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Thai Macro Economy 2026-07-24 17:17 1 views

Energy REITs: A Two-way Commitment between Capital and Industry – The Financial Bond in the Era of Green Power and Computing Power

Energy REITs are rapidly developing in China's capital market, with underlying assets covering wind, solar, hydropower and other green sectors. Driven by the Dual Carbon Goals and the Computing Power Nation strategy, Energy REITs become a vital financial bond linking green power and the digital economy, enabling the investment-construction-operation-exit capital cycle and bringing strategic opportunities for new energy industries.

Energy REITs: A Two-way Commitment between Capital and Industry – The Financial Bond in the Era of Green Power and Computing Power

Energy REITs: A Two-way Commitment between Capital and Industry – The Financial Bond in the Era of Green Power and Computing Power

Keywords

Energy REITs; Dual Carbon Goals; Computing Era; Asset Securitization; Green Finance

Introduction

From "sparks of fire" to "green matrix," energy infrastructure public REITs (hereinafter referred to as "Energy REITs") have carved a unique growth path in China's capital market. To date, nine Energy REITs have been listed domestically, with total initial fundraising exceeding 20 billion yuan. The underlying assets comprehensively cover core green sectors such as wind power, solar photovoltaics, hydropower, and natural gas power generation. This is not only an institutional innovation in the capital market but also a vivid practice of financial services supporting the real economy and national strategies.

Driven by both the Dual Carbon Goals and the "Computing Power Nation" strategy, Energy REITs are evolving from a mere financing tool into an important financial bond linking green electricity and the digital economy. Experts interviewed by China Business Journal noted that Energy REITs possess both "anti-cyclical" and "high-prosperity" attributes. As the "Computing Power Era" arrives, the demand for a "green power foundation" is growing, bringing unprecedented strategic opportunities and a clear development outlook for Energy REITs.

1. Unlocking the Capital Cycle: From "Investment-Construction-Operation-Exit" to "Exchanging Stock for Increment"

For the renewable energy industry, the core value of REITs lies in completing the full capital cycle of "investment-construction-operation-exit." Zeng Gang, Deputy Director of the National Finance and Development Laboratory, pointed out to reporters that projects such as wind and solar require huge upfront capital investment and have long payback periods, putting power generation companies under high pressure of debt ratios. By securitizing and listing mature operating assets through REITs, companies can recoup idle funds at once and invest them into new rounds of development and construction, achieving a virtuous cycle of "exchanging stock for increment."

This mechanism effectively reduces the financial leverage of the original equity holders, broadens financing channels, and structurally eliminates the industry's long-standing problem of "emphasizing construction while neglecting exit." As Zhu Yuanwei, President of the Shanghai Ruis Real Estate Finance Research Institute, stated: "New energy projects require large upfront investment and long payback periods. REITs provide companies with long-term funds that match the asset's operating life, reducing financing costs while increasing cash flow."

Innovations in capital increase are equally remarkable. In January 2026, the first clean energy capital increase project in China, the AVIC Jingneng International REIT, successfully listed its expanded shares, pioneering the "solar + hydropower" mixed capital increase model, raising 2.922 billion yuan. This not only helped companies revitalize existing assets but also smoothed the cyclical fluctuations of single assets through the complementary effect of water and solar, providing a replicable demonstration sample for the industry.

Notably, the transparency requirements of REITs' information disclosure and operational management standards push renewable energy companies to improve their asset management capabilities. In 2025, multiple Energy REITs exceeded their annual distributable amount targets, directly reflecting improved operational quality. Zhu Yuanwei emphasized: "Energy REITs channel capital market funds into the clean energy field, making them an important tool for financial services to support the real economy, achieve the Dual Carbon Goals, and accomplish the 'five major articles'."

Energy REITs asset operation diagram

2. "Stabilizer" of the Capital Market: Filling the Asset Gap between Fixed Income and Equity

For the capital market, Energy REITs also create unique value. Zhu Yuanwei pointed out that Energy REITs diversify investment products and provide stable dividend options. More critically, Energy REITs have low correlation with stocks and bonds, making their allocation value prominent against the backdrop of "asset shortage."

