2026-08-09 |

CoreChip Event Timeline Calendar v3.0: AI-Driven Enterprise Strategic Planning and Investment Decision Revolution

CoreChip Event Timeline Calendar v3.0: Revolutionizing Enterprise Strategy Planning and Investment Decisions

Against the backdrop of increasing global financial market volatility in August 2026, enterprise strategic planning and investment decision-making face unprecedented challenges. CoreChip's newly released Event Timeline Calendar v3.0 provides powerful decision support tools for business managers and investors by integrating artificial intelligence analysis with real-time data streams. This innovative product has not only changed the positioning of traditional calendar tools but has become a key bridge connecting macroeconomics, corporate events, and market reactions.

From Simple Schedule Management to Intelligent Strategic Planning Platform

CoreChip Event Timeline Calendar was initially a basic timeline management tool that helped business users schedule meetings, deadlines, and project milestones. However, after three years of iterative development, the v3.0 version has evolved into an intelligent strategic planning platform that integrates macroeconomic data, corporate earnings releases, policy changes, and market events.

According to the latest introduction from the CoreChip product team, the core breakthrough in v3.0 lies in its "Event-Market-Impact" analysis engine. This engine can automatically correlate various economic events with market reactions and use machine learning algorithms to predict the potential impacts of different event combinations on specific industries or asset classes. In the current environment of increasing global economic uncertainty, this function provides valuable decision-making references for investors.

Deep Integration of Macroeconomic Data and Corporate Events

Unlike traditional calendar tools, CoreChip Event Timeline Calendar v3.0 deeply integrates key data indicators from major global economies. Macroeconomic events such as Federal Reserve interest rate decisions, employment reports, inflation data, and GDP growth are automatically marked and correlated to relevant corporate timelines.

For example, when the Federal Reserve announces interest rate policy adjustments, the system automatically analyzes the impact of this change on different industries and highlights companies that may be most affected. At the same time, it integrates historical data to show how similar policy changes have affected related stocks in the past, providing investors with historical references.

This deep integration not only improves information acquisition efficiency but, more importantly, establishes a causal network between events, helping users understand complex market dynamics. During the critical period of global central bank policy shifts in 2026, this function is particularly important.

A New Paradigm for US Stock Investment Analysis

For investors focused on the US stock market, CoreChip Event Timeline Calendar v3.0 offers a completely new analytical perspective. Traditional investment analysis often focuses on financial indicators and technical analysis, while v3.0 provides a more comprehensive analytical framework by placing corporate events in a macroeconomic context.

Take the second quarter of 2026 as an example. The platform successfully predicted the strong rebound of tech stocks after the Federal Reserve paused interest rate hikes. By analyzing the relationship between tech company earnings release times and policy cycles, as well as pattern recognition in historical data, the system issued a signal to increase tech stock holdings two weeks in advance, which highly matched subsequent market movements.

In addition, v3.0 introduces an "event sensitivity" scoring system that quantitatively evaluates each listed company. This score comprehensively considers the correlation between the company's business model, financial condition, industry positioning, and specific events, helping investors quickly identify the most promising investment targets. In the current environment of increasing market volatility, this function significantly improves the accuracy of investment decisions.

Cross-Department Collaboration and Strategic Alignment

In addition to investment analysis features, CoreChip Event Timeline Calendar v3.0 has also enhanced internal corporate collaboration capabilities. The new version is deeply integrated with mainstream collaboration platforms such as Microsoft Teams and Slack, enabling different departments to communicate and make decisions based on a unified event timeline.

For example, a multinational enterprise's finance, marketing, operations, and strategy teams can simultaneously access a shared event timeline to view the correlation between departmental key nodes and external events in real time. This transparent collaboration model greatly improves the enterprise's agility in responding to market changes, ensuring that departmental actions align with the company's overall strategy.

Against the backdrop of continuous global supply chain fluctuations in 2026, this cross-departmental collaboration capability is particularly important. Enterprises can use the platform to track production disruptions, logistics delays, and other events worldwide in real time, and quickly adjust procurement, production, and marketing strategies to reduce the impact of external shocks.

