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examples: add a solution to the "1 Billion Row Challenge" (#23458)
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@ -242,6 +242,7 @@ pub fn new_test_session(_vargs string, will_compile bool) TestSession {
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skip_files << 'examples/database/psql/customer.v'
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}
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$if windows {
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skip_files << 'examples/1brc/solution/main.v' // requires mmap
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skip_files << 'examples/database/mysql.v'
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skip_files << 'examples/database/orm.v'
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skip_files << 'examples/smtp/mail.v' // requires OpenSSL
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53
examples/1brc/README.md
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53
examples/1brc/README.md
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@ -0,0 +1,53 @@
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# 1 Billion Row Challenge (1BRC)
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A solution to the [1 Billion Row Challenge](https://www.morling.dev/blog/one-billion-row-challenge/),
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written in [the V programming language](https://vlang.io/).
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Read more about the challenge here: https://www.morling.dev/blog/one-billion-row-challenge/
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## Running instructions
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Suggested compiler options for performance:
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`v -cc gcc -prod -cflags "-std=c17 -march=native -mtune=native" .`
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### Step 1: Create a measurements file
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Compile and run `make-samples` to create the sample file.
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```
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cd make-samples
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v -cc gcc -prod -cflags "-std=c17 -march=native -mtune=native" .
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./make-samples 1000000000 > ~/measurements.txt
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```
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NOTE: If you create a billion rows, the file will be about 12GB!
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### Step 2: Run (and time) the solution
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```
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cd solution
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v -cc gcc -prod -cflags "-std=c17 -march=native -mtune=native" .
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./solution ~/measurements.txt
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```
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You can time the solution using `v time`:
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`v time ./solution ~/measurements.txt`
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By default, the solution runs in a single thread. If you want to run
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parallel processing, use the `-n` parameter, for example, to run with
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8 threads:
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`./solution -n 8 ~/measurements.txt`
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On Linux, to run one thread per core, use
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`./solution -n $(nproc) ~/measurements.txt`
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### Step 3: Improve upon the solution
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Make changes that improve the performance and submit them.
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Let's show off what is possible in V!
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413
examples/1brc/make-samples/cities.txt
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413
examples/1brc/make-samples/cities.txt
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@ -0,0 +1,413 @@
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Abha,18.0
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Abidjan,26.0
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Abéché,29.4
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Accra,26.4
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Addis Ababa,16.0
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Adelaide,17.3
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Aden,29.1
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Ahvaz,25.4
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Albuquerque,14.0
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Alexandra,11.0
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Alexandria,20.0
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Algiers,18.2
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Alice Springs,21.0
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Almaty,10.0
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Amsterdam,10.2
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Anadyr,-6.9
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Anchorage,2.8
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Andorra la Vella,9.8
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Ankara,12.0
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Antananarivo,17.9
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Antsiranana,25.2
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Arkhangelsk,1.3
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Ashgabat,17.1
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Asmara,15.6
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Assab,30.5
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Astana,3.5
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Athens,19.2
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Atlanta,17.0
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Auckland,15.2
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Austin,20.7
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Baghdad,22.77
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Baguio,19.5
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Baku,15.1
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Baltimore,13.1
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Bamako,27.8
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Bangkok,28.6
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Bangui,26.0
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Banjul,26.0
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Barcelona,18.2
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Bata,25.1
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Batumi,14.0
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Beijing,12.9
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Beirut,20.9
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Belgrade,12.5
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Belize City,26.7
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Benghazi,19.9
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Bergen,7.7
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Berlin,10.3
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Bilbao,14.7
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Birao,26.5
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Bishkek,11.3
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Bissau,27.0
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Blantyre,22.2
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Bloemfontein,15.6
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Boise,11.4
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Bordeaux,14.2
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Bosaso,30.0
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Boston,10.9
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Bouaké,26.0
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Bratislava,10.5
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Brazzaville,25.0
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Bridgetown,27.0
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Brisbane,21.4
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Brussels,10.5
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Bucharest,10.8
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Budapest,11.3
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Bujumbura,23.8
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Bulawayo,18.9
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Burnie,13.1
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Busan,15.0
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Cabo San Lucas,23.9
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Cairns,25.0
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Cairo,21.4
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Calgary,4.4
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Canberra,13.1
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Cape Town,16.2
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Changsha,17.4
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Charlotte,16.1
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Chiang Mai,25.8
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Chicago,9.8
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Chihuahua,18.6
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Chișinău,10.2
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Chittagong,25.9
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Chongqing,18.6
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Christchurch,12.2
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City of San Marino,11.8
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Colombo,27.4
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Columbus,11.7
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Conakry,26.4
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Copenhagen,9.1
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Cotonou,27.2
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Cracow,9.3
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Da Lat,17.9
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Da Nang,25.8
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Dakar,24.0
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Dallas,19.0
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Damascus,17.0
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Dampier,26.4
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Dar es Salaam,25.8
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Darwin,27.6
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Denpasar,23.7
