1sf/bird-sql-train-with-schema huggingface dataset:
Database: mondial_geo
Tables: borders, city, continent, country, desert, economy, encompasses, ethnicGroup, geo_desert, geo_estuary, geo_island, geo_lake, geo_mountain, geo_river, geo_sea, geo_source, island, islandIn, isMember, lake, language, located, locatedOn, mergesWith, mountain, mountainOnIsland, organization, politics, population, province, religion, river, sea, target
Columns (table index, column name): -1, *, 0, Country1, 0, Country2, 0, Length, 1, Name, 1, Country, 1, Province, 1, Population, 1, Longitude, 1, Latitude, 2, Name, 2, Area, 3, Name, 3, Code, 3, Capital, 3, Province, 3, Area, 3, Population, 4, Name, 4, Area, 4, Longitude, 4, Latitude, 5, Country, 5, GDP, 5, Agriculture, 5, Service, 5, Industry, 5, Inflation, 6, Country, 6, Continent, 6, Percentage, 7, Country, 7, Name, 7, Percentage, 8, Desert, 8, Country, 8, Province, 9, River, 9, Country, 9, Province, 10, Island, 10, Country, 10, Province, 11, Lake, 11, Country, 11, Province, 12, Mountain, 12, Country, 12, Province, 13, River, 13, Country, 13, Province, 14, Sea, 14, Country, 14, Province, 15, River, 15, Country, 15, Province, 16, Name, 16, Islands, 16, Area, 16, Height, 16, Type, 16, Longitude, 16, Latitude, 17, Island, 17, Sea, 17, Lake, 17, River, 18, Country, 18, Organization, 18, Type, 19, Name, 19, Area, 19, Depth, 19, Altitude, 19, Type, 19, River, 19, Longitude, 19, Latitude, 20, Country, 20, Name, 20, Percentage, 21, City, 21, Province, 21, Country, 21, River, 21, Lake, 21, Sea, 22, City, 22, Province, 22, Country, 22, Island, 23, Sea1, 23, Sea2, 24, Name, 24, Mountains, 24, Height, 24, Type, 24, Longitude, 24, Latitude, 25, Mountain, 25, Island, 26, Abbreviation, 26, Name, 26, City, 26, Country, 26, Province, 26, Established, 27, Country, 27, Independence, 27, Dependent, 27, Government, 28, Country, 28, Population_Growth, 28, Infant_Mortality, 29, Name, 29, Country, 29, Population, 29, Area, 29, Capital, 29, CapProv, 30, Country, 30, Name, 30, Percentage, 31, Name, 31, River, 31, Lake, 31, Sea, 31, Length, 31, SourceLongitude, 31, SourceLatitude, 31, Mountains, 31, SourceAltitude, 31, EstuaryLongitude, 31, EstuaryLatitude, 32, Name, 32, Depth, 33, Country, 33, Target
Question: What is the population density of Hanoi's home country?
