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11 KiB
11 KiB
toc_priority | toc_title |
---|---|
21 | OnTime |
OnTime
航班飞行数据有以下两个方式获取:
- 从原始数据导入
- 下载预处理好的数据
从原始数据导入
下载数据:
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
(参考 https://github.com/Percona-Lab/ontime-airline-performance/blob/master/download.sh )
创建表结构:
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` Int32,
`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
) ENGINE = MergeTree
PARTITION BY Year
ORDER BY (IATA_CODE_Reporting_Airline, FlightDate)
SETTINGS index_granularity = 8192;
加载数据:
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'"
下载预处理好的分区数据
$ curl -O https://datasets.clickhouse.tech/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 "信息"
如果要运行下面的SQL查询,必须使用完整的表名,datasets.ontime
。
查询:
Q0.
SELECT avg(c1)
FROM
(
SELECT Year, Month, count(*) AS c1
FROM ontime
GROUP BY Year, Month
);
Q1. 查询从2000年到2008年每天的航班数
SELECT DayOfWeek, count(*) AS c
FROM ontime
WHERE Year>=2000 AND Year<=2008
GROUP BY DayOfWeek
ORDER BY c DESC;
Q2. 查询从2000年到2008年每周延误超过10分钟的航班数。
SELECT DayOfWeek, count(*) AS c
FROM ontime
WHERE DepDelay>10 AND Year>=2000 AND Year<=2008
GROUP BY DayOfWeek
ORDER BY c DESC;
Q3. 查询2000年到2008年每个机场延误超过10分钟以上的次数
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. 查询2007年各航空公司延误超过10分钟以上的次数
SELECT IATA_CODE_Reporting_Airline AS Carrier, count(*)
FROM ontime
WHERE DepDelay>10 AND Year=2007
GROUP BY Carrier
ORDER BY count(*) DESC;
Q5. 查询2007年各航空公司延误超过10分钟以上的百分比
SELECT Carrier, c, c2, c*100/c2 as c3
FROM
(
SELECT
IATA_CODE_Reporting_Airline AS Carrier,
count(*) AS c
FROM ontime
WHERE DepDelay>10
AND Year=2007
GROUP BY Carrier
) q
JOIN
(
SELECT
IATA_CODE_Reporting_Airline AS Carrier,
count(*) AS c2
FROM ontime
WHERE Year=2007
GROUP BY Carrier
) qq USING Carrier
ORDER BY c3 DESC;
更好的查询版本:
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. 同上一个查询一致,只是查询范围扩大到2000年到2008年
SELECT Carrier, c, c2, c*100/c2 as c3
FROM
(
SELECT
IATA_CODE_Reporting_Airline AS Carrier,
count(*) AS c
FROM ontime
WHERE DepDelay>10
AND Year>=2000 AND Year<=2008
GROUP BY Carrier
) q
JOIN
(
SELECT
IATA_CODE_Reporting_Airline AS Carrier,
count(*) AS c2
FROM ontime
WHERE Year>=2000 AND Year<=2008
GROUP BY Carrier
) qq USING Carrier
ORDER BY c3 DESC;
更好的查询版本:
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. 每年航班延误超过10分钟的百分比
SELECT Year, c1/c2
FROM
(
select
Year,
count(*)*100 as c1
from ontime
WHERE DepDelay>10
GROUP BY Year
) q
JOIN
(
select
Year,
count(*) as c2
from ontime
GROUP BY Year
) qq USING (Year)
ORDER BY Year;
更好的查询版本:
SELECT Year, avg(DepDelay>10)*100
FROM ontime
GROUP BY Year
ORDER BY Year;
Q8. 每年更受人们喜爱的目的地
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), 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:
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;
这个性能测试由Vadim Tkachenko提供。参考:
- 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