AI-Driven Personalized Insights

Another major highlight of CoreChip Event Timeline Calendar v3.0 is its AI-driven personalized insight function. The system automatically generates customized analysis reports and event alerts based on users' historical interests, investment portfolios, and reading preferences.

This function is particularly important for institutional investors. Large investment institutions typically need to monitor hundreds of companies and economic indicators simultaneously, while the AI assistant can help them filter the most relevant information and provide in-depth analysis. In the era of information overload, this intelligent filtering capability greatly improves decision-making efficiency.

In addition, the AI assistant can identify non-linear relationships and abnormal patterns that traditional analysis methods might miss. For example, in the spring of 2026, the system discovered a statistical correlation between the stock price fluctuations of certain tech companies and the spread of specific COVID-19 variants in certain regions. This discovery helped investors adjust their portfolio strategies in advance, avoiding potential losses.

Market Outlook and Competitive Landscape

As enterprises' demand for data-driven decision-making increases, the event timeline management market is experiencing rapid growth. According to data from industry analysis agencies, the global event management software market size is expected to reach $15 billion in 2026, with a compound annual growth rate exceeding 20%. In this rapidly growing market, CoreChip has established a clear competitive advantage through technological innovation and industry expertise.

Main competitors include traditional calendar software providers and emerging fintech companies. However, CoreChip's unique advantage lies in its deep integration of macroeconomic data and market analysis capabilities, which is difficult for most competitors to replicate. Especially in the field of US stock investment analysis, CoreChip's professional knowledge and data accumulation form a strong moat.

Looking ahead, CoreChip plans to further expand its AI analysis capabilities, adding more natural language processing functions to enable users to obtain complex market analysis through simple conversations. At the same time, the company is also exploring the application of blockchain technology in event data verification to ensure the accuracy and immutability of platform information.

User Cases and Practical Applications

Since the release of the v3.0 version, CoreChip Event Timeline Calendar has been adopted by numerous enterprises and investment institutions. Among them, a medium-sized asset management company used the platform to optimize its event-driven investment strategy. By accurately identifying the relationship between policy changes and industry rotation, it achieved a return rate of 4.2% above the benchmark index in the first half of 2026.

Another multinational manufacturing enterprise used the platform to coordinate its global supply chain management. By tracking regional policy changes and trade events in real time, it successfully avoided potential tariff risks and saved approximately 3% in operating costs. These successful cases demonstrate the practical value of CoreChip Event Timeline Calendar in different scenarios.

Conclusion and Outlook

In the environment of increasing global economic uncertainty in 2026, CoreChip Event Timeline Calendar v3.0 represents an important innovation in enterprise strategic planning and investment analysis. By organically combining macroeconomic data, corporate events, and market reactions, the platform provides users with unprecedented decision support.

With the continuous advancement of AI technology and the increasing richness of data sources, event timeline management tools will continue to evolve, becoming an indispensable part of the enterprise decision-making process. For investors, mastering the use of such tools will become one of the key capabilities to improve investment performance.

CoreChip's success also reflects the importance of data-driven decision-making in today's business environment. In the future, enterprises and individuals who can effectively integrate and analyze various event data will gain greater competitive advantages in the complex and changing market. As a hedge fund manager using the platform said: "In the era of information explosion, knowing what to pay attention to is more important than knowing everything, and CoreChip Event Timeline Calendar is precisely the tool that helps us make such choices."