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Denver,10.4
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Detroit,10.0
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Dhaka,25.9
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Dikson,-11.1
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Dili,26.6
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Djibouti,29.9
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Dodoma,22.7
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Dolisie,24.0
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Douala,26.7
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Dubai,26.9
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Dublin,9.8
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Dunedin,11.1
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Durban,20.6
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Dushanbe,14.7
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Edinburgh,9.3
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Edmonton,4.2
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El Paso,18.1
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Entebbe,21.0
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Erbil,19.5
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Erzurum,5.1
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Fairbanks,-2.3
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Fianarantsoa,17.9
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Flores, Petén,26.4
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Frankfurt,10.6
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Fresno,17.9
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Fukuoka,17.0
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Gabès,19.5
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Gaborone,21.0
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Gagnoa,26.0
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Gangtok,15.2
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Garissa,29.3
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Garoua,28.3
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George Town,27.9
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Ghanzi,21.4
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Gjoa Haven,-14.4
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Guadalajara,20.9
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Guangzhou,22.4
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Guatemala City,20.4
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Halifax,7.5
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Hamburg,9.7
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Hamilton,13.8
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Hanga Roa,20.5
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Hanoi,23.6
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Harare,18.4
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Harbin,5.0
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Hargeisa,21.7
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Hat Yai,27.0
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Havana,25.2
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Helsinki,5.9
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Heraklion,18.9
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Hiroshima,16.3
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Ho Chi Minh City,27.4
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Hobart,12.7
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Hong Kong,23.3
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Honiara,26.5
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Honolulu,25.4
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Houston,20.8
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Ifrane,11.4
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Indianapolis,11.8
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Iqaluit,-9.3
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Irkutsk,1.0
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Istanbul,13.9
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İzmir,17.9
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Jacksonville,20.3
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Jakarta,26.7
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Jayapura,27.0
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Jerusalem,18.3
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Johannesburg,15.5
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Jos,22.8
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Juba,27.8
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Kabul,12.1
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Kampala,20.0
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Kandi,27.7
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Kankan,26.5
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Kano,26.4
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Kansas City,12.5
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Karachi,26.0
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Karonga,24.4
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Kathmandu,18.3
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Khartoum,29.9
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Kingston,27.4
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Kinshasa,25.3
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Kolkata,26.7
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Kuala Lumpur,27.3
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Kumasi,26.0
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Kunming,15.7
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Kuopio,3.4
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Kuwait City,25.7
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Kyiv,8.4
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Kyoto,15.8
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La Ceiba,26.2
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La Paz,23.7
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Lagos,26.8
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Lahore,24.3
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Lake Havasu City,23.7
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Lake Tekapo,8.7
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Las Palmas de Gran Canaria,21.2
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Las Vegas,20.3
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Launceston,13.1
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Lhasa,7.6
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Libreville,25.9
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Lisbon,17.5
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Livingstone,21.8
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Ljubljana,10.9
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Lodwar,29.3
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Lomé,26.9
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London,11.3
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Los Angeles,18.6
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Louisville,13.9
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Luanda,25.8
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Lubumbashi,20.8
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Lusaka,19.9
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Luxembourg City,9.3
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Lviv,7.8
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Lyon,12.5
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Madrid,15.0
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Mahajanga,26.3
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Makassar,26.7
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Makurdi,26.0
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Malabo,26.3
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Malé,28.0
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Managua,27.3
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Manama,26.5
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Mandalay,28.0
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Mango,28.1
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Manila,28.4
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Maputo,22.8
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Marrakesh,19.6
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Marseille,15.8
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Maun,22.4
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Medan,26.5
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Mek'ele,22.7
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Melbourne,15.1
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Memphis,17.2
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Mexicali,23.1
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Mexico City,17.5
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Miami,24.9
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Milan,13.0
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Milwaukee,8.9
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Minneapolis,7.8
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Minsk,6.7
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Mogadishu,27.1
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Mombasa,26.3
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Monaco,16.4
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Moncton,6.1
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Monterrey,22.3
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Montreal,6.8
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Moscow,5.8
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Mumbai,27.1
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Murmansk,0.6
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Muscat,28.0
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Mzuzu,17.7
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N'Djamena,28.3
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Naha,23.1
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Nairobi,17.8
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Nakhon Ratchasima,27.3
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Napier,14.6
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Napoli,15.9
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Nashville,15.4
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Nassau,24.6
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Ndola,20.3
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New Delhi,25.0
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New Orleans,20.7
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New York City,12.9
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Ngaoundéré,22.0
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Niamey,29.3
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Nicosia,19.7
