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

# 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*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:

``` sql
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

``` sql
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:

``` sql
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

``` sql
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:

``` 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 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;
```

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-->