Zeng Gang further explained the unique position of Energy REITs: "Energy REITs fill the asset gap between fixed income and equity." Their underlying assets are power infrastructure with stable cash flows, low correlation with macroeconomic cycles, and anti-inflation properties, providing highly suitable investment targets for long-term allocation funds such as insurance and pension funds.

This allocation value has been fully validated in the market. The China Huaxia CGN Clean Energy REIT listed in February 2026 saw its offline investor valid subscription multiple exceed 340 times, public investor valid subscription multiple about 392 times, and total subscription funds before proportional allocation exceeded 160 billion yuan. This data clearly demonstrates the strong appeal of high-quality clean energy assets in the capital market.

In terms of returns, Energy REITs have also delivered "real gold and silver" for investors. Data show that since listing, the secondary market performance of Energy REITs has consistently ranked among the top, with some products seeing adjusted gains exceeding 30%. In 2025, the actual completion rate of the annual distributable amount for multiple Energy REITs exceeded 105%. Specifically on dividend data, Shanghai-listed Energy REITs have completed a total of 29 dividends since listing, distributing a total of over 4.12 billion yuan, fully demonstrating the strong cash flow generation capacity of new energy assets.

This stable dividend capability not only strengthens market confidence and attracts broader public investor participation but also effectively promotes the diversification and maturity of the capital market product structure. Against the backdrop of increasing global economic uncertainty, Energy REITs, with their "anti-cyclical" attribute, provide investors with a stable and reliable value investment path.

3. Strategic Opportunities in the Computing Era: From "Stable Utilities" to "Hard Foundation of the Digital Economy"

"The arrival of the computing era makes the development prospect of Energy REITs clearer," said Zhu Yuanwei. Data centers are typical high-energy-consumption facilities, with single-cabinet power density continuing to climb, making green power a rigid demand. Energy REITs have the advantages of strong cash flow predictability and high operational maturity, making them an excellent scenario for practicing "computing-electricity integration."

This judgment has received strong support at the policy level. "Computing-electricity synergy" has been written into the national "15th Five-Year Plan," with policies clearly requiring that from 2026, the proportion of green power used in new computing facilities must reach 80%. This means that clean energy assets are undergoing a reshaping of their valuation system—upgrading from traditional "stable utilities" to the "hard foundation of the digital economy," with their strategic position and market premium significantly enhanced.

Zeng Gang believes that in the context of the computing era, the development space for Energy REITs will continue to expand along three paths: first, the migration of computing center sites to western regions rich in clean energy will drive a large number of wind, solar, water, and storage assets into the REITs underlying pool; second, the demonstration effect of the "solar + hydropower" complementary capital increase model will promote the issuance of more mixed and diversified energy asset portfolios, enhancing the fund's anti-volatility capability; third, as storage assets mature and inter-institutional REIT pilot programs advance, the asset coverage boundary of REITs will further expand.

In the future, more innovative combinations such as "wind-solar-storage integration" and "data center + supporting renewable energy" will emerge, aligning with industrial development trends and optimizing income stability through asset portfolios. However, Zhu Yuanwei also cautioned that the development of Energy REITs in the computing era will exhibit structural differentiation, with targets possessing high-quality underlying assets, strong capital increase capabilities, and innovative portfolio models becoming more competitive.

4. The "Golden Age" of Expansion: Policy Dividends and Market Potential Continue to Unleash

Looking ahead, the development of Energy REITs is entering a normalized and steady expansion period. On one hand, China has accumulated a huge stock of energy infrastructure, but the potential to revitalize existing assets through the capital market has not been fully unleashed. With the continuous improvement of supporting systems and the sustained injection of high-quality assets, Energy REITs are becoming an effective tool for revitalizing existing assets.

On the other hand, the booming digital economy places higher demands on power infrastructure. With the accelerated deployment of computing infrastructure such as AI and big data centers, the demand for stable and green power across society is growing. By completing the capital loop, Energy REITs can precisely channel social funds into the construction of new power systems, providing a green and solid energy guarantee for computing infrastructure.

