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Original file line number Diff line number Diff line change
Expand Up @@ -151,6 +151,11 @@ public abstract class AbstractHoodieLogRecordReader {
// Use scanV2 method.
private boolean useScanV2;

private Option<String[]> partitionFields;
private Option<String[]> partitionValues;
private boolean dropPartitions = false;
private boolean hiveStylePartition = false;

protected AbstractHoodieLogRecordReader(FileSystem fs, String basePath, List<String> logFilePaths,
Schema readerSchema,
String latestInstantTime, boolean readBlocksLazily, boolean reverseReader,
Expand All @@ -172,6 +177,9 @@ protected AbstractHoodieLogRecordReader(FileSystem fs, String basePath, List<Str
HoodieTableConfig tableConfig = this.hoodieTableMetaClient.getTableConfig();
this.payloadClassFQN = tableConfig.getPayloadClass();
this.preCombineField = tableConfig.getPreCombineField();
this.dropPartitions = tableConfig.getBooleanOrDefault(HoodieTableConfig.DROP_PARTITION_COLUMNS);
this.partitionFields = tableConfig.getPartitionFields();
this.hiveStylePartition = tableConfig.getBooleanOrDefault(HoodieTableConfig.HIVE_STYLE_PARTITIONING_ENABLE);
if (this.preCombineField != null) {
this.payloadProps.setProperty(HoodiePayloadProps.PAYLOAD_ORDERING_FIELD_PROP_KEY, this.preCombineField);
}
Expand All @@ -195,6 +203,24 @@ protected AbstractHoodieLogRecordReader(FileSystem fs, String basePath, List<Str
Pair.of(tableConfig.getRecordKeyFieldProp(), tableConfig.getPartitionFieldProp()));
}
this.partitionName = partitionName;
this.partitionValues = getPartitionValues();

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It's not a good practice to call non-static methods from the ctor, since it relies implicitly on the ordering of the initialization. Let's instead make this method static and pass it all values it needs.

}

private Option<String[]> getPartitionValues() {
if (!this.partitionName.isPresent()) {
return Option.empty();
}

String[] partitionValues = this.partitionName.get().split("/");
if (this.hiveStylePartition) {
return Option.of(Arrays.stream(partitionValues)
.map(partition -> partition.split("="))
.filter(partition -> partition.length == 2)

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Why do we filter on specific length here?

.map(partition -> partition[1])
.toArray(String[]::new));
} else {
return Option.of(partitionValues);
}
}

protected String getKeyField() {
Expand Down Expand Up @@ -632,6 +658,19 @@ private void processDataBlock(HoodieDataBlock dataBlock, Option<KeySpec> keySpec
while (recordIterator.hasNext()) {
IndexedRecord currentRecord = recordIterator.next();
IndexedRecord record = schemaOption.isPresent() ? HoodieAvroUtils.rewriteRecordWithNewSchema(currentRecord, schemaOption.get(), Collections.emptyMap()) : currentRecord;

Schema schema = record.getSchema();
if (this.dropPartitions && this.partitionFields.isPresent() && this.partitionValues.isPresent()) {
String[] partitionFields = this.partitionFields.get();
String[] partitionValues = this.partitionValues.get();

if (partitionFields.length == partitionValues.length) {

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This condition should be asserted on during init

for (int i = 0; i < partitionValues.length; i++) {
record.put(schema.getField(partitionFields[i]).pos(), partitionValues[i]);

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We can't just blindly inject strings into record, we need to make sure we coercing it to a type of the column

}
}
}

processNextRecord(createHoodieRecord(record, this.hoodieTableMetaClient.getTableConfig(), this.payloadClassFQN,
this.preCombineField, this.withOperationField, this.simpleKeyGenFields, this.partitionName));
totalLogRecords.incrementAndGet();
Expand Down
Original file line number Diff line number Diff line change
@@ -0,0 +1,197 @@
/*
* 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.common.functional;