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Niigata,13.9
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Nouadhibou,21.3
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Nouakchott,25.7
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Novosibirsk,1.7
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Nuuk,-1.4
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Odesa,10.7
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Odienné,26.0
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Oklahoma City,15.9
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Omaha,10.6
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Oranjestad,28.1
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Oslo,5.7
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Ottawa,6.6
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Ouagadougou,28.3
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Ouahigouya,28.6
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Ouarzazate,18.9
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Oulu,2.7
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Palembang,27.3
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Palermo,18.5
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Palm Springs,24.5
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Palmerston North,13.2
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Panama City,28.0
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Parakou,26.8
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Paris,12.3
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Perth,18.7
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Petropavlovsk-Kamchatsky,1.9
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Philadelphia,13.2
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Phnom Penh,28.3
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Phoenix,23.9
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Pittsburgh,10.8
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Podgorica,15.3
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Pointe-Noire,26.1
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Pontianak,27.7
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Port Moresby,26.9
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Port Sudan,28.4
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Port Vila,24.3
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Port-Gentil,26.0
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Portland {OR},12.4
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Porto,15.7
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Prague,8.4
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Praia,24.4
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Pretoria,18.2
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Pyongyang,10.8
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Rabat,17.2
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Rangpur,24.4
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Reggane,28.3
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Reykjavík,4.3
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Riga,6.2
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Riyadh,26.0
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Rome,15.2
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Roseau,26.2
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Rostov-on-Don,9.9
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Sacramento,16.3
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Saint Petersburg,5.8
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Saint-Pierre,5.7
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Salt Lake City,11.6
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San Antonio,20.8
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San Diego,17.8
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San Francisco,14.6
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San Jose,16.4
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San José,22.6
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San Juan,27.2
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San Salvador,23.1
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Sana'a,20.0
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Santo Domingo,25.9
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Sapporo,8.9
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Sarajevo,10.1
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Saskatoon,3.3
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Seattle,11.3
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Ségou,28.0
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Seoul,12.5
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Seville,19.2
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Shanghai,16.7
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Singapore,27.0
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Skopje,12.4
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Sochi,14.2
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Sofia,10.6
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Sokoto,28.0
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Split,16.1
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St. John's,5.0
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St. Louis,13.9
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Stockholm,6.6
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Surabaya,27.1
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Suva,25.6
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Suwałki,7.2
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Sydney,17.7
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Tabora,23.0
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Tabriz,12.6
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Taipei,23.0
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Tallinn,6.4
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Tamale,27.9
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Tamanrasset,21.7
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Tampa,22.9
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Tashkent,14.8
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Tauranga,14.8
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Tbilisi,12.9
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Tegucigalpa,21.7
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Tehran,17.0
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Tel Aviv,20.0
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Thessaloniki,16.0
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Thiès,24.0
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Tijuana,17.8
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Timbuktu,28.0
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Tirana,15.2
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Toamasina,23.4
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Tokyo,15.4
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Toliara,24.1
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Toluca,12.4
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Toronto,9.4
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Tripoli,20.0
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Tromsø,2.9
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Tucson,20.9
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Tunis,18.4
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Ulaanbaatar,-0.4
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Upington,20.4
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Ürümqi,7.4
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Vaduz,10.1
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Valencia,18.3
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Valletta,18.8
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Vancouver,10.4
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Veracruz,25.4
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Vienna,10.4
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Vientiane,25.9
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Villahermosa,27.1
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Vilnius,6.0
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Virginia Beach,15.8
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Vladivostok,4.9
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Warsaw,8.5
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Washington, D.C.,14.6
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Wau,27.8
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Wellington,12.9
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Whitehorse,-0.1
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Wichita,13.9
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Willemstad,28.0
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Winnipeg,3.0
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Wrocław,9.6
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Xi'an,14.1
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Yakutsk,-8.8
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Yangon,27.5
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Yaoundé,23.8
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Yellowknife,-4.3
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Yerevan,12.4
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Yinchuan,9.0
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Zagreb,10.7
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Zanzibar City,26.0
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Zürich,9.3
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39
examples/1brc/make-samples/main.v
Normal file
39
examples/1brc/make-samples/main.v
Normal file
@ -0,0 +1,39 @@
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import encoding.csv
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import flag
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import os
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import rand
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struct CityMean {
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city string
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mean f64
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}
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fn main() {
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mut fp := flag.new_flag_parser(os.args)
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fp.version('1brc sample generator v1.0.0')
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fp.skip_executable()
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fp.application('Sample generator for 1 billion rows challenge')
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fp.description('The 1 billion rows challenge solved in V.\nFor details, see https://www.morling.dev/blog/one-billion-row-challenge/')
|
||||
input_file := fp.string('city-file', `i`, 'cities.txt', 'Path to input file with cities and means list')
|
||||
fp.limit_free_args_to_exactly(1)!