"Policy dividends continue to be released. In 2026, the REITs market focuses on three main lines: 'anti-cyclical,' 'high prosperity,' and 'strong capital increase.' Energy REITs simultaneously possess the dual attributes of 'anti-cyclical' and 'high prosperity,' and are expected to continue expanding in normalized issuance," Zhu Yuanwei summarized.

Zeng Gang is optimistic about the development prospects of Energy REITs. He believes that driven by both the Dual Carbon Goals and the "Computing Power Nation" strategy, Energy REITs are expected to usher in a "Golden Age" of continuous expansion. This is not only an important achievement of China's financial innovation but also a vivid manifestation of financial services supporting the real economy and national strategic transformation.

Conclusion

From "sparks of fire" to "green matrix," the successful practice of Energy REITs shows that capital and industry can achieve mutual commitment and mutual promotion. For the renewable energy industry, it unlocks the complete capital cycle of "investment-construction-operation-exit," solving the long-standing capital exit problem that has troubled the industry; for the capital market, it fills the asset gap between fixed income and equity, providing high-quality investment products with stable dividends; for national strategy, it becomes an important financial bond linking green power and the digital economy, providing strong financial support for the Dual Carbon Goals and the "Computing Power Nation" strategy.

With the full arrival of the computing era, green power will become the most scarce strategic resource. Energy REITs, with their unique institutional design, stable cash flow performance, and clear policy orientation, are standing at the starting point of a new development cycle. It can be expected that under the dual drive of policy dividends and market potential, Energy REITs will continue to expand, bringing more value to investors, injecting stronger momentum into industrial development, and providing more solid financial support for national strategy.

