Solr实现SQL的查询与统计--转载

原文地址：http://shiyanjun.cn/archives/78.html

Cloudera公司已经推出了基于Hadoop平台的查询统计分析工具Impala，只要熟悉SQL，就可以熟练地使用Impala来执行查询与分析的功能。不过Impala的SQL和关系数据库的SQL还是有一点微妙地不同的。
下面，我们设计一个表，通过该表中的数据，来将SQL查询与统计的语句，使用Solr查询的方式来与SQL查询对应。这个翻译的过程，是非常有趣的，你可以看到Solr一些很不错的功能。
用来示例的表结构设计，如图所示：

下面，我们通过给出一些SQL查询统计语句，然后对应翻译成Solr查询语句，然后对比结果。

查询对比

  • 条件组合查询

SQL查询语句：

1 SELECT log_id,start_time,end_time,prov_id,city_id,area_id,idt_id,cnt,net_type
2 FROM v_i_event
3 WHERE prov_id = 1 AND net_type = 1 AND area_id = 10304 AND time_type = 1 AND time_id >= 20130801 AND time_id <= 20130815
4 ORDER BY log_id LIMIT 10;

查询结果，如图所示：

Solr查询URL：

1 http://slave1:8888/solr-cloud/i_event/select?q=*:*&fl=log_id,start_time,end_time,prov_id,city_id,area_id,idt_id,cnt,net_type&fq=prov_id:1 AND net_type:1 AND area_id:10304 AND time_type:1 AND time_id:[20130801 TO 20130815]&sort=log_id asc&start=0&rows=10

查询结果，如下所示：

<response>
    <lst name="responseHeader">
        <int name="status">0</int>
        <int name="QTime">4</int>
    </lst>
    <result name="response" numFound="77" start="0">
        <doc>
            <int name="log_id">6827</int>
            <long name="start_time">1375072117</long>
            <long name="end_time">1375081683</long>
            <int name="prov_id">1</int>
            <int name="city_id">103</int>
            <int name="area_id">10304</int>
            <int name="idt_id">11002</int>
            <int name="cnt">0</int>
            <int name="net_type">1</int>
        </doc>
        <doc>
            <int name="log_id">6827</int>
            <long name="start_time">1375072117</long>
            <long name="end_time">1375081683</long>
            <int name="prov_id">1</int>
            <int name="city_id">103</int>
            <int name="area_id">10304</int>
            <int name="idt_id">11000</int>
            <int name="cnt">0</int>
            <int name="net_type">1</int>
        </doc>
        <doc>
            <int name="log_id">6851</int>
            <long name="start_time">1375142158</long>
            <long name="end_time">1375146391</long>
            <int name="prov_id">1</int>
            <int name="city_id">103</int>
            <int name="area_id">10304</int>
            <int name="idt_id">14001</int>
            <int name="cnt">5</int>
            <int name="net_type">1</int>
        </doc>
        <doc>
            <int name="log_id">6851</int>
            <long name="start_time">1375142158</long>
            <long name="end_time">1375146391</long>
            <int name="prov_id">1</int>
            <int name="city_id">103</int>
            <int name="area_id">10304</int>
            <int name="idt_id">11002</int>
            <int name="cnt">23</int>
            <int name="net_type">1</int>
        </doc>
        <doc>
            <int name="log_id">6851</int>
            <long name="start_time">1375142158</long>
            <long name="end_time">1375146391</long>
            <int name="prov_id">1</int>
            <int name="city_id">103</int>
            <int name="area_id">10304</int>
            <int name="idt_id">10200</int>
            <int name="cnt">55</int>
            <int name="net_type">1</int>
        </doc>
        <doc>
            <int name="log_id">6851</int>
            <long name="start_time">1375142158</long>
            <long name="end_time">1375146391</long>
            <int name="prov_id">1</int>
            <int name="city_id">103</int>
            <int name="area_id">10304</int>
            <int name="idt_id">14000</int>
            <int name="cnt">4</int>
            <int name="net_type">1</int>
        </doc>
        <doc>
            <int name="log_id">6851</int>
            <long name="start_time">1375142158</long>
            <long name="end_time">1375146391</long>
            <int name="prov_id">1</int>
            <int name="city_id">103</int>
            <int name="area_id">10304</int>
            <int name="idt_id">11000</int>
            <int name="cnt">1</int>
            <int name="net_type">1</int>
        </doc>
        <doc>
            <int name="log_id">6851</int>
            <long name="start_time">1375142158</long>
            <long name="end_time">1375146391</long>
            <int name="prov_id">1</int>
            <int name="city_id">103</int>
            <int name="area_id">10304</int>
            <int name="idt_id">10201</int>
            <int name="cnt">31</int>
            <int name="net_type">1</int>
        </doc>
        <doc>
            <int name="log_id">6851</int>
            <long name="start_time">1375142158</long>
            <long name="end_time">1375146391</long>
            <int name="prov_id">1</int>
            <int name="city_id">103</int>
            <int name="area_id">10304</int>
            <int name="idt_id">8002</int>
            <int name="cnt">8</int>
            <int name="net_type">1</int>
        </doc>
        <doc>
            <int name="log_id">6851</int>
            <long name="start_time">1375142158</long>
            <long name="end_time">1375146391</long>
            <int name="prov_id">1</int>
            <int name="city_id">103</int>
            <int name="area_id">10304</int>
            <int name="idt_id">8000</int>
            <int name="cnt">30</int>
            <int name="net_type">1</int>
        </doc>
    </result>
</response>