Evidence: population density = Population / Area
SQL: SELECT T1.Population / T1.Area FROM country AS T1 INNER JOIN province AS T2 ON T1.Code = T2.Country INNER JOIN city AS T3 ON T3.Province = T2.Name WHERE T3.Name = 'Hanoi'
Database: mondial_geo
Tables: borders, city, continent, country, desert, economy, encompasses, ethnicGroup, geo_desert, geo_estuary, geo_island, geo_lake, geo_mountain, geo_river, geo_sea, geo_source, island, islandIn, isMember, lake, language, located, locatedOn, mergesWith, mountain, mountainOnIsland, organization, politics, population, province, religion, river, sea, target
Columns (table index, column name): -1, *, 0, Country1, 0, Country2, 0, Length, 1, Name, 1, Country, 1, Province, 1, Population, 1, Longitude, 1, Latitude, 2, Name, 2, Area, 3, Name, 3, Code, 3, Capital, 3, Province, 3, Area, 3, Population, 4, Name, 4, Area, 4, Longitude, 4, Latitude, 5, Country, 5, GDP, 5, Agriculture, 5, Service, 5, Industry, 5, Inflation, 6, Country, 6, Continent, 6, Percentage, 7, Country, 7, Name, 7, Percentage, 8, Desert, 8, Country, 8, Province, 9, River, 9, Country, 9, Province, 10, Island, 10, Country, 10, Province, 11, Lake, 11, Country, 11, Province, 12, Mountain, 12, Country, 12, Province, 13, River, 13, Country, 13, Province, 14, Sea, 14, Country, 14, Province, 15, River, 15, Country, 15, Province, 16, Name, 16, Islands, 16, Area, 16, Height, 16, Type, 16, Longitude, 16, Latitude, 17, Island, 17, Sea, 17, Lake, 17, River, 18, Country, 18, Organization, 18, Type, 19, Name, 19, Area, 19, Depth, 19, Altitude, 19, Type, 19, River, 19, Longitude, 19, Latitude, 20, Country, 20, Name, 20, Percentage, 21, City, 21, Province, 21, Country, 21, River, 21, Lake, 21, Sea, 22, City, 22, Province, 22, Country, 22, Island, 23, Sea1, 23, Sea2, 24, Name, 24, Mountains, 24, Height, 24, Type, 24, Longitude, 24, Latitude, 25, Mountain, 25, Island, 26, Abbreviation, 26, Name, 26, City, 26, Country, 26, Province, 26, Established, 27, Country, 27, Independence, 27, Dependent, 27, Government, 28, Country, 28, Population_Growth, 28, Infant_Mortality, 29, Name, 29, Country, 29, Population, 29, Area, 29, Capital, 29, CapProv, 30, Country, 30, Name, 30, Percentage, 31, Name, 31, River, 31, Lake, 31, Sea, 31, Length, 31, SourceLongitude, 31, SourceLatitude, 31, Mountains, 31, SourceAltitude, 31, EstuaryLongitude, 31, EstuaryLatitude, 32, Name, 32, Depth, 33, Country, 33, Target
Question: In countries where there is more than one ethnic group, name the ethnic group with the greatest presence in each country and the country to which it corresponds.
Evidence: greatest presence can be represented by largest percentage.
SQL: SELECT Country, Name FROM ethnicGroup AS T1 WHERE Percentage < 100 AND Percentage = ( SELECT MAX(Percentage) FROM ethnicGroup AS T2 WHERE T1.Country = T2.Country )
Database: mondial_geo
Tables: borders, city, continent, country, desert, economy, encompasses, ethnicGroup, geo_desert, geo_estuary, geo_island, geo_lake, geo_mountain, geo_river, geo_sea, geo_source, island, islandIn, isMember, lake, language, located, locatedOn, mergesWith, mountain, mountainOnIsland, organization, politics, population, province, religion, river, sea, target
