2026年08月26日 Wednesday Insight into China-Singapore Capital Markets, Deep Diving into Global Asset Allocation
China-Singapore Cross-Border Financial Investment Research Global Asset Allocation
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In-depth Analysis of US Market Intraday Fluctuations: AI Giants Lead Rally and Energy Stocks Rebound, Market Sentiment Shifts

In-depth Analysis of US Market Intraday Fluctuations: AI Giants Lead Rally and Energy Stocks Rebound, Market Sentiment Shifts

On August 26, 2026, the US stock market experienced significant volatility, with intraday movements resembling a roller coaster. The rally led by AI giants and the strong rebound of traditional energy stocks formed a stark contrast, triggering widespread attention from investors as market sentiment shifted abruptly. This article will deeply analyze the driving factors behind this phenomenon and how investors should adjust their strategies to seize investment opportunities in the new landscape.

Overall Market Performance: Increased Index Volatility, Clear Sector Differentiation

After opening today, the three major US indices showed divergent trends. The Dow Jones Industrial Index opened slightly lower, then trended upward with fluctuations driven by the financial sector; the Nasdaq Index was supported by the strength of AI concept stocks, rallying strongly from the opening; the S&P 500 index showed a volatile pattern with accelerating sector rotation. In the afternoon, as energy stocks rebounded collectively, market sentiment improved significantly, with all three indices closing higher, but volatility increased markedly.

In terms of trading volume, today's total trading volume in the US market increased by about 15% compared to the previous trading day, with the technology and energy sectors contributing the main incremental funds. The market fear index VIX once broke through the 20 level intraday but closed back at 18.5, indicating that while investors have concerns, overall sentiment remains relatively stable.

AI Sector Fluctuations: Tech Giants Lead Market Sentiment

The most notable performance in today's US market was undoubtedly the strong showing of the AI sector. AI concept stocks represented by NVIDIA (NVDA) rose collectively, with NVIDIA's intraday gain once exceeding 7%, narrowing to a 5.2% close, reaching a new high in nearly two weeks. Tech giants like Microsoft (MSFT) and Google's parent Alphabet (GOOGL) also followed the trend, rising 3.8% and 3.2% respectively.

Analysts pointed out that today's AI sector fluctuations were mainly driven by multiple factors. First, the latest industry report shows that the global AI market size is expected to reach $1.5 trillion by 2030, with a compound annual growth rate exceeding 30%, far exceeding market expectations. Second, several Wall Street investment firms have upgraded ratings for AI-related stocks, believing that the commercialization process of AI technology is accelerating, and the profit prospects of related companies are clear.

In addition, rumors about NVIDIA's next-generation AI chip GTX 50, to be released soon, have also become a market focus. According to industry sources, the new chip's performance will improve by more than 40% over existing products, with significantly improved energy efficiency, further strengthening investor confidence in the AI sector.

Energy Sector Rebound: Dual Drivers of Geopolitics and Policy

In stark contrast to the AI sector, traditional energy stocks rebounded strongly today after several days of adjustment. Oil giants ExxonMobil (XOM) and Chevron (CVX) rose 4.5% and 4.1% respectively, while solar leader First Solar (FSLR) once surged by more than 8%.

Today's energy sector rebound was mainly driven by two factors. First, the geopolitical situation in the Middle East has become tense again, with markets concerned that global oil supplies might be disrupted, causing international oil prices to rise by more than 3% intraday. Second, the latest US clean energy policy shows a significant increase in subsidies for renewable energy projects, with expected investment of over $200 billion in the next five years, bringing substantial benefits to new energy companies.

Notably, today's energy sector rebound is not a one-time event. In terms of capital flows, over the past three trading days, the energy sector has seen cumulative net inflows of over $3.5 billion, indicating that institutional investors are gradually increasing their positions in this sector. Analysts believe that against the backdrop of accelerating global energy transition, the valuation restructuring of traditional and new energy sectors is still ongoing, and long-term investment value is worth looking forward to.

Market Sentiment Analysis: Capital Flows Reveal Investment Logic

Looking at today's capital flow data, market sentiment shows clear structural differentiation. The technology sector, especially AI-related stocks, has become a hot spot for capital inflows, with net inflows exceeding $8 billion in a single day. Meanwhile, the financial and consumer sectors experienced net outflows of about $1.5 billion and $1.2 billion respectively.