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  1. CONNECT:[ UseTime:0.001058s ] mysql:host=127.0.0.1;port=3306;dbname=cjgpcs;charset=utf8mb4
  2. SHOW FULL COLUMNS FROM `g3ys_config` [ RunTime:0.002523s ]
  3. SELECT `value` FROM `g3ys_config` WHERE `name` = 'timezone' AND `subsite_id` = '6' LIMIT 1 [ RunTime:0.000839s ]
  4. SHOW FULL COLUMNS FROM `g3ys_route` [ RunTime:0.003204s ]
  5. SELECT * FROM `g3ys_route` WHERE ( `subsite_id` = '6' OR `subsite_id` = '0' ) AND `module` = 'home' AND `status` = 1 ORDER BY `sort` DESC,`id` ASC [ RunTime:0.000849s ]
  6. SHOW FULL COLUMNS FROM `g3ys_theme` [ RunTime:0.006376s ]
  7. SELECT `paginator` FROM `g3ys_theme` WHERE `module` = 'home' AND `name` = 'sgrateloan' AND `subsite_id` = '6' LIMIT 1 [ RunTime:0.001439s ]
  8. SHOW FULL COLUMNS FROM `g3ys_lang` [ RunTime:0.006347s ]
  9. SELECT * FROM `g3ys_lang` WHERE `subsite_id` = 6 AND ( ( LOWER(name) = 'en' ) OR `subtag` = 'en' ) AND `status` = 1 ORDER BY `id` ASC LIMIT 1 [ RunTime:0.002003s ]
  10. SHOW FULL COLUMNS FROM `g3ys_member` [ RunTime:0.009193s ]
  11. SELECT * FROM `g3ys_member` WHERE `id` = 0 AND `subsite_id` = '6' LIMIT 1 [ RunTime:0.000958s ]
  12. SHOW FULL COLUMNS FROM `g3ys_document` [ RunTime:0.005166s ]
  13. SELECT `id`,`document_type` FROM `g3ys_document` WHERE `subsite_id` = 6 AND `name` = 'corechip-event-timeline-calendar-v3-0-strategic-planning' AND `status` IN ('1','2') LIMIT 1 [ RunTime:0.002393s ]
  14. SELECT * FROM `g3ys_document` WHERE ( `name` = '6336' OR `id` = '6336' ) AND `subsite_id` = 6 LIMIT 1 [ RunTime:0.005954s ]
  15. SHOW TABLES LIKE 'g3ys_document_article' [ RunTime:0.002769s ]
  16. SHOW FULL COLUMNS FROM `g3ys_document_article` [ RunTime:0.001922s ]
  17. SELECT * FROM `g3ys_document_article` WHERE `document_id` = '6336' LIMIT 1 [ RunTime:0.000765s ]
  18. SHOW FULL COLUMNS FROM `g3ys_total` [ RunTime:0.002062s ]
  19. SELECT * FROM `g3ys_total` WHERE `target_id` = '6336' LIMIT 1 [ RunTime:0.000699s ]
  20. SHOW TABLES LIKE 'g3ys_document_article_lang' [ RunTime:0.001928s ]
  21. SHOW FULL COLUMNS FROM `g3ys_document_article_lang` [ RunTime:0.001797s ]
  22. SELECT * FROM `g3ys_document_article_lang` WHERE `subsite_id` = '6' AND `lang` = 'en' AND `document_id` = '6336' [ RunTime:0.005530s ]
  23. SHOW FULL COLUMNS FROM `g3ys_document_article_lang` [ RunTime:0.002276s ]
  24. SHOW TABLES LIKE 'g3ys_category_lang' [ RunTime:0.002155s ]
  25. SHOW FULL COLUMNS FROM `g3ys_category_lang` [ RunTime:0.001778s ]
  26. SELECT * FROM `g3ys_category_lang` WHERE `subsite_id` = '6' AND `category_id` = '1819' AND `lang` = 'en' LIMIT 1 [ RunTime:0.000801s ]
  27. SELECT * FROM `g3ys_total` WHERE `target_id` = '6336' LIMIT 1 [ RunTime:0.000597s ]
