2026年10月05日 Monday Focus on Malaysia and Southeast Asia cross-border investment

Global Economic Indicators Turning Point: October 2026 Data Reveals New Market Landscape

2026-10-05 13:14

Global Economic Indicators Turning Point: October 2026 Data Reveals New Market Landscape

Global Economic Indicators Turning Point: October 2026 Data Reveals New Market Landscape

In October 2026, global economic data released a series of key signals, marking an important turning point in the international economic landscape. The synchronized changes in multiple core economic indicators have not only reshaped market expectations but also triggered deep adjustments in global investment asset allocation strategies. This article will deeply analyze the significance behind the latest economic data, interpret its impact on different market segments, and provide forward-looking perspectives and response strategies for investors.

Historic Transformation of Global Economic Indicators

According to the latest global economic data, multiple key indicators in the third quarter of 2026 showed trends significantly different from the past few years. The latest report from the International Monetary Fund (IMF) shows that global GDP growth is expected to be 3.2%, a slowdown from 3.8% in 2025, but structural changes are more noteworthy.

Specifically, US economic data shows that consumer spending growth rate decreased from 4.2% in the first half of the year to 2.8% in the third quarter, while corporate capital expenditure showed the strongest growth since 2020, reaching 5.6%. This transformation indicates that the US economic growth momentum is shifting from consumption-driven to investment-driven, possibly marking a deep change in the economic cycle.

European regional economic data also shows signs of transformation. Germany's manufacturing PMI index rose for two consecutive months to 50.5, ending a contraction period of 14 months; while France's service PMI reached 54.2, the highest point in nearly two years. These data suggest that the European economy may have bottomed out and started a slow recovery.

The Asia-Pacific region's economic performance shows clear differentiation. China's economy, stimulated by policies, achieved a GDP growth of 4.5% in the third quarter, exceeding market expectations; while Japan's economy was dragged by weak domestic demand, with a growth rate of only 1.2%, underperforming expectations. This differentiated pattern makes capital flows within the Asia-Pacific region more complex.

Deep Analysis of Key Economic Indicators

Analyzing the key economic indicators released in October 2026 in depth, we can identify several noteworthy transformation trends:

  • Structural Changes in Inflation Indicators: Inflation data in major global economies shows divergent trends. The US CPI year-on-year growth rate decreased from 3.8% in June to 2.9% in September, while the European core inflation rate rose from 2.1% to 2.7%. This divergence mainly stems from differences in energy price trends and supply chain structures.
  • Quality Transformation in the Job Market: The US unemployment rate remained stable at a low of 3.8%, but the labor force participation rate rose to 62.8%, indicating improved quality of the job market. Meanwhile, average hourly wage growth slowed from 4.5% to 3.8%, possibly signaling a relief in the wage-price spiral.
  • Reshaping of Trade Data: Global trade data shows that in the first three quarters of 2026, total goods trade increased by 3.2% year-on-year, while service trade growth reached 6.5%, showing significant structural changes. This reflects the long-term trend of the global economy's transformation toward the service sector.
  • Intensifying Divergence in Central Bank Policies: Central bank policies in various countries show clear divergence. The Federal Reserve maintained interest rates unchanged at its September meeting but hinted at another rate hike before the end of the year; while the European Central Bank announced a 25 basis point rate cut in October, becoming the first major central bank to pivot.

Reshaping of Market Landscape and Opportunities

The transformation of economic indicators is reshaping the global market landscape, bringing different impacts to different asset classes:

Structural Transformation in the Stock Market

Against the backdrop of economic indicator changes, the global stock market shows clear structural differentiation. The performance gap between technology stocks and traditional industrial stocks has widened, with the Nasdaq index leading the S&P 500 by 8.2%, the largest gap in nearly five years. This trend reflects the market's reassessment of long-term growth prospects in the technology sector.

Meanwhile, stimulated by signals of economic bottoming, European stocks outperformed US stocks in the third quarter, with the MSCI Europe index rising 7.5%, while the MSCI US index rose only 4.2%. This transformation marks a deep change in the global capital flow pattern.