The behavior of institutional investors is particularly noteworthy. Large hedge funds significantly increased their holdings of AI concept stocks today while reducing some overvalued growth stocks. This "structural adjustment" operation indicates that institutional investors are reassessing the valuation of the technology sector, shifting from chasing concepts to focusing on actual profitability.

In the options market, today's US options trading volume increased by about 25% compared to the previous trading day, with S&P 500 index options and Nasdaq 100 index options contributing the main increment. Notably, the proportion of put options has increased, suggesting that some investors are starting to prepare for possible corrections, forming a contrast with the current optimistic market sentiment, indicating potential divergence in the market.

Expert Interpretation: Deep Logic Behind the Market Sentiment Shift

Regarding today's US market fluctuations, several market experts have expressed their views. Morgan Stanley's Chief US Equity Strategist stated: "Today's market performance reflects the strengthening of investor expectations for an economic soft landing. The strong performance of the AI sector shows that the market is full of confidence in economic growth driven by technological innovation; while the rebound of the energy sector indicates that against the backdrop of increasing geopolitical uncertainty, investors are reassessing the importance of energy security."

Goldman Sachs analysts pointed out: "The current market is at a critical period of style conversion. In the past few months, the performance gap between growth stocks and value stocks has narrowed significantly. The simultaneous strength of the AI and energy sectors today suggests that the market is seeking a new balance point, and investors should focus on high-quality stocks that combine both growth and value attributes."

Notably, today's remarks by Federal Reserve officials also provided new reference for the market. A Fed governor stated that the current trend of inflation decline is positive, but the labor market remains strong, providing more flexibility for monetary policy. The market widely expects that the Fed may announce an interest rate cut at the September meeting, but the magnitude may be limited, providing a relatively stable policy environment for the market.

Investment Strategy Recommendations: Seizing Opportunities in the New Landscape

Short-term Strategy: Focus on Sector Rotation Rhythm

For the current market landscape, investors should focus on sector rotation rhythm in the short term. First, although the AI sector is performing strongly, some individual stocks have shown obvious overbought conditions. Investors may consider适当 reducing positions in overly appreciated stocks while allocating to AI application area stocks with relatively reasonable valuations. Second, the energy sector's rebound may continue, but investors should focus on fundamental support, prioritizing traditional energy companies with stable cash flows and reasonable valuations, as well as new energy companies with clear policy benefits.

In addition, the financial sector has performed relatively weak recently, but with the strengthening of economic soft landing expectations, banking and insurance financial sub-sectors may face valuation recovery opportunities. Investors can focus on large financial institutions with good asset quality and valuations at historical lows.

Long-term Allocation: Focus on Structural Opportunities

Looking ahead, investors should focus on three major structural opportunities. First is the AI industry chain, from upstream chips and computing power to downstream application scenarios, AI technology is reshaping various industries, and related companies are expected to continuously benefit from this trend. Second is the energy transition. Under global carbon neutrality goals, both traditional and new energy companies will face transformation opportunities, and investors can focus on companies with competitive advantages in the transition process.

Third is global allocation. With the gradual recovery of the global economy, multinational companies are expected to experience performance growth. Investors can focus on global companies with strong competitive advantages in emerging markets and reasonable valuations.

Risk Management: Control Position Sizes, Diversify Investments

Against the backdrop of increasing market volatility, investors should pay more attention to risk management. First, control the proportion of positions in a single sector to avoid over-concentration. Second, appropriately allocate defensive assets such as high-dividend stocks and bonds to balance portfolio risk. Finally, regularly review the investment portfolio and adjust strategies promptly according to market changes.

Market Outlook: Investment Logic in the New Landscape

Looking ahead, the US stock market may enter a new landscape. On one hand, technological innovation will continue to drive the market, with investment opportunities in AI, clean energy and other areas worth attention; on the other hand, with the strengthening of economic soft landing expectations, value stocks are expected to see valuation recovery opportunities. Investors should remain flexible to seize investment opportunities brought by market style changes.

Overall, the intraday fluctuations of the US stock market on August 26, 2026 reflect that the market is seeking a new balance point. The simultaneous strength of the AI and energy sectors indicates that the market is shifting from a single growth or value style to a more balanced investment logic. Investors should closely follow this trend change and adjust investment strategies in a timely manner to seize opportunities in the new landscape.

Against the backdrop of multiple challenges facing the global economy, the US stock market still has relative attractiveness. Investors should remain rational, seeing both market structural opportunities and potential risks, and actively seize high-quality investment opportunities with controlled risk to achieve long-term stable returns.