Columns (table index, column name): -1, *, 0, Country1, 0, Country2, 0, Length, 1, Name, 1, Country, 1, Province, 1, Population, 1, Longitude, 1, Latitude, 2, Name, 2, Area, 3, Name, 3, Code, 3, Capital, 3, Province, 3, Area, 3, Population, 4, Name, 4, Area, 4, Longitude, 4, Latitude, 5, Country, 5, GDP, 5, Agriculture, 5, Service, 5, Industry, 5, Inflation, 6, Country, 6, Continent, 6, Percentage, 7, Country, 7, Name, 7, Percentage, 8, Desert, 8, Country, 8, Province, 9, River, 9, Country, 9, Province, 10, Island, 10, Country, 10, Province, 11, Lake, 11, Country, 11, Province, 12, Mountain, 12, Country, 12, Province, 13, River, 13, Country, 13, Province, 14, Sea, 14, Country, 14, Province, 15, River, 15, Country, 15, Province, 16, Name, 16, Islands, 16, Area, 16, Height, 16, Type, 16, Longitude, 16, Latitude, 17, Island, 17, Sea, 17, Lake, 17, River, 18, Country, 18, Organization, 18, Type, 19, Name, 19, Area, 19, Depth, 19, Altitude, 19, Type, 19, River, 19, Longitude, 19, Latitude, 20, Country, 20, Name, 20, Percentage, 21, City, 21, Province, 21, Country, 21, River, 21, Lake, 21, Sea, 22, City, 22, Province, 22, Country, 22, Island, 23, Sea1, 23, Sea2, 24, Name, 24, Mountains, 24, Height, 24, Type, 24, Longitude, 24, Latitude, 25, Mountain, 25, Island, 26, Abbreviation, 26, Name, 26, City, 26, Country, 26, Province, 26, Established, 27, Country, 27, Independence, 27, Dependent, 27, Government, 28, Country, 28, Population_Growth, 28, Infant_Mortality, 29, Name, 29, Country, 29, Population, 29, Area, 29, Capital, 29, CapProv, 30, Country, 30, Name, 30, Percentage, 31, Name, 31, River, 31, Lake, 31, Sea, 31, Length, 31, SourceLongitude, 31, SourceLatitude, 31, Mountains, 31, SourceAltitude, 31, EstuaryLongitude, 31, EstuaryLatitude, 32, Name, 32, Depth, 33, Country, 33, Target
Question: How many deserts are not located in a single country? Name them.
SQL: SELECT Desert FROM geo_desert GROUP BY Desert HAVING COUNT(DISTINCT Country) > 1
Database: mondial_geo
Tables: borders, city, continent, country, desert, economy, encompasses, ethnicGroup, geo_desert, geo_estuary, geo_island, geo_lake, geo_mountain, geo_river, geo_sea, geo_source, island, islandIn, isMember, lake, language, located, locatedOn, mergesWith, mountain, mountainOnIsland, organization, politics, population, province, religion, river, sea, target
Columns (table index, column name): -1, *, 0, Country1, 0, Country2, 0, Length, 1, Name, 1, Country, 1, Province, 1, Population, 1, Longitude, 1, Latitude, 2, Name, 2, Area, 3, Name, 3, Code, 3, Capital, 3, Province, 3, Area, 3, Population, 4, Name, 4, Area, 4, Longitude, 4, Latitude, 5, Country, 5, GDP, 5, Agriculture, 5, Service, 5, Industry, 5, Inflation, 6, Country, 6, Continent, 6, Percentage, 7, Country, 7, Name, 7, Percentage, 8, Desert, 8, Country, 8, Province, 9, River, 9, Country, 9, Province, 10, Island, 10, Country, 10, Province, 11, Lake, 11, Country, 11, Province, 12, Mountain, 12, Country, 12, Province, 13, River, 13, Country, 13, Province, 14, Sea, 14, Country, 14, Province, 15, River, 15, Country, 15, Province, 16, Name, 16, Islands, 16, Area, 16, Height, 16, Type, 16, Longitude, 16, Latitude, 17, Island, 17, Sea, 17, Lake, 17, River, 18, Country, 18, Organization, 18, Type, 19, Name, 19, Area, 19, Depth, 19, Altitude, 19, Type, 19, River, 19, Longitude, 19, Latitude, 20, Country, 20, Name, 20, Percentage, 21, City, 21, Province, 21, Country, 21, River, 21, Lake, 21, Sea, 22, City, 22, Province, 22, Country, 22, Island, 23, Sea1, 23, Sea2, 24, Name, 24, Mountains, 24, Height, 24, Type, 24, Longitude, 24, Latitude, 25, Mountain, 25, Island, 26, Abbreviation, 26, Name, 26, City, 26, Country, 26, Province, 26, Established, 27, Country, 27, Independence, 27, Dependent, 27, Government, 28, Country, 28, Population_Growth, 28, Infant_Mortality, 29, Name, 29, Country, 29, Population, 29, Area, 29, Capital, 29, CapProv, 30, Country, 30, Name, 30, Percentage, 31, Name, 31, River, 31, Lake, 31, Sea, 31, Length, 31, SourceLongitude, 31, SourceLatitude, 31, Mountains, 31, SourceAltitude, 31, EstuaryLongitude, 31, EstuaryLatitude, 32, Name, 32, Depth, 33, Country, 33, Target
Question: How many rivers belong to more than one country? Name the provinces where we can find them.