Logic Rewriting in the Bond Market

The bond market faces logic rewriting under the transformation of economic indicators. Traditionally, economic slowdown expectations should push bond prices higher, but in the third quarter of 2026, the global bond market showed a trend opposite to expectations. The 10-year US Treasury yield rose from 3.8% in September to 4.2% in October, reaching a new high in nearly a year.

This phenomenon mainly stems from two factors: first, the market's early digestion of expectations for central bank policy shifts; second, rising risk premiums due to increased global debt supply. Notably, the 10-year German government bond yield turned positive for the first time, marking a fundamental change in the European bond market logic.

New Pattern in the Foreign Exchange Market

The foreign exchange market has formed a new pattern under the transformation of economic indicators. After reaching a high of 106 in September, the US Dollar Index fell to 103.5 in October, mainly reflecting the easing of the relative strength of the US economy. Meanwhile, stimulated by the European Central Bank's pivot to rate cuts, the euro rose against the dollar from 0.95 to 0.98, marking the largest increase in nearly three months.

Asian currencies showed mixed performance. Supported by better-than-expected economic data, the yuan stabilized against the dollar at around 7.25; while the yen continued to be pressured due to the Bank of Japan's unchanged policy, reaching the important psychological level of 150 against the dollar.

Adjustment and Recommendations for Investment Strategies

Facing the new market landscape brought by economic indicator changes, investors need to adjust strategies to cope with new challenges and opportunities:

Diversified Transformation in Asset Allocation

The traditional 60/40 asset allocation strategy (60% stocks, 40% bonds) faces challenges in the current market. Investors are advised to adopt more flexible allocation strategies, increasing the proportion of alternative assets, including private equity, real estate investment trusts (REITs), and commodities, to diversify risks and improve returns.

At the same time, geographical allocation should be more diversified. European assets show potential under economic bottoming signals, and their allocation proportion can be moderately increased; while within the Asian market, differentiated allocation should be made based on the specific performance of each economy.

Strategic Adjustment in Industry Rotation

Industry allocation should consider the阶段性 changes in the economic cycle. Against the backdrop of current economic indicator changes, the following industries are worth attention:

  • Technology and Digitalization: The digital transformation trend is irreversible in both consumer and enterprise sectors, with long-term growth prospects looking good in areas such as AI, cloud computing, and cybersecurity.
  • Sustainable Energy: The global energy transition is accelerating, and areas such as solar energy, wind energy, and energy storage technology will continue to benefit from policy support and technological advancement.
  • Healthcare: The aging population trend is intensifying, with stable growth in demand for innovative drugs, medical devices, and health management services.
  • Industry 4.0: Equipment upgrade needs brought by the automation and intelligent transformation of manufacturing, as well as opportunities in supply chain reshaping.

Strengthening of Risk Management

During the period of economic indicator changes, market volatility may increase, making risk management particularly important. Investors are advised to:

  • Regularly assess the risk exposure of investment portfolios, especially interest rate risk and exchange rate risk.
  • Increase the use of hedging tools such as options and futures to protect the portfolio from market volatility impacts.
  • Maintain appropriate cash allocation to respond to sudden market events and seize investment opportunities.
  • Diversify investments across different asset classes, regions, and industries to reduce concentration risk.

Conclusion: Investment Wisdom in Grasping Economic Turning Points

The transformation of global economic indicators in October 2026 marks a new stage in the international economic landscape. This turning point not only affects short-term market trends but will also reshape long-term investment logic. Facing this change, investors need to remain sensitive, deeply understand the economic logic behind the data, and adjust investment strategies in a timely manner.

Historical experience shows that economic turning points are often turning points for investment opportunities. Those investors who can accurately grasp trends and respond flexibly will gain advantages in the new market landscape. At the same time, risk management is crucial. While pursuing returns, effective defense mechanisms must be established.

Looking ahead, the global economy may face more uncertainties, including geopolitical risks, energy price fluctuations, and technological changes. Investors need to maintain a long-term perspective, not be disturbed by short-term fluctuations, while closely monitoring changes in key economic indicators and adjusting investment portfolios in a timely manner.

In conclusion, the economic indicator transformation in October 2026 is a key node in the reshaping of the global economic landscape. Investors should face changes with an open mindset, formulate flexible and diverse investment strategies based on in-depth data analysis, seek opportunities in the changing situation, and achieve long-term wealth growth goals.

