.params.FacetParams;
import org.apache.solr.common.util.NamedList;
import org.apache.solr.common.util.SimpleOrderedMap;

import com.my.entity.Item;

public class TestSolr {
    private static HashMap<Integer, String> mapRegion = new HashMap<Integer, String>();
    private static HashMap<Integer, String> mapCategory = new HashMap<Integer, String>();

    @SuppressWarnings("unchecked")
    public static void main(String[] args) throws IOException,
            SolrServerException {
        // ------------------------------------------------------
        // Set map
        // ------------------------------------------------------
        mapRegion.put(1, "罗湖区");
        mapRegion.put(2, "南山区");
        mapRegion.put(3, "龙岗区");
        mapRegion.put(4, "福田区");
        mapCategory.put(1, "单间");
        mapCategory.put(2, "2房1厅");
        mapCategory.put(3, "3房2厅");
        mapCategory.put(4, "1房1厅");
        
        String url = "http://localhost:8983/solr/sample5";
        HttpSolrServer core = new HttpSolrServer(url);
        core.setMaxRetries(1);
        core.setConnectionTimeout(5000);
        core.setParser(new XMLResponseParser()); // binary parser is used by
                                                    // default
        core.setSoTimeout(1000); // socket read timeout
        core.setDefaultMaxConnectionsPerHost(100);
        core.setMaxTotalConnections(100);
        core.setFollowRedirects(false); // defaults to false
        core.setAllowCompression(true);

        // ------------------------------------------------------
        // remove all data
        // ------------------------------------------------------
        core.deleteByQuery("*:*");
        List<Item> items = new ArrayList<Item>();
        items.add(makeItem(items.size() + 1, "龙城公寓一房一厅", "豪华城城公寓1房1厅，拧包入住", 1, 1, 1200f, 10, false));
        items.add(makeItem(items.size() + 1, "兴新宿舍楼 1室0厅", " 中等装修 招女性合租", 1, 1, 1000f, 11, false));
        items.add(makeItem(items.size() + 1, "西丽新屋村新宿舍楼单间", " 无敌装修只招女性", 2, 1, 1000f, 2, true));
        items.add(makeItem(items.size() + 1, "大芬村信和爱琴居地铁口2房1厅", " 地铁口 + 出行便利=居家首选", 3, 2, 2000f, 5, false));
        items.add(makeItem(items.size() + 1, "龙岗富豪花园3房2厅出租", " 离地铁口只要5分钟，快来秒杀吧", 3, 3, 4500f, 21, true));
        items.add(makeItem(items.size() + 1, "海景房园3房2厅出租", "海景房园出租，无敌海景，可以看到伦敦", 4, 3, 8500f, 12, false));
        items.add(makeItem(items.size() + 1, "天域花园1房1厅", "天域花园，男女不限，入住免水电一月", 2, 4, 1500f, 13, true));
        items.add(makeItem(items.size() + 1, "神一样的漂亮，玉馨山庄3房2厅", "心动不如行动，拧包即可入住，来吧！", 1, 3, 9500f, 8, false));
        items.add(makeItem(items.size() + 1, "玉馨山庄2房1厅，情侣最爱", "宅男宅女快来吧只要2500，走过路过，别再错过", 1, 2, 2500f, 5, false));
        items.add(makeItem(items.size() + 1, "天域花园3房2厅", "天域花园出租，都来看看，都来瞄瞄，3房出租只要7500.", 4, 3, 7500f, 6, true));
        items.add(makeItem(items.size() + 1, "深都花园出租3房2厅", "找爱干净的人氏，全新装修", 4, 3, 5200f, 31, false));
        items.add(makeItem(items.size() + 1, "This is Mobile test", "haha Hello world!", 4, 3, 1200f, 31, false));
        core.addBeans(items);
        // commit
        core.commit();
        
        // ------------------------------------------------------
        // Set search text
        // ------------------------------------------------------
        String searchText = AnalysisSearchText(core, "出租花园"); //subject:*出租* && price:[1000 TO 8000]
        System.out.println("Search Text:" + searchText);
        
        // ------------------------------------------------------
        // Set query text
        // ------------------------------------------------------
        String queryText = searchText + "&& price:[1000 TO 8000]";
        System.out.println("Query Text:" + queryText);