对比上面结果，除了根据idt_id排序方式不同以外（Impala是升序，Solr是降序），其他是相同的。

  • 单个字段分组统计

SQL查询语句：

1 SELECT prov_id, SUM(cnt) AS sum_cnt, AVG(cnt) AS avg_cnt, MAX(cnt) AS max_cnt, MIN(cnt) ASmin_cnt, COUNT(cnt) AS count_cnt
2 FROM v_i_event
3 GROUP BY prov_id;

查询结果，如图所示：

Solr查询URL：

1 http://slave1:8888/solr-cloud/i_event/select?q=*:*&stats=true&stats.field=cnt&rows=0&indent=true

查询结果，如下所示：

<response>
    <lst name="responseHeader">
        <int name="status">0</int>
        <int name="QTime">2</int>
    </lst>
    <result name="response" numFound="4088" start="0"></result>
    <lst name="stats">
        <lst name="stats_fields">
            <lst name="cnt">
                <double name="min">0.0</double>
                <double name="max">1258.0</double>
                <long name="count">4088</long>
                <long name="missing">0</long>
                <double name="sum">32587.0</double>
                <double name="sumOfSquares">9170559.0</double>
                <double name="mean">7.971379647749511</double>
                <double name="stddev">46.69344567709268</double>
                <lst name="facets" />
            </lst>
        </lst>
    </lst>
</response>

对比查询结果，Solr提供了更多的统计项，如标准差（stddev）等，与SQL查询结果是一致的。

  • IN条件查询

SQL查询语句：

1 SELECT log_id,start_time,end_time,prov_id,city_id,area_id,idt_id,cnt,net_typ
2 FROM v_i_event
3 WHERE prov_id = 1 AND net_type = 1 AND city_id IN(106,103) AND idt_idIN(12011,5004,6051,6056,8002) AND time_type = 1 AND time_id >= 20130801 AND time_id <= 20130815
4 ORDER BY log_id, start_time DESC LIMIT 10;

查询结果，如图所示：

Solr查询URL：

http://slave1:8888/solr-cloud/i_event/select?q=*:*&fl=log_id,start_time,end_time,prov_id,city_id,area_id,idt_id, cnt,net_type&fq=prov_id:1 AND net_type:1 AND (city_id:106 OR city_id:103) AND (idt_id:12011 OR idt_id:5004 OR idt_id:6051 OR idt_id:6056 OR idt_id:8002) AND time_type:1 AND time_id:[20130801 TO 20130815]&sort=log_id asc ,start_time desc&start=0&rows=10

或者：

http://slave1:8888/solr-cloud/i_event/select?q=*:*&fl=log_id,start_time,end_time,prov_id,city_id,area_id,idt_id, cnt ,net_type&fq=prov_id:1&fq=net_type:1&fq=(city_id:106 OR city_id:103)&fq=(idt_id:12011 OR idt_id:5004 OR idt_id:6051 OR idt_id:6056 OR idt_id:8002)&fq=time_type:1&fq=time_id:[20130801 TO 20130815]&sort=log_id asc,start_time desc&start=0&rows=10

