SQL: SELECT city,country,sum(events) ev FROM `joe` where country like 'gora_kalwaria' and action like 'hairdresser_%' group by 1,2 order by ev desc limit 1 ROWS: 0
SQL: SELECT city,country,sum(events) ev FROM `joe` where city like 'gora_kalwaria' and action like 'hairdresser_%' group by 1,2 order by ev desc limit 1 ROWS: 1 ROW 0: {"city":"Gora Kalwaria","country":"Poland","ev":"1"}
SQL: SELECT sVal FROM `joe_settings` where sTopic like 'hairdresser' and sName like 'color' ROWS: 5 ROW 0: {"sVal":"'25' => '#f2b434'"} ROW 1: {"sVal":"'>25' => '#990099'"} ROW 2: {"sVal":"'20' => '#259c5d'"} ROW 3: {"sVal":"'10' => '#4882ef'"} ROW 4: {"sVal":"'0' => '#d7483f'"}
SQL: SELECT sVal FROM `joe_settings` where sTopic like 'hairdresser' and sName like 'nice' ROWS: 1 ROW 0: {"sVal":"a Hairdresser (or Barber, Hair stylist, etc.)"}
SQL: SELECT sVal FROM `joe_settings` where sTopic like 'hairdresser' and sName like 'niceTagline' ROWS: 0
SQL: SELECT CASE WHEN LOWER(action) LIKE 'hairdresser_>25' THEN 30 ELSE CAST(REPLACE(LOWER(action),'hairdresser_','') AS UNSIGNED) END AS action,sum(events) events FROM joe where lower(city) like 'Gora Kalwaria' and country like 'Poland' and action like 'hairdresser_%' group by 1 order by action desc ROWS: 1 ROW 0: {"action":"20","events":"1"}
SQL: SELECT CASE WHEN LOWER(action) LIKE 'hairdresser_>25' THEN 30 ELSE CAST(REPLACE(LOWER(action),'hairdresser_','') AS UNSIGNED) END AS action,sum(events) events FROM joe where country like 'Poland' and action like 'hairdresser_%' group by 1 order by action desc ROWS: 5 ROW 0: {"action":"30","events":"2"} ROW 1: {"action":"25","events":"1"} ROW 2: {"action":"20","events":"4"} ROW 3: {"action":"10","events":"609"} ROW 4: {"action":"0","events":"7583"}
SQL: SELECT region, sum(action*events) action, sum(events) events from (SELECT CASE WHEN LOWER(action) LIKE 'hairdresser_>25' THEN 30 ELSE CAST(REPLACE(LOWER(action),'hairdresser_','') AS UNSIGNED) END AS action, region,sum(events) events FROM joe where country like 'Poland' and action like 'hairdresser%' group by 1,2) g group by 1 ROWS: 12 ROW 0: {"region":"Greater Poland Voivodeship","action":"40","events":"609"} ROW 1: {"region":"Lesser Poland Voivodeship","action":"30","events":"702"} ROW 2: {"region":"Lodz Voivodeship","action":"20","events":"2"} ROW 3: {"region":"Lower Silesian Voivodeship","action":"0","events":"1215"} ROW 4: {"region":"Lublin Voivodeship","action":"0","events":"272"} ROW 5: {"region":"Masovian Voivodeship","action":"6135","events":"3481"} ROW 6: {"region":"Opole Voivodeship","action":"0","events":"1"} ROW 7: {"region":"Podkarpackie Voivodeship","action":"0","events":"1"} ROW 8: {"region":"Podlaskie Voivodeship","action":"0","events":"1"} ROW 9: {"region":"Pomeranian Voivodeship","action":"10","events":"1775"}
SQL: SELECT country, sum(action*events) action, sum(events) events from (SELECT CASE WHEN LOWER(action) LIKE 'hairdresser_>25' THEN 30 ELSE CAST(REPLACE(LOWER(action),'hairdresser_','') AS UNSIGNED) END AS action, country,sum(events) events FROM joe where country not like '(not set)' and action like 'hairdresser%' group by 1,2) g group by 1 having sum(events)>4 ROWS: 100 ROW 0: {"country":"Algeria","action":"10","events":"40"} ROW 1: {"country":"Argentina","action":"4210","events":"249"} ROW 2: {"country":"Armenia","action":"0","events":"321"} ROW 3: {"country":"Aruba","action":"20","events":"55"} ROW 4: {"country":"Australia","action":"95735","events":"68880"} ROW 5: {"country":"Austria","action":"8645","events":"1110"} ROW 6: {"country":"Bahrain","action":"2880","events":"290"} ROW 7: {"country":"Bangladesh","action":"55","events":"339"} ROW 8: {"country":"Belgium","action":"1135","events":"5256"} ROW 9: {"country":"Bermuda","action":"420","events":"21"}
