2026年08月07日 Friday Insight into China-Singapore Capital Markets, Deep Diving into Global Asset Allocation
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SanDisk, Western Digital Earnings Miss Spark Pre-Market Selloff in Storage Stocks; Dow Futures Firm, Nasdaq Futures Lag

SanDisk, Western Digital Earnings Miss Spark Pre-Market Selloff in Storage Stocks; Dow Futures Firm, Nasdaq Futures Lag

At 8:00 a.m. ET on Thursday, August 6, U.S. stock index futures once again showed a 'tale of two markets' ahead of the open: Dow futures and S&P 500 futures edged higher, while Nasdaq futures slumped more than 0.5%. The trigger for the market turbulence was the after-hours earnings from the storage chip duo — SanDisk and Western Digital. Both companies beat expectations, but their guidance failed to satisfy Wall Street's AI-fueled appetite, sending their shares tumbling and dragging the entire storage sector into a pre-market selloff.

Index Divergence Deepens: Dow Stands Alone, Tech Stocks Give Back Gains

Let's first review the closing picture from the previous trading session. On Monday, August 5, the Dow Jones Industrial Average rose 0.49% to close at 54,349.12, marking its fifth straight record close. The S&P 500 briefly hit an intraday record of 7,793 in early trading but then turned lower and closed down 0.17% at 7,723.55. The Nasdaq fell 0.83% to 26,363.44. The sharp divergence among the three major indexes clearly outlines the current rotation pattern of 'fleeing tech, embracing traditional' — the Dow's heavy weights in banks, industrials and energy benefit from economic resilience and rising oil prices, while AI-related high-valuation growth stocks continue to face profit-taking pressure.

Pre-market trading continued that divergence. As of writing, Dow futures were up about 0.17% to 0.25%, S&P 500 futures were slightly higher around 0.1%, while Nasdaq 100 futures fell 0.5% to 0.76%. European stocks advanced modestly, with German, French and UK FTSE 100 indexes all edging up, indicating that Asian and European capital did not show systemic risk-off; selling pressure was highly concentrated in U.S. tech and semiconductor groups.

Earnings 'Surprise Becomes Shock': Storage Chip Stocks Tumble Pre-Market

The trigger for this pre-market selloff was the earnings and guidance gap from SanDisk and Western Digital. Start with SanDisk: In its fiscal fourth quarter ended July 3, revenue came in at $8.97 billion, up 372% year over year, well above the market's expected $8.39 billion. Adjusted EPS of $39.25 also beat the consensus of $34.45. Data center revenue doubled in the quarter to $2.98 billion, proving that generative AI and AI agents continue to boost demand for enterprise SSDs and NAND flash memory — the growth engine has shifted from traditional smartphones and PCs to AI infrastructure.

The problem lies in the outlook. SanDisk guided fiscal first-quarter revenue in a range of $10.3 billion to $10.8 billion. Although the midpoint was above the LSEG analyst average of $10.47 billion, it was nearly 5.5% below the more optimistic consensus of $11.16 billion compiled by another data provider. Adjusted EPS guidance midpoint of $45 was also slightly below the market's expected $45.58. In other words, the company didn't give 'bad guidance' — it gave 'not perfect enough guidance.' In the extremely optimistic mood fueled by the AI boom, any number that falls short of the ceiling gets magnified as punishment. SanDisk was down more than 11% pre-market at one point.

Western Digital's script was similar. Fiscal fourth-quarter revenue was $3.75 billion, up 44% year over year, slightly above the expected $3.68 billion. Adjusted EPS of $3.56 beat the consensus of $3.31. First-quarter revenue guidance of $4.0 billion to $4.2 billion had a midpoint above the market's $4.06 billion, reflecting near 'insatiable' global demand for nearline high-capacity HDDs. However, Western Digital's stock had already soared about 201% this year, with the market pricing in the rich dividends from HDD shortages well in advance. While this guidance beat baseline expectations, it did not offer the kind of aggressive long-term supply and order-lockup outlook that rival Seagate provided, appearing relatively cautious. So the 'expectation cliff' effect erupted — the stock plunged over 16% pre-market.

