背景：目前公司的报表计算需要20分钟，导致需要这么久的原因是，一次计算操作，执行了10万次+的update操作；看代码，有两个地方是这样写的，循环执行update，每个循环达到了4.6万次。
一，开始着手优化，第一个地方计算的是平均值，之前是根据report_date，trade_code这两个字段分组循环计算每一个平均值，现在我改成了一条SQL来执行；速度显著提高。
SET @rownum := 0; INSERT INTO zy_ticket_industry_history_0914 SELECT @rownum := @rownum +1 AS ‘id‘, zb.report_date,zi.trade_code, (SELECT COUNT(trade_code) AS ‘total‘ FROM zy_ticket_info zin WHERE zin.trade_code = zi.trade_code GROUP BY zin.trade_code) AS company_count, CONVERT(MAX(zp.total_operating_income),DECIMAL(20,2)) AS ‘business_income_top‘, (SELECT zzi.zq_jc AS ‘business_income_top_name‘ FROM zy_ticket_profit zzp ,zy_ticket_info zzi WHERE zzp.zq_code=zzi.zq_code AND zi.trade_code=zzi.trade_code AND zzi.enable=‘Y‘ ORDER BY zzp.total_operating_income DESC LIMIT 1) AS ‘business_income_top_name‘, CONVERT(AVG(zb.total_assets),DECIMAL(20,2)) AS ‘total_assets_avg‘ , CONVERT(AVG(zb.total_current_assets),DECIMAL(20,2)) AS ‘current_assets_avg‘, CONVERT(AVG( zb.total_liabilit )/ AVG( zb.total_assets ),DECIMAL(20,2)) AS ‘leverage_ratio_avg‘ , CONVERT(AVG( zb.total_current_assets )/ AVG( zb.total_current_liabilit ),DECIMAL(20,2)) AS ‘current_ratio_avg‘ , CONVERT((AVG(zb.total_current_assets)-AVG(zb.net_inventory))/AVG(zb.total_current_assets ),DECIMAL(20,2)) AS ‘quick_ratio_avg‘ , CONVERT((AVG(zc.cash_increase)+AVG(zb.account_receivable))/AVG(zb.total_current_liabilit ),DECIMAL(20,2)) AS ‘conserv_quick_ratio_avg‘ , CONVERT(AVG(zc.cash_increase),DECIMAL(20,2)) AS ‘cash_avg‘ , CONVERT(AVG(zb.total_current_liabilit),DECIMAL(20,2)) AS ‘current_liabilities_avg‘, CONVERT((AVG(zp.total_operating_income)-AVG(zp.operating_cost)-AVG(zp.income_tax_expense)),DECIMAL(20,2)) AS ‘operating_cash_avg‘, CONVERT((AVG(zp.net_profit)-AVG(zp.no_operating_income)),DECIMAL(20,2)) AS ‘kf_net_profit_avg‘, CONVERT((AVG(zb.total_current_assets)-AVG(zb.net_inventory))/AVG(zb.total_current_liabilit),DECIMAL(20,2)) AS ‘roe_avg‘, CONVERT(AVG(zp.total_profit),DECIMAL(20,2)) AS ‘sale_gross_profit_avg‘, CONVERT(AVG(zp.net_profit),DECIMAL(20,2)) AS ‘sale_net_profit_avg‘, CONVERT(AVG(zp.operating_cost)/(AVG(zb.net_inventory)+AVG(zb2.net_inventory)),DECIMAL(20,2)) AS ‘inventory_turnover_avg‘, CONVERT(AVG(zp.total_operating_income)/(AVG(zb.long_receivables)+AVG(zb2.long_receivables)),DECIMAL(20,2)) AS ‘receive_turnover_avg‘, ‘Y‘ AS `enable`, NULL AS create_by, NOW() AS create_time, NULL AS update_by, NOW() AS update_time, NULL AS remark FROM zy_ticket_balance zb LEFT JOIN zy_ticket_info zi ON(zb.zq_code=zi.zq_code) LEFT JOIN zy_ticket_cash zc ON(zb.zq_code=zc.zq_code AND zb.report_date=zc.report_date) LEFT JOIN zy_ticket_profit zp ON( zb.zq_code=zp.zq_code AND zb.report_date=zp.report_date) LEFT JOIN zy_ticket_balance zb2 ON(zb.zq_code=zb2.zq_code AND zb.report_date= DATE_ADD(zb2.report_date,INTERVAL 1 YEAR)) WHERE zb.zq_code=zi.zq_code AND zi.enable=‘Y‘ GROUP BY zi.`trade_code` ,zb.report_date ORDER BY report_date ASC,zi.trade_code ASC
第二个地方计算的是金额，排名，百分比，之前是根据zq_code，report_date，trade_code这两个字段分组循环计算的，基于前面那个，这个我也想通过一个SQL直接计算所有数据然后Insert；在SQL层面去优化；
而事实证明，想过很多种办法，都不行，SQL写出来，查询效率也很低，速度提高不明显，没有实际意义。最终的解决方案是动态校验zq_code，report_date，trade_code，只需执行16次update；
当然也可以更少，将操作表一致的进行合并，我为了SQL语句更清晰点，就分开写了。
（中间想通过SQL解决问题的时候，一到测试环境因为内存溢出，方案报废，而运营因为线上资源有限，不允许修改配置，然后才想到这个最终方案；其实应该一开始就这样做的，被第一步严重影响了思路::>_<::）
SQL：
