2026年08月15日 Saturday 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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Intraday Market Movement Deep Analysis: AI Giants Lead Rally and Energy Stocks Rebound, Market Direction Suddenly Changes

Intraday Market Movement Deep Analysis: AI Giants Lead Rally and Energy Stocks Rebound, Market Direction Suddenly Changes

Intraday Market Movement Deep Analysis: AI Giants Lead Rally and Energy Stocks Rebound, Market Direction Suddenly Changes

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On August 15, 2026, the US stock market once again experienced thrilling intraday fluctuations. After several days of consecutive volatility, the market direction showed a clear shift, with performance gaps widening between tech giants and energy sectors, prompting investors to deeply consider structural changes in the market. This article will provide a comprehensive analysis of the specific manifestations of intraday movements, the driving factors behind them, and their impact on future market trends.

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Intraday Movements: Tech and Energy Show Divergent Performance

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At the opening of the US stock market today, the three major indices showed divergent trends. The Dow Jones Industrial Average rose slightly by 0.3% driven by energy stocks, while the Nasdaq Composite Index fell by 0.2% due to selling pressure on some tech stocks. The S&P 500 index oscillated between the two, opening basically flat.

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Around 10 AM during the trading session, the market direction suddenly changed. Tech giant stocks collectively surged, with the Nasdaq index rebounding rapidly, rising by 0.8% at one point. Among them, NVIDIA (NVDA) rose by 2.5%, Microsoft (MSFT) by 1.8%, Google (GOOGL) by 1.6%, and Apple (AAPL) by 1.2%. The performance of these tech giants became the main driving force for the Nasdaq's rise.

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Meanwhile, the energy sector performed strongly during the trading session, especially oil and natural gas related stocks. ExxonMobil (XOM) rose by 1.8%, Chevron (CVX) by 1.5%, and ConocoPhillips (COP) by 2.1%. The performance of these energy stocks was significantly stronger than the broader market, becoming a supporting force for the Dow.

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Notably, market trading was active today. As of midday, NYSE trading volume increased by 15% compared to the same time yesterday, while Nasdaq trading volume increased by 12%, indicating high market participation and active investor sentiment.

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Behind the Movements: Multiple Factors Driving Market Divergence

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An in-depth analysis of the reasons behind today's intraday movements reveals that multiple factors are at work, causing clear market divergence.

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AI Technology Breakthrough Drives Tech Stock Rebound

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The rebound in tech stocks today was mainly stimulated by the latest breakthroughs in artificial intelligence technology. According to market news, a well-known AI research institution announced a major breakthrough in natural language processing, with its new model surpassing existing technologies in multiple standard tests. This news stimulated related concept stocks to rise, especially tech giants with significant AI presence.

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Analysts point out that the continuous advancement of AI technology is the foundation for the long-term strength of tech stocks. As AI applications deepen across industries, the profit expectations of tech giants are expected to be continuously upgraded, providing support for tech stocks. Meanwhile, market enthusiasm for AI-related investments remains high, with capital continuing to flow into AI concept stocks.

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Energy Demand Expectations Improve

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The performance of energy stocks benefited from improving global energy demand expectations. The latest data shows that the global industrial production index has increased for two consecutive months, with manufacturing activity showing significant signs of recovery, which supports energy demand.

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Additionally, geopolitical factors also affect the energy market. Recent tensions in the Middle East have led to market concerns about increased supply chain risks, which has pushed up energy prices, thereby benefiting related stock performance.

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Macroeconomic Data Impact

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Today's macroeconomic data also affected the market. US July retail sales data exceeded expectations, showing that consumer spending remains strong, which supports economic prospects. At the same time, inflation data was in line with expectations, reducing market inflation concerns.

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The performance of these macroeconomic data has led the market to expect that the Federal Reserve may cut interest rates in September, which supports risk assets. However, the data also shows that economic growth remains strong, which may mean that the rate cut will not be too large, and the market is reassessing this.

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Market Structural Changes: Investment Logic Transformation

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Today's intraday movements reflect not only short-term fluctuations but also structural changes in the market. Analysts believe that market investment logic is undergoing a transformation, shifting from solely pursuing tech growth to a more balanced allocation strategy.