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  1. CONNECT:[ UseTime:0.001195s ] mysql:host=127.0.0.1;port=3306;dbname=cjgpcs;charset=utf8mb4
  2. SHOW FULL COLUMNS FROM `g3ys_config` [ RunTime:0.002557s ]
  3. SELECT `value` FROM `g3ys_config` WHERE `name` = 'timezone' AND `subsite_id` = '37' LIMIT 1 [ RunTime:0.000775s ]
  4. SHOW FULL COLUMNS FROM `g3ys_route` [ RunTime:0.003179s ]
  5. SELECT * FROM `g3ys_route` WHERE ( `subsite_id` = '37' OR `subsite_id` = '0' ) AND `module` = 'home' AND `status` = 1 ORDER BY `sort` DESC,`id` ASC [ RunTime:0.001321s ]
  6. SHOW FULL COLUMNS FROM `g3ys_theme` [ RunTime:0.002973s ]
  7. SELECT `paginator` FROM `g3ys_theme` WHERE `module` = 'home' AND `name` = 'maju' AND `subsite_id` = '37' LIMIT 1 [ RunTime:0.000803s ]
  8. SHOW FULL COLUMNS FROM `g3ys_lang` [ RunTime:0.003218s ]
  9. SELECT * FROM `g3ys_lang` WHERE `subsite_id` = 37 AND ( ( LOWER(name) = 'en' ) OR `subtag` = 'en' ) AND `status` = 1 ORDER BY `id` ASC LIMIT 1 [ RunTime:0.001308s ]
  10. SHOW FULL COLUMNS FROM `g3ys_member` [ RunTime:0.003990s ]
  11. SELECT * FROM `g3ys_member` WHERE `id` = 0 AND `subsite_id` = '37' LIMIT 1 [ RunTime:0.002865s ]
  12. SHOW FULL COLUMNS FROM `g3ys_document` [ RunTime:0.012235s ]
  13. SELECT `id`,`document_type` FROM `g3ys_document` WHERE `subsite_id` = 37 AND `name` = 'global-economic-indicators-turning-point-october-2026' AND `status` IN ('1','2') LIMIT 1 [ RunTime:0.015350s ]
  14. SELECT * FROM `g3ys_document` WHERE ( `name` = '7453' OR `id` = '7453' ) AND `subsite_id` = 37 LIMIT 1 [ RunTime:0.022144s ]
  15. SHOW TABLES LIKE 'g3ys_document_article' [ RunTime:0.003185s ]
  16. SHOW FULL COLUMNS FROM `g3ys_document_article` [ RunTime:0.001632s ]
  17. SELECT * FROM `g3ys_document_article` WHERE `document_id` = '7453' LIMIT 1 [ RunTime:0.001194s ]
  18. SHOW FULL COLUMNS FROM `g3ys_total` [ RunTime:0.002207s ]
  19. SELECT * FROM `g3ys_total` WHERE `target_id` = '7453' LIMIT 1 [ RunTime:0.000719s ]
  20. SHOW TABLES LIKE 'g3ys_document_article_lang' [ RunTime:0.002449s ]
  21. SHOW FULL COLUMNS FROM `g3ys_document_article_lang` [ RunTime:0.001983s ]
  22. SELECT * FROM `g3ys_document_article_lang` WHERE `subsite_id` = '37' AND `lang` = 'en' AND `document_id` = '7453' [ RunTime:0.016991s ]
  23. SHOW FULL COLUMNS FROM `g3ys_document_article_lang` [ RunTime:0.007297s ]
  24. SHOW TABLES LIKE 'g3ys_category_lang' [ RunTime:0.007428s ]
  25. SHOW FULL COLUMNS FROM `g3ys_category_lang` [ RunTime:0.007985s ]
  26. SELECT * FROM `g3ys_category_lang` WHERE `subsite_id` = '37' AND `category_id` = '1434' AND `lang` = 'en' LIMIT 1 [ RunTime:0.001708s ]
  27. SELECT * FROM `g3ys_total` WHERE `target_id` = '7453' LIMIT 1 [ RunTime:0.002646s ]
