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
Solr实现SQL的查询与统计--转载的更多相关文章
- Solr高效利用：Solr实现SQL的查询与统计
1.如何高效使用Solr查询功能 ?2.单个字段分组统计如何实现? 3.IN条件查询有几种方式? 4.多个字段分组统计是否只支持count? Cloudera公司已经推出了基于Hadoop平台的查询统 ...
- sql语句查询经纬度范围(转载，源链接失效)
MySQL性能调优 – 使用更为快速的算法进行距离 最近遇到了一个问题,通过不断的尝试最终将某句原本占据近1秒的查询优化到了0.01秒,效率提高了100倍. 问题是这样的,有一张存放用户居住地点经纬度 ...
- 服务器文档下载zip格式 SQL Server SQL分页查询 C#过滤html标签 EF 延时加载与死锁 在JS方法中返回多个值的三种方法（转载） IEnumerable,ICollection,IList接口问题 不吹不擂，你想要的Python面试都在这里了【315+道题】 基于mvc三层架构和ajax技术实现最简单的文件上传 事件管理
服务器文档下载zip格式 刚好这次项目中遇到了这个东西,就来弄一下,挺简单的,但是前台调用的时候弄错了,浪费了大半天的时间,本人也是菜鸟一枚.开始吧.(MVC的) @using Rattan.Co ...
- Linq to SQL 语法查询(链接查询，子查询 & in操作 & join，分组统计等)
Linq to SQL 语法查询(链接查询,子查询 & in操作 & join,分组统计等) 子查询 描述:查询订单数超过5的顾客信息 查询句法: var 子查询 = from c i ...
- mysql统计类似SQL语句查询次数
mysql统计类似SQL语句查询次数 vc-mysql-sniffer 工具抓取的sql分析. 1.先用shell脚本把所有enter符号替换为null,再根据语句前后的字符分隔语句 grep -Ev ...
- [转载]编写SQL语句查询出每个各科班分数最高的同学的名字，班级名称，课程名称，分数
[转载]编写SQL语句查询出每个各科班分数最高的同学的名字,班级名称,课程名称,分数 转载自:https://blog.csdn.net/one_money/article/details/56921 ...
- 【转载】C#常用数据库Sqlserver通过SQL语句查询数据库以及表的大小
在Sqlserver数据库中,一般我们查看数据库的大小可以通过查找到数据库文件来查看,但如果要查找数据表Table的大小的话,则不可通过此方法,在Sqlserver数据库中,提供了相应的SQL语句来查 ...
- thinkphp区间查询、统计查询、SQL直接查询
区间查询 $data['id']=array(array('gt',4),array('lt',10));//默认关系是(and)并且的关系 //SELECT * FROM `tp_user` WHE ...
- 浅谈MySQL中优化sql语句查询常用的30种方法 - 转载
浅谈MySQL中优化sql语句查询常用的30种方法 1.对查询进行优化,应尽量避免全表扫描,首先应考虑在 where 及 order by 涉及的列上建立索引. 2.应尽量避免在 where 子句中使 ...
随机推荐
- 初识Linux的感受与对它的印象——20155328张钰清
之前从未接触过虚拟机的我,由于这次寒假预备作业,稍稍地认识了一下Linux操作系统. 在自己笔记本上安装Linux操作系统 根据老师提供的<基于VirtualBox虚拟机安装Ubuntu图文教程 ...
- 20155329胡佩伦《Java程序设计》第2周学习总结
学号 20155329 <Java程序设计>第2周学习总结 教材学习内容总结 基本类型 整数(short.int.long) 字节(byte) 浮点数(float/double) 字符(c ...
- [BZOJ2738]矩阵乘法-[整体二分+树状数组]
Description 给你一个N*N的矩阵,不用算矩阵乘法,但是每次询问一个子矩形的第K小数. (N<=500,Q<=60000) Solution 考虑二分答案,问题转化为求矩阵内为1 ...
- Mac下布置appium环境
1.下载或者更新Homebrew:homebrew官网 macOS 不可或缺的套件管理器 $ /usr/bin/ruby -e "$(curl -fsSL https://raw.githu ...
- linux-ubuntu常用命令（深圳文鹏）
系统信息 arch 显示机器的处理器架构(1) uname -m 显示机器的处理器架构(2) uname -r 显示正在使用的内核版本 dmidecode -q 显示硬件系统部件 - (SMBIOS ...
- nodejs的路径问题
最近公司的一个开发项目,后端用的是nodejs.这两天需要打包给客户演示,就让公司一个小伙把之前3D机房的打包工具移植过来.打包之后,发现原本在开发环境下的跑的好好的项目,不能访问了.出现项目的首页不 ...
- redis主从配置+sentinel哨兵
redis主从配置+sentinel哨兵 1:编译环境准备 1.1环境确认 Redis是一个开源.支持网络.基于内存.键值对存储数据库,使用ANSI C编写.所以在搭建Redis服务器时需要C语言的编 ...
- Amazon.com Seller Distributed Inventory Placement Inventory Placement Service
Greetings, Thank you for writing to us. I understand that you would like to send inventory to our wa ...
- 亚马逊AWS业务副总裁：如何在基础设施上降成本
腾讯科技 林靖东 11月17日编译 亚马逊Amazon Web Services业务的副总裁.著名工程师詹姆斯汉密尔顿(James Hamilton)在AWS re:Invent大会上解释了公司是如何 ...
- mysql常用语句入门整理
这篇属于小白入门级别,如果你已经高手可以直接跳过 1.运行数据库mysqld.exe,客户端直接mysql -uroot(root是默认用户名) -p 2 showdatabases,showtabl ...