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On one hand, the rapid development of AI technology does provide strong support for tech stocks, especially those companies with core competitiveness in the AI field. These companies can not only benefit from technological advancements but also use AI technology to improve their efficiency, achieving dual growth.

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On the other hand, the strengthening of the energy sector also reflects the market's reassessment of economic fundamentals. As the global economy recovers from the pandemic, energy demand is steadily increasing, while supply remains constrained, which provides support for energy prices. The stable cash flow and higher dividend rates of the energy sector make it attractive in the current market environment.

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Additionally, market expectations for the interest rate environment are changing. Although the market expects rate cuts, the uncertainty about the magnitude and timing of these cuts still exists. In this context, assets that can interest rate risks and have stable cash flows are more favored, which is also one of the reasons for the strong performance of the energy sector.

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Investment Strategy Recommendations: Seizing Market Transformation Opportunities

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In the face of current market changes, investors need to adjust their strategies and seize the opportunities brought by market transformation. Here are some specific recommendations:

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  • Balanced Allocation of Tech and Energy: The divergent performance of tech and energy stocks suggests that investors need to achieve balanced portfolio allocation to avoid single-sector risks. Consider allocating funds to AI-related tech stocks and the energy sector in certain proportions to achieve risk diversification.
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  • Focus on AI Application Implementation: For tech stock investments, it is important not only to follow the development of AI technology itself but also to pay attention to the implementation of AI in various industries. Companies that can transform AI technology into actual business value have more investment value.
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  • Long-term Holding of Energy Sector: The strengthening of the energy sector may not be a short-term phenomenon but reflects a long-term trend. Investors can consider long-term holdings in the energy sector, especially those companies with stable cash flow and higher dividends, to share in the long-term growth dividends of the energy industry.
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  • Monitor Macroeconomic Data Changes: Macroeconomic data has a significant impact on market trends. Investors need to closely monitor key indicators such as retail sales, inflation, and employment, and adjust investment strategies in a timely manner based on data changes.
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  • Utilize Volatility Opportunities: Increased market volatility also brings investment opportunities. Investors can use market fluctuations to buy quality assets during price adjustments, achieving low-cost allocation.
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Future Outlook: Market Divergence May Continue

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Looking ahead, market divergence may become the new normal. On one hand, the continuous advancement of AI technology will support the strength of tech stocks; on the other hand, the stable growth of energy demand and supply constraints will support the performance of the energy sector.

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At the same time, market expectations for Federal Reserve policy will continue to affect capital flows. If rate cut expectations strengthen, risk assets will benefit; if economic data continues to be strong, value stocks may have opportunities.

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Investors need to remain flexible, adjusting strategies in a timely manner according to market changes, while grasping long-term trends and responding to short-term fluctuations. In such a market environment, in-depth research and rational judgment will become key to investment success.

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Conclusion

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The US stock market intraday movements on August 15, 2026, reflect not only short-term market fluctuations but also deep-seated changes in economic structure. The breakthrough in AI technology and the improvement in energy demand are reshaping the market landscape. Investors need to adjust their strategies in a timely manner to seize the opportunities brought by this transformation.

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In the current complex and changing market environment, deeply understanding market dynamics, grasping industry trends, and achieving portfolio diversification will be the only way to investment success. Facing future uncertainties, only by maintaining learning and adaptation can one navigate market storms steadily and achieve long-term wealth growth.

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Huaxin Insight Financial Research will continue to monitor market dynamics, providing timely and accurate analysis and recommendations to help you achieve steady progress on your investment journey.

