我正在尝试使用 SuperCSV 将数据库中的大量行(约 200 万行)写入 CSV 文件。我需要在编写每个单元格时对其执行验证,内置的 CellProcessors 做得非常好。我想捕获 CellProcessors 抛出的所有异常,以便我可以返回到源数据并进行更改。
问题是,当一行中有多个错误时(例如,第一个值超出范围,第二个值是 null 但不应该是),只有第一个 CellProcessor 会执行,所以我会只看到其中一个错误。我想一次处理整个文件,并在最后处理一整套异常。
这是我正在尝试的一种方法:
for (Row row : rows) {
try {
csvBeanWriter.write(row, HEADER_MAPPINGS, CELL_PROCESSORS);
} catch (SuperCsvCellProcessorException e) {
log(e);
}
}
我怎样才能做到这一点?谢谢!
编辑:这是我编写的与 Hound Dog 类似的代码,以防对任何人有帮助:
import java.util.List;
import org.supercsv.cellprocessor.CellProcessorAdaptor;
import org.supercsv.cellprocessor.ift.CellProcessor;
import org.supercsv.exception.SuperCsvCellProcessorException;
import org.supercsv.util.CsvContext;
public class ExceptionCapturingCellProcessor extends CellProcessorAdaptor {
private final List<Exception> exceptions;
private final CellProcessor current;
public ExceptionCapturingCellProcessor(CellProcessor current, CellProcessor next, List<Exception> exceptions) {
super(next);
this.exceptions = exceptions;
this.current = current;
}
@Override
public Object execute(Object value, CsvContext context) {
// Check input is not null
try {
validateInputNotNull(value, context);
} catch (SuperCsvCellProcessorException e) {
exceptions.add(e);
}
// Execute wrapped CellProcessor
try {
current.execute(value, context);
} catch (SuperCsvCellProcessorException e) {
exceptions.add(e);
}
return next.execute(value, context);
}
}
最佳答案
我推荐 writing a custom CellProcessor为了达成这个。下面的处理器可以放在每个 CellProcessor 链的开头 - 它只会委托(delegate)给链接在它后面的处理器,并将抑制任何单元格处理异常。
package example;
import java.util.ArrayList;
import java.util.List;
import org.supercsv.cellprocessor.CellProcessorAdaptor;
import org.supercsv.cellprocessor.ift.CellProcessor;
import org.supercsv.exception.SuperCsvCellProcessorException;
import org.supercsv.util.CsvContext;
public class SuppressException extends CellProcessorAdaptor {
public static List<SuperCsvCellProcessorException> SUPPRESSED_EXCEPTIONS =
new ArrayList<SuperCsvCellProcessorException>();
public SuppressException(CellProcessor next) {
super(next);
}
public Object execute(Object value, CsvContext context) {
try {
// attempt to execute the next processor
return next.execute(value, context);
} catch (SuperCsvCellProcessorException e) {
// save the exception
SUPPRESSED_EXCEPTIONS.add(e);
// and suppress it (null is written as "")
return null;
}
}
}
这是实际操作:
package example;
import java.io.StringWriter;
import java.util.Arrays;
import java.util.List;
import org.supercsv.cellprocessor.constraint.NotNull;
import org.supercsv.cellprocessor.constraint.StrMinMax;
import org.supercsv.cellprocessor.ift.CellProcessor;
import org.supercsv.exception.SuperCsvCellProcessorException;
import org.supercsv.io.CsvBeanWriter;
import org.supercsv.io.ICsvBeanWriter;
import org.supercsv.prefs.CsvPreference;
public class TestSuppressExceptions {
private static final CellProcessor[] PROCESSORS = {
new SuppressException(new StrMinMax(0, 4)),
new SuppressException(new NotNull()) };
private static final String[] HEADER = { "name", "age" };
public static void main(String[] args) throws Exception {
final StringWriter stringWriter = new StringWriter();
ICsvBeanWriter beanWriter = null;
try {
beanWriter = new CsvBeanWriter(stringWriter,
CsvPreference.STANDARD_PREFERENCE);
beanWriter.writeHeader(HEADER);
// set up the data
Person valid = new Person("Rick", 43);
Person nullAge = new Person("Lori", null);
Person totallyInvalid = new Person("Shane", null);
Person valid2 = new Person("Carl", 12);
List<Person> people = Arrays.asList(valid, nullAge, totallyInvalid,
valid2);
for (Person person : people) {
beanWriter.write(person, HEADER, PROCESSORS);
if (!SuppressException.SUPPRESSED_EXCEPTIONS.isEmpty()) {
System.out.println("Suppressed exceptions for row "
+ beanWriter.getRowNumber() + ":");
for (SuperCsvCellProcessorException e :
SuppressException.SUPPRESSED_EXCEPTIONS) {
System.out.println(e);
}
// clear ready for next row
SuppressException.SUPPRESSED_EXCEPTIONS.clear();
}
}
} finally {
beanWriter.close();
}
// CSV will have empty columns for invalid data
System.out.println(stringWriter);
}
}
这是被抑制的异常输出(第 4 行有两个异常,每列一个):
Suppressed exceptions for row 3:
org.supercsv.exception.SuperCsvConstraintViolationException: null value
encountered processor=org.supercsv.cellprocessor.constraint.NotNull
context={lineNo=3, rowNo=3, columnNo=2, rowSource=[Lori, null]}
Suppressed exceptions for row 4:
org.supercsv.exception.SuperCsvConstraintViolationException: the length (5)
of value 'Shane' does not lie between the min (0) and max (4) values (inclusive)
processor=org.supercsv.cellprocessor.constraint.StrMinMax
context={lineNo=4, rowNo=4, columnNo=2, rowSource=[Shane, null]}
org.supercsv.exception.SuperCsvConstraintViolationException: null value
encountered processor=org.supercsv.cellprocessor.constraint.NotNull
context={lineNo=4, rowNo=4, columnNo=2, rowSource=[Shane, null]}
和 CSV 输出
name,age
Rick,43
Lori,
,
Carl,12
请注意无效值是如何写成 ""
的,因为 SuppressException
处理器为这些值返回了 null
(不是您要使用的CSV 输出,因为它无效!)。
关于java - 使用 SuperCSV 一次性验证每个字段,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/13646982/