szehon-ho commented on a change in pull request #3273:
URL: https://github.com/apache/iceberg/pull/3273#discussion_r732365632
##########
File path:
spark/v3.0/spark3-extensions/src/test/java/org/apache/iceberg/spark/extensions/TestAddFilesProcedure.java
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@@ -106,6 +119,68 @@ public void addDataUnpartitionedOrc() {
sql("SELECT * FROM %s ORDER BY id", tableName));
}
+ @Test
+ public void addAvroFile() throws Exception {
+ // Spark Session Catalog cannot load metadata tables
+ // with "The namespace in session catalog must have exactly one name part"
+ Assume.assumeFalse(catalogName.equals("spark_catalog"));
+
+ Schema schema = new Schema(
+ Types.NestedField.required(1, "id", Types.LongType.get()),
+ Types.NestedField.optional(2, "data", Types.StringType.get()));
+
+ GenericRecord baseRecord = GenericRecord.create(schema);
+
+ ImmutableList.Builder<Record> builder = ImmutableList.builder();
+ builder.add(baseRecord.copy(ImmutableMap.of("id", 1L, "data", "a")));
+ builder.add(baseRecord.copy(ImmutableMap.of("id", 2L, "data", "b")));
+ List<Record> records = builder.build();
+
+ OutputFile file = Files.localOutput(temp.newFile());
+
+ DataWriter<Record> dataWriter = Avro.writeData(file)
+ .schema(schema)
+ .createWriterFunc(org.apache.iceberg.data.avro.DataWriter::create)
+ .overwrite()
+ .withSpec(PartitionSpec.unpartitioned())
+ .build();
+
+ try {
+ for (Record record : records) {
+ dataWriter.add(record);
+ }
+ } finally {
+ dataWriter.close();
+ }
+
+ String path = dataWriter.toDataFile().path().toString();
+
+ String createIceberg =
+ "CREATE TABLE %s (id Long, data String) USING iceberg";
+ sql(createIceberg, tableName);
+
+ Object result = scalarSql("CALL %s.system.add_files('%s', '`avro`.`%s`')",
+ catalogName, tableName, path);
Review comment:
Changed to using native Avro writers, does that do the trick?
Re: fieldId check, sounds good, probably we can look at that and also add
general schema validation while importing the file.
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