The domino effect quickly spread across the entire storage supply chain: SK Hynix's U.S.-listed shares fell more than 6% pre-market, Micron fell more than 3% to 4%, and Seagate also dropped more than 3.5%. The Philadelphia Semiconductor Index had already fallen 1.4% in the previous session, and with renewed pre-market selling, semiconductor stocks may find it hard to stabilize in the short term.

AppLovin Plunges 18%, OXY Hits Four-Year Profit High

Pre-market movers were not limited to storage chips. Ad-tech company AppLovin's second-quarter revenue was $1.92 billion, up 53% year over year, slightly below analysts' estimate of $1.94 billion. Net profit rose 55% to $1.27 billion, with adjusted EPS of $3.76 slightly beating. But the CEO admitted that the company's games-focused ad business is highly reliant on AI model performance iterations, and in the second quarter 'the expected jump in model performance did not materialize.' Combined with third-quarter revenue guidance midpoint of $2.07 billion, slightly below the market's $2.08 billion, investors showed no mercy, sending the stock down more than 18% pre-market.

Energy stocks received a completely different treatment from earnings. Benefiting from higher oil prices amid Middle East turmoil, Occidental Petroleum reported second-quarter revenue of $8.32 billion, up 57% year over year, beating expectations by $1.07 billion. Adjusted EPS of $2.40 beat by $0.55, and profit hit a four-year high. The realized crude price rose more than 50% year over year to $96.78 per barrel, while global average production grew 2.4% to 1.43 million barrels of oil equivalent per day. The company also cut its 2026 capital expenditure guidance from $6.3-$6.7 billion to $5.5-$5.9 billion, showing a preference for returning cash to shareholders as cash flow improves. The stock rose nearly 2% pre-market against the trend. In addition, Moderna's first mRNA flu vaccine, mFLUSIVA, received FDA approval, and its stock rose nearly 4% pre-market. Advertising giant WPP surged more than 25% pre-market as cost cuts boosted first-half profit above expectations.

Macro Crosscurrents: Employment Resilience Meets Inflation Worries

Macro headlines also moved pre-market sentiment. San Francisco Fed President Daly endorsed holding rates steady in July, but issued a rare warning that inflation could 'spread': rising tariffs, climbing energy costs and increasing AI investment could make price pressures broader and more persistent, suggesting policymakers should be prepared to take more aggressive action. Divisions within the Fed over the rate-cut path are escalating amid stubborn inflation.

The labor market brought good news. According to the latest Challenger report, U.S. employers announced 33,429 job cuts in July, down sharply from roughly 46,000 in June and the lowest monthly total in nearly two years. Corporate hiring plans hit their highest level for the same period since 2022. Although AI continues to reshape tech employment — with tech still the hardest-hit sector for layoffs, accounting for about a third of this year's total — strong demand from manufacturing and offline services continues to support the labor market. Market attention has turned to Friday's July nonfarm payrolls report, which is generally expected to show 83,000 jobs added and the unemployment rate holding at a low 4.2%. While strong employment data underscores economic resilience, it could also further delay the Fed's rate cuts, posing a challenge to tech stocks' high valuations.

Institutions Warn: Tech Stocks May Become More 'Retail-Driven' with Hidden Leverage Risks

Regarding July's sharp tech-stock swings, JPMorgan published an assessment saying the selloff may be structurally changing the market microstructure of tech trading. Hedge funds, after losses, are forced to adopt stricter risk controls and concentration limits, reducing their ability to trade highly volatile tech stocks; prime brokers may also shrink related balance-sheet space. If this trend continues, tech trading will rely more heavily on retail money and become more susceptible to volatility shocks from leveraged ETFs, retail options buying and margin accounts. JPMorgan CEO Jamie Dimon went further, saying current market leverage is 'quite high,' with margin debt at record levels and substantial hidden borrowing under other guises across prime brokerage, hedge funds, ETFs and Treasury arbitrage. The risk that any single entity quickly disrupts the market and sparks panic is rising.