|
||||
sample_count := fp.remaining_parameters()[0].u64()
|
||||
|
||||
content := os.read_file(input_file) or { panic(err) }
|
||||
mut reader := csv.new_reader(content, csv.ReaderConfig{ delimiter: `,` })
|
||||
mut means := []CityMean{}
|
||||
for {
|
||||
rec := reader.read() or { break }
|
||||
means << CityMean{
|
||||
city: rec[0]
|
||||
mean: rec[1].f64()
|
||||
}
|
||||
}
|
||||
|
||||
for _ in 0 .. sample_count / 2 {
|
||||
mut city := rand.intn(means.len)!
|
||||
m1, m2 := rand.normal_pair(mu: means[city].mean, sigma: 10)!
|
||||
println('${means[city].city};${m1:.1f}')
|
||||
city = rand.intn(means.len)!
|
||||
println('${means[city].city};${m2:.1f}')
|
||||
}
|
||||
}
|
||||
199
examples/1brc/solution/main.v
Normal file
199
examples/1brc/solution/main.v
Normal file
@ -0,0 +1,199 @@
|
||||
import flag
|
||||
import math
|
||||
import os
|
||||
|
||||
#include <sys/mman.h>
|
||||
|
||||
fn C.mmap(addr voidptr, len u64, prot int, flags int, fd int, offset i64) voidptr
|
||||
fn C.munmap(addr voidptr, len u64) int
|
||||
|
||||
struct MemoryMappedFile {
|
||||
size u64
|
||||
mut:
|
||||
data &u8
|
||||
file os.File
|
||||
}
|
||||
|
||||
fn mmap_file(path string) MemoryMappedFile {
|
||||
mut mf := MemoryMappedFile{
|
||||
file: os.open_file(path, 'r', 0) or { panic('fail') }
|
||||
size: os.file_size(path)
|
||||
data: C.NULL
|
||||
}
|
||||
|
||||
mf.data = &u8(C.mmap(C.NULL, mf.size, C.PROT_READ, C.MAP_SHARED, mf.file.fd, 0))
|
||||
return mf
|
||||
}
|
||||
|
||||
fn (mut mf MemoryMappedFile) unmap() {
|
||||
if C.munmap(mf.data, mf.size) != 0 {
|
||||
panic('(${C.errno}) munmap() failed')
|
||||
}
|
||||
mf.file.close()
|
||||
}
|
||||
|
||||
enum ReadState {
|
||||
city
|
||||
temp
|
||||
}
|
||||
|
||||
struct Result {
|
||||
pub mut:
|
||||
min i32
|
||||
max i32
|
||||
sum i32
|
||||
count u32
|
||||
}
|
||||
|
||||
fn format_value(value i32) string {
|
||||
return '${value / 10}.${math.abs(value % 10)}'
|
||||
}
|
||||
|
||||
fn print_results(results map[string]Result, print_nicely bool) {
|
||||
mut output := []string{cap: results.len}
|
||||
mut cities := results.keys()
|
||||
cities.sort()
|
||||
for city in cities {
|
||||
v := results[city]
|
||||
mean := f64(v.sum) / v.count / 10
|
||||
output << '${city}=${format_value(v.min)}/${mean:.1f}/${format_value(v.max)}'
|
||||
}
|
||||
if print_nicely {
|
||||
println(output.join('\n'))
|
||||
} else {
|
||||
println('{' + output.join(', ') + '}')
|
||||
}
|
||||
}
|
||||
|
||||
fn combine_results(results []map[string]Result) map[string]Result {
|
||||
mut combined_result := map[string]Result{}
|
||||
for result in results {
|
||||
for city, r in result {
|
||||
if city !in combined_result {
|
||||
combined_result[city] = r
|
||||
} else {
|
||||
if r.max > combined_result[city].max {
|
||||
combined_result[city].max = r.max
|
||||
}
|
||||
if r.min < combined_result[city].min {
|
||||
combined_result[city].min = r.min
|
||||
}
|
||||
combined_result[city].sum += r.sum
|
||||
combined_result[city].count += r.count
|
||||
}
|
||||
}
|
||||
}
|
||||
return combined_result
|
||||
}
|
||||