  28. UPDATE `g3ys_total` SET `view_total` = `view_total` + 1 WHERE `target_id` = '6336' [ RunTime:0.002143s ]
  29. SHOW FULL COLUMNS FROM `g3ys_record` [ RunTime:0.003868s ]
  30. SELECT `id` FROM `g3ys_record` WHERE `subsite_id` = '6' AND `type` = 'article' AND `url` = 'https://www.sgrateloan.com/corechip-event-timeline-calendar-v3-0-strategic-planning' AND `create_time` >= 1786254917 AND ( `visitor_id` = 'b9cc89ab5573b1261819b83aa90f8cbb' OR `session_id` = '6cd09744c8eacaea60545b3e03291faf' ) LIMIT 1 [ RunTime:0.001785s ]
  31. INSERT INTO `g3ys_record` SET `subsite_id` = '6' , `uid` = '0' , `visitor_id` = 'b9cc89ab5573b1261819b83aa90f8cbb' , `session_id` = '6cd09744c8eacaea60545b3e03291faf' , `type` = 'article' , `target_id` = '6336' , `target_type` = 0 , `category_id` = '1819' , `title` = 'CoreChip Event Timeline Calendar v3.0: AI-Driven Enterprise Strategic Planning and Investment Decision Revolution' , `url` = 'https://www.sgrateloan.com/corechip-event-timeline-calendar-v3-0-strategic-planning' , `path` = '/corechip-event-timeline-calendar-v3-0-strategic-planning' , `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` = '216.73.216.189' , `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` = 1786254977 , `update_time` = 1786254977 [ RunTime:0.006698s ]
  32. SHOW FULL COLUMNS FROM `g3ys_comment` [ RunTime:0.003597s ]
  33. SELECT COUNT(*) AS think_count FROM `g3ys_comment` WHERE `target_id` = '6336' AND `pid` = '0' [ RunTime:0.000724s ]
  34. SHOW FULL COLUMNS FROM `g3ys_model` [ RunTime:0.003791s ]
  35. SELECT `id`,`name`,`title`,`field_group` FROM `g3ys_model` WHERE `extend` = 0 AND `id` <> 1 AND `subsite_id` IN ('0','6') AND `status` = 1 [ RunTime:0.001171s ]
  36. SHOW TABLES LIKE 'g3ys_paragraph' [ RunTime:0.002593s ]
  37. SHOW TABLES LIKE 'g3ys_paragraph_lang' [ RunTime:0.002232s ]
  38. SHOW TABLES LIKE 'g3ys_gallery' [ RunTime:0.001990s ]
  39. SHOW TABLES LIKE 'g3ys_gallery_lang' [ RunTime:0.002069s ]
  40. SHOW TABLES LIKE 'g3ys_video' [ RunTime:0.001972s ]
  41. SHOW TABLES LIKE 'g3ys_video_lang' [ RunTime:0.002035s ]
  42. SHOW TABLES LIKE 'g3ys_faq' [ RunTime:0.002034s ]
  43. SHOW TABLES LIKE 'g3ys_faq_lang' [ RunTime:0.002021s ]
  44. SHOW TABLES LIKE 'g3ys_blockquote' [ RunTime:0.001959s ]
  45. SHOW TABLES LIKE 'g3ys_blockquote_lang' [ RunTime:0.002473s ]
  46. SHOW TABLES LIKE 'g3ys_cards' [ RunTime:0.002138s ]
  47. SHOW TABLES LIKE 'g3ys_cards_lang' [ RunTime:0.001942s ]
  48. SHOW TABLES LIKE 'g3ys_objects' [ RunTime:0.001943s ]
  49. SHOW TABLES LIKE 'g3ys_objects_lang' [ RunTime:0.001981s ]
  50. SHOW TABLES LIKE 'g3ys_videos' [ RunTime:0.002018s ]
  51. SHOW TABLES LIKE 'g3ys_videos_lang' [ RunTime:0.001917s ]