Meanwhile, oil prices and geopolitics remain the biggest wildcards. Brent crude has fallen to below $80, down from a peak of $100 per barrel in late July, mainly reflecting market hopes that the U.S., Iran and Gulf states are close to an agreement restoring partial passage through the Strait of Hormuz. However, the strong 'backwardation' structure — October contracts trading at a premium of as much as $1.50 over November — signals extremely tight physical supply. Distillate inventories such as diesel have been nearly depleted during the summer peak-demand season. If diplomatic talks falter, energy prices could spike again, reigniting dual pressure on inflation and equities.

Investment Takeaways: Crowded-Trade Backlash and Diversified Allocation

Taken together, the U.S. market is in a typical phase of 'record-high indexes with intense internal rotation.' The SanDisk and Western Digital lesson is highly representative: fundamentals continue to deliver, but share prices have already priced years of growth ahead of time, so any signal of 'slowing growth' triggers a stampede-like correction. This echoes JPMorgan's warning about tech stocks becoming 'retail-driven and highly volatile' — when positions are overly concentrated in a single narrative, even small negative news surprises can be amplified by leverage.

For investors, three points deserve attention at this moment. First, examine the 'expectation overhang' in your holdings — beating earnings doesn't mean the stock will rise; the match between guidance and valuation is what matters. Second, moderately reduce concentration in tech and semiconductors, and watch for rotation opportunities in sectors benefiting from the cycle and geopolitical tailwinds, such as energy, industrials and financials. Third, strictly control leverage and avoid taking on hidden borrowing risks in a more volatile environment. Friday's payrolls report and the evolution of Middle East tensions will be two key variables determining whether U.S. stocks can continue their run at historical highs.

