ClickHouse/docs/en/getting-started/example-datasets/ontime.md

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---
toc_priority: 21
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toc_title: OnTime
---
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# OnTime {#ontime}
This dataset can be obtained in two ways:
- import from raw data
- download of prepared partitions
## Import from Raw Data {#import-from-raw-data}
Downloading data:
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``` bash
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wget --no-check-certificate --continue https://transtats.bts.gov/PREZIP/On_Time_Reporting_Carrier_On_Time_Performance_1987_present_{1987..2021}_{1..12}.zip
```
Creating a table:
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``` sql
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CREATE TABLE `ontime`
(
`Year` UInt16,
`Quarter` UInt8,
`Month` UInt8,
`DayofMonth` UInt8,
`DayOfWeek` UInt8,
`FlightDate` Date,
`Reporting_Airline` String,
`DOT_ID_Reporting_Airline` Int32,
`IATA_CODE_Reporting_Airline` String,
`Tail_Number` String,
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`Flight_Number_Reporting_Airline` 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` Nullable(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
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) ENGINE = MergeTree
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PARTITION BY Year
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ORDER BY (IATA_CODE_Reporting_Airline, FlightDate)
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SETTINGS index_granularity = 8192;
```
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Loading data with multiple threads:
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``` bash
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ls -1 *.zip | xargs -I{} -P $(nproc) bash -c "echo {}; unzip -cq {} '*.csv' | sed 's/\.00//g' | clickhouse-client --input_format_with_names_use_header=0 --query='INSERT INTO ontime FORMAT CSVWithNames'"
```
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(if you will have memory shortage or other issues on your server, remove the `-P $(nproc)` part)
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## Download of Prepared Partitions {#download-of-prepared-partitions}
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``` bash
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$ curl -O https://datasets.clickhouse.com/ontime/partitions/ontime.tar
DOCAPI-8530: Code blocks markup fix (#7060) * Typo fix. * Links fix. * Fixed links in docs. * More fixes. * docs/en: cleaning some files * docs/en: cleaning data_types * docs/en: cleaning database_engines * docs/en: cleaning development * docs/en: cleaning getting_started * docs/en: cleaning interfaces * docs/en: cleaning operations * docs/en: cleaning query_lamguage * docs/en: cleaning en * docs/ru: cleaning data_types * docs/ru: cleaning index * docs/ru: cleaning database_engines * docs/ru: cleaning development * docs/ru: cleaning general * docs/ru: cleaning getting_started * docs/ru: cleaning interfaces * docs/ru: cleaning operations * docs/ru: cleaning query_language * docs: cleaning interfaces/http * Update docs/en/data_types/array.md decorated ``` Co-Authored-By: BayoNet <da-daos@yandex.ru> * Update docs/en/getting_started/example_datasets/nyc_taxi.md fixed typo Co-Authored-By: BayoNet <da-daos@yandex.ru> * Update docs/en/getting_started/example_datasets/ontime.md fixed typo Co-Authored-By: BayoNet <da-daos@yandex.ru> * Update docs/en/interfaces/formats.md fixed error Co-Authored-By: BayoNet <da-daos@yandex.ru> * Update docs/en/operations/table_engines/custom_partitioning_key.md Co-Authored-By: BayoNet <da-daos@yandex.ru> * Update docs/en/operations/utils/clickhouse-local.md Co-Authored-By: BayoNet <da-daos@yandex.ru> * Update docs/en/query_language/dicts/external_dicts_dict_sources.md Co-Authored-By: BayoNet <da-daos@yandex.ru> * Update docs/en/operations/utils/clickhouse-local.md Co-Authored-By: BayoNet <da-daos@yandex.ru> * Update docs/en/query_language/functions/json_functions.md Co-Authored-By: BayoNet <da-daos@yandex.ru> * Update docs/en/query_language/functions/json_functions.md Co-Authored-By: BayoNet <da-daos@yandex.ru> * Update docs/en/query_language/functions/other_functions.md Co-Authored-By: BayoNet <da-daos@yandex.ru> * Update docs/en/query_language/functions/other_functions.md Co-Authored-By: BayoNet <da-daos@yandex.ru> * Update docs/en/query_language/functions/date_time_functions.md Co-Authored-By: BayoNet <da-daos@yandex.ru> * Update docs/en/operations/table_engines/jdbc.md Co-Authored-By: BayoNet <da-daos@yandex.ru> * docs: fixed error * docs: fixed error
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$ 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"
```
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!!! info "Info"
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If you will run the queries described below, you have to use the full table name, `datasets.ontime`.
