jonvex commented on code in PR #10858:
URL: https://github.com/apache/hudi/pull/10858#discussion_r1538421938
##########
hudi-utilities/src/main/java/org/apache/hudi/utilities/streamer/StreamSync.java:
##########
@@ -623,15 +649,19 @@ private InputBatch
fetchNextBatchFromSource(Option<String> resumeCheckpointStr,
}
} else {
if (useRowWriter) {
- inputBatchForWriter =
formatAdapter.fetchNewDataInRowFormat(resumeCheckpointStr, cfg.sourceLimit);
+ InputBatch inputBatchNeedsDeduceSchema =
formatAdapter.fetchNewDataInRowFormat(resumeCheckpointStr, cfg.sourceLimit);
+ inputBatchForWriter = new
InputBatch<>(inputBatchNeedsDeduceSchema.getBatch(),
inputBatchNeedsDeduceSchema.getCheckpointForNextBatch(),
+
getDeducedSchemaProvider(inputBatchNeedsDeduceSchema.getSchemaProvider().getTargetSchema(),
inputBatchNeedsDeduceSchema.getSchemaProvider(), metaClient));
} else {
// Pull the data from the source & prepare the write
InputBatch<JavaRDD<GenericRecord>> dataAndCheckpoint =
formatAdapter.fetchNewDataInAvroFormat(resumeCheckpointStr, cfg.sourceLimit);
checkpointStr = dataAndCheckpoint.getCheckpointForNextBatch();
// Rewrite transformed records into the expected target schema
schemaProvider =
getDeducedSchemaProvider(dataAndCheckpoint.getSchemaProvider().getTargetSchema(),
dataAndCheckpoint.getSchemaProvider(), metaClient);
String serializedTargetSchema =
schemaProvider.getTargetSchema().toString();
- if (errorTableWriter.isPresent()
+ if
(schemaProvider.getTargetSchema().equals(dataAndCheckpoint.getSchemaProvider().getTargetSchema()))
{
+ avroRDDOptional = dataAndCheckpoint.getBatch();
Review Comment:
I meant to check source schema vs deduced target schema but even that is no
good, because we need to validate that source -> target transformation is
possible so I got rid of this change
##########
hudi-utilities/src/test/java/org/apache/hudi/utilities/streamer/TestFetchNextBatchFromSource.java:
##########
@@ -0,0 +1,199 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied. See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied. See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.hudi.utilities.streamer;
+
+import org.apache.hudi.DataSourceWriteOptions;
+import org.apache.hudi.client.common.HoodieSparkEngineContext;
+import org.apache.hudi.common.config.TypedProperties;
+import org.apache.hudi.common.table.HoodieTableMetaClient;
+import org.apache.hudi.common.util.Option;
+import org.apache.hudi.config.HoodieErrorTableConfig;
+import org.apache.hudi.utilities.schema.SchemaProvider;
+import org.apache.hudi.utilities.sources.InputBatch;
+import org.apache.hudi.utilities.transform.Transformer;
+
+import org.apache.avro.Schema;
+import org.apache.avro.generic.GenericRecord;
+import org.apache.hadoop.conf.Configuration;
+import org.apache.hadoop.fs.FileSystem;
+import org.apache.spark.api.java.JavaRDD;
+import org.apache.spark.sql.Dataset;
+import org.apache.spark.sql.Row;
+import org.apache.spark.sql.SparkSession;
+import org.junit.jupiter.params.ParameterizedTest;
+import org.junit.jupiter.params.provider.Arguments;
+import org.junit.jupiter.params.provider.MethodSource;
+
+import java.util.stream.Stream;
+
+import static
org.apache.hudi.config.HoodieErrorTableConfig.ERROR_ENABLE_VALIDATE_TARGET_SCHEMA;
+import static org.mockito.ArgumentMatchers.any;
+import static org.mockito.ArgumentMatchers.anyLong;
+import static org.mockito.Mockito.atLeastOnce;
+import static org.mockito.Mockito.doReturn;
+import static org.mockito.Mockito.mock;
+import static org.mockito.Mockito.never;
+import static org.mockito.Mockito.spy;
+import static org.mockito.Mockito.times;
+import static org.mockito.Mockito.verify;
+import static org.mockito.Mockito.when;
+
+public class TestFetchNextBatchFromSource {
+
+ @ParameterizedTest
+ @MethodSource("testCases")
+ void testFetchNextBatchFromSource(Boolean useRowWriter, Boolean