  28. UPDATE `g3ys_total` SET `view_total` = `view_total` + 1 WHERE `target_id` = '7453' [ RunTime:0.002210s ]
  29. SHOW FULL COLUMNS FROM `g3ys_record` [ RunTime:0.011030s ]
  30. SELECT `id` FROM `g3ys_record` WHERE `subsite_id` = '37' AND `type` = 'article' AND `url` = 'https://www.setmal.asia/global-economic-indicators-turning-point-october-2026' AND `create_time` >= 1791183232 AND ( `visitor_id` = 'e58e4222eb932157e7b5b97c5d7767c3' OR `session_id` = '03cf28e6d0568d9c8210de9ea92d6e6d' ) LIMIT 1 [ RunTime:0.007630s ]
  31. INSERT INTO `g3ys_record` SET `subsite_id` = '37' , `uid` = '0' , `visitor_id` = 'e58e4222eb932157e7b5b97c5d7767c3' , `session_id` = '03cf28e6d0568d9c8210de9ea92d6e6d' , `type` = 'article' , `target_id` = '7453' , `target_type` = 0 , `category_id` = '1434' , `title` = 'Global Economic Indicators Turning Point: October 2026 Data Reveals New Market Landscape' , `url` = 'https://www.setmal.asia/global-economic-indicators-turning-point-october-2026' , `path` = '/global-economic-indicators-turning-point-october-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` = '216.73.216.248' , `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` = 1791183292 , `update_time` = 1791183292 [ RunTime:0.021045s ]
  32. SHOW FULL COLUMNS FROM `g3ys_comment` [ RunTime:0.012033s ]
  33. SELECT COUNT(*) AS think_count FROM `g3ys_comment` WHERE `target_id` = '7453' AND `pid` = '0' [ RunTime:0.003736s ]
  34. SHOW FULL COLUMNS FROM `g3ys_model` [ RunTime:0.014430s ]
  35. SELECT `id`,`name`,`title`,`field_group` FROM `g3ys_model` WHERE `extend` = 0 AND `id` <> 1 AND `subsite_id` IN ('0','37') AND `status` = 1 [ RunTime:0.005761s ]
  36. SHOW TABLES LIKE 'g3ys_paragraph' [ RunTime:0.007800s ]
  37. SHOW TABLES LIKE 'g3ys_paragraph_lang' [ RunTime:0.007280s ]
  38. SHOW TABLES LIKE 'g3ys_gallery' [ RunTime:0.007878s ]
  39. SHOW TABLES LIKE 'g3ys_gallery_lang' [ RunTime:0.005869s ]
  40. SHOW TABLES LIKE 'g3ys_video' [ RunTime:0.005494s ]
  41. SHOW TABLES LIKE 'g3ys_video_lang' [ RunTime:0.009935s ]
  42. SHOW TABLES LIKE 'g3ys_faq' [ RunTime:0.005290s ]
  43. SHOW TABLES LIKE 'g3ys_faq_lang' [ RunTime:0.009854s ]
  44. SHOW TABLES LIKE 'g3ys_blockquote' [ RunTime:0.008899s ]
  45. SHOW TABLES LIKE 'g3ys_blockquote_lang' [ RunTime:0.006406s ]
  46. SHOW TABLES LIKE 'g3ys_cards' [ RunTime:0.005803s ]
  47. SHOW TABLES LIKE 'g3ys_cards_lang' [ RunTime:0.009243s ]
  48. SHOW TABLES LIKE 'g3ys_objects' [ RunTime:0.004601s ]
  49. SHOW TABLES LIKE 'g3ys_objects_lang' [ RunTime:0.004693s ]
  50. SHOW TABLES LIKE 'g3ys_videos' [ RunTime:0.003747s ]
  51. SHOW TABLES LIKE 'g3ys_videos_lang' [ RunTime:0.006610s ]
  52. SHOW TABLES LIKE 'g3ys_audios' [ RunTime:0.007272s ]
  53. SHOW TABLES LIKE 'g3ys_audios_lang' [ RunTime:0.006908s ]
