tl;博士
读取一个 20 MB 的 CSV 文件并每行实例化一个对象，总耗时不到 1 秒。
详情
您没有定义“慢”一词。所以我做了一个实验，一个随意的基准测试。
首先，我们创建一个包含 40,000 条 Person 记录的 20 MB 文件。每个Person 都包含一个法语名字和姓氏，一个UUID，以及一些任意文本作为描述。数据在UTF-8 的CSV 文件中作为四列写入。我使用Apache Commons CSV 库进行读写。
其次，读取这个写入的文件。将每一行数据读入内存，然后用于实例化并收集一个Person 对象。
读取此文件并为每一行实例化Person 对象总用时不到一秒。每行大约需要 20K nanoseconds。实际上，这包括读取文件两次，因为我们进行扫描以计算数据行数以设置收集实例的初始容量。此外，我们正在将十六进制字符串输入解析为 UUID 的 128 位值，因此我们有一些时间花在数据处理上（不仅仅是读取）。
这是Person 类。
package work.basil.example;
import java.util.UUID;
public class Person
{
// Static
static public String LOREM_IPSUM = "Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.";
// Member variables.
public String givenName, surname, description;
public UUID id;
public Person ( String givenName , String surname , UUID id , String description)
{
this.givenName = givenName;
this.surname = surname;
this.id = id;
this.description = description ;
}
@Override
public String toString ()
{
return "Person{ " +
"givenName='" + givenName + '\'' +
" | surname='" + surname + '\'' +
" | id='" + id + '\'' +
" }";
}
}
这是一个完整的应用程序，它写入然后读取 20 MB 文件。请学习和批评，因为我很快就完成了这个。我没有仔细检查我的工作。
您将找到一个write 方法和一个read 方法。 main 方法调用两者，并跟踪时间。
package work.basil.example;
import org.apache.commons.csv.CSVFormat;
import org.apache.commons.csv.CSVPrinter;
import org.apache.commons.csv.CSVRecord;
import java.io.BufferedReader;
import java.io.IOException;
import java.nio.charset.StandardCharsets;
import java.nio.file.Files;
import java.nio.file.Path;
import java.nio.file.Paths;
import java.time.Duration;
import java.time.Instant;
import java.time.temporal.ChronoUnit;
import java.util.ArrayList;
import java.util.List;
import java.util.UUID;
import java.util.concurrent.ThreadLocalRandom;
public class CsvSpeed
{
public List < Person > read ( Path path )
{
// TODO: Add a check for valid file existing.
List < Person > list = List.of(); // Default to empty list.
try
{
// Prepare list.
int initialCapacity = ( int ) Files.lines( path ).count();
list = new ArrayList <>( initialCapacity );
// Read CSV file. For each row, instantiate and collect `DailyProduct`.
BufferedReader reader = Files.newBufferedReader( path );
Iterable < CSVRecord > records = CSVFormat.RFC4180.withFirstRecordAsHeader().parse( reader );
for ( CSVRecord record : records )
{
String givenName = record.get( "givenName" );
String surname = record.get( "surname" );
UUID id = UUID.fromString( record.get( "id" ) );
String description = record.get( "description" );
// Instantiate `Person` object, and collect it.
Person person = new Person( givenName , surname , id , description );
list.add( person );
}
} catch ( IOException e )
{
e.printStackTrace();
}
return list;
}
public void write ( final Path path )
{
ThreadLocalRandom random = ThreadLocalRandom.current();
try ( final CSVPrinter printer = CSVFormat.RFC4180.withHeader( "givenName" , "surname" , "id" , "description" ).print( path , StandardCharsets.UTF_8 ) ; )
{
int limit = 40_000; // 40_000 yields about 20 MB of data.