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  195. /www/wwwroot/cjgpcs.cn/vendor/topthink/framework/src/think/middleware/LoadLangPack.php ( 3.50 KB )
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  1. CONNECT:[ UseTime:0.001232s ] mysql:host=127.0.0.1;port=3306;dbname=cjgpcs;charset=utf8mb4
  2. SHOW FULL COLUMNS FROM `g3ys_config` [ RunTime:0.003276s ]
  3. SELECT `value` FROM `g3ys_config` WHERE `name` = 'timezone' AND `subsite_id` = '38' LIMIT 1 [ RunTime:0.000683s ]
  4. SHOW FULL COLUMNS FROM `g3ys_route` [ RunTime:0.003786s ]
  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:0.000914s ]
  6. SHOW FULL COLUMNS FROM `g3ys_theme` [ RunTime:0.004053s ]
  7. SELECT `paginator` FROM `g3ys_theme` WHERE `module` = 'home' AND `name` = 'slogan' AND `subsite_id` = '38' LIMIT 1 [ RunTime:0.000798s ]
  8. SHOW FULL COLUMNS FROM `g3ys_lang` [ RunTime:0.005162s ]
  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:0.001748s ]
  10. SHOW FULL COLUMNS FROM `g3ys_member` [ RunTime:0.007672s ]
  11. SELECT * FROM `g3ys_member` WHERE `id` = 0 AND `subsite_id` = '38' LIMIT 1 [ RunTime:0.001634s ]
  12. SHOW FULL COLUMNS FROM `g3ys_document` [ RunTime:0.011144s ]
  13. SELECT `id`,`document_type` FROM `g3ys_document` WHERE `subsite_id` = 38 AND `name` = 'us-stock-premarket-storage-chip-selloff-2026' AND `status` IN ('1','2') LIMIT 1 [ RunTime:0.019760s ]
  14. SELECT * FROM `g3ys_document` WHERE ( `name` = '6223' OR `id` = '6223' ) AND `subsite_id` = 38 LIMIT 1 [ RunTime:0.016229s ]
  15. SHOW TABLES LIKE 'g3ys_document_article' [ RunTime:0.006887s ]
  16. SHOW FULL COLUMNS FROM `g3ys_document_article` [ RunTime:0.003069s ]
  17. SELECT * FROM `g3ys_document_article` WHERE `document_id` = '6223' LIMIT 1 [ RunTime:0.001302s ]
  18. SHOW FULL COLUMNS FROM `g3ys_total` [ RunTime:0.003960s ]
  19. SELECT * FROM `g3ys_total` WHERE `target_id` = '6223' LIMIT 1 [ RunTime:0.000928s ]
  20. SHOW TABLES LIKE 'g3ys_document_article_lang' [ RunTime:0.003723s ]
  21. SHOW FULL COLUMNS FROM `g3ys_document_article_lang` [ RunTime:0.003029s ]
  22. SELECT * FROM `g3ys_document_article_lang` WHERE `subsite_id` = '38' AND `lang` = 'en-US' AND `document_id` = '6223' [ RunTime:0.008675s ]
  23. SHOW FULL COLUMNS FROM `g3ys_document_article_lang` [ RunTime:0.003188s ]
  24. SHOW TABLES LIKE 'g3ys_category_lang' [ RunTime:0.002139s ]
  25. SHOW FULL COLUMNS FROM `g3ys_category_lang` [ RunTime:0.002868s ]
  26. SELECT * FROM `g3ys_category_lang` WHERE `subsite_id` = '38' AND `category_id` = '1464' AND `lang` = 'en-US' LIMIT 1 [ RunTime:0.000999s ]
  27. SELECT * FROM `g3ys_total` WHERE `target_id` = '6223' LIMIT 1 [ RunTime:0.000880s ]
  28. UPDATE `g3ys_total` SET `view_total` = `view_total` + 1 WHERE `target_id` = '6223' [ RunTime:0.002857s ]
  29. SHOW FULL COLUMNS FROM `g3ys_record` [ RunTime:0.009391s ]
  30. SELECT `id` FROM `g3ys_record` WHERE `subsite_id` = '38' AND `type` = 'article' AND `url` = 'https://www.cninsgx.com/us-stock-premarket-storage-chip-selloff-2026' AND `create_time` >= 1786070074 AND ( `visitor_id` = '791c33931529fadf5943344bfb345d07' OR `session_id` = 'b043dc5346d3133308c6d6004af05e55' ) LIMIT 1 [ RunTime:0.001634s ]
  31. INSERT INTO `g3ys_record` SET `subsite_id` = '38' , `uid` = '0' , `visitor_id` = '791c33931529fadf5943344bfb345d07' , `session_id` = 'b043dc5346d3133308c6d6004af05e55' , `type` = 'article' , `target_id` = '6223' , `target_type` = 0 , `category_id` = '1464' , `title` = 'SanDisk, Western Digital Earnings Miss Spark Pre-Market Selloff in Storage Stocks; Dow Futures Firm, Nasdaq Futures Lag' , `url` = 'https://www.cninsgx.com/us-stock-premarket-storage-chip-selloff-2026' , `path` = '/us-stock-premarket-storage-chip-selloff-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` = '216.73.216.246' , `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` = 1786070134 , `update_time` = 1786070134 [ RunTime:0.009039s ]