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  1. CONNECT:[ UseTime:0.001356s ] mysql:host=127.0.0.1;port=3306;dbname=cjgpcs;charset=utf8mb4
  2. SHOW FULL COLUMNS FROM `g3ys_config` [ RunTime:0.003963s ]
  3. SELECT `value` FROM `g3ys_config` WHERE `name` = 'timezone' AND `subsite_id` = '46' LIMIT 1 [ RunTime:0.000731s ]
  4. SHOW FULL COLUMNS FROM `g3ys_route` [ RunTime:0.004704s ]
  5. SELECT * FROM `g3ys_route` WHERE ( `subsite_id` = '46' OR `subsite_id` = '0' ) AND `module` = 'home' AND `status` = 1 ORDER BY `sort` DESC,`id` ASC [ RunTime:0.001122s ]
  6. SHOW FULL COLUMNS FROM `g3ys_theme` [ RunTime:0.005156s ]
  7. SELECT `paginator` FROM `g3ys_theme` WHERE `module` = 'home' AND `name` = 'thaiptt' AND `subsite_id` = '46' LIMIT 1 [ RunTime:0.001116s ]
  8. SHOW FULL COLUMNS FROM `g3ys_member` [ RunTime:0.011095s ]
  9. SELECT * FROM `g3ys_member` WHERE `id` = 0 AND `subsite_id` = '46' LIMIT 1 [ RunTime:0.001574s ]
  10. SHOW FULL COLUMNS FROM `g3ys_lang` [ RunTime:0.010020s ]
  11. SELECT * FROM `g3ys_lang` WHERE `subsite_id` = 46 AND ( ( LOWER(name) = 'en' ) OR `subtag` = 'en' ) AND `status` = 1 ORDER BY `id` ASC LIMIT 1 [ RunTime:0.002212s ]
  12. SHOW FULL COLUMNS FROM `g3ys_document` [ RunTime:0.004711s ]
  13. SELECT `id`,`document_type` FROM `g3ys_document` WHERE `subsite_id` = 46 AND `name` = 'neng-yuan-reits-zi-ben-yu-chan-ye-de-shuang-xiang-ben-fu-lv-se-dian-li-yu-suan-li-shi-dai-de-jin-ron' AND `status` IN ('1','2') LIMIT 1 [ RunTime:0.009286s ]
  14. SELECT * FROM `g3ys_document` WHERE ( `name` = '5600' OR `id` = '5600' ) AND `subsite_id` = 46 LIMIT 1 [ RunTime:0.015891s ]
  15. SHOW TABLES LIKE 'g3ys_document_article' [ RunTime:0.009458s ]
  16. SHOW FULL COLUMNS FROM `g3ys_document_article` [ RunTime:0.005036s ]
  17. SELECT * FROM `g3ys_document_article` WHERE `document_id` = '5600' LIMIT 1 [ RunTime:0.001059s ]
  18. SHOW FULL COLUMNS FROM `g3ys_total` [ RunTime:0.004877s ]
  19. SELECT * FROM `g3ys_total` WHERE `target_id` = '5600' LIMIT 1 [ RunTime:0.001577s ]
  20. SHOW TABLES LIKE 'g3ys_document_article_lang' [ RunTime:0.006234s ]
  21. SHOW FULL COLUMNS FROM `g3ys_document_article_lang` [ RunTime:0.003874s ]
  22. SELECT * FROM `g3ys_document_article_lang` WHERE `subsite_id` = '46' AND `lang` = 'en' AND `document_id` = '5600' [ RunTime:0.010863s ]
  23. SHOW FULL COLUMNS FROM `g3ys_document_article_lang` [ RunTime:0.004977s ]
  24. SHOW TABLES LIKE 'g3ys_category_lang' [ RunTime:0.005894s ]
  25. SHOW FULL COLUMNS FROM `g3ys_category_lang` [ RunTime:0.003191s ]
  26. SELECT * FROM `g3ys_category_lang` WHERE `subsite_id` = '46' AND `category_id` = '1845' AND `lang` = 'en' LIMIT 1 [ RunTime:0.001057s ]
  27. SELECT * FROM `g3ys_total` WHERE `target_id` = '5600' LIMIT 1 [ RunTime:0.000885s ]
  28. UPDATE `g3ys_total` SET `view_total` = `view_total` + 1 WHERE `target_id` = '5600' [ RunTime:0.003353s ]
  29. SHOW FULL COLUMNS FROM `g3ys_record` [ RunTime:0.010083s ]
