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I m Md Nazim, working in this field for more than two years and research with off-page SEO and Backlink Industry. I work as a professional Digital Marketing Expert and SEO specialist in different online marketplace as well as the local market. Currently, I study in China with International Economic

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Hey there everyone! I am Shiblu offering the standard service you would like for your project. I m an SEO expert and have strong control over on-page optimization and off-page optimization. If you re trying to find professional and technical SEO services then you ve got come to the correct place.

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Possible Duplicate queries found!
MatchCountSQLScript
SELECT * FROM query_cache WHERE query= ? LIMIT 1 1SELECT `value`, `last_checked` FROM query_cache WHERE query= ? LIMIT 1

/opt/clerks-staging/docroot/libraries/adodb5/adodb.inc.php 1899 CacheExecute() queryCache()

SELECT * FROM members WHERE show_freelancer = 1 AND status = 1 AND total_recommendations > 0 AND (skills LIKE '%Technicalseo%') ORDER BY total_recommendations desc LIMIT 0,401SELECT * FROM members WHERE show_freelancer = 1 AND status = 1 AND total_recommendations > 0 AND (skills LIKE '%Technicalseo%') ORDER BY total_recommendations desc LIMIT 0,40

/opt/clerks-staging/docroot/libraries/adodb5/adodb.inc.php 1899 CacheExecute() ()

SELECT * FROM posts WHERE USERID=9389301SELECT sum(positive_ratings) as thumbup, sum(negative_ratings) as thumbdown FROM posts WHERE USERID=938930

/opt/clerks-staging/docroot/libraries/adodb5/adodb.inc.php 1899 CacheExecute() GetBuyerRatingsTotal()

SELECT * FROM posts WHERE USERID=10223521SELECT sum(positive_ratings) as thumbup, sum(negative_ratings) as thumbdown FROM posts WHERE USERID=1022352

/opt/clerks-staging/docroot/libraries/adodb5/adodb.inc.php 1899 CacheExecute() GetBuyerRatingsTotal()

SELECT * FROM posts WHERE USERID=9829731SELECT sum(positive_ratings) as thumbup, sum(negative_ratings) as thumbdown FROM posts WHERE USERID=982973

/opt/clerks-staging/docroot/libraries/adodb5/adodb.inc.php 1899 CacheExecute() GetBuyerRatingsTotal()

SELECT * FROM posts WHERE USERID=9415351SELECT sum(positive_ratings) as thumbup, sum(negative_ratings) as thumbdown FROM posts WHERE USERID=941535

/opt/clerks-staging/docroot/libraries/adodb5/adodb.inc.php 1899 CacheExecute() GetBuyerRatingsTotal()

SELECT * FROM categories1SELECT * FROM categories

/opt/clerks-staging/docroot/libraries/adodb5/adodb.inc.php 1899 CacheExecute() parseRedundantQueriesCache()

select * from categories_software order by name asc1select * from categories_software order by name asc

/opt/clerks-staging/docroot/libraries/adodb5/adodb.inc.php 1899 CacheExecute() insert_GetSoftwareCategories()

select * from categories_wanttobuy order by name asc1select * from categories_wanttobuy order by name asc

/opt/clerks-staging/docroot/libraries/adodb5/adodb.inc.php 1899 CacheExecute() insert_get_wantcategories()

select * from categories_wanttotrade order by name asc1select * from categories_wanttotrade order by name asc

/opt/clerks-staging/docroot/libraries/adodb5/adodb.inc.php 1899 CacheExecute() insert_get_tradecategories()

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Tuning the following SQL could reduce the server load substantially
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Suspicious SQL

The following SQL have high average execution times
Avg TimeCountSQLMaxMin
0.5324431SELECT A.*, C.username, C.profilepicture, C.userlevel, C.ratingcount, C.rating, C.lastlogin, C.ip, C.lip, C.profile_data from posts A, seoclerks.members C WHERE A.active=1 AND A.USERID=C.USERID AND A.sold_out=0 AND category IN (37) AND gtags like'%BLOG%' AND type !=99 AND A.feat=0 AND A.catfeatured_upgrade=0 order by A.lastgigedit desc limit 0, 400.5324430.532443
0.4324141SELECT A.*, C.username, C.profilepicture, C.userlevel, C.ratingcount, C.rating, C.lastlogin, C.ip, C.lip, C.profile_data from posts A, seoclerks.members C WHERE A.active=1 AND A.USERID=C.USERID AND A.sold_out=0 AND category IN (62) AND gtags like'%website%' AND type !=99 AND A.feat=0 AND A.catfeatured_upgrade=0 order by A.lastgigedit desc limit 0, 400.4324140.432414
0.0961711SELECT * FROM members WHERE show_freelancer = 1 AND status = 1 AND total_recommendations > 0 AND (skills LIKE '%Technicalseo%') ORDER BY total_recommendations desc LIMIT 0,400.0961710.096171