  32. SHOW FULL COLUMNS FROM `g3ys_comment` [ RunTime:0.007901s ]
  33. SELECT COUNT(*) AS think_count FROM `g3ys_comment` WHERE `target_id` = '6223' AND `pid` = '0' [ RunTime:0.002477s ]
  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 < 6223) ) ORDER BY `sort` ASC,`id` DESC LIMIT 1 [ RunTime:0.001978s ]
  35. SELECT * FROM `g3ys_document` WHERE `category_id` = 1464 AND `subsite_id` = 38 AND `pid` = '6171' AND `status` = '1' ORDER BY `sort` ASC,`id` DESC LIMIT 1 [ RunTime:0.003250s ]
  36. SELECT * FROM `g3ys_document_article_lang` WHERE `subsite_id` = '38' AND `lang` = 'en-US' AND `document_id` = '6171' [ RunTime:0.012050s ]
  37. SELECT * FROM `g3ys_document` WHERE `category_id` = 1464 AND `subsite_id` = 38 AND `pid` = '6223' AND `status` = '1' AND `document_type` = 0 ORDER BY `sort` DESC,`id` ASC LIMIT 1 [ RunTime:0.003034s ]
  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!=6223) or ( sort = 0 and id > 6223) ) ORDER BY `sort` DESC,`id` ASC LIMIT 1 [ RunTime:0.003963s ]
  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:0.002862s ]
  40. SELECT * FROM `g3ys_total` WHERE `target_id` = '6223' LIMIT 1 [ RunTime:0.001261s ]
  41. SHOW FULL COLUMNS FROM `g3ys_ad_location` [ RunTime:0.008577s ]
  42. SELECT * FROM `g3ys_ad_location` WHERE `name` = 'ad-detail-full' AND `subsite_id` = '38' AND `status` = 1 LIMIT 1 [ RunTime:0.001141s ]
  43. SHOW FULL COLUMNS FROM `g3ys_ad` [ RunTime:0.005648s ]
  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` <= 1786070135 ) AND ( `end_time` = 0 OR `end_time` >= 1786070135 ) ORDER BY `sort` DESC,`id` DESC [ RunTime:0.003091s ]
  45. SHOW FULL COLUMNS FROM `g3ys_ad_lang` [ RunTime:0.002558s ]
  46. SELECT * FROM `g3ys_ad_lang` WHERE `ad_id` = 74 AND `subsite_id` = '38' AND `lang` = 'en-US' [ RunTime:0.002623s ]
  47. SHOW FULL COLUMNS FROM `g3ys_ad_lang` [ RunTime:0.004999s ]
  48. SHOW FULL COLUMNS FROM `g3ys_tags` [ RunTime:0.005289s ]
  49. SELECT `title`,`color`,`description`,`seotitle`,`keyword`,`name`,`id` FROM `g3ys_tags` WHERE `id` IN (427,452,449,440,438,446,454,443) AND `status` = 1 [ RunTime:0.002600s ]
  50. SHOW FULL COLUMNS FROM `g3ys_tags_lang` [ RunTime:0.004155s ]
  51. SELECT * FROM `g3ys_tags_lang` WHERE `tags_id` IN (427,452,449,440,438,446,454,443) AND `subsite_id` = 38 AND `lang` = 'en-US' [ RunTime:0.003395s ]
  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:0.002919s ]
  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:0.001144s ]
  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:0.003052s ]
  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:0.002409s ]
  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:0.001306s ]
  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:0.001340s ]
  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:0.001131s ]
  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:0.002489s ]
  60. SELECT * FROM `g3ys_ad_location` WHERE `name` = 'ad-right' AND `subsite_id` = '38' AND `status` = 1 LIMIT 1 [ RunTime:0.000921s ]
  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` <= 1786070135 ) AND ( `end_time` = 0 OR `end_time` >= 1786070135 ) ORDER BY `sort` DESC,`id` DESC [ RunTime:0.001615s ]
  62. SELECT * FROM `g3ys_ad_lang` WHERE `ad_id` = 76 AND `subsite_id` = '38' AND `lang` = 'en-US' [ RunTime:0.002420s ]
  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:0.000911s ]
  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:0.001006s ]
  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:0.002246s ]
  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:0.001001s ]
  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:0.002408s ]
  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:0.000981s ]
  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:0.000902s ]
  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:0.000833s ]
  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:0.001018s ]
0.746676s