查询结果，如下所示：

<response>
    <lst name="responseHeader">
        <int name="status">0</int>
        <int name="QTime">6</int>
    </lst>
    <result name="response" numFound="63" start="0">
        <doc>
            <int name="log_id">6553</int>
            <long name="start_time">1374054184</long>
            <long name="end_time">1374054254</long>
            <int name="prov_id">1</int>
            <int name="city_id">103</int>
            <int name="area_id">10307</int>
            <int name="idt_id">12011</int>
            <int name="cnt">0</int>
            <int name="net_type">1</int>
        </doc>
        <doc>
            <int name="log_id">6553</int>
            <long name="start_time">1374054184</long>
            <long name="end_time">1374054254</long>
            <int name="prov_id">1</int>
            <int name="city_id">103</int>
            <int name="area_id">10307</int>
            <int name="idt_id">5004</int>
            <int name="cnt">2</int>
            <int name="net_type">1</int>
        </doc>
        <doc>
            <int name="log_id">6555</int>
            <long name="start_time">1374055060</long>
            <long name="end_time">1374055158</long>
            <int name="prov_id">1</int>
            <int name="city_id">103</int>
            <int name="area_id">70104</int>
            <int name="idt_id">5004</int>
            <int name="cnt">3</int>
            <int name="net_type">1</int>
        </doc>
        <doc>
            <int name="log_id">6555</int>
            <long name="start_time">1374055060</long>
            <long name="end_time">1374055158</long>
            <int name="prov_id">1</int>
            <int name="city_id">103</int>
            <int name="area_id">70104</int>
            <int name="idt_id">12011</int>
            <int name="cnt">0</int>
            <int name="net_type">1</int>
        </doc>
        <doc>
            <int name="log_id">6595</int>
            <long name="start_time">1374292508</long>
            <long name="end_time">1374292639</long>
            <int name="prov_id">1</int>
            <int name="city_id">103</int>
            <int name="area_id">10307</int>
            <int name="idt_id">5004</int>
            <int name="cnt">4</int>
            <int name="net_type">1</int>
        </doc>
        <doc>
            <int name="log_id">6611</int>
            <long name="start_time">1374461233</long>
            <long name="end_time">1374461245</long>
            <int name="prov_id">1</int>
            <int name="city_id">103</int>
            <int name="area_id">10307</int>
            <int name="idt_id">5004</int>
            <int name="cnt">1</int>
            <int name="net_type">1</int>
        </doc>
        <doc>
            <int name="log_id">6612</int>
            <long name="start_time">1374461261</long>
            <long name="end_time">1374461269</long>
            <int name="prov_id">1</int>
            <int name="city_id">103</int>
            <int name="area_id">10307</int>
            <int name="idt_id">5004</int>
            <int name="cnt">1</int>
            <int name="net_type">1</int>
        </doc>
        <doc>
            <int name="log_id">6612</int>
            <long name="start_time">1374461261</long>
            <long name="end_time">1374461269</long>
            <int name="prov_id">1</int>
            <int name="city_id">103</int>
            <int name="area_id">10307</int>
            <int name="idt_id">12011</int>
            <int name="cnt">0</int>
            <int name="net_type">1</int>
        </doc>
        <doc>
            <int name="log_id">6613</int>
            <long name="start_time">1374461422</long>
            <long name="end_time">1374461489</long>
            <int name="prov_id">1</int>
            <int name="city_id">103</int>
            <int name="area_id">10307</int>
            <int name="idt_id">6056</int>
            <int name="cnt">1</int>
            <int name="net_type">1</int>
        </doc>
        <doc>
            <int name="log_id">6613</int>
            <long name="start_time">1374461422</long>
            <long name="end_time">1374461489</long>
            <int name="prov_id">1</int>
            <int name="city_id">103</int>
            <int name="area_id">10307</int>
            <int name="idt_id">6051</int>
            <int name="cnt">1</int>
            <int name="net_type">1</int>
        </doc>
    </result>
</response>

对比查询结果，是一致的。

  • 开区间范围条件查询

SQL查询语句：

1 SELECT log_id,start_time,end_time,prov_id,city_id,area_id,idt_id,cnt,net_type
2 FROM v_i_event
3 WHERE net_type = 1 AND idt_id IN(12011,5004,6051,6056,8002) AND time_type = 1 ANDstart_time >= 1373598465 AND end_time < 1374055254
4 ORDER BY log_id, start_time, idt_id DESC LIMIT 30;