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  1. CONNECT:[ UseTime:0.001014s ] mysql:host=127.0.0.1;port=3306;dbname=cjgpcs;charset=utf8mb4
  2. SHOW FULL COLUMNS FROM `g3ys_config` [ RunTime:0.002385s ]
  3. SELECT `value` FROM `g3ys_config` WHERE `name` = 'timezone' AND `subsite_id` = '38' LIMIT 1 [ RunTime:0.000716s ]
  4. SHOW FULL COLUMNS FROM `g3ys_route` [ RunTime:0.002540s ]
  5. SELECT * FROM `g3ys_route` WHERE ( `subsite_id` = '38' OR `subsite_id` = '0' ) AND `module` = 'home' AND `status` = 1 ORDER BY `sort` DESC,`id` ASC [ RunTime:0.000878s ]
  6. SHOW FULL COLUMNS FROM `g3ys_theme` [ RunTime:0.003117s ]
  7. SELECT `paginator` FROM `g3ys_theme` WHERE `module` = 'home' AND `name` = 'slogan' AND `subsite_id` = '38' LIMIT 1 [ RunTime:0.000758s ]
  8. SHOW FULL COLUMNS FROM `g3ys_lang` [ RunTime:0.006262s ]
  9. SELECT * FROM `g3ys_lang` WHERE `subsite_id` = 38 AND ( ( LOWER(name) = 'en-us' ) OR `subtag` = 'en-us' ) AND `status` = 1 ORDER BY `id` ASC LIMIT 1 [ RunTime:0.001234s ]
  10. SHOW FULL COLUMNS FROM `g3ys_member` [ RunTime:0.004241s ]
  11. SELECT * FROM `g3ys_member` WHERE `id` = 0 AND `subsite_id` = '38' LIMIT 1 [ RunTime:0.000994s ]
  12. SHOW FULL COLUMNS FROM `g3ys_document` [ RunTime:0.004799s ]
  13. SELECT `id`,`document_type` FROM `g3ys_document` WHERE `subsite_id` = 38 AND `name` = 'us-stock-market-intra-day-movement-analysis' AND `status` IN ('1','2') LIMIT 1 [ RunTime:0.003038s ]
  14. SELECT * FROM `g3ys_document` WHERE ( `name` = '6964' OR `id` = '6964' ) AND `subsite_id` = 38 LIMIT 1 [ RunTime:0.008463s ]
  15. SHOW TABLES LIKE 'g3ys_document_article' [ RunTime:0.002957s ]
  16. SHOW FULL COLUMNS FROM `g3ys_document_article` [ RunTime:0.001651s ]
  17. SELECT * FROM `g3ys_document_article` WHERE `document_id` = '6964' LIMIT 1 [ RunTime:0.000787s ]
  18. SHOW FULL COLUMNS FROM `g3ys_total` [ RunTime:0.002126s ]
  19. SELECT * FROM `g3ys_total` WHERE `target_id` = '6964' LIMIT 1 [ RunTime:0.000889s ]
  20. SHOW TABLES LIKE 'g3ys_document_article_lang' [ RunTime:0.002148s ]
  21. SHOW FULL COLUMNS FROM `g3ys_document_article_lang` [ RunTime:0.002390s ]
  22. SELECT * FROM `g3ys_document_article_lang` WHERE `subsite_id` = '38' AND `lang` = 'en-US' AND `document_id` = '6964' [ RunTime:0.007764s ]
  23. SHOW FULL COLUMNS FROM `g3ys_document_article_lang` [ RunTime:0.002347s ]
  24. SHOW TABLES LIKE 'g3ys_category_lang' [ RunTime:0.002355s ]
  25. SHOW FULL COLUMNS FROM `g3ys_category_lang` [ RunTime:0.001862s ]
  26. SELECT * FROM `g3ys_category_lang` WHERE `subsite_id` = '38' AND `category_id` = '1464' AND `lang` = 'en-US' LIMIT 1 [ RunTime:0.000718s ]
  27. SELECT * FROM `g3ys_total` WHERE `target_id` = '6964' LIMIT 1 [ RunTime:0.000675s ]
  28. UPDATE `g3ys_total` SET `view_total` = `view_total` + 1 WHERE `target_id` = '6964' [ RunTime:0.003147s ]
  29. SHOW FULL COLUMNS FROM `g3ys_record` [ RunTime:0.006252s ]
