OnTime¶
This dataset can be obtained in two ways:
- import from raw data
- download of prepared partitions
Import From Raw Data¶
Downloading data:
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
(from https://github.com/Percona-Lab/ontime-airline-performance/blob/master/download.sh )
Creating a table:
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(FlightDate, (Year, FlightDate), 8192)
Loading data:
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
Dowload of Prepared Partitions¶
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
If you will run queries described below, you have to use full table name,
datasets.ontime
.
Queries¶
Q0.
select avg(c1) from (select Year, Month, count(*) as c1 from ontime group by Year, Month);
Q1. The number of flights per day from the year 2000 to 2008
SELECT DayOfWeek, count(*) AS c FROM ontime WHERE Year >= 2000 AND Year <= 2008 GROUP BY DayOfWeek ORDER BY c DESC;
Q2. The number of flights delayed by more than 10 minutes, grouped by the day of the week, for 2000-2008
SELECT DayOfWeek, count(*) AS c FROM ontime WHERE DepDelay>10 AND Year >= 2000 AND Year <= 2008 GROUP BY DayOfWeek ORDER BY c DESC
Q3. The number of delays by airport for 2000-2008
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
Q4. The number of delays by carrier for 2007
SELECT Carrier, count(*) FROM ontime WHERE DepDelay>10 AND Year = 2007 GROUP BY Carrier ORDER BY count(*) DESC
Q5. The percentage of delays by carrier for 2007
SELECT Carrier, c, c2, c*1000/c2 as c3 FROM ( SELECT Carrier, count(*) AS c FROM ontime WHERE DepDelay>10 AND Year=2007 GROUP BY Carrier ) ANY INNER JOIN ( SELECT Carrier, count(*) AS c2 FROM ontime WHERE Year=2007 GROUP BY Carrier ) USING Carrier ORDER BY c3 DESC;
Better version of the same query:
SELECT Carrier, avg(DepDelay > 10) * 1000 AS c3 FROM ontime WHERE Year = 2007 GROUP BY Carrier ORDER BY Carrier
Q6. The previous request for a broader range of years, 2000-2008
SELECT Carrier, c, c2, c*1000/c2 as c3 FROM ( SELECT Carrier, count(*) AS c FROM ontime WHERE DepDelay>10 AND Year >= 2000 AND Year <= 2008 GROUP BY Carrier ) ANY INNER JOIN ( SELECT Carrier, count(*) AS c2 FROM ontime WHERE Year >= 2000 AND Year <= 2008 GROUP BY Carrier ) USING Carrier ORDER BY c3 DESC;
Better version of the same query:
SELECT Carrier, avg(DepDelay > 10) * 1000 AS c3 FROM ontime WHERE Year >= 2000 AND Year <= 2008 GROUP BY Carrier ORDER BY Carrier
Q7. Percentage of flights delayed for more than 10 minutes, by year
SELECT Year, c1/c2 FROM ( select Year, count(*)*1000 as c1 from ontime WHERE DepDelay>10 GROUP BY Year ) ANY INNER JOIN ( select Year, count(*) as c2 from ontime GROUP BY Year ) USING (Year) ORDER BY Year
Better version of the same query:
SELECT Year, avg(DepDelay > 10) FROM ontime GROUP BY Year ORDER BY Year
Q8. The most popular destinations by the number of directly connected cities for various year ranges
SELECT DestCityName, uniqExact(OriginCityName) AS u FROM ontime WHERE Year >= 2000 and Year <= 2010 GROUP BY DestCityName ORDER BY u DESC LIMIT 10;
Q9.
select Year, count(*) as c1 from ontime group by Year;
Q10.
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;
Bonus:
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;
This performance test was created by Vadim Tkachenko. See:
- 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