SQL: SELECT city,country,sum(events) ev FROM `joe` where country like 'torokbalint' 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 'torokbalint' and action like 'hairdresser%' group by 1,2 order by ev desc limit 1 ROWS: 0
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 action like '%_20' then 10 when action like '%_15' then 5 when action like '%_13' then 2 when action like '%_12' then 1 else 0 end as action,sum(events) events FROM joe where lower(city) like 'torokbalint' and country like '%' and action like 'hairdresser2_%' group by 1 order by action desc ROWS: 0
SQL: SELECT case when action like '%_20' then 10 when action like '%_15' then 5 when action like '%_13' then 2 when action like '%_12' then 1 else 0 end as action,sum(events) events FROM joe where country like '%' and action like 'hairdresser2_%' group by 1 order by action desc ROWS: 0
SQL: SELECT region, sum(action*events) action, sum(events) events from (SELECT case when action like '%_20' then 10 when action like '%_15' then 5 when action like '%_13' then 2 when action like '%_12' then 1 else 0 end as action, region,sum(events) events FROM joe where country like '%' and action like 'hairdresser2%' group by 1,2) g group by 1 ROWS: 0
SQL: SELECT country, sum(action*events) action, sum(events) events from (SELECT case when action like '%_20' then 10 when action like '%_15' then 5 when action like '%_13' then 2 when action like '%_12' then 1 else 0 end as action, country,sum(events) events FROM joe where country not like '(not set)' and action like 'hairdresser2%' group by 1,2) g group by 1 having sum(events)>4 ROWS: 0
SQL: SELECT lat, lon,t.city city, sum(action*events) action, sum(events) events from (SELECT case when action like '%_20' then 10 when action like '%_15' then 5 when action like '%_13' then 2 when action like '%_12' then 1 else 0 end as action, city,sum(events) events FROM joe where country like '%' and action like 'hairdresser2%' 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: 0
SQL: SELECT city,country,sum(events) ev FROM `joe` where country like 'torokbalint' and action like '{$action_string}_%' group by 1,2 order by ev desc limit 1 ROWS: 0
SQL: SELECT city,country,sum(events) ev FROM `joe` where city like 'torokbalint' and action like '{$action_string}_%' group by 1,2 order by ev desc limit 1 ROWS: 0SQL: SELECT * FROM joe where lower(city) like 'torokbalint' and country like '%' 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 'hairdresser2_%') then events else 0 end) as love, sum(events) users from joe where action like 'hairdresser2_%' ; ROWS: 1 ROW 0: {"countries":"0","cities":"0","love":null,"users":null}
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 'torokbalint' order by events desc limit 1 ) b on a.country = b.country_2 where country_2 is not null and city not like 'torokbalint' and city not like '(not set)' group by 1 order by 2 desc ) yo limit 25 ROWS: 25 ROW 0: {"city":"Budapest"} ROW 1: {"city":"Godollo"} ROW 2: {"city":"Szeged"} ROW 3: {"city":"Balatonfured"} ROW 4: {"city":"Pecs"} ROW 5: {"city":"Debrecen"} ROW 6: {"city":"Dunakeszi"} ROW 7: {"city":"Veresegyhaz"} ROW 8: {"city":"Vac"} ROW 9: {"city":"Szekesfehervar"}Budapest - Godollo - Szeged - Balatonfured - Pecs - Debrecen - Dunakeszi - Veresegyhaz - Vac - Szekesfehervar - Gyor - Szentendre - Miskolc - Siofok - Many - Nyiregyhaza - Szombathely - Badacsonytomaj - Gyorujbarat - Veszprem - Torokszentmiklos - Aszod - Biatorbagy - Nagykovacsi - Paty -
SQL: SELECT * FROM joe_serp WHERE city like 'torokbalint' ROWS: 0
SQL: SELECT city from ( SELECT city,sum(events) FROM joe WHERE city not like '(not set)' and city not like 'torokbalint' group by 1 order by 2 desc limit 100) c ORDER BY RAND() limit 20 ROWS: 20 ROW 0: {"city":"Newcastle upon Tyne"} ROW 1: {"city":"Lisbon"} ROW 2: {"city":"Washington"} ROW 3: {"city":"Copenhagen"} ROW 4: {"city":"Miami"} ROW 5: {"city":"Oslo Municipality"} ROW 6: {"city":"Paris"} ROW 7: {"city":"Wellington"} ROW 8: {"city":"Sacramento"} ROW 9: {"city":"Brussels"}Tipping in Glasgow , Tipping in Irvine , Tipping in Cape Town , Tipping in Sydney , Tipping in Amsterdam , Tipping in Munich , Tipping in Liverpool , Tipping in Winnipeg , Tipping in Paris , Tipping in San Diego , Tipping in Washington , Tipping in Burnaby , Tipping in Leeds , Tipping in Honolulu , Tipping in Phoenix , Tipping in Jakarta , Tipping in Montreal , Tipping in Seattle , Tipping in Philadelphia , Tipping in Dallas ,