SQL: SELECT River, GROUP_CONCAT(Province) FROM geo_river GROUP BY River HAVING COUNT(DISTINCT Country) > 1
Database: mondial_geo
Tables: borders, city, continent, country, desert, economy, encompasses, ethnicGroup, geo_desert, geo_estuary, geo_island, geo_lake, geo_mountain, geo_river, geo_sea, geo_source, island, islandIn, isMember, lake, language, located, locatedOn, mergesWith, mountain, mountainOnIsland, organization, politics, population, province, religion, river, sea, target
Columns (table index, column name): -1, *, 0, Country1, 0, Country2, 0, Length, 1, Name, 1, Country, 1, Province, 1, Population, 1, Longitude, 1, Latitude, 2, Name, 2, Area, 3, Name, 3, Code, 3, Capital, 3, Province, 3, Area, 3, Population, 4, Name, 4, Area, 4, Longitude, 4, Latitude, 5, Country, 5, GDP, 5, Agriculture, 5, Service, 5, Industry, 5, Inflation, 6, Country, 6, Continent, 6, Percentage, 7, Country, 7, Name, 7, Percentage, 8, Desert, 8, Country, 8, Province, 9, River, 9, Country, 9, Province, 10, Island, 10, Country, 10, Province, 11, Lake, 11, Country, 11, Province, 12, Mountain, 12, Country, 12, Province, 13, River, 13, Country, 13, Province, 14, Sea, 14, Country, 14, Province, 15, River, 15, Country, 15, Province, 16, Name, 16, Islands, 16, Area, 16, Height, 16, Type, 16, Longitude, 16, Latitude, 17, Island, 17, Sea, 17, Lake, 17, River, 18, Country, 18, Organization, 18, Type, 19, Name, 19, Area, 19, Depth, 19, Altitude, 19, Type, 19, River, 19, Longitude, 19, Latitude, 20, Country, 20, Name, 20, Percentage, 21, City, 21, Province, 21, Country, 21, River, 21, Lake, 21, Sea, 22, City, 22, Province, 22, Country, 22, Island, 23, Sea1, 23, Sea2, 24, Name, 24, Mountains, 24, Height, 24, Type, 24, Longitude, 24, Latitude, 25, Mountain, 25, Island, 26, Abbreviation, 26, Name, 26, City, 26, Country, 26, Province, 26, Established, 27, Country, 27, Independence, 27, Dependent, 27, Government, 28, Country, 28, Population_Growth, 28, Infant_Mortality, 29, Name, 29, Country, 29, Population, 29, Area, 29, Capital, 29, CapProv, 30, Country, 30, Name, 30, Percentage, 31, Name, 31, River, 31, Lake, 31, Sea, 31, Length, 31, SourceLongitude, 31, SourceLatitude, 31, Mountains, 31, SourceAltitude, 31, EstuaryLongitude, 31, EstuaryLatitude, 32, Name, 32, Depth, 33, Country, 33, Target
Question: What percentage of the border does Angola share with each of the countries with which it borders?