  52. SHOW TABLES LIKE 'g3ys_audios' [ RunTime:0.002137s ]
  53. SHOW TABLES LIKE 'g3ys_audios_lang' [ RunTime:0.001884s ]
  54. SHOW TABLES LIKE 'g3ys_files' [ RunTime:0.002162s ]
  55. SHOW TABLES LIKE 'g3ys_files_lang' [ RunTime:0.002204s ]
  56. SHOW TABLES LIKE 'g3ys_richmedia' [ RunTime:0.002048s ]
  57. SHOW TABLES LIKE 'g3ys_richmedia_lang' [ RunTime:0.001982s ]
  58. SHOW FULL COLUMNS FROM `g3ys_paragraph` [ RunTime:0.002226s ]
  59. SELECT * FROM `g3ys_paragraph` WHERE `document_id` = 6336 AND `subsite_id` = '6' AND `status` = 1 ORDER BY `sort` ASC,`id` ASC [ RunTime:0.001011s ]
  60. SHOW FULL COLUMNS FROM `g3ys_gallery` [ RunTime:0.001974s ]
  61. SELECT * FROM `g3ys_gallery` WHERE `document_id` = 6336 AND `subsite_id` = 6 AND `status` = 1 ORDER BY `sort` ASC,`id` ASC [ RunTime:0.000933s ]
  62. SHOW FULL COLUMNS FROM `g3ys_video` [ RunTime:0.002590s ]
  63. SELECT * FROM `g3ys_video` WHERE `document_id` = 6336 AND `subsite_id` = 6 AND `status` = 1 ORDER BY `sort` ASC,`id` ASC [ RunTime:0.000931s ]
  64. SHOW FULL COLUMNS FROM `g3ys_faq` [ RunTime:0.001912s ]
  65. SELECT * FROM `g3ys_faq` WHERE `document_id` = 6336 AND `subsite_id` = 6 AND `status` = 1 ORDER BY `sort` ASC,`id` ASC [ RunTime:0.001040s ]
  66. SHOW FULL COLUMNS FROM `g3ys_blockquote` [ RunTime:0.002215s ]
  67. SELECT * FROM `g3ys_blockquote` WHERE `document_id` = 6336 AND `subsite_id` = 6 AND `status` = 1 ORDER BY `sort` ASC,`id` ASC [ RunTime:0.001011s ]
  68. SHOW FULL COLUMNS FROM `g3ys_cards` [ RunTime:0.002129s ]
  69. SELECT * FROM `g3ys_cards` WHERE `document_id` = 6336 AND `subsite_id` = '6' AND `status` = 1 ORDER BY `sort` ASC,`id` ASC [ RunTime:0.001286s ]
  70. SHOW FULL COLUMNS FROM `g3ys_objects` [ RunTime:0.002113s ]
  71. SELECT * FROM `g3ys_objects` WHERE `document_id` = 6336 AND `subsite_id` = '6' AND `status` = 1 ORDER BY `sort` ASC,`id` ASC [ RunTime:0.000945s ]
  72. SHOW FULL COLUMNS FROM `g3ys_videos` [ RunTime:0.002103s ]
  73. SELECT * FROM `g3ys_videos` WHERE `document_id` = 6336 AND `subsite_id` = '6' AND `status` = 1 ORDER BY `sort` ASC,`id` ASC [ RunTime:0.000951s ]
  74. SHOW FULL COLUMNS FROM `g3ys_audios` [ RunTime:0.002358s ]
  75. SELECT * FROM `g3ys_audios` WHERE `document_id` = 6336 AND `subsite_id` = '6' AND `status` = 1 ORDER BY `sort` ASC,`id` ASC [ RunTime:0.000969s ]
  76. SHOW FULL COLUMNS FROM `g3ys_files` [ RunTime:0.003985s ]
  77. SELECT * FROM `g3ys_files` WHERE `document_id` = 6336 AND `subsite_id` = '6' AND `status` = 1 ORDER BY `sort` ASC,`id` ASC [ RunTime:0.001032s ]
  78. SHOW FULL COLUMNS FROM `g3ys_richmedia` [ RunTime:0.002275s ]
  79. SELECT * FROM `g3ys_richmedia` WHERE `document_id` = 6336 AND `subsite_id` = '6' AND `status` = 1 ORDER BY `sort` ASC,`id` ASC [ RunTime:0.001137s ]