  30. SELECT `id` FROM `g3ys_record` WHERE `subsite_id` = '46' AND `type` = 'article' AND `url` = 'https://www.thaiptt.com/neng-yuan-reits-zi-ben-yu-chan-ye-de-shuang-xiang-ben-fu-lv-se-dian-li-yu-suan-li-shi-dai-de-jin-ron' AND `create_time` >= 1784893392 AND ( `visitor_id` = '05e1975cb1e154acd9fc19d6a52503bb' OR `session_id` = '02f5c77caf7688c090672f15bf9874e8' ) LIMIT 1 [ RunTime:0.002364s ]
  31. INSERT INTO `g3ys_record` SET `subsite_id` = '46' , `uid` = '0' , `visitor_id` = '05e1975cb1e154acd9fc19d6a52503bb' , `session_id` = '02f5c77caf7688c090672f15bf9874e8' , `type` = 'article' , `target_id` = '5600' , `target_type` = 0 , `category_id` = '1845' , `title` = 'Energy REITs: A Two-way Commitment between Capital and Industry – The Financial Bond in the Era of Green Power and Computing Power' , `url` = 'https://www.thaiptt.com/neng-yuan-reits-zi-ben-yu-chan-ye-de-shuang-xiang-ben-fu-lv-se-dian-li-yu-suan-li-shi-dai-de-jin-ron' , `path` = '/neng-yuan-reits-zi-ben-yu-chan-ye-de-shuang-xiang-ben-fu-lv-se-dian-li-yu-suan-li-shi-dai-de-jin-ron' , `query_string` = '' , `referer` = '' , `referer_domain` = '' , `source_type` = 'direct' , `source_domain` = '' , `search_engine` = '' , `search_keyword` = '' , `utm_source` = '' , `utm_medium` = '' , `utm_campaign` = '' , `utm_term` = '' , `utm_content` = '' , `ip` = '216.73.217.145' , `user_agent` = 'Mozilla/5.0 AppleWebKit/537.36 (KHTML, like Gecko; compatible; ClaudeBot/1.0; +claudebot@anthropic.com)' , `device_type` = 'pc' , `browser` = '其他' , `browser_version` = '' , `os` = '其他' , `os_version` = '' , `language` = '' , `is_spider` = 0 , `spider_name` = '' , `status_code` = 200 , `country` = '' , `province` = '' , `city` = '' , `district` = '' , `isp` = '' , `region_code` = '' , `geo_status` = 0 , `geo_time` = 0 , `create_time` = 1784893452 , `update_time` = 1784893452 [ RunTime:0.006446s ]
  32. SHOW FULL COLUMNS FROM `g3ys_comment` [ RunTime:0.008852s ]
  33. SELECT COUNT(*) AS think_count FROM `g3ys_comment` WHERE `target_id` = '5600' AND `pid` = '0' [ RunTime:0.001269s ]
  34. SHOW FULL COLUMNS FROM `g3ys_model` [ RunTime:0.010389s ]
  35. SELECT `id`,`name`,`title`,`field_group` FROM `g3ys_model` WHERE `extend` = 0 AND `id` <> 1 AND `subsite_id` IN ('0','46') AND `status` = 1 [ RunTime:0.002858s ]
  36. SHOW TABLES LIKE 'g3ys_paragraph' [ RunTime:0.004567s ]
  37. SHOW TABLES LIKE 'g3ys_paragraph_lang' [ RunTime:0.004879s ]
  38. SHOW TABLES LIKE 'g3ys_gallery' [ RunTime:0.005958s ]
  39. SHOW TABLES LIKE 'g3ys_gallery_lang' [ RunTime:0.006277s ]
  40. SHOW TABLES LIKE 'g3ys_video' [ RunTime:0.005336s ]
  41. SHOW TABLES LIKE 'g3ys_video_lang' [ RunTime:0.007232s ]
  42. SHOW TABLES LIKE 'g3ys_faq' [ RunTime:0.003511s ]
  43. SHOW TABLES LIKE 'g3ys_faq_lang' [ RunTime:0.005668s ]
  44. SHOW TABLES LIKE 'g3ys_blockquote' [ RunTime:0.003825s ]
  45. SHOW TABLES LIKE 'g3ys_blockquote_lang' [ RunTime:0.003556s ]
  46. SHOW TABLES LIKE 'g3ys_cards' [ RunTime:0.004011s ]
  47. SHOW TABLES LIKE 'g3ys_cards_lang' [ RunTime:0.003442s ]
  48. SHOW TABLES LIKE 'g3ys_objects' [ RunTime:0.003754s ]
  49. SHOW TABLES LIKE 'g3ys_objects_lang' [ RunTime:0.003551s ]
  50. SHOW TABLES LIKE 'g3ys_videos' [ RunTime:0.003036s ]
  51. SHOW TABLES LIKE 'g3ys_videos_lang' [ RunTime:0.005220s ]