        // ------------------------------------------------------
        // search
        // ------------------------------------------------------
        SolrQuery query = new SolrQuery();
        query.setQuery(queryText);
        query.setStart(0); // query的开始行数(分页使用)
        query.setRows(100); // query的返回行数(分页使用)
        query.setFacet(true); // 设置使用facet
        query.setFacetMinCount(0); // 设置facet最少的统计数量
        query.setFacetLimit(10); // facet结果的返回行数
        query.addFacetField("categoryId", "regionId"); // facet的字段
        query.setFacetSort(FacetParams.FACET_SORT_COUNT);
        //query.addSort(new SortClause("id", ORDER.asc)); // 排序
        query.setRequestHandler("/browse");
        QueryResponse response = core.query(query);
        List<Item> items_rep = response.getBeans(Item.class);
        List<FacetField> facetFields = response.getFacetFields();
        // 因为上面的start和rows均设置为0，所以这里不会有query结果输出
        System.out.println("--------------------");
        System.out.println("Search result:");
        for (Item item : items_rep) {
            System.out.println("id=" + item.getId() + "\tsubject=" + item.getSubject()
                    + "\tregion=" + mapRegion.get(item.getRegionId())
                    + "\tcategory=" + mapCategory.get(item.getCategoryId())
                    + "\tprice=" + item.getPrice());
        }
        // 打印所有facet
        for (FacetField ff : facetFields) {
            System.out.println("--------------------");
            System.out.println("name=" + ff.getName() + "\tcount=" + ff.getValueCount());
            System.out.println("--------------------");
            switch (ff.getName()) {
            case "regionId":
                printOut(mapRegion, ff.getValues());
                break;
            case "categoryId":
                printOut(mapCategory, ff.getValues());
                break;
            }
        }
    }
    
    @SuppressWarnings({ "rawtypes" })
    private static void printOut(HashMap map, List<Count> counts) {
        for (Count count : counts) {
            System.out.println("name=" + map.get(Integer.parseInt(count.getName())) + "\tcount=" + count.getCount());
        }
        System.out.println("--------------------");
    }

    private static Item makeItem(long id, String subject, String content, int regionId, int categoryId, float price,
            long point, boolean vip) {
        Calendar cale = Calendar.getInstance();
        cale.setTime(new Date());
        cale.add(Calendar.DATE, (int)id);
        Item item = new Item();
        item.setId(id);
        item.setSubject(subject);
        item.setContent(content);
        item.setRegionId(regionId);
        item.setCategoryId(categoryId);
        item.setPrice(price);
        item.setCreateTime(cale.getTime());
        item.setPoint(point);
        item.setVip(vip);
        return item;
    }
    
    @SuppressWarnings("unchecked")
    /**
     * 重新将需要查询的文本内容解析成分词
     * @param core
     * @param searchText
     * @return
     * @throws SolrServerException
     */
    private static String AnalysisSearchText(HttpSolrServer core, String searchText) throws SolrServerException {
        StringBuilder strSearchText = new StringBuilder();
        final String STR_FIELD_TYPE = "text_cn";
        SolrQuery queryAnalysis = new SolrQuery();
        queryAnalysis.add(CommonParams.QT, "/analysis/field"); // query type
        queryAnalysis.add(AnalysisParams.FIELD_VALUE, searchText);
        queryAnalysis.add(AnalysisParams.FIELD_TYPE, STR_FIELD_TYPE);
        QueryResponse responseAnalysis = core.query(queryAnalysis);
        //对响应进行解析
        NamedList<Object> analysis = (NamedList<Object>) responseAnalysis.getResponse().get("analysis");// analysis node
        NamedList<Object> field_types = (NamedList<Object>) analysis.get("field_types");// field_types node
        NamedList<Object> fieldType = (NamedList<Object>) field_types.get(STR_FIELD_TYPE);// text_cn node
        NamedList<Object> index = (NamedList<Object>) fieldType.get("index");// index node
        List<SimpleOrderedMap<String>> list = (ArrayList<SimpleOrderedMap<String>>)index.get("org.wltea.analyzer.lucene.IKTokenizer");// tokenizer node
        // 在每个词条中间加上空格，为每个词条进行或运算
        for(Iterator<SimpleOrderedMap<String>> iter = list.iterator(); iter.hasNext();)
        {
            strSearchText.append(iter.next().get("text") + " ");
        }
        return strSearchText.toString();
    }
}

说明：

a)AnalysisSearchText(...)方法：此方法会把需要查询的语句先使用分词分析，如上例子“出租花园”，调用AnalysisSearchText(...)后，会得到“出租花园”，会把两个词分拆成以空格分隔的字符串。不然solr会以“出租花园”整体做为词做查询而得不到结果。

b)使用自定义的Handler，需要在代码中加入这句：

query.setRequestHandler("/browse");

对应的是solrconfig.xml中的requestHandler的:/browse

5、运行结果：

或者使用solr的query查询查看结果：

posted @ 2015-05-28 13:42 lvyafei 阅读(1421) 评论(0) 编辑收藏举报

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solr特点三: defType(查询权重排序)

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