--- machine_translated: true machine_translated_rev: 72537a2d527c63c07aa5d2361a8829f3895cf2bd toc_priority: 15 toc_title: A tiempo --- # A tiempo {#ontime} Este conjunto de datos se puede obtener de dos maneras: - importación de datos sin procesar - descarga de particiones preparadas ## Importar desde datos sin procesar {#import-from-raw-data} Descarga de datos: ``` bash for s in `seq 1987 2018` do for m in `seq 1 12` do wget https://transtats.bts.gov/PREZIP/On_Time_Reporting_Carrier_On_Time_Performance_1987_present_${s}_${m}.zip done done ``` (a partir de https://github.com/Percona-Lab/ontime-airline-performance/blob/master/download.sh ) Creación de una tabla: ``` sql CREATE TABLE `ontime` ( `Year` UInt16, `Quarter` UInt8, `Month` UInt8, `DayofMonth` UInt8, `DayOfWeek` UInt8, `FlightDate` Date, `UniqueCarrier` FixedString(7), `AirlineID` Int32, `Carrier` FixedString(2), `TailNum` String, `FlightNum` String, `OriginAirportID` Int32, `OriginAirportSeqID` Int32, `OriginCityMarketID` Int32, `Origin` FixedString(5), `OriginCityName` String, `OriginState` FixedString(2), `OriginStateFips` String, `OriginStateName` String, `OriginWac` Int32, `DestAirportID` Int32, `DestAirportSeqID` Int32, `DestCityMarketID` Int32, `Dest` FixedString(5), `DestCityName` String, `DestState` FixedString(2), `DestStateFips` String, `DestStateName` String, `DestWac` Int32, `CRSDepTime` Int32, `DepTime` Int32, `DepDelay` Int32, `DepDelayMinutes` Int32, `DepDel15` Int32, `DepartureDelayGroups` String, `DepTimeBlk` String, `TaxiOut` Int32, `WheelsOff` Int32, `WheelsOn` Int32, `TaxiIn` Int32, `CRSArrTime` Int32, `ArrTime` Int32, `ArrDelay` Int32, `ArrDelayMinutes` Int32, `ArrDel15` Int32, `ArrivalDelayGroups` Int32, `ArrTimeBlk` String, `Cancelled` UInt8, `CancellationCode` FixedString(1), `Diverted` UInt8, `CRSElapsedTime` Int32, `ActualElapsedTime` Int32, `AirTime` Int32, `Flights` Int32, `Distance` Int32, `DistanceGroup` UInt8, `CarrierDelay` Int32, `WeatherDelay` Int32, `NASDelay` Int32, `SecurityDelay` Int32, `LateAircraftDelay` Int32, `FirstDepTime` String, `TotalAddGTime` String, `LongestAddGTime` String, `DivAirportLandings` String, `DivReachedDest` String, `DivActualElapsedTime` String, `DivArrDelay` String, `DivDistance` String, `Div1Airport` String, `Div1AirportID` Int32, `Div1AirportSeqID` Int32, `Div1WheelsOn` String, `Div1TotalGTime` String, `Div1LongestGTime` String, `Div1WheelsOff` String, `Div1TailNum` String, `Div2Airport` String, `Div2AirportID` Int32, `Div2AirportSeqID` Int32, `Div2WheelsOn` String, `Div2TotalGTime` String, `Div2LongestGTime` String, `Div2WheelsOff` String, `Div2TailNum` String, `Div3Airport` String, `Div3AirportID` Int32, `Div3AirportSeqID` Int32, `Div3WheelsOn` String, `Div3TotalGTime` String, `Div3LongestGTime` String, `Div3WheelsOff` String, `Div3TailNum` String, `Div4Airport` String, `Div4AirportID` Int32, `Div4AirportSeqID` Int32, `Div4WheelsOn` String, `Div4TotalGTime` String, `Div4LongestGTime` String, `Div4WheelsOff` String, `Div4TailNum` String, `Div5Airport` String, `Div5AirportID` Int32, `Div5AirportSeqID` Int32, `Div5WheelsOn` String, `Div5TotalGTime` String, `Div5LongestGTime` String, `Div5WheelsOff` String, `Div5TailNum` String ) ENGINE = MergeTree PARTITION BY Year ORDER BY (Carrier, FlightDate) SETTINGS index_granularity = 8192; ``` Carga de datos: ``` bash $ for i in *.zip; do echo $i; unzip -cq $i '*.csv' | sed 's/\.00//g' | clickhouse-client --host=example-perftest01j --query="INSERT INTO ontime FORMAT CSVWithNames"; done ``` ## Descarga de Prepared Partitions {#download-of-prepared-partitions} ``` bash $ curl -O https://clickhouse-datasets.s3.yandex.net/ontime/partitions/ontime.tar $ tar xvf ontime.tar -C /var/lib/clickhouse # path to ClickHouse data directory $ # check permissions of unpacked data, fix if required $ sudo service clickhouse-server restart $ clickhouse-client --query "select count(*) from datasets.ontime" ``` !!! info "INFO" Si va a ejecutar las consultas que se describen a continuación, debe usar el nombre completo de la tabla, `datasets.ontime`. ## Consulta {#queries} Q0. ``` sql SELECT avg(c1) FROM ( SELECT Year, Month, count(*) AS c1 FROM ontime GROUP BY Year, Month ); ``` Q1. El número de vuelos por día desde el año 2000 hasta 