import org.apache.hudi.avro.HoodieAvroUtils;
import org.apache.hudi.common.fs.FSUtils;
import org.apache.hudi.common.model.HoodieAvroPayload;
import org.apache.hudi.common.model.HoodieLogFile;
import org.apache.hudi.common.model.HoodieRecord;
import org.apache.hudi.common.model.HoodieTableType;
import org.apache.hudi.common.table.HoodieTableConfig;
import org.apache.hudi.common.table.log.HoodieLogFormat;
import org.apache.hudi.common.table.log.HoodieMergedLogRecordScanner;
import org.apache.hudi.common.table.log.block.HoodieAvroDataBlock;
import org.apache.hudi.common.table.log.block.HoodieDataBlock;
import org.apache.hudi.common.table.log.block.HoodieLogBlock;
import org.apache.hudi.common.testutils.FileCreateUtils;
import org.apache.hudi.common.testutils.HoodieTestUtils;
import org.apache.hudi.common.testutils.SchemaTestUtil;

import org.apache.avro.Schema;
import org.apache.avro.generic.GenericRecord;
import org.apache.avro.generic.IndexedRecord;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.FileSystem;
import org.apache.hadoop.fs.FileUtil;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.hdfs.DFSConfigKeys;
import org.apache.hadoop.hdfs.MiniDFSCluster;
import org.junit.jupiter.api.AfterAll;
import org.junit.jupiter.api.AfterEach;
import org.junit.jupiter.api.BeforeAll;
import org.junit.jupiter.api.BeforeEach;
import org.junit.jupiter.api.Test;

import java.io.File;
import java.io.IOException;
import java.net.URISyntaxException;
import java.util.ArrayList;
import java.util.HashMap;
import java.util.HashSet;
import java.util.List;
import java.util.Map;
import java.util.Properties;
import java.util.Set;
import java.util.UUID;
import java.util.stream.Collectors;

import static org.apache.hudi.common.testutils.SchemaTestUtil.getSimpleSchema;
import static org.apache.hudi.common.util.collection.ExternalSpillableMap.DiskMapType.BITCASK;
import static org.junit.jupiter.api.Assertions.assertEquals;

public class TestHoodieLogRecordReader {

private static File dfsBaseDir;
private static MiniDFSCluster cluster;

private FileSystem fs;
private String basePath;
private Path partitionPath;
private String partitionValue = "my_partition";
private String partitionName = "partition";

@BeforeAll
public static void setUpClass() throws IOException, InterruptedException {
dfsBaseDir = new File("/tmp/" + UUID.randomUUID().toString());
FileUtil.fullyDelete(dfsBaseDir);
// Append is not supported in LocalFileSystem. HDFS needs to be setup.
Configuration conf = new Configuration();
// lower heartbeat interval for fast recognition of DN
conf.set(MiniDFSCluster.HDFS_MINIDFS_BASEDIR, dfsBaseDir.getAbsolutePath());

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I don't think we really need HDFS for this test. What's the idea behind doing it on HDFS?

conf.setInt(DFSConfigKeys.DFS_NAMENODE_HEARTBEAT_RECHECK_INTERVAL_KEY, 1000);
conf.setInt(DFSConfigKeys.DFS_HEARTBEAT_INTERVAL_KEY, 1);
conf.setInt(DFSConfigKeys.DFS_CLIENT_SOCKET_TIMEOUT_KEY, 3000);
cluster = new MiniDFSCluster.Builder(conf).checkExitOnShutdown(true).numDataNodes(4).build();
}

@AfterAll
public static void tearDownClass() {
cluster.shutdown(true);
FileUtil.fullyDelete(dfsBaseDir);
}

@BeforeEach
public void setUp() throws IOException, InterruptedException {
this.fs = cluster.getFileSystem();

this.partitionPath = new Path(dfsBaseDir.toString(), partitionValue);
this.basePath = dfsBaseDir.toString();
}

@AfterEach
public void tearDown() throws IOException {
fs.delete(partitionPath, true);
}

@Test
public void testLogRecordReaderExtractPartitionFromPath() throws IOException, URISyntaxException, InterruptedException {

Properties properties = new Properties();
properties.setProperty(HoodieTableConfig.DROP_PARTITION_COLUMNS.key(), "true");
properties.setProperty(HoodieTableConfig.PARTITION_FIELDS.key(), partitionName);
HoodieTestUtils.init(fs.getConf(), basePath, HoodieTableType.MERGE_ON_READ, properties);

