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Bug
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Resolution: Fixed
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Minor
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None
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All
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Small
This is related to the MapLang processor development in Pipeline Designer.
We have a use case where the MQL interpreter generates a record containing an array of array of record. The MQL interpreter uses the RecordBuilderFactory API in order to create the TCK schema and record.
But the generated TCK record seems invalid. It is actually an instance of AvroRecord which encapsulates an instance of GenericData$Record. But this Avro record does not contain GenericData$Array but simple Collections. And these collections does not contain GenericData$Record but AvroRecord instances. So we get an avro record which contains TCK record, which seems invalid.
In order to reproduce easily this issue, i provide the following simple code example:
// get RecordBuilderFactory AvroRecordBuilderFactoryProvider recordBuilderFactoryProvider = new AvroRecordBuilderFactoryProvider(); System.setProperty("talend.component.beam.record.factory.impl", "avro"); RecordBuilderFactory recordBuilderFactory = recordBuilderFactoryProvider.apply("test"); // customer record schema org.talend.sdk.component.api.record.Schema.Builder schemaBuilder = recordBuilderFactory.newSchemaBuilder(Type.RECORD); Entry nameEntry = recordBuilderFactory.newEntryBuilder().withName("name") .withNullable(true).withType(Type.STRING).build(); Entry ageEntry = recordBuilderFactory.newEntryBuilder().withName("age") .withNullable(true).withType(Type.INT).build(); Schema customerSchema = schemaBuilder.withEntry(nameEntry).withEntry(ageEntry).build(); // record 1 Builder recordBuilder = recordBuilderFactory.newRecordBuilder(customerSchema); recordBuilder.withString("name", "Tom Cruise"); recordBuilder.withInt("age", 58); Record record1 = recordBuilder.build(); // record 2 recordBuilder = recordBuilderFactory.newRecordBuilder(customerSchema); recordBuilder.withString("name", "Meryl Streep"); recordBuilder.withInt("age", 63); Record record2 = recordBuilder.build(); // list 1 Collection<Record> list1 = new ArrayList<Record>(); list1.add(record1); list1.add(record2); // record 3 recordBuilder = recordBuilderFactory.newRecordBuilder(customerSchema); recordBuilder.withString("name", "Client Eastwood"); recordBuilder.withInt("age", 89); Record record3 = recordBuilder.build(); // record 4 recordBuilder = recordBuilderFactory.newRecordBuilder(customerSchema); recordBuilder.withString("name", "Jessica Chastain"); recordBuilder.withInt("age", 36); Record record4 = recordBuilder.build(); // list 2 Collection<Record> list2 = new ArrayList<Record>(); list2.add(record3); list2.add(record4); // main list Collection<Object> list3 = new ArrayList<Object>(); list3.add(list1); list3.add(list2); // schema of sub list schemaBuilder = recordBuilderFactory.newSchemaBuilder(Type.ARRAY); Schema subListSchema = schemaBuilder.withElementSchema(customerSchema).build(); // main record recordBuilder = recordBuilderFactory.newRecordBuilder(); Entry entry = recordBuilderFactory.newEntryBuilder().withName("customers") .withNullable(true).withType(Type.ARRAY).withElementSchema(subListSchema).build(); recordBuilder.withArray(entry, list3); Record record = recordBuilder.build();
The produced Record is like that:
AvroRecord{delegate={"customers": [[AvroRecord{delegate={"name": "Tom Cruise", "age": 58}}, AvroRecord{delegate={"name": "Meryl Streep", "age": 63}}], [AvroRecord{delegate={"name": "Client Eastwood", "age": 89}}, AvroRecord{delegate={"name": "Jessica Chastain", "age": 36}}]]}}
We can see that delegate Avro record contains TCK records.
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