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  1. CONNECT:[ UseTime:0.001308s ] mysql:host=127.0.0.1;port=3306;dbname=cjgpcs;charset=utf8mb4
  2. SHOW FULL COLUMNS FROM `g3ys_config` [ RunTime:0.002436s ]
  3. SELECT `value` FROM `g3ys_config` WHERE `name` = 'timezone' AND `subsite_id` = '38' LIMIT 1 [ RunTime:0.000707s ]
  4. SHOW FULL COLUMNS FROM `g3ys_route` [ RunTime:0.002571s ]
  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:0.000725s ]
  6. SHOW FULL COLUMNS FROM `g3ys_theme` [ RunTime:0.002771s ]
  7. SELECT `paginator` FROM `g3ys_theme` WHERE `module` = 'home' AND `name` = 'slogan' AND `subsite_id` = '38' LIMIT 1 [ RunTime:0.000769s ]
  8. SHOW FULL COLUMNS FROM `g3ys_lang` [ RunTime:0.002974s ]
  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:0.001058s ]
  10. SHOW FULL COLUMNS FROM `g3ys_member` [ RunTime:0.003833s ]
  11. SELECT * FROM `g3ys_member` WHERE `id` = 0 AND `subsite_id` = '38' LIMIT 1 [ RunTime:0.001038s ]
  12. SHOW FULL COLUMNS FROM `g3ys_document` [ RunTime:0.004769s ]
  13. SELECT `id`,`document_type` FROM `g3ys_document` WHERE `subsite_id` = 38 AND `name` = 'us-stock-market-intra-day-movement-analysis-2026' AND `status` IN ('1','2') LIMIT 1 [ RunTime:0.002796s ]
  14. SELECT * FROM `g3ys_document` WHERE ( `name` = '6692' OR `id` = '6692' ) AND `subsite_id` = 38 LIMIT 1 [ RunTime:0.007240s ]
  15. SHOW TABLES LIKE 'g3ys_document_article' [ RunTime:0.002824s ]
  16. SHOW FULL COLUMNS FROM `g3ys_document_article` [ RunTime:0.002107s ]
  17. SELECT * FROM `g3ys_document_article` WHERE `document_id` = '6692' LIMIT 1 [ RunTime:0.000757s ]
  18. SHOW FULL COLUMNS FROM `g3ys_total` [ RunTime:0.002140s ]
  19. SELECT * FROM `g3ys_total` WHERE `target_id` = '6692' LIMIT 1 [ RunTime:0.000696s ]
  20. SHOW TABLES LIKE 'g3ys_document_article_lang' [ RunTime:0.002023s ]
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  23. SHOW FULL COLUMNS FROM `g3ys_document_article_lang` [ RunTime:0.002495s ]
  24. SHOW TABLES LIKE 'g3ys_category_lang' [ RunTime:0.002121s ]
  25. SHOW FULL COLUMNS FROM `g3ys_category_lang` [ RunTime:0.001810s ]
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  27. SELECT * FROM `g3ys_total` WHERE `target_id` = '6692' LIMIT 1 [ RunTime:0.000904s ]
  28. UPDATE `g3ys_total` SET `view_total` = `view_total` + 1 WHERE `target_id` = '6692' [ RunTime:0.001832s ]
  29. SHOW FULL COLUMNS FROM `g3ys_record` [ RunTime:0.003670s ]
  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-2026' AND `create_time` >= 1786784214 AND ( `visitor_id` = 'ce1fa3f359608ca9c10c420433af3cd8' OR `session_id` = 'a8e498329e29502b800e5c15e0714dc0' ) LIMIT 1 [ RunTime:0.001409s ]
  31. INSERT INTO `g3ys_record` SET `subsite_id` = '38' , `uid` = '0' , `visitor_id` = 'ce1fa3f359608ca9c10c420433af3cd8' , `session_id` = 'a8e498329e29502b800e5c15e0714dc0' , `type` = 'article' , `target_id` = '6692' , `target_type` = 0 , `category_id` = '1464' , `title` = 'Intraday Market Movement Deep Analysis: AI Giants Lead Rally and Energy Stocks Rebound, Market Direction Suddenly Changes' , `url` = 'https://www.cninsgx.com/us-stock-market-intra-day-movement-analysis-2026' , `path` = '/us-stock-market-intra-day-movement-analysis-2026' , `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` = '216.73.217.176' , `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` = 1786784274 , `update_time` = 1786784274 [ RunTime:0.003362s ]
  32. SHOW FULL COLUMNS FROM `g3ys_comment` [ RunTime:0.002738s ]
  33. SELECT COUNT(*) AS think_count FROM `g3ys_comment` WHERE `target_id` = '6692' AND `pid` = '0' [ RunTime:0.000656s ]
  34. 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 < 6692) ) ORDER BY `sort` ASC,`id` DESC LIMIT 1 [ RunTime:0.001418s ]