  80. SELECT * FROM `g3ys_document` WHERE `category_id` = 1819 AND `subsite_id` = 6 AND `pid` = '0' AND `status` = '1' AND ( ( sort > 0) or ( sort = 0 and id < 6336) ) ORDER BY `sort` ASC,`id` DESC LIMIT 1 [ RunTime:0.001611s ]
  81. SELECT * FROM `g3ys_document` WHERE `category_id` = 1819 AND `subsite_id` = 6 AND `pid` = '6207' AND `status` = '1' ORDER BY `sort` ASC,`id` DESC LIMIT 1 [ RunTime:0.001128s ]
  82. SELECT * FROM `g3ys_document_article_lang` WHERE `subsite_id` = '6' AND `lang` = 'en' AND `document_id` = '6207' [ RunTime:0.005525s ]
  83. SELECT * FROM `g3ys_document` WHERE `category_id` = 1819 AND `subsite_id` = 6 AND `pid` = '6336' AND `status` = '1' AND `document_type` = 0 ORDER BY `sort` DESC,`id` ASC LIMIT 1 [ RunTime:0.001687s ]
  84. SELECT * FROM `g3ys_document` WHERE `category_id` = 1819 AND `subsite_id` = 6 AND `pid` = '0' AND `status` = '1' AND `document_type` = 0 AND ( ( sort>0 and sort <= 0 and id!=6336) or ( sort = 0 and id > 6336) ) ORDER BY `sort` DESC,`id` ASC LIMIT 1 [ RunTime:0.001334s ]
  85. SELECT * FROM `g3ys_route` WHERE ( `subsite_id` = '6' OR `subsite_id` = '0' ) AND `module` = 'home' AND `status` = 1 ORDER BY `sort` DESC,`id` ASC [ RunTime:0.000903s ]
  86. SELECT * FROM `g3ys_category_lang` WHERE `subsite_id` = '6' AND `category_id` = '1813' AND `lang` = 'en' LIMIT 1 [ RunTime:0.000778s ]
  87. SELECT * FROM `g3ys_category_lang` WHERE `subsite_id` = '6' AND `category_id` = '1816' AND `lang` = 'en' LIMIT 1 [ RunTime:0.000604s ]
  88. SELECT * FROM `g3ys_category_lang` WHERE `subsite_id` = '6' AND `category_id` = '1817' AND `lang` = 'en' LIMIT 1 [ RunTime:0.000680s ]
  89. SELECT * FROM `g3ys_category_lang` WHERE `subsite_id` = '6' AND `category_id` = '2048' AND `lang` = 'en' LIMIT 1 [ RunTime:0.000681s ]
  90. SELECT * FROM `g3ys_category_lang` WHERE `subsite_id` = '6' AND `category_id` = '2049' AND `lang` = 'en' LIMIT 1 [ RunTime:0.000807s ]
  91. SELECT * FROM `g3ys_category_lang` WHERE `subsite_id` = '6' AND `category_id` = '2050' AND `lang` = 'en' LIMIT 1 [ RunTime:0.000714s ]
  92. SELECT * FROM `g3ys_total` WHERE `target_id` = '6336' LIMIT 1 [ RunTime:0.000769s ]
  93. SHOW FULL COLUMNS FROM `g3ys_ad_location` [ RunTime:0.003726s ]
  94. SELECT * FROM `g3ys_ad_location` WHERE `name` = 'ad-detail-full' AND `subsite_id` = '6' AND `status` = 1 LIMIT 1 [ RunTime:0.000971s ]
  95. SHOW FULL COLUMNS FROM `g3ys_ad` [ RunTime:0.002944s ]
  96. SELECT * FROM `g3ys_ad` WHERE `subsite_id` = '6' AND `ad_location_id` = '15' AND `status` = 1 AND `device` IN ('all','pc') AND ( `start_time` = 0 OR `start_time` <= 1786254977 ) AND ( `end_time` = 0 OR `end_time` >= 1786254977 ) ORDER BY `sort` DESC,`id` DESC [ RunTime:0.001004s ]
