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342 lines
8.4 KiB
Markdown
342 lines
8.4 KiB
Markdown
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# OnTime
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This dataset can be obtained in two ways:
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- import from raw data
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- download of prepared partitions
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## Import From Raw Data
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Downloading data:
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```bash
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for s in `seq 1987 2018`
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do
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for m in `seq 1 12`
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do
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wget https://transtats.bts.gov/PREZIP/On_Time_Reporting_Carrier_On_Time_Performance_1987_present_${s}_${m}.zip
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done
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done
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```
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(from <https://github.com/Percona-Lab/ontime-airline-performance/blob/master/download.sh> )
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Creating a table:
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``` sql
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CREATE TABLE `ontime` (
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`Year` UInt16,
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`Quarter` UInt8,
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`Month` UInt8,
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`DayofMonth` UInt8,
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`DayOfWeek` UInt8,
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`FlightDate` Date,
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`UniqueCarrier` FixedString(7),
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`AirlineID` Int32,
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`Carrier` FixedString(2),
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`TailNum` String,
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`FlightNum` String,
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`OriginAirportID` Int32,
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`OriginAirportSeqID` Int32,
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`OriginCityMarketID` Int32,
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`Origin` FixedString(5),
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`OriginCityName` String,
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`OriginState` FixedString(2),
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`OriginStateFips` String,
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`OriginStateName` String,
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`OriginWac` Int32,
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`DestAirportID` Int32,
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`DestAirportSeqID` Int32,
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`DestCityMarketID` Int32,
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`Dest` FixedString(5),
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`DestCityName` String,
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`DestState` FixedString(2),
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`DestStateFips` String,
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`DestStateName` String,
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`DestWac` Int32,
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`CRSDepTime` Int32,
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`DepTime` Int32,
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`DepDelay` Int32,
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`DepDelayMinutes` Int32,
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`DepDel15` Int32,
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`DepartureDelayGroups` String,
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`DepTimeBlk` String,
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`TaxiOut` Int32,
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`WheelsOff` Int32,
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`WheelsOn` Int32,
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`TaxiIn` Int32,
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`CRSArrTime` Int32,
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`ArrTime` Int32,
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`ArrDelay` Int32,
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`ArrDelayMinutes` Int32,
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`ArrDel15` Int32,
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`ArrivalDelayGroups` Int32,
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`ArrTimeBlk` String,
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`Cancelled` UInt8,
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`CancellationCode` FixedString(1),
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`Diverted` UInt8,
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`CRSElapsedTime` Int32,
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`ActualElapsedTime` Int32,
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`AirTime` Int32,
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`Flights` Int32,
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`Distance` Int32,
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`DistanceGroup` UInt8,
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`CarrierDelay` Int32,
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`WeatherDelay` Int32,
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`NASDelay` Int32,
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`SecurityDelay` Int32,
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`LateAircraftDelay` Int32,
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`FirstDepTime` String,
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`TotalAddGTime` String,
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`LongestAddGTime` String,
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`DivAirportLandings` String,
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`DivReachedDest` String,
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`DivActualElapsedTime` String,
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`DivArrDelay` String,
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`DivDistance` String,
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`Div1Airport` String,
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`Div1AirportID` Int32,
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`Div1AirportSeqID` Int32,
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`Div1WheelsOn` String,
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`Div1TotalGTime` String,
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`Div1LongestGTime` String,
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`Div1WheelsOff` String,
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`Div1TailNum` String,
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`Div2Airport` String,
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`Div2AirportID` Int32,
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`Div2AirportSeqID` Int32,
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`Div2WheelsOn` String,
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`Div2TotalGTime` String,
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`Div2LongestGTime` String,
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`Div2WheelsOff` String,
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`Div2TailNum` String,
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`Div3Airport` String,
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`Div3AirportID` Int32,
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`Div3AirportSeqID` Int32,
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`Div3WheelsOn` String,
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`Div3TotalGTime` String,
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`Div3LongestGTime` String,
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`Div3WheelsOff` String,
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`Div3TailNum` String,
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`Div4Airport` String,
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`Div4AirportID` Int32,
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`Div4AirportSeqID` Int32,
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`Div4WheelsOn` String,
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`Div4TotalGTime` String,
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`Div4LongestGTime` String,
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`Div4WheelsOff` String,
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`Div4TailNum` String,
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`Div5Airport` String,
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`Div5AirportID` Int32,
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`Div5AirportSeqID` Int32,
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`Div5WheelsOn` String,
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`Div5TotalGTime` String,
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`Div5LongestGTime` String,
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`Div5WheelsOff` String,
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`Div5TailNum` String
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) ENGINE = MergeTree(FlightDate, (Year, FlightDate), 8192)
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```
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Loading data:
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```bash
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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
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```
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## Dowload of Prepared Partitions
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```bash
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curl -O https://clickhouse-datasets.s3.yandex.net/ontime/partitions/ontime.tar
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tar xvf ontime.tar -C /var/lib/clickhouse # path to ClickHouse data directory
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# check permissions of unpacked data, fix if required
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sudo service clickhouse-server restart
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clickhouse-client --query "select count(*) from datasets.ontime"
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```
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!!!info
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If you will run queries described below, you have to use full table name,
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`datasets.ontime`.
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## Queries
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Q0.