  30. SELECT `id` FROM `g3ys_record` WHERE `subsite_id` = '38' AND `type` = 'article' AND `url` = 'https://www.cninsgx.com/us-stock-market-intra-day-movement-analysis' AND `create_time` >= 1787725486 AND ( `visitor_id` = '3acfc11b00083e6057145ef45e0c75c2' OR `session_id` = '795591816f33fe07e1b428897e2737d7' ) LIMIT 1 [ RunTime:0.003463s ]
  31. INSERT INTO `g3ys_record` SET `subsite_id` = '38' , `uid` = '0' , `visitor_id` = '3acfc11b00083e6057145ef45e0c75c2' , `session_id` = '795591816f33fe07e1b428897e2737d7' , `type` = 'article' , `target_id` = '6964' , `target_type` = 0 , `category_id` = '1464' , `title` = 'In-depth Analysis of US Market Intraday Fluctuations: AI Giants Lead Rally and Energy Stocks Rebound, Market Sentiment Shifts' , `url` = 'https://www.cninsgx.com/us-stock-market-intra-day-movement-analysis' , `path` = '/us-stock-market-intra-day-movement-analysis' , `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` = '216.73.216.152' , `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` = 1787725546 , `update_time` = 1787725546 [ RunTime:0.002992s ]
  32. SHOW FULL COLUMNS FROM `g3ys_comment` [ RunTime:0.003305s ]
  33. SELECT COUNT(*) AS think_count FROM `g3ys_comment` WHERE `target_id` = '6964' AND `pid` = '0' [ RunTime:0.000764s ]
  34. SHOW FULL COLUMNS FROM `g3ys_model` [ RunTime:0.004122s ]
  35. SELECT `id`,`name`,`title`,`field_group` FROM `g3ys_model` WHERE `extend` = 0 AND `id` <> 1 AND `subsite_id` IN ('0','38') AND `status` = 1 [ RunTime:0.001091s ]
  36. SHOW TABLES LIKE 'g3ys_paragraph' [ RunTime:0.002385s ]
  37. SHOW TABLES LIKE 'g3ys_paragraph_lang' [ RunTime:0.002319s ]
  38. SHOW TABLES LIKE 'g3ys_gallery' [ RunTime:0.002179s ]
  39. SHOW TABLES LIKE 'g3ys_gallery_lang' [ RunTime:0.002236s ]
  40. SHOW TABLES LIKE 'g3ys_video' [ RunTime:0.002149s ]
  41. SHOW TABLES LIKE 'g3ys_video_lang' [ RunTime:0.003945s ]
  42. SHOW TABLES LIKE 'g3ys_faq' [ RunTime:0.003126s ]
  43. SHOW TABLES LIKE 'g3ys_faq_lang' [ RunTime:0.003426s ]
  44. SHOW TABLES LIKE 'g3ys_blockquote' [ RunTime:0.002591s ]
  45. SHOW TABLES LIKE 'g3ys_blockquote_lang' [ RunTime:0.002026s ]
  46. SHOW TABLES LIKE 'g3ys_cards' [ RunTime:0.002027s ]
  47. SHOW TABLES LIKE 'g3ys_cards_lang' [ RunTime:0.001889s ]
  48. SHOW TABLES LIKE 'g3ys_objects' [ RunTime:0.002016s ]
  49. SHOW TABLES LIKE 'g3ys_objects_lang' [ RunTime:0.002158s ]
  50. SHOW TABLES LIKE 'g3ys_videos' [ RunTime:0.002229s ]
  51. SHOW TABLES LIKE 'g3ys_videos_lang' [ RunTime:0.002532s ]
  52. SHOW TABLES LIKE 'g3ys_audios' [ RunTime:0.002168s ]
  53. SHOW TABLES LIKE 'g3ys_audios_lang' [ RunTime:0.002015s ]
  54. SHOW TABLES LIKE 'g3ys_files' [ RunTime:0.002022s ]
  55. SHOW TABLES LIKE 'g3ys_files_lang' [ RunTime:0.001913s ]
  56. SHOW TABLES LIKE 'g3ys_richmedia' [ RunTime:0.003284s ]
  57. SHOW TABLES LIKE 'g3ys_richmedia_lang' [ RunTime:0.003805s ]