SQL: SELECT lat, lon,t.city city, sum(action*events) action, sum(events) events from (SELECT CASE WHEN LOWER(action) LIKE 'hairdresser_>25' THEN 30 ELSE CAST(REPLACE(LOWER(action),'hairdresser_','') AS UNSIGNED) END AS action, city,sum(events) events FROM joe where country like 'Poland' and action like 'hairdresser%' group by 1,2) t left join citiesLatLon ltln on t.city = ltln.city where lat is not null and t.city not like '(not set)' group by 1,2,3 having sum(events)>2 ROWS: 6 ROW 0: {"lat":"50.0646501","lon":"19.9449799","city":"Krakow","action":"0","events":"699"} ROW 1: {"lat":"51.1078852","lon":"17.0385376","city":"Wroclaw","action":"0","events":"1215"} ROW 2: {"lat":"51.2464536","lon":"22.5684463","city":"Lublin","action":"0","events":"272"} ROW 3: {"lat":"52.2296756","lon":"21.0122287","city":"Warsaw","action":"6090","events":"2873"} ROW 4: {"lat":"52.406374","lon":"16.9251681","city":"Poznan","action":"10","events":"607"} ROW 5: {"lat":"54.3520252","lon":"18.6466384","city":"Gdansk","action":"0","events":"1774"}
SQL: SELECT city,country,sum(events) ev FROM `joe` where country like 'Gora Kalwaria' and action like '{$action_string}_%' group by 1,2 order by ev desc limit 1 ROWS: 0
SQL: SELECT city,country,sum(events) ev FROM `joe` where city like 'Gora Kalwaria' and action like '{$action_string}_%' group by 1,2 order by ev desc limit 1 ROWS: 0SQL: SELECT * FROM joe where lower(city) like 'Gora Kalwaria' and country like 'Poland' and action like '{$action_string}__%' order by events desc ROWS: 0
SQL: Select count(distinct country) countries,count(distinct city) cities,sum(case when action not in (select min(action) from joe where action like 'hairdresser_%') then events else 0 end) as love, sum(events) users from joe where action like 'hairdresser_%' ; ROWS: 1 ROW 0: {"countries":"145","cities":"4093","love":"304013","users":"699495"}
CITIES
Countries
USERS
Tip more than 0%
SQL: SELECT city from (SELECT city,sum(events) FROM ( SELECT * FROM joe) a left join ( select country country_2 FROM joe where lower(city) like 'Gora Kalwaria' order by events desc limit 1 ) b on a.country = b.country_2 where country_2 is not null and city not like 'Gora Kalwaria' and city not like '(not set)' group by 1 order by 2 desc ) yo limit 25 ROWS: 25 ROW 0: {"city":"Warsaw"} ROW 1: {"city":"Wroclaw"} ROW 2: {"city":"Krakow"} ROW 3: {"city":"Gdansk"} ROW 4: {"city":"Poznan"} ROW 5: {"city":"Katowice"} ROW 6: {"city":"Ozarow Mazowiecki"} ROW 7: {"city":"Lodz"} ROW 8: {"city":"Swiebodzin"} ROW 9: {"city":"Lublin"}Warsaw - Wroclaw - Krakow - Gdansk - Poznan - Katowice - Ozarow Mazowiecki - Lodz - Swiebodzin - Lublin - Ruda Slaska - Orzesze - Szczecin - Skoczow - Krasnik - Bielsk Podlaski - Bielsko-Biala - Tychy - Boleslawiec - Jastrzebie-Zdroj - Bialystok - Nowy Sacz - Gdynia - Czestochowa - Radom -
SQL: SELECT * FROM joe_serp WHERE city like 'Gora Kalwaria' ROWS: 0
SQL: SELECT city from ( SELECT city,sum(events) FROM joe WHERE city not like '(not set)' and city not like 'Gora Kalwaria' group by 1 order by 2 desc limit 100) c ORDER BY RAND() limit 20 ROWS: 20 ROW 0: {"city":"Budapest"} ROW 1: {"city":"Quezon City"} ROW 2: {"city":"Ottawa"} ROW 3: {"city":"Beirut"} ROW 4: {"city":"Seattle"} ROW 5: {"city":"Edmonton"} ROW 6: {"city":"Wroclaw"} ROW 7: {"city":"Helsinki"} ROW 8: {"city":"Cape Town"} ROW 9: {"city":"Lisbon"}Tipping in Montreal , Tipping in Munich , Tipping in San Jose , Tipping in Bristol , Tipping in Frankfurt , Tipping in Washington , Tipping in Nashville , Tipping in Ottawa , Tipping in Vilnius , Tipping in Glasgow , Tipping in Perth , Tipping in Helsinki , Tipping in Kuala Lumpur , Tipping in Liverpool , Tipping in Nottingham , Tipping in Prague , Tipping in Brighton , Tipping in Hamilton , Tipping in Victoria , Tipping in Brisbane ,