  54. SHOW TABLES LIKE 'g3ys_files' [ RunTime:0.005265s ]
  55. SHOW TABLES LIKE 'g3ys_files_lang' [ RunTime:0.006767s ]
  56. SHOW TABLES LIKE 'g3ys_richmedia' [ RunTime:0.005239s ]
  57. SHOW TABLES LIKE 'g3ys_richmedia_lang' [ RunTime:0.003642s ]
  58. SHOW FULL COLUMNS FROM `g3ys_paragraph` [ RunTime:0.002285s ]
  59. SELECT * FROM `g3ys_paragraph` WHERE `document_id` = 7453 AND `subsite_id` = '37' AND `status` = 1 ORDER BY `sort` ASC,`id` ASC [ RunTime:0.001017s ]
  60. SHOW FULL COLUMNS FROM `g3ys_gallery` [ RunTime:0.001988s ]
  61. SELECT * FROM `g3ys_gallery` WHERE `document_id` = 7453 AND `subsite_id` = 37 AND `status` = 1 ORDER BY `sort` ASC,`id` ASC [ RunTime:0.004472s ]
  62. SHOW FULL COLUMNS FROM `g3ys_video` [ RunTime:0.002812s ]
  63. SELECT * FROM `g3ys_video` WHERE `document_id` = 7453 AND `subsite_id` = 37 AND `status` = 1 ORDER BY `sort` ASC,`id` ASC [ RunTime:0.001161s ]
  64. SHOW FULL COLUMNS FROM `g3ys_faq` [ RunTime:0.002409s ]
  65. SELECT * FROM `g3ys_faq` WHERE `document_id` = 7453 AND `subsite_id` = 37 AND `status` = 1 ORDER BY `sort` ASC,`id` ASC [ RunTime:0.001054s ]
  66. SHOW FULL COLUMNS FROM `g3ys_blockquote` [ RunTime:0.002042s ]
  67. SELECT * FROM `g3ys_blockquote` WHERE `document_id` = 7453 AND `subsite_id` = 37 AND `status` = 1 ORDER BY `sort` ASC,`id` ASC [ RunTime:0.001039s ]
  68. SHOW FULL COLUMNS FROM `g3ys_cards` [ RunTime:0.002328s ]
  69. SELECT * FROM `g3ys_cards` WHERE `document_id` = 7453 AND `subsite_id` = '37' AND `status` = 1 ORDER BY `sort` ASC,`id` ASC [ RunTime:0.001111s ]
  70. SHOW FULL COLUMNS FROM `g3ys_objects` [ RunTime:0.002293s ]
  71. SELECT * FROM `g3ys_objects` WHERE `document_id` = 7453 AND `subsite_id` = '37' AND `status` = 1 ORDER BY `sort` ASC,`id` ASC [ RunTime:0.001186s ]
  72. SHOW FULL COLUMNS FROM `g3ys_videos` [ RunTime:0.002518s ]
  73. SELECT * FROM `g3ys_videos` WHERE `document_id` = 7453 AND `subsite_id` = '37' AND `status` = 1 ORDER BY `sort` ASC,`id` ASC [ RunTime:0.001116s ]
  74. SHOW FULL COLUMNS FROM `g3ys_audios` [ RunTime:0.002693s ]
  75. SELECT * FROM `g3ys_audios` WHERE `document_id` = 7453 AND `subsite_id` = '37' AND `status` = 1 ORDER BY `sort` ASC,`id` ASC [ RunTime:0.001037s ]
  76. SHOW FULL COLUMNS FROM `g3ys_files` [ RunTime:0.002243s ]
  77. SELECT * FROM `g3ys_files` WHERE `document_id` = 7453 AND `subsite_id` = '37' AND `status` = 1 ORDER BY `sort` ASC,`id` ASC [ RunTime:0.001093s ]
  78. SHOW FULL COLUMNS FROM `g3ys_richmedia` [ RunTime:0.002326s ]
  79. SELECT * FROM `g3ys_richmedia` WHERE `document_id` = 7453 AND `subsite_id` = '37' AND `status` = 1 ORDER BY `sort` ASC,`id` ASC [ RunTime:0.001106s ]
  80. SELECT * FROM `g3ys_document` WHERE `category_id` = 1434 AND `subsite_id` = 37 AND `pid` = '0' AND `status` = '1' AND ( ( sort > 0) or ( sort = 0 and id < 7453) ) ORDER BY `sort` ASC,`id` DESC LIMIT 1 [ RunTime:0.003105s ]