查询结果，如图所示：

Solr查询URL：

1 http://slave1:8888/solr-cloud/i_event/select?q=*:*&fl=log_id,start_time,end_time,prov_id,city_id,area_id,idt_id,cnt,net_type&fq=net_type:1 AND (idt_id:12011 OR idt_id:5004 OR idt_id:6051 OR idt_id:6056 OR idt_id:8002) AND time_type:1 AND start_time:[1373598465 TO 1374055254]&fq =-start_time:1374055254&sort=log_id asc,start_time asc,idt_id desc&start=0&rows=30

或

1 http://slave1:8888/solr-cloud/i_event/select?q=*:*&fl=log_id,start_time,end_time,prov_id,city_id,area_id,idt_id,cnt,net_type&fq=net_type:1 AND (idt_id:12011 OR idt_id:5004 OR idt_id:6051 OR idt_id:6056 OR idt_id:8002) AND time_type:1 AND start_time:[1373598465 TO 1374055254] AND -start_time:1374055254&sort=log_id asc,start_time asc,idt_id desc&start=0&rows=30

或

1 http://slave1:8888/solr-cloud/i_event/select?q=*:*&fl=log_id,start_time,end_time,prov_id,city_id,area_id,idt_id,cnt,net_type&fq=net_type:1&fq=idt_id:12011 OR idt_id:5004 OR idt_id:6051 OR idt_id:6056 OR idt_id:8002&fq =time_type:1&fq=start_time:[1373598465 TO 1374055254]&fq =-start_time:1374055254&sort=log_id asc,start_time asc,idt_id desc&start=0&rows=30

查询结果，如下所示：

<response>
    <lst name="responseHeader">
        <int name="status">0</int>
        <int name="QTime">5</int>
    </lst>
    <result name="response" numFound="4" start="0">
        <doc>
            <int name="log_id">6553</int>
            <long name="start_time">1374054184</long>
            <long name="end_time">1374054254</long>
            <int name="prov_id">1</int>
            <int name="city_id">103</int>
            <int name="area_id">10307</int>
            <int name="idt_id">12011</int>
            <int name="cnt">0</int>
            <int name="net_type">1</int>
        </doc>
        <doc>
            <int name="log_id">6553</int>
            <long name="start_time">1374054184</long>
            <long name="end_time">1374054254</long>
            <int name="prov_id">1</int>
            <int name="city_id">103</int>
            <int name="area_id">10307</int>
            <int name="idt_id">5004</int>
            <int name="cnt">2</int>
            <int name="net_type">1</int>
        </doc>
        <doc>
            <int name="log_id">6555</int>
            <long name="start_time">1374055060</long>
            <long name="end_time">1374055158</long>
            <int name="prov_id">1</int>
            <int name="city_id">103</int>
            <int name="area_id">70104</int>
            <int name="idt_id">12011</int>
            <int name="cnt">0</int>
            <int name="net_type">1</int>
        </doc>
        <doc>
            <int name="log_id">6555</int>
            <long name="start_time">1374055060</long>
            <long name="end_time">1374055158</long>
            <int name="prov_id">1</int>
            <int name="city_id">103</int>
            <int name="area_id">70104</int>
            <int name="idt_id">5004</int>
            <int name="cnt">3</int>
            <int name="net_type">1</int>
        </doc>
    </result>
</response>
  • 多个字段分组统计（只支持count函数）

SQL查询语句：

1 SELECT city_id, area_id, COUNT(cnt) AS count_cnt
2 FROM v_i_event
3 WHERE prov_id = 1 AND net_type = 1
4 GROUP BY city_id, area_id;

查询结果，如图所示：

Solr查询URL：

1 http://slave1:8888/solr-cloud/i_event/select?q=*:*&facet=true&facet.pivot=city_id,area_id&fq=prov_id:1 AND net_type:1&rows=0&indent=true