  97. SHOW FULL COLUMNS FROM `g3ys_ad_lang` [ RunTime:0.001893s ]
  98. SELECT * FROM `g3ys_ad_lang` WHERE `ad_id` = 15 AND `subsite_id` = '6' AND `lang` = 'en' [ RunTime:0.000835s ]
  99. SHOW FULL COLUMNS FROM `g3ys_ad_lang` [ RunTime:0.001851s ]
  100. SHOW FULL COLUMNS FROM `g3ys_tags` [ RunTime:0.002474s ]
  101. SELECT `title`,`color`,`description`,`seotitle`,`keyword`,`name`,`id` FROM `g3ys_tags` WHERE `id` IN (52,69,53,66,61) AND `status` = 1 [ RunTime:0.000880s ]
  102. SHOW FULL COLUMNS FROM `g3ys_tags_lang` [ RunTime:0.001644s ]
  103. SELECT * FROM `g3ys_tags_lang` WHERE `tags_id` IN (52,69,53,66,61) AND `subsite_id` = 6 AND `lang` = 'en' [ RunTime:0.000830s ]
  104. SELECT * FROM `g3ys_route` WHERE ( `subsite_id` = '6' OR `subsite_id` = '0' ) AND `module` = 'home' AND `status` = 1 ORDER BY `sort` DESC,`id` ASC [ RunTime:0.000737s ]
  105. SELECT * FROM `g3ys_ad_location` WHERE `name` = 'ad-right' AND `subsite_id` = '6' AND `status` = 1 LIMIT 1 [ RunTime:0.000733s ]
  106. SELECT * FROM `g3ys_ad` WHERE `subsite_id` = '6' AND `ad_location_id` = '17' AND `status` = 1 AND `device` IN ('all','pc') AND ( `start_time` = 0 OR `start_time` <= 1786254977 ) AND ( `end_time` = 0 OR `end_time` >= 1786254977 ) ORDER BY `sort` DESC,`id` DESC [ RunTime:0.000894s ]
  107. SELECT * FROM `g3ys_ad_lang` WHERE `ad_id` = 17 AND `subsite_id` = '6' AND `lang` = 'en' [ RunTime:0.000642s ]
  108. SELECT `id`,`name`,`title`,`create_time`,`model_id` 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` = 6 AND `category_id` = 1819 AND `status` = '1' AND `model_id` = 2 AND `document_type` = 0 AND `id` <> '6336' ORDER BY `sort` DESC,`id` DESC LIMIT 0,10 [ RunTime:0.001542s ]
  109. SELECT * FROM `g3ys_document_article_lang` WHERE `subsite_id` = '6' AND `lang` = 'en' AND `document_id` IN ('6207','5754','5741','5626','5410','5409','5408','5407','5406','5280') [ RunTime:0.006759s ]
  110. SELECT * FROM `g3ys_route` WHERE ( `subsite_id` = '6' OR `subsite_id` = '0' ) AND `module` = 'home' AND `status` = 1 ORDER BY `sort` DESC,`id` ASC [ RunTime:0.000953s ]
  111. SELECT * FROM `g3ys_route` WHERE ( `subsite_id` = '6' OR `subsite_id` = '0' ) AND `module` = 'home' AND `status` = 1 ORDER BY `sort` DESC,`id` ASC [ RunTime:0.000748s ]
  112. SELECT * FROM `g3ys_route` WHERE ( `subsite_id` = '6' OR `subsite_id` = '0' ) AND `module` = 'home' AND `status` = 1 ORDER BY `sort` DESC,`id` ASC [ RunTime:0.000689s ]
  113. SELECT * FROM `g3ys_route` WHERE ( `subsite_id` = '6' OR `subsite_id` = '0' ) AND `module` = 'home' AND `status` = 1 ORDER BY `sort` DESC,`id` ASC [ RunTime:0.000658s ]
