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## Introduction
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For a start, we need a computer. For example, let's create virtual instance in Openstack with following characteristics:
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```
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RAM 61GB
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VCPUs 16 VCPU
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Disk 40GB
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Ephemeral Disk 100GB
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```
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OS:
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```
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$ lsb_release -a
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No LSB modules are available.
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Distributor ID: Ubuntu
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Description: Ubuntu 16.04 LTS
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Release: 16.04
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Codename: xenial
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```
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We gonna have a try with open data from On Time database, which is arranged by United States Department of
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Transportation). One can find information about it, structure of the table and examples of queries here:
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```
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https://github.com/yandex/ClickHouse/blob/master/doc/example_datasets/1_ontime.txt
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```
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## Building
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To build ClickHouse we will use a manual located here:
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```
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https://github.com/yandex/ClickHouse/blob/master/doc/build.md
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```
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Install required packages. After that let's run the following command from directory with source code of ClickHouse:
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```
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~/ClickHouse$ ./release
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```
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The build successfully completed:
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![](images/build_completed.png)
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Installing packages and running ClickHouse:
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```
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sudo apt-get install ../clickhouse-server-base_1.1.53960_amd64.deb ../clickhouse-server-common_1.1.53960_amd64.deb
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sudo apt-get install ../clickhouse-client_1.1.53960_amd64.deb
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sudo service clickhouse-server start
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```
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## Creation of table
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Before loading the date into ClickHouse, let's start console client of ClickHouse in order to create a table with necessary fields:
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```
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$ clickhouse-client
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```
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The table is being created with following query:
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```
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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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![](images/table_created.png)
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One can get information about table using following queries:
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```
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:) desc ontime
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```
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```
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:) show create ontime
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```
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## Filling in the data
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Let's download the data:
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```
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for s in `seq 1987 2015`; do
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for m in `seq 1 12`; do
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wget http://tsdata.bts.gov/PREZIP/On_Time_On_Time_Performance_${s}_${m}.zip
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done
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done
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```
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After that, add the data to ClickHouse:
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```
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for i in *.zip; do
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echo $i
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unzip -cq $i '*.csv' | sed 's/\.00//g' | clickhouse-client --query="insert into ontime format CSVWithNames"
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done
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```
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## Working with data
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Let's check if the table contains something:
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```
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:) select FlightDate, FlightNum, OriginCityName, DestCityName from ontime limit 10;
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```
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![](images/something.png)
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Now we'll craft more complicated query. E.g., output fraction of flights delayed for more than 10 minutes, for each year:
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```
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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(*)*100 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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![](images/complicated.png)
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## Additionally
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### Copying a table
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Suppose we need to copy 1% of records (luckiest ones) from ```ontime``` table to new table named ```ontime_ltd```.
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To achieve that make the queries:
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```
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:) create table ontime_ltd as ontime;
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:) insert into ontime_ltd select * from ontime where rand() % 100 = 42;
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```
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### Working with multiple tables
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If one need to collect data from multiple tables, use function ```merge(database, regexp)```:
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```
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:) select (select count(*) from merge(default, 'ontime.*'))/(select count() from ontime);
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```
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![](images/1_percent.png)
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### List of running queries
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For diagnostics one usually need to know what exactly ClickHouse is doing at the moment. Let's execute a query that gonna last long:
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```
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:) select sleep(1000);
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```
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If we run ```clickhouse-client``` after that in another terminal, one can output list of queries and some additional useful information about them:
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```
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:) show processlist;
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```
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![](images/long_query.png)
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@ -1,267 +0,0 @@
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## Введение
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Для начала, возьмём какую-нибудь машину, например, создадим виртуальный инстанс в Openstack со следующими характеристиками:
|
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```
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RAM 61GB
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VCPUs 16 VCPU
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Disk 40GB
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||||
Ephemeral Disk 100GB
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```
|
||||
|
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ОС:
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||||
```
|
||||
$ lsb_release -a
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No LSB modules are available.