hasTransformer, Boolean hasSchemaProvider,
+ Boolean nullTargetSchema, Boolean
hasErrorTable, Boolean deduceSchemaSame) {
+ //basic deltastreamer inputs
+ HoodieSparkEngineContext hoodieSparkEngineContext =
mock(HoodieSparkEngineContext.class);
+ FileSystem fs = mock(FileSystem.class);
+ SparkSession sparkSession = mock(SparkSession.class);
+ Configuration configuration = mock(Configuration.class);
+ HoodieStreamer.Config cfg = new HoodieStreamer.Config();
+ cfg.targetTableName = "testTableName";
+ cfg.targetBasePath = "/fake/table/name";
+ cfg.tableType = "MERGE_ON_READ";
+
+ //Source format adapter
+ SourceFormatAdapter sourceFormatAdapter = mock(SourceFormatAdapter.class);
+ SchemaProvider inputBatchSchemaProvider = getSchemaProvider("InputBatch",
false);
+ Option<Dataset<Row>> fakeDataFrame = Option.of(mock(Dataset.class));
+ InputBatch<Dataset<Row>> fakeRowInputBatch = new
InputBatch<>(fakeDataFrame, "chkpt", inputBatchSchemaProvider);
+ when(sourceFormatAdapter.fetchNewDataInRowFormat(any(),
anyLong())).thenReturn(fakeRowInputBatch);
+ //batch is empty because we don't want getBatch().map() to do anything
because it calls static method we can't mock
+ InputBatch<JavaRDD<GenericRecord>> fakeAvroInputBatch = new
InputBatch<>(Option.empty(), "chkpt", inputBatchSchemaProvider);
+
when(sourceFormatAdapter.fetchNewDataInAvroFormat(any(),anyLong())).thenReturn(fakeAvroInputBatch);
+
+ //transformer
+ //return empty because we don't want .map() to do anything because it
calls static method we can't mock
+ when(sourceFormatAdapter.processErrorEvents(any(),
any())).thenReturn(Option.empty());
+ Option<Transformer> transformerOption = Option.empty();
+ if (hasTransformer) {
+ transformerOption = Option.of(mock(Transformer.class));
+ }
+
+ //user provided schema provider
+ SchemaProvider schemaProvider = null;
+ if (hasSchemaProvider) {
+ schemaProvider = getSchemaProvider("UserProvided", nullTargetSchema);
+ }
+
+ //error table
+ TypedProperties props = new TypedProperties();
+ props.put(DataSourceWriteOptions.RECONCILE_SCHEMA().key(), false);
+ Option<BaseErrorTableWriter> errorTableWriterOption = Option.empty();
+ if (hasErrorTable) {
+ errorTableWriterOption = Option.of(mock(BaseErrorTableWriter.class));
+ props.put(ERROR_ENABLE_VALIDATE_TARGET_SCHEMA.key(), true);
+ }
+ TypedProperties propsSpy = spy(props);
+
+
+ //Actually create the deltastreamer
+ StreamSync streamSync = new StreamSync(cfg, sparkSession, propsSpy,
hoodieSparkEngineContext,
+ fs, configuration, client -> true, schemaProvider,
errorTableWriterOption, sourceFormatAdapter, transformerOption, useRowWriter,
false);
+ StreamSync spy = spy(streamSync);
+ SchemaProvider deducedSchemaProvider;
+ if (deduceSchemaSame) {
+ deducedSchemaProvider = inputBatchSchemaProvider;
+ } else {
+ deducedSchemaProvider = getSchemaProvider("deduced", false);
+ }
+ doReturn(deducedSchemaProvider).when(spy).getDeducedSchemaProvider(any(),
any(), any());
+
+ //run the method we are unit testing:
+ spy.fetchNextBatchFromSource(Option.empty(),
mock(HoodieTableMetaClient.class));
+
+ //make sure getDeducedSchemaProvider is always called once
+ verify(spy, times(1)).getDeducedSchemaProvider(any(), any(), any());
+
+ //make sure we use error table when we should
+ //
+ //When should we use error table?
+ // - error table enabled obviously: hasErrorTable
+ // - row writer disabled (not implemented yet): !useRowWriter
+ // - if there is a transformer: hasTransformer
+ // - if schema provider is present and the target schema is non null:
!nullTargetSchema && hasSchemaProvider
+ // - if there is no transformer: !hasTransformer
+ // - if the deduced schema is different than the schema of the input
batch: !deduceSchemaSame
+ verify(propsSpy, hasErrorTable && !useRowWriter
Review Comment:
fixed
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