-- DBMS: snowflake
create or replace TABLE COMPETITIONS (
	"ValidationSetValue" VARCHAR(16777216),
	"EnableSubmissionModelAttachments" BOOLEAN,
	"TotalCompetitors" NUMBER(38,0),
	"TotalTeams" NUMBER(38,0),
	"CanQualifyTiers" BOOLEAN,
	"EnableSubmissionModelHashes" BOOLEAN,
	"UserRankMultiplier" FLOAT,
	"RewardType" VARCHAR(16777216),
	"CompetitionTypeId" NUMBER(38,0),
	"NumPrizes" NUMBER(38,0),
	"MaxTeamSize" NUMBER(38,0),
	"NumScoredSubmissions" NUMBER(38,0),
	"ValidationSetName" VARCHAR(16777216),
	"EvaluationAlgorithmAbbreviation" VARCHAR(16777216),
	"Slug" VARCHAR(16777216),
	"HasLeaderboard" BOOLEAN,
	"HasKernels" BOOLEAN,
	"FinalLeaderboardHasBeenVerified" BOOLEAN,
	"ModelSubmissionDeadlineDate" NUMBER(38,0),
	"EvaluationAlgorithmIsMax" BOOLEAN,
	"DeadlineDate" NUMBER(38,0),
	"TotalSubmissions" NUMBER(38,0),
	"EnabledDate" NUMBER(38,0),
	"OnlyAllowKernelSubmissions" BOOLEAN,
	"EvaluationAlgorithmDescription" VARCHAR(16777216),
	"ProhibitNewEntrantsDeadlineDate" NUMBER(38,0),
	"HostName" VARCHAR(16777216),
	"MaxDailySubmissions" NUMBER(38,0),
	"OrganizationId" FLOAT,
	"Subtitle" VARCHAR(16777216),
	"TeamModelDeadlineDate" NUMBER(38,0),
	"EvaluationAlgorithmName" VARCHAR(16777216),
	"LeaderboardPercentage" NUMBER(38,0),
	"EnableTeamModels" BOOLEAN,
	"BanTeamMergers" BOOLEAN,
	"Id" NUMBER(38,0),
	"RewardQuantity" FLOAT,
	"HostSegmentTitle" VARCHAR(16777216),
	"TeamMergerDeadlineDate" NUMBER(38,0),
	"ForumId" NUMBER(38,0),
	"ScoreTruncationNumDecimals" NUMBER(38,0),
	"Title" VARCHAR(16777216)
);

INSERT INTO "META_KAGGLE"."META_KAGGLE"."COMPETITIONS" (Title, LeaderboardPercentage, TeamMergerDeadlineDate, NumScoredSubmissions, MaxTeamSize, Slug, HasLeaderboard, ScoreTruncationNumDecimals, EvaluationAlgorithmName, EnabledDate, MaxDailySubmissions, ModelSubmissionDeadlineDate, FinalLeaderboardHasBeenVerified, DeadlineDate, HasKernels, EvaluationAlgorithmDescription, HostName, RewardQuantity, Id, ValidationSetValue, EvaluationAlgorithmIsMax, CompetitionTypeId, ValidationSetName, UserRankMultiplier, ForumId, OnlyAllowKernelSubmissions, Subtitle, RewardType, BanTeamMergers, EnableTeamModels, EnableSubmissionModelAttachments, EnableSubmissionModelHashes, NumPrizes, OrganizationId, EvaluationAlgorithmAbbreviation, TeamModelDeadlineDate, ProhibitNewEntrantsDeadlineDate, HostSegmentTitle, TotalTeams, TotalSubmissions, CanQualifyTiers, TotalCompetitors) VALUES ('ITMO year2012 ML RecSys (track 1)', 30, NULL, 2, 1, 'itmo-year2012-ml-recsys-track-1', True, 5, 'Root Mean Squared Error', 1447716414000000, 1440, NULL, True, 1451606340000000, False, 'Square root of the average of the squared errors.', NULL, 0.0, 4758, NULL, False, 1, NULL, 0.0, 923, False, 'Задача для студентов 4-го курса КТ по рекомендательным системам в рамках курса по машинному обучению. Track 1', 'Knowledge', True, False, False, False, 1, NULL, 'RMSE', NULL, NULL, 'Community', 14, 117, False, 19), ('Swimming Pool Visitor Forecasting', 50, NULL, 3, 1, 'swimming-pool-visitor-forecasting', True, 5, 'Root Mean Squared Error', 1477586443000000, 250, NULL, True, 1499471940000000, False, 'Square root of the average of the squared errors.', NULL, 0.0, 5686, NULL, False, 1, NULL, 0.0, 1797, False, 'Predict the number of daily visitors of Nettebad Osnabrück', 'Knowledge', True, False, False, False, 1, NULL, 'RMSE', NULL, NULL, 'Community', 28, 2602, False, 43), ('SPRLNaiveBayesFAST', 50, NULL, 500, 1, 'sprlnaivebayesfast', True, 5, 'Area Under Receiver Operating Characteristic Curve', 1503957354000000, 500, NULL, True, 1513382340000000, False, 'Measures discrimination. Calculates how well an algorithm separates true positives from false positives. Overall good metric for classification problems. Has range [0.5, 1.0]', NULL, nan, 7100, NULL, True, 1, NULL, 0.0, 6106, False, 'Assignment 1.  Solve using naive Bayes''', 'Knowledge', True, False, False, False, 1, NULL, 'AUC', NULL, NULL, 'Community', 24, 693, False, 24), ('Late Arrival of Flights', 50, NULL, 2, 1, 'late-arrival-of-flights', True, 5, 'Area Under Receiver Operating Characteristic Curve', 1491572280000000, 30, NULL, True, 1492387140000000, False, 'Measures discrimination. Calculates how well an algorithm separates true positives from false positives. Overall good metric for classification problems. Has range [0.5, 1.0]', NULL, 0.0, 6443, NULL, True, 1, NULL, 0.0, 3080, False, 'Which flights will be late? Find this out!', 'Knowledge', True, False, False, False, 1, NULL, 'AUC', NULL, NULL, 'Community', 4, 42, False, 4), ('Random Forests Competition', 50, NULL, 40, 1, 'random-forests-competition', True, 5, 'Area Under Receiver Operating Characteristic Curve', 1506745154000000, 40, NULL, True, 1507089540000000, False, 'Measures discrimination. Calculates how well an algorithm separates true positives from false positives. Overall good metric for classification problems. Has range [0.5, 1.0]', NULL, 0.0, 7318, NULL, True, 1, NULL, 0.0, 7130, False, '.', NULL, True, False, False, False, 0, NULL, 'AUC', NULL, NULL, 'Community', 11, 251, False, 11);