  52. SHOW TABLES LIKE 'g3ys_audios' [ RunTime:0.005225s ]
  53. SHOW TABLES LIKE 'g3ys_audios_lang' [ RunTime:0.006199s ]
  54. SHOW TABLES LIKE 'g3ys_files' [ RunTime:0.004629s ]
  55. SHOW TABLES LIKE 'g3ys_files_lang' [ RunTime:0.006107s ]
  56. SHOW TABLES LIKE 'g3ys_richmedia' [ RunTime:0.003241s ]
  57. SHOW TABLES LIKE 'g3ys_richmedia_lang' [ RunTime:0.004722s ]
  58. SHOW FULL COLUMNS FROM `g3ys_paragraph` [ RunTime:0.004237s ]
  59. SELECT * FROM `g3ys_paragraph` WHERE `document_id` = 5600 AND `subsite_id` = '46' AND `status` = 1 ORDER BY `sort` ASC,`id` ASC [ RunTime:0.001431s ]
  60. SHOW FULL COLUMNS FROM `g3ys_gallery` [ RunTime:0.003297s ]
  61. SELECT * FROM `g3ys_gallery` WHERE `document_id` = 5600 AND `subsite_id` = 46 AND `status` = 1 ORDER BY `sort` ASC,`id` ASC [ RunTime:0.001836s ]
  62. SHOW FULL COLUMNS FROM `g3ys_video` [ RunTime:0.003281s ]
  63. SELECT * FROM `g3ys_video` WHERE `document_id` = 5600 AND `subsite_id` = 46 AND `status` = 1 ORDER BY `sort` ASC,`id` ASC [ RunTime:0.001422s ]
  64. SHOW FULL COLUMNS FROM `g3ys_faq` [ RunTime:0.003299s ]
  65. SELECT * FROM `g3ys_faq` WHERE `document_id` = 5600 AND `subsite_id` = 46 AND `status` = 1 ORDER BY `sort` ASC,`id` ASC [ RunTime:0.001090s ]
  66. SHOW FULL COLUMNS FROM `g3ys_blockquote` [ RunTime:0.003635s ]
  67. SELECT * FROM `g3ys_blockquote` WHERE `document_id` = 5600 AND `subsite_id` = 46 AND `status` = 1 ORDER BY `sort` ASC,`id` ASC [ RunTime:0.001159s ]
  68. SHOW FULL COLUMNS FROM `g3ys_cards` [ RunTime:0.004062s ]
  69. SELECT * FROM `g3ys_cards` WHERE `document_id` = 5600 AND `subsite_id` = '46' AND `status` = 1 ORDER BY `sort` ASC,`id` ASC [ RunTime:0.001714s ]
  70. SHOW FULL COLUMNS FROM `g3ys_objects` [ RunTime:0.003087s ]
  71. SELECT * FROM `g3ys_objects` WHERE `document_id` = 5600 AND `subsite_id` = '46' AND `status` = 1 ORDER BY `sort` ASC,`id` ASC [ RunTime:0.001477s ]
  72. SHOW FULL COLUMNS FROM `g3ys_videos` [ RunTime:0.003336s ]
  73. SELECT * FROM `g3ys_videos` WHERE `document_id` = 5600 AND `subsite_id` = '46' AND `status` = 1 ORDER BY `sort` ASC,`id` ASC [ RunTime:0.001347s ]
  74. SHOW FULL COLUMNS FROM `g3ys_audios` [ RunTime:0.003384s ]
  75. SELECT * FROM `g3ys_audios` WHERE `document_id` = 5600 AND `subsite_id` = '46' AND `status` = 1 ORDER BY `sort` ASC,`id` ASC [ RunTime:0.001246s ]
  76. SHOW FULL COLUMNS FROM `g3ys_files` [ RunTime:0.004659s ]
  77. SELECT * FROM `g3ys_files` WHERE `document_id` = 5600 AND `subsite_id` = '46' AND `status` = 1 ORDER BY `sort` ASC,`id` ASC [ RunTime:0.001195s ]
  78. SHOW FULL COLUMNS FROM `g3ys_richmedia` [ RunTime:0.004216s ]
  79. SELECT * FROM `g3ys_richmedia` WHERE `document_id` = 5600 AND `subsite_id` = '46' AND `status` = 1 ORDER BY `sort` ASC,`id` ASC [ RunTime:0.001554s ]
  80. SELECT * FROM `g3ys_document` WHERE `category_id` = 1845 AND `subsite_id` = 46 AND `pid` = '0' AND `status` = '1' AND ( ( sort > 0) or ( sort = 0 and id < 5600) ) ORDER BY `sort` ASC,`id` DESC LIMIT 1 [ RunTime:0.002229s ]
  81. SELECT * FROM `g3ys_document` WHERE `category_id` = 1845 AND `subsite_id` = 46 AND `pid` = '5526' AND `status` = '1' ORDER BY `sort` ASC,`id` DESC LIMIT 1 [ RunTime:0.002155s ]
