我正在使用databricks spark-avro将数据帧模式转换为avro schema.The返回的avro模式没有默认值。
Dataset<Row> sellableDs = sparkSession.sql("sql query");
SchemaBuilder.RecordBuilder<Schema> rb = SchemaBuilder.record("testrecord").namespace("test_namespace");
Schema sc = SchemaConverters.convertStructToAvro(sellableDs.schema(), rb, "test_namespace");
System.out.println(sc.toString());
System.out.println(sc.getFields().get(0).toString());
String schemaString = sc.toString();
sellableDs.foreach(
(ForeachFunction<Row>) row -> {
Schema scEx = new Schema.Parser().parse(schemaString);
GenericRecord gr;
gr = new GenericData.Record(scEx);
System.out.println("Generic record Created");
int fieldSize = scEx.getFields().size();
for (int i = 0; i < fieldSize; i++ ) {
// System.out.println( row.get(i).toString());
System.out.println("field: " + scEx.getFields().get(i).toString() + "::" + "value:" + row.get(i));
gr.put(scEx.getFields().get(i).toString(), row.get(i));
//i++;
}
}
);这是df模式:
StructType(StructField(key,IntegerType,true), StructField(value,DoubleType,true))这是avro转换后的模式:
{"type":"record","name":"testrecord","namespace":"test_namespace","fields":[{"name":"key","type":["int","null"]},{"name":"value","type":["double","null"]}]}发布于 2018-12-04 22:01:13
问题是SchemaConverters类在模式创建过程中没有包含默认值。您有两种选择,一种是修改模式,在创建记录之前添加默认值,另一种是在构建某些值之前填充记录(实际上可以是您的行中的值)。例如null。这是如何使用您的方案创建记录的示例
import org.apache.avro.generic.GenericRecordBuilder
import org.apache.avro.Schema
var schema = new Schema.Parser().parse("{\"type\":\"record\",\"name\":\"testrecord\",\"namespace\":\"test_namespace\",\"fields\":[{\"name\":\"key\",\"type\":[\"int\",\"null\"]},{\"name\":\"value\",\"type\":[\"double\",\"null\"]}]}")
var builder = new GenericRecordBuilder(schema);
for (i <- 0 to schema.getFields().size() - 1 ) {
builder.set(schema.getFields().get(i).name(), null)
}
var record = builder.build();
print(record.toString())https://stackoverflow.com/questions/53612711
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