|
||||
Distributor ID: Ubuntu
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||||
Description: Ubuntu 16.04 LTS
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||||
Release: 16.04
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Codename: xenial
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||||
```
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Будем работать с открытыми данными базы данных On Time, предоставленной Министерством транспорта США (United States Department of
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Transportation). Информация о ней, структура таблицы, а также примеры запросов приведены здесь:
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||||
```
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https://github.com/yandex/ClickHouse/blob/master/doc/example_datasets/1_ontime.txt
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```
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## Сборка
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||||
|
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При сборке ClickHouse будем использовать инструкцию, расположенную по адресу:
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||||
```
|
||||
https://github.com/yandex/ClickHouse/blob/master/doc/build.md
|
||||
```
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||||
|
||||
Установим необходимые пакеты. После этого выполним следующую команду из директории с исходными кодами ClickHouse:
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```
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~/ClickHouse$ ./release
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```
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|
||||
Сборка успешно завершена:
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||||
![](images/build_completed.png)
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||||
|
||||
Установим пакеты и запустим ClickHouse:
|
||||
```
|
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sudo apt-get install ../clickhouse-server-base_1.1.53960_amd64.deb ../clickhouse-server-common_1.1.53960_amd64.deb
|
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sudo apt-get install ../clickhouse-client_1.1.53960_amd64.deb
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sudo service clickhouse-server start
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```
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## Создание таблицы
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Перед тем, как загружать данные базы данных On Time в ClickHouse, запустим консольный клиент ClickHouse, для того, чтобы создать таблицу с
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необходимыми полями:
|
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```
|
||||
$ clickhouse-client
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```
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Таблица создаётся следующим запросом:
|
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```
|
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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,
|
||||
`DayOfWeek` UInt8,
|
||||
`FlightDate` Date,
|
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`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)
|
||||
```
|
||||
![](images/table_created.png)
|
||||
|
||||
Информацию о таблице можно посмотреть следующими запросами:
|
||||
```
|
||||
:) desc ontime
|
||||
```
|
||||
|
||||
```
|
||||
:) show create ontime
|
||||
```
|
||||
|
||||
## Наливка данных
|
||||
|
||||
Загрузим данные:
|
||||
```
|
||||
for s in `seq 1987 2015`; do
|
||||
for m in `seq 1 12`; do
|
||||
wget http://tsdata.bts.gov/PREZIP/On_Time_On_Time_Performance_${s}_${m}.zip
|
||||
done
|
||||
done
|
||||
```
|
||||
|
||||
Теперь необходимо загрузить данные в ClickHouse:
|
||||
```
|
||||
for i in *.zip; do
|
||||
echo $i
|
||||
unzip -cq $i '*.csv' | sed 's/\.00//g' | clickhouse-client --query="insert into ontime format CSVWithNames"
|
||||
done
|
||||
```
|
||||
|
||||
## Работа с данными
|
||||
|
||||
Проверим, что в таблице что-то есть:
|
||||
```
|
||||
:) select FlightDate, FlightNum, OriginCityName, DestCityName from ontime limit 10;
|
||||
```
|
||||
|
||||
![](images/something.png)
|
||||
|
||||
Теперь придумаем более сложный запрос. Например, выведем процент задержанных больше чем на 10 минут полётов за каждый год:
|
||||
```
|
||||
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;
|
||||
```
|
||||
|
||||
![](images/complicated.png)
|
||||
|
||||
## Дополнительно
|
||||
|
||||
### Копирование таблицы
|
||||
|
||||
Предположим, нам нужно скопировать 1% записей из таблицы (самых удачливых) ```ontime``` в новую таблицу ```ontime_ltd```. Для этого выполним запросы:
|
||||
```
|
||||
:) create table ontime_ltd as ontime;
|
||||
:) insert into ontime_ltd select * from ontime where rand() % 100 = 42;
|
||||
```
|
||||
|
||||
### Работа с несколькими таблицами
|
||||
|
||||
Если необходимо выполнять запросы над многими таблицами сразу, воспользуемся функцией ```merge(database, regexp)```:
|
||||
```
|
||||
:) select (select count(*) from merge(default, 'ontime.*'))/(select count() from ontime);
|
||||
```
|
||||
|
||||
![](images/1_percent.png)
|
||||
|
||||
### Список выполняющихся запросов
|
||||
|
||||
В целях диагностики часто бывает нужно узнать, что именно в данный момент делает ClickHouse. Запустим запрос, который выполняется очень долго:
|
||||
```
|
||||
:) select sleep(1000);
|
||||
```
|
||||
|
||||
Если теперь запустить ```clickhouse-client``` в другом терминале, можно будет вывести список запросов, а также некоторую
|
||||
полезную информацию о них:
|
||||
```
|
||||
:) show processlist;
|
||||
```
|
||||
|
||||
![](images/long_query.png)
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Loading…
Reference in New Issue
Block a user