  58. SHOW FULL COLUMNS FROM `g3ys_paragraph` [ RunTime:0.002381s ]
  59. SELECT * FROM `g3ys_paragraph` WHERE `document_id` = 6964 AND `subsite_id` = '38' AND `status` = 1 ORDER BY `sort` ASC,`id` ASC [ RunTime:0.000957s ]
  60. SHOW FULL COLUMNS FROM `g3ys_gallery` [ RunTime:0.002169s ]
  61. SELECT * FROM `g3ys_gallery` WHERE `document_id` = 6964 AND `subsite_id` = 38 AND `status` = 1 ORDER BY `sort` ASC,`id` ASC [ RunTime:0.000944s ]
  62. SHOW FULL COLUMNS FROM `g3ys_video` [ RunTime:0.002047s ]
  63. SELECT * FROM `g3ys_video` WHERE `document_id` = 6964 AND `subsite_id` = 38 AND `status` = 1 ORDER BY `sort` ASC,`id` ASC [ RunTime:0.001011s ]
  64. SHOW FULL COLUMNS FROM `g3ys_faq` [ RunTime:0.002049s ]
  65. SELECT * FROM `g3ys_faq` WHERE `document_id` = 6964 AND `subsite_id` = 38 AND `status` = 1 ORDER BY `sort` ASC,`id` ASC [ RunTime:0.001398s ]
  66. SHOW FULL COLUMNS FROM `g3ys_blockquote` [ RunTime:0.002002s ]
  67. SELECT * FROM `g3ys_blockquote` WHERE `document_id` = 6964 AND `subsite_id` = 38 AND `status` = 1 ORDER BY `sort` ASC,`id` ASC [ RunTime:0.000912s ]
  68. SHOW FULL COLUMNS FROM `g3ys_cards` [ RunTime:0.002537s ]
  69. SELECT * FROM `g3ys_cards` WHERE `document_id` = 6964 AND `subsite_id` = '38' AND `status` = 1 ORDER BY `sort` ASC,`id` ASC [ RunTime:0.000985s ]
  70. SHOW FULL COLUMNS FROM `g3ys_objects` [ RunTime:0.002129s ]
  71. SELECT * FROM `g3ys_objects` WHERE `document_id` = 6964 AND `subsite_id` = '38' AND `status` = 1 ORDER BY `sort` ASC,`id` ASC [ RunTime:0.000954s ]
  72. SHOW FULL COLUMNS FROM `g3ys_videos` [ RunTime:0.002149s ]
  73. SELECT * FROM `g3ys_videos` WHERE `document_id` = 6964 AND `subsite_id` = '38' AND `status` = 1 ORDER BY `sort` ASC,`id` ASC [ RunTime:0.000970s ]
  74. SHOW FULL COLUMNS FROM `g3ys_audios` [ RunTime:0.002526s ]
  75. SELECT * FROM `g3ys_audios` WHERE `document_id` = 6964 AND `subsite_id` = '38' AND `status` = 1 ORDER BY `sort` ASC,`id` ASC [ RunTime:0.000917s ]
  76. SHOW FULL COLUMNS FROM `g3ys_files` [ RunTime:0.002062s ]
  77. SELECT * FROM `g3ys_files` WHERE `document_id` = 6964 AND `subsite_id` = '38' AND `status` = 1 ORDER BY `sort` ASC,`id` ASC [ RunTime:0.001232s ]
  78. SHOW FULL COLUMNS FROM `g3ys_richmedia` [ RunTime:0.002083s ]
  79. SELECT * FROM `g3ys_richmedia` WHERE `document_id` = 6964 AND `subsite_id` = '38' AND `status` = 1 ORDER BY `sort` ASC,`id` ASC [ RunTime:0.000971s ]
  80. SELECT * FROM `g3ys_document` WHERE `category_id` = 1464 AND `subsite_id` = 38 AND `pid` = '0' AND `status` = '1' AND ( ( sort > 0) or ( sort = 0 and id < 6964) ) ORDER BY `sort` ASC,`id` DESC LIMIT 1 [ RunTime:0.001531s ]
  81. SELECT * FROM `g3ys_document` WHERE `category_id` = 1464 AND `subsite_id` = 38 AND `pid` = '6913' AND `status` = '1' ORDER BY `sort` ASC,`id` DESC LIMIT 1 [ RunTime:0.001234s ]
  82. SELECT * FROM `g3ys_document_article_lang` WHERE `subsite_id` = '38' AND `lang` = 'en-US' AND `document_id` = '6913' [ RunTime:0.007252s ]