Schema schema = HoodieAvroUtils.addMetadataFields(getSimpleSchema());
HoodieLogFormat.Writer writer =
HoodieLogFormat.newWriterBuilder().onParentPath(partitionPath).withFileExtension(HoodieLogFile.DELTA_EXTENSION)
.withFileId("test-fileid1").overBaseCommit("100").withFs(fs).withSizeThreshold(500).build();
// Write 1
List<IndexedRecord> records1 = SchemaTestUtil.generateHoodieTestRecords(0, 100);
List<IndexedRecord> copyOfRecords1 = records1.stream()
.map(record -> HoodieAvroUtils.rewriteRecord((GenericRecord) record, schema)).collect(Collectors.toList());

Map<HoodieLogBlock.HeaderMetadataType, String> header = new HashMap<>();
header.put(HoodieLogBlock.HeaderMetadataType.INSTANT_TIME, "100");
header.put(HoodieLogBlock.HeaderMetadataType.SCHEMA, schema.toString());
HoodieDataBlock dataBlock = new HoodieAvroDataBlock(records1, header, HoodieRecord.RECORD_KEY_METADATA_FIELD);
writer.appendBlock(dataBlock);

// Write 2
List<IndexedRecord> records2 = SchemaTestUtil.generateHoodieTestRecords(0, 100);
List<IndexedRecord> copyOfRecords2 = records2.stream()
.map(record -> HoodieAvroUtils.rewriteRecord((GenericRecord) record, schema)).collect(Collectors.toList());
header.put(HoodieLogBlock.HeaderMetadataType.SCHEMA, schema.toString());
dataBlock = new HoodieAvroDataBlock(records2, header, HoodieRecord.RECORD_KEY_METADATA_FIELD);
writer.appendBlock(dataBlock);
writer.close();

List<String> allLogFiles =
FSUtils.getAllLogFiles(fs, partitionPath, "test-fileid1", HoodieLogFile.DELTA_EXTENSION, "100")
.map(s -> s.getPath().toString()).collect(Collectors.toList());

FileCreateUtils.createDeltaCommit(basePath, "100", fs);

// generate reader schema
List<Schema.Field> fields = new ArrayList<>();
fields.add(new Schema.Field(partitionName, Schema.create(Schema.Type.STRING), null, ""));
for (Schema.Field field : schema.getFields()) {
Schema.Field newField = new Schema.Field(field.name(), field.schema(), field.doc(), field.defaultVal());
for (Map.Entry<String, Object> prop : field.getObjectProps().entrySet()) {
newField.addProp(prop.getKey(), prop.getValue());
}
fields.add(newField);
}
Schema readerSchema = Schema.createRecord(schema.getName(), schema.getDoc(), schema.getNamespace(), false);
readerSchema.setFields(fields);

HoodieMergedLogRecordScanner scanner = HoodieMergedLogRecordScanner.newBuilder()
.withFileSystem(fs)
.withBasePath(basePath)
.withLogFilePaths(allLogFiles)
.withReaderSchema(readerSchema)
.withLatestInstantTime("102")
.withMaxMemorySizeInBytes(10240L)
.withReverseReader(false)
.withBufferSize(4096)
.withDiskMapType(BITCASK)
.withPartition(partitionValue)
.build();
assertEquals(200, scanner.getTotalLogRecords());
Set<String> readKeys = new HashSet<>(200);
scanner.forEach(s -> {
readKeys.add(s.getKey().getRecordKey());
try {
IndexedRecord record = ((HoodieAvroPayload)s.getData()).getInsertValue(readerSchema, new Properties()).get();
String partition = record.get(record.getSchema().getField(partitionName).pos()).toString();
// The value of field "partition" should be "my_partition" passed to scanner
assertEquals(partitionValue, partition);
} catch (IOException e) {
throw new RuntimeException(e);
}
});

assertEquals(200, readKeys.size(), "Stream collect should return all 200 records");
copyOfRecords1.addAll(copyOfRecords2);
Set<String> originalKeys =
copyOfRecords1.stream().map(s -> ((GenericRecord) s).get(HoodieRecord.RECORD_KEY_METADATA_FIELD).toString())
.collect(Collectors.toSet());
assertEquals(originalKeys, readKeys, "CompositeAvroLogReader should return 200 records from 2 versions");
}
}