StringTokenizer - reading lines with integers

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(updated answer)

I can say that whatever the problems in your program speed, the choice of tokenizer is not one of them. After an initial run of each method to even out initialisation quirks, I can parse 1000000 rows of "12 34" in milliseconds. You could switch to using indexOf if you like but I really think you need to look at other bits of code for the bottleneck rather than this micro-optimisation. Split was a surprise for me - it's really, really slow compared to the other methods. I've added in Guava split test and it's faster than String.split but slightly slower than StringTokenizer.

  • Split: 371ms
  • IndexOf: 48ms
  • StringTokenizer: 92ms
  • Guava Splitter.split(): 108ms
  • CsvMapper build a csv doc and parse into POJOS: 237ms (or 175 if you build the lines into one doc!)

The difference here is pretty negligible even over millions of rows.

There's now a write up of this on my blog: http://demeranville.com/battle-of-the-tokenizers-delimited-text-parser-performance/

Code I ran was:

import java.util.StringTokenizer;
import org.junit.Test;

public class TestSplitter {

private static final String line = "12 34";
private static final int RUNS = 1000000;//000000;

public final void testSplit() {
    long start = System.currentTimeMillis();
    for (int i=0;i<RUNS;i++){
        String[] st = line.split(" ");
        int x = Integer.parseInt(st[0]);
        int y = Integer.parseInt(st[1]);
    }
    System.out.println("Split: "+(System.currentTimeMillis() - start)+"ms");
}

public final void testIndexOf() {
    long start = System.currentTimeMillis();
    for (int i=0;i<RUNS;i++){
        int index = line.indexOf(' ');
        int x = Integer.parseInt(line.substring(0,index));
        int y = Integer.parseInt(line.substring(index+1));
    }       
    System.out.println("IndexOf: "+(System.currentTimeMillis() - start)+"ms");      
}

public final void testTokenizer() {
    long start = System.currentTimeMillis();
    for (int i=0;i<RUNS;i++){
        StringTokenizer st = new StringTokenizer(line, " ");
        int x = Integer.parseInt(st.nextToken());
        int y = Integer.parseInt(st.nextToken());
    }
    System.out.println("StringTokenizer: "+(System.currentTimeMillis() - start)+"ms");
}

@Test
public final void testAll() {
    this.testSplit();
    this.testIndexOf();
    this.testTokenizer();
    this.testSplit();
    this.testIndexOf();
    this.testTokenizer();
}

}

eta: here's the guava code:

public final void testGuavaSplit() {
    long start = System.currentTimeMillis();
    Splitter split = Splitter.on(" ");
    for (int i=0;i<RUNS;i++){
        Iterator<String> it = split.split(line).iterator();
        int x = Integer.parseInt(it.next());
        int y = Integer.parseInt(it.next());
    }
    System.out.println("GuavaSplit: "+(System.currentTimeMillis() - start)+"ms");
}

update

I've added in a CsvMapper test too:

public static class CSV{
    public int x;
    public int y;
}

public final void testJacksonSplit() throws JsonProcessingException, IOException {
    CsvMapper mapper = new CsvMapper();
    CsvSchema schema = CsvSchema.builder().addColumn("x", ColumnType.NUMBER).addColumn("y", ColumnType.NUMBER).setColumnSeparator(' ').build();

    long start = System.currentTimeMillis();
    StringBuilder builder = new StringBuilder();
    for (int i = 0; i < RUNS; i++) {
        builder.append(line);
        builder.append('\n');
    }       
    String input = builder.toString();
    MappingIterator<CSV> it = mapper.reader(CSV.class).with(schema).readValues(input);
    while (it.hasNext()){
        CSV csv = it.next();
    }
    System.out.println("CsvMapperSplit: " + (System.currentTimeMillis() - start) + "ms");
}
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Smajl
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Smajl

Software developer with focus on Java and cloud technologies.

Updated on September 16, 2022

Comments

  • Smajl
    Smajl over 1 year

    I have a question about optimization of my code (which works but is too slow...). I am reading an input in a form

    X1 Y1
    X2 Y2
    etc
    

    where Xi, Yi are integers. I am using bufferedReader for reading lines and then StringTokenizer for processing those numbers like this:

    StringTokenizer st = new StringTokenizer(line, " ");
    
    int x = Integer.parseInt(st.nextToken());
    int y = Integer.parseInt(st.nextToken());
    

    The problem is that this approach seems time inefficient when coping with large data sets. Could you suggest me some simple improvement (I have heard that some integer parse int or regex can be used) which would improve the performance? Thanks for any tips

    EDIT: Perhaps I misjudged myself and some improvements have to be done elsewhere in the code...

    • Smajl
      Smajl over 10 years
      The bottlneck (and core of my problem) lay somewhere else than in the piece of code I shown in my question - I wronglz classified my problem...
  • Fedy2
    Fedy2 over 10 years
    In the indexOf method can you move the indexOf calculation in a single statement? int index = line.indexOf(' ');
  • Fedy2
    Fedy2 over 10 years
    One more "crazy" solution, with some limitations and not well tested: pastebin.com/9Cf2ZVT0
  • tom
    tom over 10 years
    wow. Just ran that through and it came out at 15ms on the same box as the other tests! 3x faster, 50x less readable :D
  • Carlos Vega
    Carlos Vega about 10 years
    Could you explain the "crazy" solution, it would be really useful for me.
  • Gerard
    Gerard almost 7 years
    @CarlosVega the "crazy" solution is specifically built to parse this exact file format, the two loops for two data points, the loops read the numbers backward and rather than isolating the string then using a parse function, it keeps a running total and knows the power multiplier for each character depending on its left position from the commencement of the loop (back to front), clever shortcuts like breaking loop when number sign (+/-) read, space check only on 1st loop, adding byte/char total as it steps make it as near fast as it can be. v nice Fred2