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## Queries {#queries}
Q0.
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``` 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
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``` 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
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``` sql
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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Q3. The number of delays by the airport for 2000-2008
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``` 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
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``` sql
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SELECT IATA_CODE_Reporting_Airline AS 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
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``` sql
SELECT Carrier, c, c2, c*100/c2 as c3
FROM
(
SELECT
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IATA_CODE_Reporting_Airline AS Carrier,
count(*) AS c
FROM ontime
WHERE DepDelay>10
AND Year=2007
GROUP BY Carrier
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) q
JOIN
(
SELECT
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IATA_CODE_Reporting_Airline AS Carrier,
count(*) AS c2
FROM ontime
WHERE Year=2007
GROUP BY Carrier
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) qq USING Carrier
ORDER BY c3 DESC;
```
Better version of the same query:
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``` sql
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SELECT IATA_CODE_Reporting_Airline AS Carrier, avg(DepDelay>10)*100 AS c3
FROM ontime
WHERE Year=2007
GROUP BY Carrier
ORDER BY c3 DESC
```
Q6. The previous request for a broader range of years, 2000-2008
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``` sql
SELECT Carrier, c, c2, c*100/c2 as c3
FROM
(
SELECT
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IATA_CODE_Reporting_Airline AS Carrier,
count(*) AS c
FROM ontime
WHERE DepDelay>10
AND Year>=2000 AND Year<=2008
GROUP BY Carrier
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) q
JOIN
(
SELECT
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IATA_CODE_Reporting_Airline AS Carrier,
count(*) AS c2
FROM ontime
WHERE Year>=2000 AND Year<=2008
GROUP BY Carrier
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) qq USING Carrier
ORDER BY c3 DESC;
```
Better version of the same query:
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``` sql
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SELECT IATA_CODE_Reporting_Airline AS Carrier, avg(DepDelay>10)*100 AS c3
FROM ontime
WHERE Year>=2000 AND Year<=2008
GROUP BY Carrier
ORDER BY c3 DESC;
```
Q7. Percentage of flights delayed for more than 10 minutes, by year
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``` sql
SELECT Year, c1/c2
FROM
(
select
Year,
count(*)*100 as c1
from ontime
WHERE DepDelay>10
GROUP BY Year
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) q
JOIN
(
select
Year,
count(*) as c2
from ontime
GROUP BY Year
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) qq USING (Year)
ORDER BY Year;
```
Better version of the same query:
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``` sql
SELECT Year, avg(DepDelay>10)*100
FROM ontime
GROUP BY Year
ORDER BY Year;
```
Q8. The most popular destinations by the number of directly connected cities for various year ranges
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``` 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.
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``` sql
SELECT Year, count(*) AS c1
FROM ontime
GROUP BY Year;
```
Q10.
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``` sql
SELECT
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min(Year), max(Year), IATA_CODE_Reporting_Airline AS 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:
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``` 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;
```
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You can also play with the data in Playground, [example](https://gh-api.clickhouse.com/play?user=play#U0VMRUNUIERheU9mV2VlaywgY291bnQoKikgQVMgYwpGUk9NIG9udGltZQpXSEVSRSBZZWFyPj0yMDAwIEFORCBZZWFyPD0yMDA4CkdST1VQIEJZIERheU9mV2VlawpPUkRFUiBCWSBjIERFU0M7Cg==).
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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.com/docs/en/getting_started/example_datasets/ontime/) <!--hide-->