使用Java 8 Stream解析日志文件，求完善代码实现

Let's break down how to fix your code to achieve the desired output. First, let's clarify the steps needed for each log entry:

1. Extract the 3-letter racer code (e.g., SVF) as the key.
2. Split the remaining part of the entry into date and time using the underscore (_) as the separator.
3. Wrap the date and time into an ArrayList<String>.
4. Create a single-entry HashMap for each racer, then collect all these maps into a List.

Corrected Code #

import java.io.IOException;
import java.net.URISyntaxException;
import java.util.ArrayList;
import java.util.HashMap;
import java.util.List;
import java.util.Arrays;
import java.util.stream.Collectors;
import java.util.stream.Stream;

public class FileParser {
    private Stream<String> outputStream;

    // Adjusted the FileReader constructor call (assuming your custom class takes fileName as input)
    public FileParser(String fileName) throws IOException, URISyntaxException {
        FileReader fr = new FileReader(fileName);
        this.outputStream = fr.getStreamFromFile(fileName);
    }

    public List<HashMap<String, ArrayList<String>>> getRacersInfo() {
        return outputStream
                // Split single-line log content into individual entries (remove if entries are already on separate lines)
                .flatMap(line -> Arrays.stream(line.split("\\s+")))
                // Process each entry into a single-entry HashMap
                .map(entry -> {
                    String racerCode = entry.substring(0, 3);
                    String[] dateTimeParts = entry.substring(3).split("_");
                    ArrayList<String> dateTimeList = new ArrayList<>(Arrays.asList(dateTimeParts));
                    
                    HashMap<String, ArrayList<String>> racerMap = new HashMap<>();
                    racerMap.put(racerCode, dateTimeList);
                    
                    return racerMap;
                })
                // Collect all maps into the final List
                .collect(Collectors.toList());
    }
}

Key Details: #

• Entry Splitting: The flatMap step handles cases where the entire log is stored as a single line with entries separated by spaces. If each entry is already on its own line in the file, you can remove this line and process each line directly with map.
• Custom FileReader: I adjusted the FileReader constructor to pass the fileName since empty file reader constructors are uncommon—tweak this if your custom class uses a different initialization pattern.
• Flexibility Note: While you specified ArrayList<String> in the return type, using List<String> (instead of the concrete ArrayList) is generally better for code flexibility. If possible, updating the return type to List<HashMap<String, List<String>>> would be a cleaner approach.
• Error Handling: This code assumes all log entries are well-formed. To handle invalid entries (e.g., missing underscore, short code), add a filter or try-catch block inside the map operation to skip or log bad entries.

Example Output: #

For your sample entry SVF2018-05-24_12:02:58.917, the resulting map will be:

{SVF = [2018-05-24, 12:02:58.917]}

The full list will contain one such map for every log entry as you requested.

内容的提问来源于stack exchange，提问作者IceTeaGreen