ClickHouse/docs/en/getting_started/example_datasets/ontime.md

407 lines
8.4 KiB
Markdown

# OnTime
This dataset can be obtained in two ways:
- import from raw data
- download of prepared partitions
## Import From Raw Data
Downloading data:
```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
```
(from <https://github.com/Percona-Lab/ontime-airline-performance/blob/master/download.sh> )
Creating a table:
``` 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(FlightDate, (Year, FlightDate), 8192)
```
Loading data:
```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
```
## Dowload 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
If you will run queries described below, you have to use full table name,
`datasets.ontime`.
## Queries
Q0.
``` sql
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
``` sql
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
``` 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. The number of delays by airport for 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;
```
Q4. The number of delays by carrier for 2007
``` sql
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
``` 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
)
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:
``` sql
SELECT Carrier, avg(DepDelay>10)*100 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
``` 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
)
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:
``` sql
SELECT Carrier, avg(DepDelay>10)*100 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
``` sql
SELECT Year, c1/c2
FROM
(
select
Year,
count(*)*100 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:
``` sql
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
``` sql
SELECT DestCityName, uniqExact(OriginCityName) AS u F
ROM 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;
```
Bonus:
``` 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;
```
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>
[Original article](https://clickhouse.yandex/docs/en/getting_started/example_datasets/ontime/) <!--hide-->