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``` sql
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select avg(c1) from (select Year, Month, count(*) as c1 from ontime group by Year, Month);
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```
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Q1. The number of flights per day from the year 2000 to 2008
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``` sql
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SELECT DayOfWeek, count(*) AS c FROM ontime WHERE Year >= 2000 AND Year <= 2008 GROUP BY DayOfWeek ORDER BY c DESC;
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```
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Q2. The number of flights delayed by more than 10 minutes, grouped by the day of the week, for 2000-2008
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``` sql
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SELECT DayOfWeek, count(*) AS c FROM ontime WHERE DepDelay>10 AND Year >= 2000 AND Year <= 2008 GROUP BY DayOfWeek ORDER BY c DESC
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```
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Q3. The number of delays by airport for 2000-2008
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``` sql
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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
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```
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Q4. The number of delays by carrier for 2007
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``` sql
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SELECT Carrier, count(*) FROM ontime WHERE DepDelay>10 AND Year = 2007 GROUP BY Carrier ORDER BY count(*) DESC
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```
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Q5. The percentage of delays by carrier for 2007
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``` sql
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SELECT Carrier, c, c2, c*1000/c2 as c3
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FROM
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(
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SELECT
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Carrier,
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count(*) AS c
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FROM ontime
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WHERE DepDelay>10
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AND Year=2007
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GROUP BY Carrier
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)
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ANY INNER JOIN
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(
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SELECT
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Carrier,
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count(*) AS c2
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FROM ontime
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WHERE Year=2007
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GROUP BY Carrier
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) USING Carrier
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ORDER BY c3 DESC;
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```
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Better version of the same query:
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``` sql
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SELECT Carrier, avg(DepDelay > 10) * 1000 AS c3 FROM ontime WHERE Year = 2007 GROUP BY Carrier ORDER BY Carrier
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```
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Q6. The previous request for a broader range of years, 2000-2008
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``` sql
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SELECT Carrier, c, c2, c*1000/c2 as c3
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FROM
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(
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SELECT
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Carrier,
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count(*) AS c
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FROM ontime
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WHERE DepDelay>10
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AND Year >= 2000 AND Year <= 2008
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GROUP BY Carrier
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)
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ANY INNER JOIN
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(
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SELECT
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Carrier,
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count(*) AS c2
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FROM ontime
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WHERE Year >= 2000 AND Year <= 2008
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GROUP BY Carrier
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) USING Carrier
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ORDER BY c3 DESC;
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```
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Better version of the same query:
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``` sql
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SELECT Carrier, avg(DepDelay > 10) * 1000 AS c3 FROM ontime WHERE Year >= 2000 AND Year <= 2008 GROUP BY Carrier ORDER BY Carrier
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```
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Q7. Percentage of flights delayed for more than 10 minutes, by year
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``` sql
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SELECT Year, c1/c2
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FROM
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(
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select
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Year,
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count(*)*1000 as c1
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from ontime
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WHERE DepDelay>10
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GROUP BY Year
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)
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ANY INNER JOIN
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(
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select
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Year,
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count(*) as c2
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from ontime
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GROUP BY Year
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) USING (Year)
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ORDER BY Year
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```
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Better version of the same query:
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``` sql
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SELECT Year, avg(DepDelay > 10) FROM ontime GROUP BY Year ORDER BY Year
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```
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Q8. The most popular destinations by the number of directly connected cities for various year ranges
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``` sql
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SELECT DestCityName, uniqExact(OriginCityName) AS u FROM ontime WHERE Year >= 2000 and Year <= 2010 GROUP BY DestCityName ORDER BY u DESC LIMIT 10;
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```
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Q9.
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``` sql
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select Year, count(*) as c1 from ontime group by Year;
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```
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Q10.
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``` sql
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select
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min(Year), max(Year), Carrier, count(*) as cnt,
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sum(ArrDelayMinutes>30) as flights_delayed,
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round(sum(ArrDelayMinutes>30)/count(*),2) as rate
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FROM ontime
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WHERE
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DayOfWeek not in (6,7) and OriginState not in ('AK', 'HI', 'PR', 'VI')
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and DestState not in ('AK', 'HI', 'PR', 'VI')
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and FlightDate < '2010-01-01'
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GROUP by Carrier
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HAVING cnt > 100000 and max(Year) > 1990
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ORDER by rate DESC
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LIMIT 1000;
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```
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Bonus:
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``` sql
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SELECT avg(cnt) FROM (SELECT Year,Month,count(*) AS cnt FROM ontime WHERE DepDel15=1 GROUP BY Year,Month)
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select avg(c1) from (select Year,Month,count(*) as c1 from ontime group by Year,Month)
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SELECT DestCityName, uniqExact(OriginCityName) AS u FROM ontime GROUP BY DestCityName ORDER BY u DESC LIMIT 10;
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SELECT OriginCityName, DestCityName, count() AS c FROM ontime GROUP BY OriginCityName, DestCityName ORDER BY c DESC LIMIT 10;
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SELECT OriginCityName, count() AS c FROM ontime GROUP BY OriginCityName ORDER BY c DESC LIMIT 10;
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```
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This performance test was created by Vadim Tkachenko. See:
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- <https://www.percona.com/blog/2009/10/02/analyzing-air-traffic-performance-with-infobright-and-monetdb/>
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- <https://www.percona.com/blog/2009/10/26/air-traffic-queries-in-luciddb/>
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- <https://www.percona.com/blog/2009/11/02/air-traffic-queries-in-infinidb-early-alpha/>
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- <https://www.percona.com/blog/2014/04/21/using-apache-hadoop-and-impala-together-with-mysql-for-data-analysis/>
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- <https://www.percona.com/blog/2016/01/07/apache-spark-with-air-ontime-performance-data/>
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- <http://nickmakos.blogspot.ru/2012/08/analyzing-air-traffic-performance-with.html>
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[Original article](https://clickhouse.yandex/docs/en/getting_started/example_datasets/ontime/) <!--hide-->
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