SQL: SELECT SUM(CASE WHEN T2.Name = 'Angola' THEN T1.Length ELSE 0 END) * 100 / SUM(T1.Length) FROM borders AS T1 LEFT JOIN country AS T2 ON T1.Country1 = T2.Code
Database: mondial_geo
Tables: borders, city, continent, country, desert, economy, encompasses, ethnicGroup, geo_desert, geo_estuary, geo_island, geo_lake, geo_mountain, geo_river, geo_sea, geo_source, island, islandIn, isMember, lake, language, located, locatedOn, mergesWith, mountain, mountainOnIsland, organization, politics, population, province, religion, river, sea, target
Columns (table index, column name): -1, *, 0, Country1, 0, Country2, 0, Length, 1, Name, 1, Country, 1, Province, 1, Population, 1, Longitude, 1, Latitude, 2, Name, 2, Area, 3, Name, 3, Code, 3, Capital, 3, Province, 3, Area, 3, Population, 4, Name, 4, Area, 4, Longitude, 4, Latitude, 5, Country, 5, GDP, 5, Agriculture, 5, Service, 5, Industry, 5, Inflation, 6, Country, 6, Continent, 6, Percentage, 7, Country, 7, Name, 7, Percentage, 8, Desert, 8, Country, 8, Province, 9, River, 9, Country, 9, Province, 10, Island, 10, Country, 10, Province, 11, Lake, 11, Country, 11, Province, 12, Mountain, 12, Country, 12, Province, 13, River, 13, Country, 13, Province, 14, Sea, 14, Country, 14, Province, 15, River, 15, Country, 15, Province, 16, Name, 16, Islands, 16, Area, 16, Height, 16, Type, 16, Longitude, 16, Latitude, 17, Island, 17, Sea, 17, Lake, 17, River, 18, Country, 18, Organization, 18, Type, 19, Name, 19, Area, 19, Depth, 19, Altitude, 19, Type, 19, River, 19, Longitude, 19, Latitude, 20, Country, 20, Name, 20, Percentage, 21, City, 21, Province, 21, Country, 21, River, 21, Lake, 21, Sea, 22, City, 22, Province, 22, Country, 22, Island, 23, Sea1, 23, Sea2, 24, Name, 24, Mountains, 24, Height, 24, Type, 24, Longitude, 24, Latitude, 25, Mountain, 25, Island, 26, Abbreviation, 26, Name, 26, City, 26, Country, 26, Province, 26, Established, 27, Country, 27, Independence, 27, Dependent, 27, Government, 28, Country, 28, Population_Growth, 28, Infant_Mortality, 29, Name, 29, Country, 29, Population, 29, Area, 29, Capital, 29, CapProv, 30, Country, 30, Name, 30, Percentage, 31, Name, 31, River, 31, Lake, 31, Sea, 31, Length, 31, SourceLongitude, 31, SourceLatitude, 31, Mountains, 31, SourceAltitude, 31, EstuaryLongitude, 31, EstuaryLatitude, 32, Name, 32, Depth, 33, Country, 33, Target
Question: What percent of the non volcanic islands in the Lesser Antilles group of islands have an area of no more than 300 square kilometers?
Evidence: Percent = [count(non volcanic islands Lesser Antilles area 300 or less) / count(non volcanic islands Lesser Antilles)] * 100%
SQL: SELECT SUM(CASE WHEN Area <= 300 THEN 1 ELSE 0 END) * 100 / COUNT(*) FROM island WHERE Islands = 'Lesser Antilles' AND (Type != 'volcanic' OR Type IS NULL)
Database: mondial_geo
Tables: borders, city, continent, country, desert, economy, encompasses, ethnicGroup, geo_desert, geo_estuary, geo_island, geo_lake, geo_mountain, geo_river, geo_sea, geo_source, island, islandIn, isMember, lake, language, located, locatedOn, mergesWith, mountain, mountainOnIsland, organization, politics, population, province, religion, river, sea, target
Columns (table index, column name): -1, *, 0, Country1, 0, Country2, 0, Length, 1, Name, 1, Country, 1, Province, 1, Population, 1, Longitude, 1, Latitude, 2, Name, 2, Area, 3, Name, 3, Code, 3, Capital, 3, Province, 3, Area, 3, Population, 4, Name, 4, Area, 4, Longitude, 4, Latitude, 5, Country, 5, GDP, 5, Agriculture, 5, Service, 5, Industry, 5, Inflation, 6, Country, 6, Continent, 6, Percentage, 7, Country, 7, Name, 7, Percentage, 8, Desert, 8, Country, 8, Province, 9, River, 9, Country, 9, Province, 10, Island, 10, Country, 10, Province, 11, Lake, 11, Country, 11, Province, 12, Mountain, 12, Country, 12, Province, 13, River, 13, Country, 13, Province, 14, Sea, 14, Country, 