查询结果，如下所示：

<response>
    <lst name="responseHeader">
        <int name="status">0</int>
        <int name="QTime">72</int>
    </lst>
    <result name="response" numFound="1171" start="0"></result>
    <lst name="facet_counts">
        <lst name="facet_queries" />
        <lst name="facet_fields" />
        <lst name="facet_dates" />
        <lst name="facet_ranges" />
        <lst name="facet_pivot">
            <arr name="city_id,area_id">
                <lst>
                    <str name="field">city_id</str>
                    <int name="value">103</int>
                    <int name="count">678</int>
                    <arr name="pivot">
                        <lst>
                            <str name="field">area_id</str>
                            <int name="value">10307</int>
                            <int name="count">298</int>
                        </lst>
                        <lst>
                            <str name="field">area_id</str>
                            <int name="value">10315</int>
                            <int name="count">120</int>
                        </lst>
                        <lst>
                            <str name="field">area_id</str>
                            <int name="value">10317</int>
                            <int name="count">86</int>
                        </lst>
                        <lst>
                            <str name="field">area_id</str>
                            <int name="value">10304</int>
                            <int name="count">67</int>
                        </lst>
                        <lst>
                            <str name="field">area_id</str>
                            <int name="value">10310</int>
                            <int name="count">49</int>
                        </lst>
                        <lst>
                            <str name="field">area_id</str>
                            <int name="value">70104</int>
                            <int name="count">48</int>
                        </lst>
                        <lst>
                            <str name="field">area_id</str>
                            <int name="value">10308</int>
                            <int name="count">6</int>
                        </lst>
                        <lst>
                            <str name="field">area_id</str>
                            <int name="value">0</int>
                            <int name="count">2</int>
                        </lst>
                        <lst>
                            <str name="field">area_id</str>
                            <int name="value">10311</int>
                            <int name="count">2</int>
                        </lst>
                    </arr>
                </lst>
                <lst>
                    <str name="field">city_id</str>
                    <int name="value">0</int>
                    <int name="count">463</int>
                    <arr name="pivot">
                        <lst>
                            <str name="field">area_id</str>
                            <int name="value">0</int>
                            <int name="count">395</int>
                        </lst>
                        <lst>
                            <str name="field">area_id</str>
                            <int name="value">10307</int>
                            <int name="count">68</int>
                        </lst>
                    </arr>
                </lst>
                <lst>
                    <str name="field">city_id</str>
                    <int name="value">106</int>
                    <int name="count">10</int>
                    <arr name="pivot">
                        <lst>
                            <str name="field">area_id</str>
                            <int name="value">10304</int>
                            <int name="count">10</int>
                        </lst>
                    </arr>
                </lst>
                <lst>
                    <str name="field">city_id</str>
                    <int name="value">110</int>
                    <int name="count">8</int>
                    <arr name="pivot">
                        <lst>
                            <str name="field">area_id</str>
                            <int name="value">0</int>
                            <int name="count">8</int>
                        </lst>
                    </arr>
                </lst>
                <lst>
                    <str name="field">city_id</str>
                    <int name="value">118</int>
                    <int name="count">8</int>
                    <arr name="pivot">
                        <lst>
                            <str name="field">area_id</str>
                            <int name="value">10316</int>
                            <int name="count">8</int>
                        </lst>
                    </arr>
                </lst>
                <lst>
                    <str name="field">city_id</str>
                    <int name="value">105</int>
                    <int name="count">4</int>
                    <arr name="pivot">
                        <lst>
                            <str name="field">area_id</str>
                            <int name="value">0</int>
                            <int name="count">4</int>
                        </lst>
                    </arr>
                </lst>
            </arr>
        </lst>
    </lst>
</response>

对比上面结果，Solr查询结果，需要从上面的各组中进行合并，得到最终的统计结果，结果和SQL结果是一致的。

  • 多个字段分组统计（支持count、sum、max、min等函数）

一次对多个字段进行独立分组统计，Solr可以很好的支持。这相当于执行两个带有GROUP BY子句的SQL，这两个GROUP BY分别只对一个字段进行汇总统计。
SQL查询语句：

1 SELECT city_id, area_id, COUNT(cnt) AS count_cnt
2 FROM v_i_event
3 WHERE prov_id = 1 AND net_type = 1
4 GROUP BY city_id;
5  
6 SELECT city_id, area_id, COUNT(cnt) AS count_cnt
7 FROM v_i_event
8 WHERE prov_id = 1 AND net_type = 1
9 GROUP BY area_id;