  81. SELECT * FROM `g3ys_document` WHERE `category_id` = 1434 AND `subsite_id` = 37 AND `pid` = '7426' AND `status` = '1' ORDER BY `sort` ASC,`id` DESC LIMIT 1 [ RunTime:0.005026s ]
  82. SELECT * FROM `g3ys_document_article_lang` WHERE `subsite_id` = '37' AND `lang` = 'en' AND `document_id` = '7426' [ RunTime:0.032298s ]
  83. SELECT * FROM `g3ys_document` WHERE `category_id` = 1434 AND `subsite_id` = 37 AND `pid` = '7453' AND `status` = '1' AND `document_type` = 0 ORDER BY `sort` DESC,`id` ASC LIMIT 1 [ RunTime:0.003074s ]
  84. SELECT * FROM `g3ys_document` WHERE `category_id` = 1434 AND `subsite_id` = 37 AND `pid` = '0' AND `status` = '1' AND `document_type` = 0 AND ( ( sort>0 and sort <= 0 and id!=7453) or ( sort = 0 and id > 7453) ) ORDER BY `sort` DESC,`id` ASC LIMIT 1 [ RunTime:0.003432s ]
  85. SELECT * FROM `g3ys_route` WHERE ( `subsite_id` = '37' OR `subsite_id` = '0' ) AND `module` = 'home' AND `status` = 1 ORDER BY `sort` DESC,`id` ASC [ RunTime:0.001338s ]
  86. SHOW FULL COLUMNS FROM `g3ys_file` [ RunTime:0.003700s ]
  87. SELECT * FROM `g3ys_file` WHERE `status` = 1 AND `id` = 7108 LIMIT 1 [ RunTime:0.001528s ]
  88. SHOW FULL COLUMNS FROM `g3ys_ad_location` [ RunTime:0.003794s ]
  89. SELECT * FROM `g3ys_ad_location` WHERE `name` = 'ad-detail-full' AND `subsite_id` = '37' AND `status` = 1 LIMIT 1 [ RunTime:0.001084s ]
  90. SHOW FULL COLUMNS FROM `g3ys_ad` [ RunTime:0.003042s ]
  91. SELECT * FROM `g3ys_ad` WHERE `subsite_id` = '37' AND `ad_location_id` = '70' AND `status` = 1 AND `device` IN ('all','pc') AND ( `start_time` = 0 OR `start_time` <= 1791183292 ) AND ( `end_time` = 0 OR `end_time` >= 1791183292 ) ORDER BY `sort` DESC,`id` DESC [ RunTime:0.001283s ]
  92. SHOW FULL COLUMNS FROM `g3ys_ad_lang` [ RunTime:0.002044s ]
  93. SELECT * FROM `g3ys_ad_lang` WHERE `ad_id` = 70 AND `subsite_id` = '37' AND `lang` = 'en' [ RunTime:0.000898s ]
  94. SHOW FULL COLUMNS FROM `g3ys_ad_lang` [ RunTime:0.002993s ]
  95. SELECT * FROM `g3ys_route` WHERE ( `subsite_id` = '37' OR `subsite_id` = '0' ) AND `module` = 'home' AND `status` = 1 ORDER BY `sort` DESC,`id` ASC [ RunTime:0.001579s ]
  96. SELECT * FROM `g3ys_route` WHERE ( `subsite_id` = '37' OR `subsite_id` = '0' ) AND `module` = 'home' AND `status` = 1 ORDER BY `sort` DESC,`id` ASC [ RunTime:0.001594s ]
  97. SELECT * FROM `g3ys_route` WHERE ( `subsite_id` = '37' OR `subsite_id` = '0' ) AND `module` = 'home' AND `status` = 1 ORDER BY `sort` DESC,`id` ASC [ RunTime:0.002570s ]
  98. SELECT * FROM `g3ys_route` WHERE ( `subsite_id` = '37' OR `subsite_id` = '0' ) AND `module` = 'home' AND `status` = 1 ORDER BY `sort` DESC,`id` ASC [ RunTime:0.002932s ]
0.944857s