  83. SELECT * FROM `g3ys_document` WHERE `category_id` = 1464 AND `subsite_id` = 38 AND `pid` = '6964' AND `status` = '1' AND `document_type` = 0 ORDER BY `sort` DESC,`id` ASC LIMIT 1 [ RunTime:0.001503s ]
  84. SELECT * FROM `g3ys_document` WHERE `category_id` = 1464 AND `subsite_id` = 38 AND `pid` = '0' AND `status` = '1' AND `document_type` = 0 AND ( ( sort>0 and sort <= 0 and id!=6964) or ( sort = 0 and id > 6964) ) ORDER BY `sort` DESC,`id` ASC LIMIT 1 [ RunTime:0.001374s ]
  85. SHOW FULL COLUMNS FROM `g3ys_file` [ RunTime:0.004031s ]
  86. SELECT * FROM `g3ys_file` WHERE `status` = 1 AND `id` = 6017 LIMIT 1 [ RunTime:0.001034s ]
  87. SELECT * FROM `g3ys_route` WHERE ( `subsite_id` = '38' OR `subsite_id` = '0' ) AND `module` = 'home' AND `status` = 1 ORDER BY `sort` DESC,`id` ASC [ RunTime:0.000856s ]
  88. SELECT * FROM `g3ys_total` WHERE `target_id` = '6964' LIMIT 1 [ RunTime:0.000866s ]
  89. SHOW FULL COLUMNS FROM `g3ys_ad_location` [ RunTime:0.002374s ]
  90. SELECT * FROM `g3ys_ad_location` WHERE `name` = 'ad-detail-full' AND `subsite_id` = '38' AND `status` = 1 LIMIT 1 [ RunTime:0.001036s ]
  91. SHOW FULL COLUMNS FROM `g3ys_ad` [ RunTime:0.003168s ]
  92. SELECT * FROM `g3ys_ad` WHERE `subsite_id` = '38' AND `ad_location_id` = '74' AND `status` = 1 AND `device` IN ('all','pc') AND ( `start_time` = 0 OR `start_time` <= 1787725547 ) AND ( `end_time` = 0 OR `end_time` >= 1787725547 ) ORDER BY `sort` DESC,`id` DESC [ RunTime:0.000979s ]
  93. SHOW FULL COLUMNS FROM `g3ys_ad_lang` [ RunTime:0.002122s ]
  94. SELECT * FROM `g3ys_ad_lang` WHERE `ad_id` = 74 AND `subsite_id` = '38' AND `lang` = 'en-US' [ RunTime:0.000792s ]
  95. SHOW FULL COLUMNS FROM `g3ys_ad_lang` [ RunTime:0.001830s ]
  96. SHOW FULL COLUMNS FROM `g3ys_tags` [ RunTime:0.002220s ]
  97. SELECT `title`,`color`,`description`,`seotitle`,`keyword`,`name`,`id` FROM `g3ys_tags` WHERE `id` IN (447,448,437,421,423,425,444,440) AND `status` = 1 [ RunTime:0.000862s ]
  98. SHOW FULL COLUMNS FROM `g3ys_tags_lang` [ RunTime:0.001712s ]
  99. SELECT * FROM `g3ys_tags_lang` WHERE `tags_id` IN (447,448,437,421,423,425,444,440) AND `subsite_id` = 38 AND `lang` = 'en-US' [ RunTime:0.001060s ]
  100. SELECT * FROM `g3ys_route` WHERE ( `subsite_id` = '38' OR `subsite_id` = '0' ) AND `module` = 'home' AND `status` = 1 ORDER BY `sort` DESC,`id` ASC [ RunTime:0.000991s ]
  101. SELECT * FROM `g3ys_route` WHERE ( `subsite_id` = '38' OR `subsite_id` = '0' ) AND `module` = 'home' AND `status` = 1 ORDER BY `sort` DESC,`id` ASC [ RunTime:0.000655s ]
  102. SELECT * FROM `g3ys_route` WHERE ( `subsite_id` = '38' OR `subsite_id` = '0' ) AND `module` = 'home' AND `status` = 1 ORDER BY `sort` DESC,`id` ASC [ RunTime:0.000657s ]
  103. SELECT * FROM `g3ys_route` WHERE ( `subsite_id` = '38' OR `subsite_id` = '0' ) AND `module` = 'home' AND `status` = 1 ORDER BY `sort` DESC,`id` ASC [ RunTime:0.000808s ]