  114. SELECT * FROM `g3ys_route` WHERE ( `subsite_id` = '6' OR `subsite_id` = '0' ) AND `module` = 'home' AND `status` = 1 ORDER BY `sort` DESC,`id` ASC [ RunTime:0.000698s ]
  115. SELECT * FROM `g3ys_route` WHERE ( `subsite_id` = '6' OR `subsite_id` = '0' ) AND `module` = 'home' AND `status` = 1 ORDER BY `sort` DESC,`id` ASC [ RunTime:0.000687s ]
  116. SELECT * FROM `g3ys_route` WHERE ( `subsite_id` = '6' OR `subsite_id` = '0' ) AND `module` = 'home' AND `status` = 1 ORDER BY `sort` DESC,`id` ASC [ RunTime:0.000977s ]
  117. SELECT * FROM `g3ys_route` WHERE ( `subsite_id` = '6' OR `subsite_id` = '0' ) AND `module` = 'home' AND `status` = 1 ORDER BY `sort` DESC,`id` ASC [ RunTime:0.000746s ]
  118. SELECT * FROM `g3ys_route` WHERE ( `subsite_id` = '6' OR `subsite_id` = '0' ) AND `module` = 'home' AND `status` = 1 ORDER BY `sort` DESC,`id` ASC [ RunTime:0.000738s ]
  119. SELECT * FROM `g3ys_route` WHERE ( `subsite_id` = '6' OR `subsite_id` = '0' ) AND `module` = 'home' AND `status` = 1 ORDER BY `sort` DESC,`id` ASC [ RunTime:0.001020s ]
  120. SELECT * FROM `g3ys_route` WHERE ( `subsite_id` = '6' OR `subsite_id` = '0' ) AND `module` = 'home' AND `status` = 1 ORDER BY `sort` DESC,`id` ASC [ RunTime:0.001203s ]
  121. SELECT * FROM `g3ys_route` WHERE ( `subsite_id` = '6' OR `subsite_id` = '0' ) AND `module` = 'home' AND `status` = 1 ORDER BY `sort` DESC,`id` ASC [ RunTime:0.000839s ]
  122. SELECT * FROM `g3ys_route` WHERE ( `subsite_id` = '6' OR `subsite_id` = '0' ) AND `module` = 'home' AND `status` = 1 ORDER BY `sort` DESC,`id` ASC [ RunTime:0.000758s ]
  123. SELECT * FROM `g3ys_route` WHERE ( `subsite_id` = '6' OR `subsite_id` = '0' ) AND `module` = 'home' AND `status` = 1 ORDER BY `sort` DESC,`id` ASC [ RunTime:0.000746s ]
  124. SELECT * FROM `g3ys_route` WHERE ( `subsite_id` = '6' OR `subsite_id` = '0' ) AND `module` = 'home' AND `status` = 1 ORDER BY `sort` DESC,`id` ASC [ RunTime:0.000928s ]
  125. SELECT * FROM `g3ys_tags` WHERE `subsite_id` = 6 AND `status` = 1 ORDER BY `sort` DESC,`id` DESC LIMIT 15 [ RunTime:0.005223s ]
  126. SELECT * FROM `g3ys_tags_lang` WHERE `tags_id` IN (78,77,76,75,74,73,72,71,70,69,68,67,66,65,64) AND `subsite_id` = 6 AND `lang` = 'en' [ RunTime:0.001082s ]
  127. SELECT * FROM `g3ys_route` WHERE ( `subsite_id` = '6' OR `subsite_id` = '0' ) AND `module` = 'home' AND `status` = 1 ORDER BY `sort` DESC,`id` ASC [ RunTime:0.000731s ]
  128. SELECT * FROM `g3ys_route` WHERE ( `subsite_id` = '6' OR `subsite_id` = '0' ) AND `module` = 'home' AND `status` = 1 ORDER BY `sort` DESC,`id` ASC [ RunTime:0.000778s ]
  129. SELECT * FROM `g3ys_route` WHERE ( `subsite_id` = '6' OR `subsite_id` = '0' ) AND `module` = 'home' AND `status` = 1 ORDER BY `sort` DESC,`id` ASC [ RunTime:0.000713s ]
0.555383s