2008 ``` sql SELECT DayOfWeek, count(*) AS c FROM ontime WHERE Year>=2000 AND Year<=2008 GROUP BY DayOfWeek ORDER BY c DESC; ``` Preguntas frecuentes El número de vuelos retrasados por más de 10 minutos, agrupados por el día de la semana, para 2000-2008 ``` sql SELECT DayOfWeek, count(*) AS c FROM ontime WHERE DepDelay>10 AND Year>=2000 AND Year<=2008 GROUP BY DayOfWeek ORDER BY c DESC; ``` Q3. El número de retrasos por parte del aeropuerto para 2000-2008 ``` sql SELECT Origin, count(*) AS c FROM ontime WHERE DepDelay>10 AND Year>=2000 AND Year<=2008 GROUP BY Origin ORDER BY c DESC LIMIT 10; ``` Preguntas más frecuentes Número de retrasos por transportista para 2007 ``` sql SELECT Carrier, count(*) FROM ontime WHERE DepDelay>10 AND Year=2007 GROUP BY Carrier ORDER BY count(*) DESC; ``` Q5. El porcentaje de retrasos por transportista para 2007 ``` sql SELECT Carrier, c, c2, c*100/c2 as c3 FROM ( SELECT Carrier, count(*) AS c FROM ontime WHERE DepDelay>10 AND Year=2007 GROUP BY Carrier ) JOIN ( SELECT Carrier, count(*) AS c2 FROM ontime WHERE Year=2007 GROUP BY Carrier ) USING Carrier ORDER BY c3 DESC; ``` Mejor versión de la misma consulta: ``` sql SELECT Carrier, avg(DepDelay>10)*100 AS c3 FROM ontime WHERE Year=2007 GROUP BY Carrier ORDER BY c3 DESC ``` ¿Por qué? La solicitud anterior de una gama más amplia de años, 2000-2008 ``` sql SELECT Carrier, c, c2, c*100/c2 as c3 FROM ( SELECT Carrier, count(*) AS c FROM ontime WHERE DepDelay>10 AND Year>=2000 AND Year<=2008 GROUP BY Carrier ) JOIN ( SELECT Carrier, count(*) AS c2 FROM ontime WHERE Year>=2000 AND Year<=2008 GROUP BY Carrier ) USING Carrier ORDER BY c3 DESC; ``` Mejor versión de la misma consulta: ``` sql SELECT Carrier, avg(DepDelay>10)*100 AS c3 FROM ontime WHERE Year>=2000 AND Year<=2008 GROUP BY Carrier ORDER BY c3 DESC; ``` Preguntas frecuentes Porcentaje de vuelos retrasados por más de 10 minutos, por año ``` sql SELECT Year, c1/c2 FROM ( select Year, count(*)*100 as c1 from ontime WHERE DepDelay>10 GROUP BY Year ) JOIN ( select Year, count(*) as c2 from ontime GROUP BY Year ) USING (Year) ORDER BY Year; ``` Mejor versión de la misma consulta: ``` sql SELECT Year, avg(DepDelay>10)*100 FROM ontime GROUP BY Year ORDER BY Year; ``` ¿Por qué? Los destinos más populares por el número de ciudades conectadas directamente para varios rangos de año ``` sql SELECT DestCityName, uniqExact(OriginCityName) AS u FROM ontime WHERE Year >= 2000 and Year <= 2010 GROUP BY DestCityName ORDER BY u DESC LIMIT 10; ``` Q9. ``` sql SELECT Year, count(*) AS c1 FROM ontime GROUP BY Year; ``` Q10. ``` sql SELECT min(Year), max(Year), Carrier, count(*) AS cnt, sum(ArrDelayMinutes>30) AS flights_delayed, round(sum(ArrDelayMinutes>30)/count(*),2) AS rate FROM ontime WHERE DayOfWeek NOT IN (6,7) AND OriginState NOT IN ('AK', 'HI', 'PR', 'VI') AND DestState NOT IN ('AK', 'HI', 'PR', 'VI') AND FlightDate < '2010-01-01' GROUP by Carrier HAVING cnt>100000 and max(Year)>1990 ORDER by rate DESC LIMIT 1000; ``` Bono: ``` sql SELECT avg(cnt) FROM ( SELECT Year,Month,count(*) AS cnt FROM ontime WHERE DepDel15=1 GROUP BY Year,Month ); SELECT avg(c1) FROM ( SELECT Year,Month,count(*) AS c1 FROM ontime GROUP BY Year,Month ); SELECT DestCityName, uniqExact(OriginCityName) AS u FROM ontime GROUP BY DestCityName ORDER BY u DESC LIMIT 10; SELECT OriginCityName, DestCityName, count() AS c FROM ontime GROUP BY OriginCityName, DestCityName ORDER BY c DESC LIMIT 10; SELECT OriginCityName, count() AS c FROM ontime GROUP BY OriginCityName ORDER BY c DESC LIMIT 10; ``` Esta prueba de rendimiento fue creada por Vadim Tkachenko. Ver: - https://www.percona.com/blog/2009/10/02/analyzing-air-traffic-performance-with-infobright-and-monetdb/ - https://www.percona.com/blog/2009/10/26/air-traffic-queries-in-luciddb/ - https://www.percona.com/blog/2009/11/02/air-traffic-queries-in-infinidb-early-alpha/ - https://www.percona.com/blog/2014/04/21/using-apache-hadoop-and-impala-together-with-mysql-for-data-analysis/ - https://www.percona.com/blog/2016/01/07/apache-spark-with-air-ontime-performance-data/ - http://nickmakos.blogspot.ru/2012/08/analyzing-air-traffic-performance-with.html [Artículo Original](https://clickhouse.tech/docs/en/getting_started/example_datasets/ontime/)