  35. SELECT * FROM `g3ys_document` WHERE `category_id` = 1464 AND `subsite_id` = 38 AND `pid` = '6637' AND `status` = '1' ORDER BY `sort` ASC,`id` DESC LIMIT 1 [ RunTime:0.001487s ]
  36. SELECT * FROM `g3ys_document_article_lang` WHERE `subsite_id` = '38' AND `lang` = 'en-US' AND `document_id` = '6637' [ RunTime:0.018130s ]
  37. SELECT * FROM `g3ys_document` WHERE `category_id` = 1464 AND `subsite_id` = 38 AND `pid` = '6692' AND `status` = '1' AND `document_type` = 0 ORDER BY `sort` DESC,`id` ASC LIMIT 1 [ RunTime:0.004648s ]
  38. 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!=6692) or ( sort = 0 and id > 6692) ) ORDER BY `sort` DESC,`id` ASC LIMIT 1 [ RunTime:0.002979s ]
  39. 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:0.003177s ]
  40. SELECT * FROM `g3ys_total` WHERE `target_id` = '6692' LIMIT 1 [ RunTime:0.001010s ]
  41. SHOW FULL COLUMNS FROM `g3ys_ad_location` [ RunTime:0.007354s ]
  42. SELECT * FROM `g3ys_ad_location` WHERE `name` = 'ad-detail-full' AND `subsite_id` = '38' AND `status` = 1 LIMIT 1 [ RunTime:0.003025s ]
  43. SHOW FULL COLUMNS FROM `g3ys_ad` [ RunTime:0.007521s ]
  44. 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` <= 1786784274 ) AND ( `end_time` = 0 OR `end_time` >= 1786784274 ) ORDER BY `sort` DESC,`id` DESC [ RunTime:0.001872s ]
  45. SHOW FULL COLUMNS FROM `g3ys_ad_lang` [ RunTime:0.004463s ]
  46. SELECT * FROM `g3ys_ad_lang` WHERE `ad_id` = 74 AND `subsite_id` = '38' AND `lang` = 'en-US' [ RunTime:0.001404s ]
  47. SHOW FULL COLUMNS FROM `g3ys_ad_lang` [ RunTime:0.002860s ]
  48. SHOW FULL COLUMNS FROM `g3ys_tags` [ RunTime:0.003018s ]
  49. SELECT `title`,`color`,`description`,`seotitle`,`keyword`,`name`,`id` FROM `g3ys_tags` WHERE `id` IN (447,448,437,440,445,435,434,421) AND `status` = 1 [ RunTime:0.001654s ]
  50. SHOW FULL COLUMNS FROM `g3ys_tags_lang` [ RunTime:0.003874s ]
  51. SELECT * FROM `g3ys_tags_lang` WHERE `tags_id` IN (447,448,437,440,445,435,434,421) AND `subsite_id` = 38 AND `lang` = 'en-US' [ RunTime:0.002946s ]
  52. 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:0.001211s ]
  53. 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:0.000974s ]
  54. 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:0.000858s ]
  55. 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:0.000937s ]
  56. 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:0.000924s ]
  57. 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:0.000999s ]
  58. 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:0.000863s ]
  59. 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:0.001423s ]
  60. SELECT * FROM `g3ys_ad_location` WHERE `name` = 'ad-right' AND `subsite_id` = '38' AND `status` = 1 LIMIT 1 [ RunTime:0.000916s ]
  61. 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` <= 1786784274 ) AND ( `end_time` = 0 OR `end_time` >= 1786784274 ) ORDER BY `sort` DESC,`id` DESC [ RunTime:0.001380s ]
  62. SELECT * FROM `g3ys_ad_lang` WHERE `ad_id` = 76 AND `subsite_id` = '38' AND `lang` = 'en-US' [ RunTime:0.000963s ]
  63. 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:0.000850s ]
  64. 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:0.000915s ]
  65. 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:0.000896s ]
  66. 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:0.000888s ]
  67. 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:0.003220s ]
  68. 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:0.000929s ]
  69. 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:0.000904s ]
  70. 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:0.002187s ]
  71. 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:0.001707s ]
0.582436s