|
||||
@[direct_array_access]
|
||||
fn process_chunk(addr &u8, from u64, to u64) map[string]Result {
|
||||
mut results := map[string]Result{}
|
||||
mut state := ReadState.city
|
||||
mut city := ''
|
||||
mut temp := i32(0)
|
||||
mut mod := i32(1)
|
||||
mut j := int(0)
|
||||
for i in from .. to {
|
||||
c := unsafe { u8(addr[i]) }
|
||||
match state {
|
||||
.city {
|
||||
match c {
|
||||
`;` {
|
||||
state = .temp
|
||||
city = unsafe { tos(addr[i - u64(j)], j) }
|
||||
}
|
||||
else {
|
||||
j += 1
|
||||
}
|
||||
}
|
||||
}
|
||||
.temp {
|
||||
match c {
|
||||
`\n` {
|
||||
temp *= mod
|
||||
if city !in results {
|
||||
results[city] = Result{
|
||||
min: temp
|
||||
max: temp
|
||||
sum: temp
|
||||
count: 1
|
||||
}
|
||||
} else {
|
||||
if temp > results[city].max {
|
||||
results[city].max = temp
|
||||
}
|
||||
if temp < results[city].min {
|
||||
results[city].min = temp
|
||||
}
|
||||
results[city].sum += temp
|
||||
results[city].count += 1
|
||||
}
|
||||
state = .city
|
||||
temp = 0
|
||||
mod = 1
|
||||
j = 0
|
||||
}
|
||||
`-` {
|
||||
mod = -1
|
||||
}
|
||||
`.` {}
|
||||
else {
|
||||
// ASCII 48 = '0' ... ASCII 57 = '9' => (ASCII value) - 48 = decimal value
|
||||
temp = temp * 10 + (c - 48)
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
return results
|
||||
}
|
||||
|
||||
fn process_in_parallel(mf MemoryMappedFile, thread_count u32) map[string]Result {
|
||||
mut threads := []thread map[string]Result{}
|
||||
approx_chunk_size := mf.size / thread_count
|
||||
mut from := u64(0)
|
||||
mut to := approx_chunk_size
|
||||
for _ in 0 .. thread_count - 1 {
|
||||
unsafe {
|
||||
for mf.data[to] != `\n` {
|
||||
to += 1
|
||||
}
|
||||
}
|
||||
threads << spawn process_chunk(mf.data, from, to)
|
||||
from = to + 1
|
||||
to = from + approx_chunk_size
|
||||
}
|
||||
to = mf.size
|
||||
threads << spawn process_chunk(mf.data, from, to)
|
||||
res := threads.wait()
|
||||
return combine_results(res)
|
||||
}
|
||||
|
||||
fn main() {
|
||||
mut fp := flag.new_flag_parser(os.args)
|
||||
fp.version('1brc v1.0.0')
|
||||
fp.skip_executable()
|
||||
fp.application('1 billion rows challenge')
|
||||
fp.description('The 1 billion rows challenge solved in V.\nFor details, see https://www.morling.dev/blog/one-billion-row-challenge/')
|
||||
thread_count := u32(fp.int('threads', `n`, 1, 'number of threads for parallel processing.'))
|
||||
print_nicely := fp.bool('human-readable', `h`, false, 'Print results with new lines rather than following challenge spec')
|
||||
quiet := fp.bool('quiet', `q`, false, 'Suppress the results output (e.g., if you only care about timing)')
|
||||
fp.limit_free_args_to_exactly(1)!
|
||||
path := fp.remaining_parameters()[0]
|
||||
|
||||
mut mf := mmap_file(path)
|
||||
defer {
|
||||
mf.unmap()
|
||||
}
|
||||
|
||||
results := if thread_count > 1 {
|
||||
process_in_parallel(mf, thread_count)
|
||||
} else {
|
||||
process_chunk(mf.data, 0, mf.size)
|
||||
}
|
||||
|
||||
if !quiet {
|
||||
print_results(results, print_nicely)
|
||||
}
|
||||
}
|
||||
Loading…
x
Reference in New Issue
Block a user