查询结果，不再显示。
Solr查询URL：

1 >http://slave1:8888/solr-cloud/i_event/select?q=*:*&stats=true&stats.field=cnt&f.cnt.stats.facet=city_id&&f.cnt.stats.facet=area_id&fq=prov_id:1 AND net_type:1&rows=0&indent=true

查询结果，如下所示：

<response>
    <lst name="responseHeader">
        <int name="status">0</int>
        <int name="QTime">6</int>
    </lst>
    <result name="response" numFound="1171" start="0"></result>
    <lst name="stats">
        <lst name="stats_fields">
            <lst name="cnt">
                <double name="min">0.0</double>
                <double name="max">167.0</double>
                <long name="count">1171</long>
                <long name="missing">0</long>
                <double name="sum">3701.0</double>
                <double name="sumOfSquares">249641.0</double>
                <double name="mean">3.1605465414175917</double>
                <double name="stddev">14.260812879164407</double>
                <lst name="facets">
                    <lst name="city_id">
                        <lst name="0">
                            <double name="min">0.0</double>
                            <double name="max">167.0</double>
                            <long name="count">463</long>
                            <long name="missing">0</long>
                            <double name="sum">2783.0</double>
                            <double name="sumOfSquares">238819.0</double>
                            <double name="mean">6.010799136069115</double>
                            <double name="stddev">21.92524420257807</double>
                            <lst name="facets" />
                        </lst>
                        <lst name="110">
                            <double name="min">0.0</double>
                            <double name="max">1.0</double>
                            <long name="count">8</long>
                            <long name="missing">0</long>
                            <double name="sum">3.0</double>
                            <double name="sumOfSquares">3.0</double>
                            <double name="mean">0.375</double>
                            <double name="stddev">0.5175491695067657</double>
                            <lst name="facets" />
                        </lst>
                        <lst name="106">
                            <double name="min">0.0</double>
                            <double name="max">0.0</double>
                            <long name="count">10</long>
                            <long name="missing">0</long>
                            <double name="sum">0.0</double>
                            <double name="sumOfSquares">0.0</double>
                            <double name="mean">0.0</double>
                            <double name="stddev">0.0</double>
                            <lst name="facets" />
                        </lst>
                        <lst name="105">
                            <double name="min">0.0</double>
                            <double name="max">0.0</double>
                            <long name="count">4</long>
                            <long name="missing">0</long>
                            <double name="sum">0.0</double>
                            <double name="sumOfSquares">0.0</double>
                            <double name="mean">0.0</double>
                            <double name="stddev">0.0</double>
                            <lst name="facets" />
                        </lst>
                        <lst name="103">
                            <double name="min">0.0</double>
                            <double name="max">55.0</double>
                            <long name="count">678</long>
                            <long name="missing">0</long>
                            <double name="sum">915.0</double>
                            <double name="sumOfSquares">10819.0</double>
                            <double name="mean">1.3495575221238938</double>
                            <double name="stddev">3.7625525739676986</double>
                            <lst name="facets" />
                        </lst>
                        <lst name="118">
                            <double name="min">0.0</double>
                            <double name="max">0.0</double>
                            <long name="count">8</long>
                            <long name="missing">0</long>
                            <double name="sum">0.0</double>
                            <double name="sumOfSquares">0.0</double>
                            <double name="mean">0.0</double>
                            <double name="stddev">0.0</double>
                            <lst name="facets" />
                        </lst>
                    </lst>
                    <lst name="area_id">
                        <lst name="10308">
                            <double name="min">0.0</double>
                            <double name="max">1.0</double>
                            <long name="count">6</long>
                            <long name="missing">0</long>
                            <double name="sum">1.0</double>
                            <double name="sumOfSquares">1.0</double>
                            <double name="mean">0.16666666666666666</double>
                            <double name="stddev">0.408248290463863</double>
                            <lst name="facets" />
                        </lst>
                        <lst name="10310">
                            <double name="min">0.0</double>
                            <double name="max">5.0</double>
                            <long name="count">49</long>
                            <long name="missing">0</long>
                            <double name="sum">40.0</double>
                            <double name="sumOfSquares">108.0</double>