  104. SELECT * FROM `g3ys_route` WHERE ( `subsite_id` = '38' OR `subsite_id` = '0' ) AND `module` = 'home' AND `status` = 1 ORDER BY `sort` DESC,`id` ASC [ RunTime:0.000669s ]
  105. SELECT * FROM `g3ys_route` WHERE ( `subsite_id` = '38' OR `subsite_id` = '0' ) AND `module` = 'home' AND `status` = 1 ORDER BY `sort` DESC,`id` ASC [ RunTime:0.000695s ]
  106. SELECT * FROM `g3ys_route` WHERE ( `subsite_id` = '38' OR `subsite_id` = '0' ) AND `module` = 'home' AND `status` = 1 ORDER BY `sort` DESC,`id` ASC [ RunTime:0.000684s ]
  107. SELECT * FROM `g3ys_route` WHERE ( `subsite_id` = '38' OR `subsite_id` = '0' ) AND `module` = 'home' AND `status` = 1 ORDER BY `sort` DESC,`id` ASC [ RunTime:0.000709s ]
  108. SELECT * FROM `g3ys_ad_location` WHERE `name` = 'ad-right' AND `subsite_id` = '38' AND `status` = 1 LIMIT 1 [ RunTime:0.000734s ]
  109. SELECT * FROM `g3ys_ad` WHERE `subsite_id` = '38' AND `ad_location_id` = '76' AND `status` = 1 AND `device` IN ('all','pc') AND ( `start_time` = 0 OR `start_time` <= 1787725547 ) AND ( `end_time` = 0 OR `end_time` >= 1787725547 ) ORDER BY `sort` DESC,`id` DESC [ RunTime:0.000880s ]
  110. SELECT * FROM `g3ys_ad_lang` WHERE `ad_id` = 76 AND `subsite_id` = '38' AND `lang` = 'en-US' [ RunTime:0.000648s ]
  111. SELECT * FROM `g3ys_route` WHERE ( `subsite_id` = '38' OR `subsite_id` = '0' ) AND `module` = 'home' AND `status` = 1 ORDER BY `sort` DESC,`id` ASC [ RunTime:0.000760s ]
  112. SELECT * FROM `g3ys_route` WHERE ( `subsite_id` = '38' OR `subsite_id` = '0' ) AND `module` = 'home' AND `status` = 1 ORDER BY `sort` DESC,`id` ASC [ RunTime:0.000762s ]
  113. SELECT * FROM `g3ys_route` WHERE ( `subsite_id` = '38' OR `subsite_id` = '0' ) AND `module` = 'home' AND `status` = 1 ORDER BY `sort` DESC,`id` ASC [ RunTime:0.000674s ]
  114. SELECT * FROM `g3ys_route` WHERE ( `subsite_id` = '38' OR `subsite_id` = '0' ) AND `module` = 'home' AND `status` = 1 ORDER BY `sort` DESC,`id` ASC [ RunTime:0.000645s ]
  115. SELECT * FROM `g3ys_route` WHERE ( `subsite_id` = '38' OR `subsite_id` = '0' ) AND `module` = 'home' AND `status` = 1 ORDER BY `sort` DESC,`id` ASC [ RunTime:0.000680s ]
  116. SELECT * FROM `g3ys_route` WHERE ( `subsite_id` = '38' OR `subsite_id` = '0' ) AND `module` = 'home' AND `status` = 1 ORDER BY `sort` DESC,`id` ASC [ RunTime:0.000668s ]
  117. SELECT * FROM `g3ys_route` WHERE ( `subsite_id` = '38' OR `subsite_id` = '0' ) AND `module` = 'home' AND `status` = 1 ORDER BY `sort` DESC,`id` ASC [ RunTime:0.000740s ]
  118. SELECT * FROM `g3ys_route` WHERE ( `subsite_id` = '38' OR `subsite_id` = '0' ) AND `module` = 'home' AND `status` = 1 ORDER BY `sort` DESC,`id` ASC [ RunTime:0.000654s ]
  119. SELECT * FROM `g3ys_route` WHERE ( `subsite_id` = '38' OR `subsite_id` = '0' ) AND `module` = 'home' AND `status` = 1 ORDER BY `sort` DESC,`id` ASC [ RunTime:0.001226s ]
0.543581s