  82. SELECT * FROM `g3ys_document_article_lang` WHERE `subsite_id` = '46' AND `lang` = 'en' AND `document_id` = '5526' [ RunTime:0.005923s ]
  83. SELECT * FROM `g3ys_document` WHERE `category_id` = 1845 AND `subsite_id` = 46 AND `pid` = '5600' AND `status` = '1' AND `document_type` = 0 ORDER BY `sort` DESC,`id` ASC LIMIT 1 [ RunTime:0.001593s ]
  84. SELECT * FROM `g3ys_document` WHERE `category_id` = 1845 AND `subsite_id` = 46 AND `pid` = '0' AND `status` = '1' AND `document_type` = 0 AND ( ( sort>0 and sort <= 0 and id!=5600) or ( sort = 0 and id > 5600) ) ORDER BY `sort` DESC,`id` ASC LIMIT 1 [ RunTime:0.001518s ]
  85. SELECT * FROM `g3ys_route` WHERE ( `subsite_id` = '46' OR `subsite_id` = '0' ) AND `module` = 'home' AND `status` = 1 ORDER BY `sort` DESC,`id` ASC [ RunTime:0.001751s ]
  86. SELECT * FROM `g3ys_route` WHERE ( `subsite_id` = '46' OR `subsite_id` = '0' ) AND `module` = 'home' AND `status` = 1 ORDER BY `sort` DESC,`id` ASC [ RunTime:0.000944s ]
  87. SELECT * FROM `g3ys_route` WHERE ( `subsite_id` = '46' OR `subsite_id` = '0' ) AND `module` = 'home' AND `status` = 1 ORDER BY `sort` DESC,`id` ASC [ RunTime:0.002459s ]
  88. SELECT * FROM `g3ys_route` WHERE ( `subsite_id` = '46' OR `subsite_id` = '0' ) AND `module` = 'home' AND `status` = 1 ORDER BY `sort` DESC,`id` ASC [ RunTime:0.001044s ]
  89. SELECT * FROM `g3ys_route` WHERE ( `subsite_id` = '46' OR `subsite_id` = '0' ) AND `module` = 'home' AND `status` = 1 ORDER BY `sort` DESC,`id` ASC [ RunTime:0.001113s ]
  90. SELECT * FROM `g3ys_route` WHERE ( `subsite_id` = '46' OR `subsite_id` = '0' ) AND `module` = 'home' AND `status` = 1 ORDER BY `sort` DESC,`id` ASC [ RunTime:0.001044s ]
  91. SELECT * FROM `g3ys_route` WHERE ( `subsite_id` = '46' OR `subsite_id` = '0' ) AND `module` = 'home' AND `status` = 1 ORDER BY `sort` DESC,`id` ASC [ RunTime:0.002210s ]
  92. SELECT * FROM `g3ys_route` WHERE ( `subsite_id` = '46' OR `subsite_id` = '0' ) AND `module` = 'home' AND `status` = 1 ORDER BY `sort` DESC,`id` ASC [ RunTime:0.003288s ]
  93. SELECT * FROM `g3ys_category_lang` WHERE `subsite_id` = '46' AND `category_id` = '1843' AND `lang` = 'en' LIMIT 1 [ RunTime:0.001271s ]
  94. SELECT * FROM `g3ys_category_lang` WHERE `subsite_id` = '46' AND `category_id` = '1842' AND `lang` = 'en' LIMIT 1 [ RunTime:0.000784s ]
  95. SELECT * FROM `g3ys_category_lang` WHERE `subsite_id` = '46' AND `category_id` = '1841' AND `lang` = 'en' LIMIT 1 [ RunTime:0.000784s ]
  96. SELECT * FROM `g3ys_total` WHERE `target_id` = '5600' LIMIT 1 [ RunTime:0.001209s ]
  97. SELECT * FROM `g3ys_route` WHERE ( `subsite_id` = '46' OR `subsite_id` = '0' ) AND `module` = 'home' AND `status` = 1 ORDER BY `sort` DESC,`id` ASC [ RunTime:0.001120s ]