                            <double name="mean">0.8163265306122449</double>
                            <double name="stddev">1.2528878206593208</double>
                            <lst name="facets" />
                        </lst>
                        <lst name="0">
                            <double name="min">0.0</double>
                            <double name="max">167.0</double>
                            <long name="count">409</long>
                            <long name="missing">0</long>
                            <double name="sum">2722.0</double>
                            <double name="sumOfSquares">238550.0</double>
                            <double name="mean">6.6552567237163816</double>
                            <double name="stddev">23.243931908854</double>
                            <lst name="facets" />
                        </lst>
                        <lst name="10311">
                            <double name="min">0.0</double>
                            <double name="max">0.0</double>
                            <long name="count">2</long>
                            <long name="missing">0</long>
                            <double name="sum">0.0</double>
                            <double name="sumOfSquares">0.0</double>
                            <double name="mean">0.0</double>
                            <double name="stddev">0.0</double>
                            <lst name="facets" />
                        </lst>
                        <lst name="10304">
                            <double name="min">0.0</double>
                            <double name="max">55.0</double>
                            <long name="count">77</long>
                            <long name="missing">0</long>
                            <double name="sum">370.0</double>
                            <double name="sumOfSquares">9476.0</double>
                            <double name="mean">4.805194805194805</double>
                            <double name="stddev">10.064318107786017</double>
                            <lst name="facets" />
                        </lst>
                        <lst name="70104">
                            <double name="min">0.0</double>
                            <double name="max">3.0</double>
                            <long name="count">48</long>
                            <long name="missing">0</long>
                            <double name="sum">51.0</double>
                            <double name="sumOfSquares">117.0</double>
                            <double name="mean">1.0625</double>
                            <double name="stddev">1.1560433254047038</double>
                            <lst name="facets" />
                        </lst>
                        <lst name="10307">
                            <double name="min">0.0</double>
                            <double name="max">12.0</double>
                            <long name="count">366</long>
                            <long name="missing">0</long>
                            <double name="sum">274.0</double>
                            <double name="sumOfSquares">768.0</double>
                            <double name="mean">0.7486338797814208</double>
                            <double name="stddev">1.2418218134151426</double>
                            <lst name="facets" />
                        </lst>
                        <lst name="10315">
                            <double name="min">0.0</double>
                            <double name="max">4.0</double>
                            <long name="count">120</long>
                            <long name="missing">0</long>
                            <double name="sum">143.0</double>
                            <double name="sumOfSquares">359.0</double>
                            <double name="mean">1.1916666666666667</double>
                            <double name="stddev">1.2588899560996694</double>
                            <lst name="facets" />
                        </lst>
                        <lst name="10316">
                            <double name="min">0.0</double>
                            <double name="max">0.0</double>
                            <long name="count">8</long>
                            <long name="missing">0</long>
                            <double name="sum">0.0</double>
                            <double name="sumOfSquares">0.0</double>
                            <double name="mean">0.0</double>
                            <double name="stddev">0.0</double>
                            <lst name="facets" />
                        </lst>
                        <lst name="10317">
                            <double name="min">0.0</double>
                            <double name="max">5.0</double>
                            <long name="count">86</long>
                            <long name="missing">0</long>
                            <double name="sum">100.0</double>
                            <double name="sumOfSquares">262.0</double>
                            <double name="mean">1.1627906976744187</double>
                            <double name="stddev">1.3093371930442208</double>
                            <lst name="facets" />
                        </lst>
                    </lst>
                </lst>
            </lst>
        </lst>
    </lst>
</response>
  • 多个字段联合分组统计（支持count、sum、max、min等函数）

SQL查询语句：

1 SELECT city_id, area_id, SUM(cnt) AS sum_cnt, AVG(cnt) AS avg_cnt, MAX(cnt) AS max_cnt,MIN(cnt) AS min_cnt, COUNT(cnt) AS count_cnt
2 FROM v_i_event
3 WHERE prov_id = 1 AND net_type = 1
4 GROUP BY city_id, area_id;

查询结果，如图所示：

Solr目前不能简单的支持这种查询，如果想要满足这种查询统计，需要在schema的设计上，将一个字段设置为多值，然后通过多个值进行分组统计。如果应用中查询统计分析的模式比较固定，预先知道哪些字段会用于联合分组统计，完全可以在设计的时候，考虑设置多值字段来满足这种需求。

参考链接

时间： 2024-11-05 13:03:46

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