要使用Avro Schema Java验证API,您需要按照以下步骤进行操作:
Maven:
org.apache.avro
avro
1.10.2
Gradle:
implementation 'org.apache.avro:avro:1.10.2'
示例avsc文件(person.avsc):
{
"type": "record",
"name": "Person",
"fields": [
{"name": "name", "type": "string"},
{"name": "age", "type": "int"}
]
}
使用Avro工具编译为Java类:
$ java -jar avro-tools-1.10.2.jar compile schema person.avsc ./generated-java
import org.apache.avro.Schema;
import org.apache.avro.generic.GenericData;
import org.apache.avro.generic.GenericRecord;
import org.apache.avro.io.DatumReader;
import org.apache.avro.io.DatumWriter;
import org.apache.avro.io.Decoder;
import org.apache.avro.io.DecoderFactory;
import org.apache.avro.io.Encoder;
import org.apache.avro.io.EncoderFactory;
import org.apache.avro.specific.SpecificDatumReader;
import org.apache.avro.specific.SpecificDatumWriter;
import java.io.ByteArrayInputStream;
import java.io.ByteArrayOutputStream;
import java.io.IOException;
public class AvroSchemaValidationExample {
public static void main(String[] args) throws IOException {
// Load the schema
Schema schema = new Schema.Parser().parse(AvroSchemaValidationExample.class.getResourceAsStream("/person.avsc"));
// Create a GenericRecord
GenericRecord record = new GenericData.Record(schema);
record.put("name", "John");
record.put("age", 25);
// Serialize the record
ByteArrayOutputStream outputStream = new ByteArrayOutputStream();
Encoder encoder = EncoderFactory.get().binaryEncoder(outputStream, null);
DatumWriter writer = new SpecificDatumWriter<>(schema);
writer.write(record, encoder);
encoder.flush();
byte[] serializedBytes = outputStream.toByteArray();
// Deserialize the record
ByteArrayInputStream inputStream = new ByteArrayInputStream(serializedBytes);
Decoder decoder = DecoderFactory.get().binaryDecoder(inputStream, null);
DatumReader reader = new SpecificDatumReader<>(schema);
GenericRecord deserializedRecord = reader.read(null, decoder);
// Validate the deserialized record against the schema
if (schema.equals(deserializedRecord.getSchema())) {
System.out.println("Record is valid against the schema!");
} else {
System.out.println("Record is not valid against the schema!");
}
}
}
以上代码示例中,我们首先加载了之前生成的Person.avsc文件的Schema。然后,我们创建了一个GenericRecord对象,该对象符合Schema定义。接下来,我们将GenericRecord序列化为字节数组。然后,我们将字节数组反序列化为一个新的GenericRecord对象。最后,我们将原始Schema和反序列化的记录的Schema进行比较,以验证数据是否符合Schema定义。
请确保将person.avsc文件放在与代码示例相同的目录下,并将其编译为Java类。