-- 将数据先计算出来，然后在动态判断zq_code,trade_code,report_date，在进行更新。 UPDATE zy_ticket_report t1 INNER JOIN ( SELECT tt.*,ROUND((companyCount-totalAssetsRank)/companyCount*100,2) AS totalAssetsTranscend FROM ( SELECT t.*, IF (@pa = t.tradeCode,@curRank := @curRank + 1,@curRank := 1) AS totalAssetsRank,@pa := t.tradeCode AS blTradeCode FROM ( SELECT zb.report_date AS reportDate,zi.zq_code AS zqCode,zi.trade_code AS tradeCode,zi.zq_jc AS zqJc,com.companyCount,zb.total_assets AS ‘totalAssets‘ FROM zy_ticket_info zi JOIN zy_ticket_balance zb ON (zb.zq_code = zi.zq_code ) JOIN (SELECT trade_code,COUNT(trade_code) AS ‘companyCount‘ FROM zy_ticket_info zin GROUP BY zin.trade_code) AS com ON(com.trade_code = zi.trade_code) WHERE zi.enable = ‘Y‘ GROUP BY zb.report_date,zi.trade_code,zb.id ORDER BY zb.report_date,zi.trade_code,zb.total_assets DESC ) AS t, (SELECT @curRank := 0, @pa := ‘‘) b ) AS tt ) AS t2 SET t1.total_assets=t2.totalAssets,t1.total_assets_rank=t2.totalAssetsRank, t1.total_assets_transcend=t2.totalAssetsTranscend,t1.update_time = NOW() WHERE t1.`zq_code` = t2.zqCode AND t1.`trade_code` = t2.tradeCode AND t1.`report_date` = t2.reportDate
JAVA：
优化后，数据计算只需60秒左右。o(*￣▽￣*)ブ
记录下这次优化，学到的：
1，查询Map结构的对象集合，根据key获取整个对象。
XML:
<select id="getZys" resultMap="retMap"> SELECT CONCAT_WS(‘-‘,t.zqCode,t.tradeCode,t.reportDate) AS mapKey,t.*,IF (@pa = t.tradeCode,@curRank := @curRank + 1,@curRank := 1) AS totalOperatingIncomeRank, @pa := t.tradeCode AS blTradeCode FROM (SELECT zp.report_date AS reportDate,zi.zq_code AS zqCode,zi.trade_code AS tradeCode,zi.zq_jc AS zqJc,com.companyCount,zp.total_operating_income AS ‘totalOperatingIncome‘ FROM zy_ticket_info zi JOIN zy_ticket_profit zp ON (zp.zq_code = zi.zq_code) JOIN (SELECT trade_code,COUNT(trade_code) AS ‘companyCount‘ FROM zy_ticket_info zin GROUP BY zin.trade_code) AS com ON(com.trade_code = zi.trade_code) WHERE zi.enable = ‘Y‘ GROUP BY zp.report_date,zi.trade_code,zp.id ORDER BY zp.report_date,zi.trade_code,zp.total_operating_income DESC) AS t, (SELECT @curRank := 0, @pa := ‘‘) b </select>
<resultMap id="retMap" type="com.zy.ticket.model.vo.TicketReportVO"> <result column="mapKey" property="mapKey" javaType="String"/> <result column="zqCode" property="zqCode" javaType="String"/> <result column="zqJc" property="zqJc" javaType="String"/> <result column="tradeName" property="tradeName" javaType="String"/> <result column="tradeCode" property="tradeCode" javaType="String"/> <result column="reportDate" property="reportDate" javaType="String"/> <result column="companyCount" property="companyCount" javaType="Integer"/> <result column="totalAssets" property="totalAssets" javaType="BigDecimal"/> <result column="totalAssetsRank" property="totalAssetsRank" javaType="Integer"/> <result column="totalAssetsTranscend" property="totalAssetsTranscend" javaType="BigDecimal"/> </resultMap>
Mapper:
@MapKey("mapKey") Map<String,TicketReportVO> getZys();
Service:
Map<String,TicketReportVO> zysMap = zyTicketReportMapper.getZys();
zysMap.get(vo.getZqCode()+"-"+vo.getTradeCode()+"-"+vo.getReportDate()).getLeverageRatio()
2，insert语句插入的字段越少，速度越快。以下4.6万条数据，只需4秒。
<insert id="baseInsert" parameterType="java.util.List"> <selectKey resultType="java.lang.Long" keyProperty="id" order="AFTER"> SELECT LAST_INSERT_ID() </selectKey> insert into zy_ticket_report (zq_code, zq_jc,trade_name, trade_code, report_date,company_count) values <foreach collection="list" item="item" separator=","> (#{item.zqCode}, #{item.zqJc},#{item.tradeName}, #{item.tradeCode}, #{item.reportDate},#{item.companyCount}) </foreach> ;COMMIT; </insert>
3，如果同一个表的insert和updat在一个事务里操作，在insert语句后写commit，手动进行数据库提交，速度会提高很多。
4，只有insert操作的时候，不需要去添加事务处理。
Springboot+Mybatis+Mysql 关于一次报表数据计算的优化经历
原文：https://www.cnblogs.com/fugitive/p/13704879.html