问题
I'm trying to parse a CSV file using jackson-dataformat-csv
and I want to map the numeric column to the Number java type.
CsvSchema schema = CsvSchema.builder().setUseHeader(true)
.addColumn("firstName", CsvSchema.ColumnType.STRING)
.addColumn("lastName", CsvSchema.ColumnType.STRING)
.addColumn("age", CsvSchema.ColumnType.NUMBER)
.build();
CsvMapper csvMapper = new CsvMapper();
MappingIterator<Map<String, Object>> mappingIterator = csvMapper
.readerFor(Map.class)
.with(schema)
.readValues(is);
while (mappingIterator.hasNext()) {
Map<String, Object> entryMap = mappingIterator.next();
Number age = (Number) entryMap.get("age");
}
I'm expecting entryMap.get("age")
should be a Number
, but I get String
instead.
My CSV file:
firstName,lastName,age
John,Doe,21
Error,Name,-10
I know that CsvSchema
works fine with POJOs, but I need to process arbitrary CSV schemas, so I can't create a new java class for every case.
Any way to parse CSV into a typed Map
or Array
?
回答1:
You can use univocity-parsers for this sort of thing. It's faster and way more flexible:
var settings = new CsvParserSettings(); //configure the parser if needed
var parser = new CsvParser(settings);
for (Record record : parser.iterateRecords(is)) {
Short age = record.getShort("age");
}
To get a typed map, tell the parser what is the type of the columns you are working with:
parser.getRecordMetadata().setTypeOfColumns(Short.class, "age" /*, and other column names*/);
//to get 0 instead of nulls when the field is empty in the file:
parser.getRecordMetadata().setDefaultValueOfColumns("0", "age", /*, and other column names*/);
// then parse
for (Record record : parser.iterateRecords(is)) {
Map<String,Object> map = record.toFieldMap();
}
Hope this helps
Disclaimer: I'm the author of this library. It's open source and free (Apache 2.0 license)
回答2:
Right now it is not possible to configure Map
deserialisation using CsvSchema
. Process uses com.fasterxml.jackson.databind.deser.std.MapDeserializer
which right now does not check schema. We could write custom Map
deserialiser. There is a question on GitHub: CsvMapper does not respect CsvSchema.ColumnType when using @JsonAnySetter where cowtowncoder
answered:
At this point schema type is not used much for anything, but I agree it should.
EDIT
I decided to take a look closer what we can do with that fact that com.fasterxml.jackson.databind.deser.std.MapDeserializer
is used behind the scene. Implementing custom Map
deserialiser which will take care about types would be tricky to implement and register but we can use knowledge about ValueInstantiator
. Let's define new Map
type which knows what to do with ColumnType
info:
class CsvMap extends HashMap<String, Object> {
private final CsvSchema schema;
private final NumberFormat numberFormat = NumberFormat.getInstance();
public CsvMap(CsvSchema schema) {
this.schema = schema;
}
@Override
public Object put(String key, Object value) {
value = convertIfNeeded(key, value);
return super.put(key, value);
}
private Object convertIfNeeded(String key, Object value) {
CsvSchema.Column column = schema.column(key);
if (column.getType() == CsvSchema.ColumnType.NUMBER) {
try {
return numberFormat.parse(value.toString());
} catch (ParseException e) {
// leave it as it is
}
}
return value;
}
}
For new type without no-arg
constructor we should create new ValueInstantiator
:
class CsvMapInstantiator extends ValueInstantiator.Base {
private final CsvSchema schema;
public CsvMapInstantiator(CsvSchema schema) {
super(CsvMap.class);
this.schema = schema;
}
@Override
public Object createUsingDefault(DeserializationContext ctxt) {
return new CsvMap(schema);
}
@Override
public boolean canCreateUsingDefault() {
return true;
}
}
Example usage:
import com.fasterxml.jackson.databind.DeserializationContext;
import com.fasterxml.jackson.databind.MappingIterator;
import com.fasterxml.jackson.databind.ObjectReader;
import com.fasterxml.jackson.databind.deser.ValueInstantiator;
import com.fasterxml.jackson.databind.module.SimpleModule;
import com.fasterxml.jackson.dataformat.csv.CsvMapper;
import com.fasterxml.jackson.dataformat.csv.CsvSchema;
import java.io.File;
import java.io.IOException;
import java.text.NumberFormat;
import java.text.ParseException;
import java.util.HashMap;
public class CsvApp {
public static void main(String[] args) throws IOException {
File csvFile = new File("./resource/test.csv").getAbsoluteFile();
CsvSchema schema = CsvSchema.builder()
.addColumn("firstName", CsvSchema.ColumnType.STRING)
.addColumn("lastName", CsvSchema.ColumnType.STRING)
.addColumn("age", CsvSchema.ColumnType.NUMBER)
.build().withHeader();
// Create schema aware map module
SimpleModule csvMapModule = new SimpleModule();
csvMapModule.addValueInstantiator(CsvMap.class, new CsvMapInstantiator(schema));
// register map
CsvMapper csvMapper = new CsvMapper();
csvMapper.registerModule(csvMapModule);
// get reader for CsvMap + schema
ObjectReader objectReaderWithSchema = csvMapper
.readerWithSchemaFor(CsvMap.class)
.with(schema);
MappingIterator<CsvMap> mappingIterator = objectReaderWithSchema.readValues(csvFile);
while (mappingIterator.hasNext()) {
CsvMap entryMap = mappingIterator.next();
Number age = (Number) entryMap.get("age");
System.out.println(age + " (" + age.getClass() + ")");
}
}
}
Above code for below CSV
payload:
firstName,lastName,age
John,Doe,21
Error,Name,-10.1
prints:
21 (class java.lang.Long)
-10.1 (class java.lang.Double)
It looks like a hack but I wanted to show this possibility.
来源:https://stackoverflow.com/questions/55110124/jackson-dataformat-csv-mapping-number-value-without-pojo