List < String > givenNames = List.of( "Adrien" , "Aimon" , "Alerion" , "Alexis" , "Alezan" , "Ancil" , "Andre" , "Antoine" , "Archard" , "Aurélien" , "Averill" , "Baptiste" , "Barnard" , "Bartelemy" , "Bastien" , "Baylee" , "Beale" , "Beau" , "Beaumont" , "Beauregard" , "Bellamy" , "Berger" , "Blaize" , "Blondel" , "Boyce" , "Bruce" , "Brunelle" , "Brys" , "Burcet" , "Burnell" , "Burrell" , "Byron" , "Canaan" , "Carden" , "Carolas" , "Cavell" , "Chace" , "Chanler" , "Chante" , "Chappel" , "Charles" , "Chasen" , "Chason" , "Chemin" , "Chene" , "Cher" , "Chevalier" , "Cheyne" , "Clément" , "Clemence" , "Corbin" , "Coty" , "Cygne" , "Damien" , "Dandre" , "Dariel" , "Darl" , "Dauphine" , "Davet" , "Dax" , "Dean" , "Delice" , "Delmon" , "Destin" , "Dominique" , "Donatien" , "Duke" , "Eliott" , "Elroy" , "Enzo" , "Erwan" , "Etalon" , "Ethan" , "Fabron" , "Ferrand" , "Filberte" , "Florent" , "Florian" , "Fontaine" , "Forest" , "Fortune" , "Franchot" , "Francois" , "Fraser" , "Frayne" , "Gaëtan" , "Gabin" , "Gage" , "Gaige" , "Garland" , "Garner" , "Gaston" , "Gauge" , "Gaylord" , "Germain" , "Germaine" , "German" , "Gervaise" , "Giles" , "Gilles" , "Gitan" , "Grosvener" , "Guifford" , "Guion" , "Guy" , "Guzman" , "Henri" , "Holland" , "Hugo" , "Hugues" , "Hyacinthe" , "Jérémy" , "Jacquan" , "Jacques" , "Jacquez" , "Janvier" , "Jardan" , "Jay" , "Jaye" , "Jehan" , "Jemond" , "Jocquez" , "Jonathan" , "Jules" , "Julien" , "Justus" , "Karoly" , "Lado" , "Lafayette" , "Lamond" , "Lancelin" , "Landis" , "Landry" , "Laron" , "Larrimore" , "Laurent" , "LaValle" , "Leandre" , "Leggett" , "Leonce" , "Leron" , "Leverett" , "Lilian" , "Loïc" , "Lorenzo" , "Louis" , "Lowell" , "Luc" , "Lucien" , "Lukas" , "Macaire" , "Mace" , "Mahieu" , "Maison" , "Malleville" , "Manneville" , "Mantel" , "Marc" , "Marcel" , "Marion" , "Marius" , "Markez" , "Markis" , "Marmion" , "Marquis" , "Marquise" , "Marshall" , "Martial" , "Maslin" , "Mason" , "Matheo" , "Mathias" , "Mathys" , "Matthieu" , "Maxence" , "Mayson" , "Mehdi" , "Merle" , "Merville" , "Montague" , "Montaigu" , "Monte" , "Montgomery" , "Montreal" , "Montrel" , "Moore" , "Morel" , "Mortimer" , "Nerville" , "Neuveville" , "Nicolas" , "Noë" , "Noah" , "Noe" , "Norman" , "Norville" , "Nouel" , "Olivier" , "Onfroi" , "Paien" , "Parfait" , "Parnell" , "Pascal" , "Patrice" , "Paul" , "Peppin" , "Percival" , "Percy" , "Pernell" , "Peverell" , "Philipe" , "Pierpont" , "Pierre" , "Pomeroy" , "Prewitt" , "Purvis" , "Quennell" , "Quentin" , "Quincey" , "Quincy" , "Quintin" , "Rémi" , "Rafaelle" , "Ranger" , "Raoul" , "Raphaël" , "Rapier" , "Rawlins" , "Ray" , "Raynard" , "Remi" , "René" , "Renard" , "Rene" , "Reule" , "Reynard" , "Robin" , "Romain" , "Rondel" , "Roy" , "Royal" , "Ruff" , "Rush" , "Russel" , "Rustin" , "Sabastien" , "Sacha" , "Salomon" , "Samuel" , "Satordi" , "Saville" , "Scoville" , "Sebastien" , "Sennett" , "Severin" , "Shant" , "Shantae" , "Sidney" , "Siffre" , "Simeon" , "Simon" , "Sinclair" , "Sofiane" , "Somer" , "Stephane" , "Sully" , "Sydney" , "Sylvain" , "Talbot" , "Talon" , "Telford" , "Tempest" , "Teppo" , "Théo" , "Thayer" , "Thibault" , "Thibaut" , "Thiery" , "Tiennan" , "Tiennot" , "Titouan" , "Toussaint" , "Travaris" , "Tyson" , "Urson" , "Vachel" , "Valentin" , "Valere" , "Vallis" , "Verdun" , "Victoir" , "Victor" , "Waltier" , "William" , "Wyatt" , "Yanis" , "Yann" , "Yves" , "Yvon" , "Zosime" , "Abrial" , "Abrielle" , "Abril" , "Adele" , "Alair" , "Alerion" , "Amee" , "Angelique" , "Annette" , "Antonella" , "Arian" , "Ariane" , "Armandina" , "Aubree" , "Aubrielle" , "Audra" , "Avril" , "Bella" , "Berneta" , "Bette" , "Blaise" , "Blanche" , "Blasa" , "Bonte" , "Brie" , "Brienne" , "Brigit" , "Cachay" , "Calice" , "Camille" , "Camylle" , "Caprice" , "Caressa" , "Caroline" , "Catin" , "Celesta" , "Celeste" , "Cera" , "Cerise" , "Chablis" , "Chalice" , "Chambray" , "Champagne" , "Chandell" , "Chaney" , "Chantal" , "Chante" , "Chanterelle" , "Chantile" , "Chantilly" , "Chantrice" , "Charla" , "Charlotte" , "Charmane" , "Chaton" , "Chemin" , "Chenetta" , "Cher" , "Chere" , "Cheri" , "Cheryl" , "Christine" , "Cidney" , "Cinderella" , "Claire" , "Claudette" , "Colette" , "Cordelle" , "Cydnee" , "Daeja" , "Daija" , "Daja" , "Damzel" , "Darelle" , "Darlene" , "Darselle" , "Dejanelle" , "Deleena" , "Delice" , "Demeri" , "Deni" , "Denise" , "Desgracias" , "Desire" , "Desiree" , "Destanee" , "Destiny" , "Dior" , "Domanique" , "Dominique" , "Elaina" , "Elaine" , "Elayna" , "Elise" , "Eloisa" , "Elyse" , "Emeline" , "Emmaline" , "Emmeline" , "Estella" , "Estrella" , "Etiennette" , "Evette" , "Fabienne" , "Fabrienne" , "Fanchon" , "Fancy" , "Fawna" , "Fayana" , "Fayette" , "Fifi" , "Fleur" , "Fleurette" , "Fontanna" , "Fosette" , "Francine" , "Frederique" , "Gabriel" , "Gabriele" , "Gabrielle" , "Gaby" , "Garcelle" , "Gena" , "Genie" , "Georgette" , "Germaine" , "Gervaise" , "Gitana" , "Harriet" , "Heloisa" , "Holland" , "Honnetta" , "Isabelle" , "Ivette" , "Ivonne" , "Jacqueena" , "Jacquetta" , "Jacquiline" , "Jacyline" , "Jaime" , "Jakqueline" , "Janeen" , "Janelly" , "Janina" , "Janiqua" , "Janique" , "Jannnelle" , "Jaquita" , "Jardena" , "Jeanetta" , "Jermaine" , "Jessamine" , "Jewel" , "Jewell" , "Joli" , "Jolie" , "Josephine" , "Jozephine" , "Julieta" , "Karessa" , "Karmaine" , "Klara" , "Laine" , "Lanelle" , "Laramie" , "Layne" , "Layney" , "Leala" , "Leonette" , "Lissette" , "Lizette" , "Lourdes" , "Lucienne" , "Ly" , "Lyla" , "Lysette" , "Madelaine" , "Malerie" , "Manette" , "Marais" , "Marcelle" , "Marché" , "Mardi" , "Margo" , "Marguerite" , "Marie" , "Marie Claude" , "Marie Frances" , "Marie Joelle" , "Marie Pascale" , "Marie Sophie" , "Marjolaine" , "Marquise" , "Marvella" , "Mathieu" , "Matisse" , "Maurelle" , "Maurissa" , "Mavis" , "Melisande" , "Michelle" , "Miette" , "Mignon" , "Mimi" , "Mirya" , "Monet" , "Moniqua" , "Monteen" , "Musetta" , "Myrlie" , "Nadeen" , "Nadia" , "Nadiyah" , "Naeva" , "Nanon" , "Natalle" , "Naudia" , "Nettie" , "Nicholas" , "Nicki" , "Nicky" , "Nicole" , "Nicolette" , "Nicolina" , "Nicolle" , "Nikolette" , "Ninette" , "Ninon" , "Noelle" , "Nycole" , "Odelette" , "Opaline" , "Orane" , "Orva" , "Page" , "Parisa" , "Parnel" , "Parris" , "Patrice" , "Peridot" , "Pippi" , "Prairie" , "Rachele" , "Rachelle" , "Racquel" , "Raphaelle" , "Raquelle" , "Remi" , "Renée" , "Renea" , "Renelle" , "Renita" , "Risette" , "Rochelle" , "Romy" , "Rosabel" , "Rosiclara" , "Ruba" , "Russhell" , "Saleena" , "Salina" , "Satin" , "Sedona" , "Serene" , "Shandelle" , "Shanta" , "Shante" , "Shariah" , "Sharita" , "Sharleen" , "Sheree" , "Shereen" , "Sherell" , "Sherice" , "Sherry" , "Sidnee" , "Sidney" , "Sidnie" , "Sidonie" , "Sinclaire" , "Solange" , "Solen" , "Sorrel" , "Suzette" , "Sydnee" , "Sydney" , "Tallis" , "Tempest" , "Toinette" , "Turquoise" , "Veronique" , "Vignette" , "Villette" , "Violeta" , "Virginie" , "Voleta" , "Vonny" );
List < String > surnames = List.of( "Arceneau" , "Aucoin" , "Babin" , "Babineaux" , "Benoit" , "Bergeron" , "Bernard" , "Bertrand" , "Bessette" , "Blanc" , "Blanchard" , "Bonnet" , "Boucher" , "Bourg" , "Bourque" , "Boutin" , "Bouvier" , "Braud" , "Broussard" , "Brun" , "Chevalier" , "David" , "Depaul" , "Desmarais" , "Disney" , "Dubois" , "Dupont" , "Dupuis" , "Durand" , "Fortescue" , "Fournier" , "Garnier" , "Gaudet" , "Gillet" , "Gillette" , "Girard" , "Gravois" , "Grosvenor" , "Lambert" , "Landry" , "Laroche" , "Laurent" , "Lefevre" , "Leroy" , "Leveque" , "Lisle" , "Martin" , "Michel" , "Molyneux" , "Moreau" , "Morel" , "Neville" , "Pelletier" , "Petit" , "Prideux" , "Renard" , "Richard" , "Robert" , "Rousseau" , "Roux" , "Rufus" , "Simon" , "Thomas" );
for ( int i = 1 ; i <= limit ; i++ )
{
String givenName = givenNames.get( random.nextInt( 0 , givenNames.size() ) );
String surname = surnames.get( random.nextInt( 0 , surnames.size() ) );
UUID id = UUID.randomUUID();
String description = Person.LOREM_IPSUM;
printer.printRecord( givenName , surname , id , description );
}
} catch ( IOException e )
{
e.printStackTrace();
}
}
public static void main ( final String[] args )
{
// Launch the app.
CsvSpeed app = new CsvSpeed();
// Write.
String when = Instant.now().truncatedTo( ChronoUnit.SECONDS ).toString().replace( ":" , "•" );
Path pathOutput = Paths.get( "/Users/basilbourque/persons.csv" );
app.write( pathOutput );
System.out.println( "Writing file: " + pathOutput );
// Read.
long start = System.nanoTime();
Path pathInput = Paths.get( "/Users/basilbourque/persons.csv" );
List < Person > list = app.read( pathInput );
long stop = System.nanoTime();
// Time.
long elapsed = ( stop - start );
Duration d = Duration.ofNanos( elapsed );
System.out.println( "Reading elapsed: " + d );
System.out.println( "Reading took nanos per row: " + ( elapsed / list.size() ) );
System.out.println( "nanos elapsed: " + elapsed + " | list.size: " + list.size() );
}
}
运行时：
编写文件：/Users/basilbourque/persons.csv
已读：PT0.857816234S
每行读取纳秒数：21445
nanos 经过：857816234 | list.size: 40000
技术栈：
- Java 11.0.2 — Azul Systems 的 Zulu（基于 OpenJDK 构建）
- 在 IntelliJ 2019.1 中运行
- macOS Mojave
- MacBook Pro（Retina，15 英寸，2013 年末）
- 处理器：2.3 GHz Intel Core i7（4 核，8 超）
- 16 GB 1600 MHz DDR3
- 存储：Apple 内置固态