  98. SELECT `id`,`uid`,`name`,`title`,`category_id`,`description`,`pid`,`model_id`,`position`,`url`,`pic`,`sort`,`create_time`,`update_time`,`status`,`price`,`brand`,`percent`,`keywords`,`seotitle`,`subsite_id`,`intro`,`pics`,`tags`,`error`,`lat`,`lng`,`country`,`province`,`city`,`district`,`community`,`sync`,`shorttitle`,`template`,`video`,`show_groups`,`relative`,`money_type`,`document_type`,`object_type`,`object_id`,`object_category_id`,`object_sort`,`object_position`,`attr`,`attr_id`,`buy_groups`,`discount`,`pics_data`,`spec`,`object_status`,`audio`,`is_single`,`is_commission`,`commission`,`is_discount`,`category_ids`,`stock`,`volume`,`weight`,`combined`,`object_category_ids`,`combo` FROM `g3ys_document` `a` INNER JOIN `g3ys_total` `b` ON `a`.`id`=`b`.`target_id` INNER JOIN `g3ys_document_article` `c` ON `a`.`id`=`c`.`document_id` WHERE `subsite_id` = 46 AND `category_id` = 1845 AND `status` = '1' AND `model_id` = 2 AND `document_type` = 0 ORDER BY `sort` DESC,`id` DESC LIMIT 0,8 [ RunTime:0.003376s ]
  99. SELECT * FROM `g3ys_document_article_lang` WHERE `subsite_id` = '46' AND `lang` = 'en' AND `document_id` IN ('5600','5526','5263') [ RunTime:0.012284s ]
  100. SELECT * FROM `g3ys_route` WHERE ( `subsite_id` = '46' OR `subsite_id` = '0' ) AND `module` = 'home' AND `status` = 1 ORDER BY `sort` DESC,`id` ASC [ RunTime:0.001476s ]
  101. SELECT * FROM `g3ys_route` WHERE ( `subsite_id` = '46' OR `subsite_id` = '0' ) AND `module` = 'home' AND `status` = 1 ORDER BY `sort` DESC,`id` ASC [ RunTime:0.000965s ]
  102. SELECT * FROM `g3ys_route` WHERE ( `subsite_id` = '46' OR `subsite_id` = '0' ) AND `module` = 'home' AND `status` = 1 ORDER BY `sort` DESC,`id` ASC [ RunTime:0.001231s ]
  103. SELECT * FROM `g3ys_route` WHERE ( `subsite_id` = '46' OR `subsite_id` = '0' ) AND `module` = 'home' AND `status` = 1 ORDER BY `sort` DESC,`id` ASC [ RunTime:0.000828s ]
  104. SELECT * FROM `g3ys_route` WHERE ( `subsite_id` = '46' OR `subsite_id` = '0' ) AND `module` = 'home' AND `status` = 1 ORDER BY `sort` DESC,`id` ASC [ RunTime:0.001302s ]
  105. SELECT * FROM `g3ys_route` WHERE ( `subsite_id` = '46' OR `subsite_id` = '0' ) AND `module` = 'home' AND `status` = 1 ORDER BY `sort` DESC,`id` ASC [ RunTime:0.000914s ]
  106. SELECT * FROM `g3ys_route` WHERE ( `subsite_id` = '46' OR `subsite_id` = '0' ) AND `module` = 'home' AND `status` = 1 ORDER BY `sort` DESC,`id` ASC [ RunTime:0.000801s ]
  107. SELECT * FROM `g3ys_route` WHERE ( `subsite_id` = '46' OR `subsite_id` = '0' ) AND `module` = 'home' AND `status` = 1 ORDER BY `sort` DESC,`id` ASC [ RunTime:0.000976s ]
  108. SELECT * FROM `g3ys_route` WHERE ( `subsite_id` = '46' OR `subsite_id` = '0' ) AND `module` = 'home' AND `status` = 1 ORDER BY `sort` DESC,`id` ASC [ RunTime:0.001359s ]
  109. SHOW FULL COLUMNS FROM `g3ys_tags` [ RunTime:0.004377s ]
  110. SELECT * FROM `g3ys_tags` WHERE `subsite_id` = 46 AND `status` = 1 ORDER BY `sort` DESC,`id` DESC LIMIT 12 [ RunTime:0.002612s ]
  111. SELECT * FROM `g3ys_category_lang` WHERE `subsite_id` = '46' AND `category_id` = '2098' AND `lang` = 'en' LIMIT 1 [ RunTime:0.000993s ]
  112. SELECT * FROM `g3ys_category_lang` WHERE `subsite_id` = '46' AND `category_id` = '2099' AND `lang` = 'en' LIMIT 1 [ RunTime:0.000910s ]
  113. SELECT * FROM `g3ys_category_lang` WHERE `subsite_id` = '46' AND `category_id` = '2100' AND `lang` = 'en' LIMIT 1 [ RunTime:0.001043s ]
0.908999s