14, Province, 15, River, 15, Country, 15, Province, 16, Name, 16, Islands, 16, Area, 16, Height, 16, Type, 16, Longitude, 16, Latitude, 17, Island, 17, Sea, 17, Lake, 17, River, 18, Country, 18, Organization, 18, Type, 19, Name, 19, Area, 19, Depth, 19, Altitude, 19, Type, 19, River, 19, Longitude, 19, Latitude, 20, Country, 20, Name, 20, Percentage, 21, City, 21, Province, 21, Country, 21, River, 21, Lake, 21, Sea, 22, City, 22, Province, 22, Country, 22, Island, 23, Sea1, 23, Sea2, 24, Name, 24, Mountains, 24, Height, 24, Type, 24, Longitude, 24, Latitude, 25, Mountain, 25, Island, 26, Abbreviation, 26, Name, 26, City, 26, Country, 26, Province, 26, Established, 27, Country, 27, Independence, 27, Dependent, 27, Government, 28, Country, 28, Population_Growth, 28, Infant_Mortality, 29, Name, 29, Country, 29, Population, 29, Area, 29, Capital, 29, CapProv, 30, Country, 30, Name, 30, Percentage, 31, Name, 31, River, 31, Lake, 31, Sea, 31, Length, 31, SourceLongitude, 31, SourceLatitude, 31, Mountains, 31, SourceAltitude, 31, EstuaryLongitude, 31, EstuaryLatitude, 32, Name, 32, Depth, 33, Country, 33, Target
Question: Of all the countries in which English is spoken, what percentage has English as their only language?
Evidence: Percentage = [count(countries 100% English) / count(countries English)] * 100%
SQL: SELECT CAST(SUM(CASE WHEN T2.Percentage = 100 THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(T1.Name) FROM country AS T1 INNER JOIN language AS T2 ON T1.Code = T2.Country WHERE T2.Name = 'English'
Database: mondial_geo
Tables: borders, city, continent, country, desert, economy, encompasses, ethnicGroup, geo_desert, geo_estuary, geo_island, geo_lake, geo_mountain, geo_river, geo_sea, geo_source, island, islandIn, isMember, lake, language, located, locatedOn, mergesWith, mountain, mountainOnIsland, organization, politics, population, province, religion, river, sea, target
Columns (table index, column name): -1, *, 0, Country1, 0, Country2, 0, Length, 1, Name, 1, Country, 1, Province, 1, Population, 1, Longitude, 1, Latitude, 2, Name, 2, Area, 3, Name, 3, Code, 3, Capital, 3, Province, 3, Area, 3, Population, 4, Name, 4, Area, 4, Longitude, 4, Latitude, 5, Country, 5, GDP, 5, Agriculture, 5, Service, 5, Industry, 5, Inflation, 6, Country, 6, Continent, 6, Percentage, 7, Country, 7, Name, 7, Percentage, 8, Desert, 8, Country, 8, Province, 9, River, 9, Country, 9, Province, 10, Island, 10, Country, 10, Province, 11, Lake, 11, Country, 11, Province, 12, Mountain, 12, Country, 12, Province, 13, River, 13, Country, 13, Province, 14, Sea, 14, Country, 14, Province, 15, River, 15, Country, 15, Province, 16, Name, 16, Islands, 16, Area, 16, Height, 16, Type, 16, Longitude, 16, Latitude, 17, Island, 17, Sea, 17, Lake, 17, River, 18, Country, 18, Organization, 18, Type, 19, Name, 19, Area, 19, Depth, 19, Altitude, 19, Type, 19, River, 19, Longitude, 19, Latitude, 20, Country, 20, Name, 20, Percentage, 21, City, 21, Province, 21, Country, 21, River, 21, Lake, 21, Sea, 22, City, 22, Province, 22, Country, 22, Island, 23, Sea1, 23, Sea2, 24, Name, 24, Mountains, 24, Height, 24, Type, 24, Longitude, 24, Latitude, 25, Mountain, 25, Island, 26, Abbreviation, 26, Name, 26, City, 26, Country, 26, Province, 26, Established, 27, Country, 27, Independence, 27, Dependent, 27, Government, 28, Country, 28, Population_Growth, 28, Infant_Mortality, 29, Name, 29, Country, 29, Population, 29, Area, 29, Capital, 29, CapProv, 30, Country, 30, Name, 30, Percentage, 31, Name, 31, River, 31, Lake, 31, Sea, 31, Length, 31, SourceLongitude, 31, SourceLatitude, 31, Mountains, 31, SourceAltitude, 31, EstuaryLongitude, 31, EstuaryLatitude, 32, Name, 32, Depth, 33, Country, 33, Target
Question: Name of the capitals of the countries that have less than 99.95% less population than the country that has the most population.
SQL: SELECT Capital FROM country WHERE Population <= ( SELECT MAX(Population) - MAX(Population) * 0.9995 FROM country )
Database: mondial_geo
Tables: borders, city, continent, country, desert, economy, encompasses, ethnicGroup, geo_desert, geo_estuary, geo_island, geo_lake, geo_mountain, geo_river, geo_sea, geo_source, island, islandIn, isMember, lake, language, located, locatedOn, mergesWith, mountain, mountainOnIsland, organization, politics, population, province, religion, river, sea, target
Columns (table index, column name): -1, *, 0, Country1, 0, Country2, 0, Length, 1, Name, 1, Country, 1, Province, 1, Population, 1, Longitude, 1, Latitude, 2, Name, 2, Area, 3, Name, 3, Code, 3, Capital, 3, Province, 3, Area, 3, Population, 4, Name, 4, Area, 4, Longitude, 4, Latitude, 5, Country, 5, GDP, 5, Agriculture, 5, Service, 5, Industry, 5, Inflation, 6, Country, 6, Continent, 6, Percentage, 7, Country, 7, Name, 7, Percentage, 8, Desert, 8, Country, 8, Province, 9, River, 9, Country, 9, Province, 10, Island, 10, Country, 10, Province, 11, Lake, 11, Country, 11, Province, 12, Mountain, 12, Country, 12, Province, 13, River, 13, Country, 13, Province, 14, Sea, 14, Country, 14, Province, 15, River, 15, Country, 15, Province, 16, Name, 16, Islands, 16, Area, 16, Height, 16, Type, 16, Longitude, 16, Latitude, 17, Island, 17, Sea, 17, Lake, 17, River, 18, Country, 18, Organization, 18, Type, 19, Name, 19, Area, 19, Depth, 19, Altitude, 19, Type, 19, River, 19, Longitude, 19, Latitude, 20, Country, 20, Name, 20, Percentage, 21, City, 21, Province, 21, Country, 21, River, 21, Lake, 21, Sea, 22, City, 22, Province, 22, Country, 22, Island, 23, Sea1, 23, Sea2, 24, Name, 24, Mountains, 24, Height, 24, Type, 24, Longitude, 24, Latitude, 25, Mountain, 25, Island, 26, Abbreviation, 26, Name, 26, City, 26, Country, 26, Province, 26, Established, 27, Country, 27, Independence, 27, Dependent, 27, Government, 28, Country, 28, Population_Growth, 28, Infant_Mortality, 29, Name, 29, Country, 29, Population, 29, Area, 29, Capital, 29, CapProv, 30, Country, 30, Name, 30, Percentage, 31, Name, 31, River, 31, Lake, 31, Sea, 31, Length, 31, SourceLongitude, 31, SourceLatitude, 31, Mountains, 31, SourceAltitude, 31, EstuaryLongitude, 31, EstuaryLatitude, 32, Name, 32, Depth, 33, Country, 33, Target
Question: Average length of the rivers flowing into the Donau River.
SQL: SELECT * FROM river WHERE Name = 'Donau'