[HUDI-1332] Introduce FlinkHoodieBloomIndex to hudi-flink-client (#2375)

* [HUDI] Add bloom index for hudi-flink-client

Co-authored-by: yangxiang <yangxiang@oppo.com>

hudi-client/hudi-flink-client/src/main/java/org/apache/hudi/index/FlinkHoodieIndex.java

@@ -29,6 +29,7 @@ import org.apache.hudi.common.util.ReflectionUtils;
 import org.apache.hudi.common.util.StringUtils;
 import org.apache.hudi.config.HoodieWriteConfig;
 import org.apache.hudi.exception.HoodieIndexException;
+import org.apache.hudi.index.bloom.FlinkHoodieBloomIndex;
 import org.apache.hudi.index.state.FlinkInMemoryStateIndex;
 import org.apache.hudi.PublicAPIMethod;
 import org.apache.hudi.table.HoodieTable;
@@ -58,6 +59,8 @@ public abstract class FlinkHoodieIndex<T extends HoodieRecordPayload> extends Ho
     switch (config.getIndexType()) {
       case INMEMORY:
         return new FlinkInMemoryStateIndex<>(context, config);
+      case BLOOM:
+        return new FlinkHoodieBloomIndex(config);
       default:
         throw new HoodieIndexException("Unsupported index type " + config.getIndexType());
     }

hudi-client/hudi-flink-client/src/main/java/org/apache/hudi/index/bloom/FlinkHoodieBloomIndex.java

@@ -0,0 +1,267 @@
+/*
+ * 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.index.bloom;
+
+import org.apache.hudi.client.WriteStatus;
+import org.apache.hudi.common.engine.HoodieEngineContext;
+import org.apache.hudi.common.model.HoodieKey;
+import org.apache.hudi.common.model.HoodieRecord;
+import org.apache.hudi.common.model.HoodieRecordLocation;
+import org.apache.hudi.common.model.HoodieRecordPayload;
+import org.apache.hudi.common.util.Option;
+import org.apache.hudi.common.util.collection.Pair;
+import org.apache.hudi.config.HoodieWriteConfig;
+import org.apache.hudi.exception.MetadataNotFoundException;
+import org.apache.hudi.index.FlinkHoodieIndex;
+import org.apache.hudi.index.HoodieIndexUtils;
+import org.apache.hudi.io.HoodieKeyLookupHandle;
+import org.apache.hudi.io.HoodieRangeInfoHandle;
+import org.apache.hudi.table.HoodieTable;
+
+import org.apache.log4j.LogManager;
+import org.apache.log4j.Logger;
+import com.beust.jcommander.internal.Lists;
+
+import java.util.ArrayList;
+import java.util.HashMap;
+import java.util.Iterator;
+import java.util.List;
+import java.util.Map;
+
+import scala.Tuple2;
+
+import static java.util.stream.Collectors.mapping;
+import static java.util.stream.Collectors.groupingBy;
+import static java.util.stream.Collectors.toList;
+import static org.apache.hudi.index.HoodieIndexUtils.getLatestBaseFilesForAllPartitions;
+
+/**
+ * Indexing mechanism based on bloom filter. Each parquet file includes its row_key bloom filter in its metadata.
+ */
+@SuppressWarnings("checkstyle:LineLength")
+public class FlinkHoodieBloomIndex<T extends HoodieRecordPayload> extends FlinkHoodieIndex<T> {
+
+  private static final Logger LOG = LogManager.getLogger(FlinkHoodieBloomIndex.class);
+
+  public FlinkHoodieBloomIndex(HoodieWriteConfig config) {
+    super(config);
+  }
+
+  @Override
+  public List<HoodieRecord<T>> tagLocation(List<HoodieRecord<T>> records, HoodieEngineContext context,
+                                           HoodieTable<T, List<HoodieRecord<T>>, List<HoodieKey>, List<WriteStatus>> hoodieTable) {
+    // Step 1: Extract out thinner Map of (partitionPath, recordKey)
+    Map<String, List<String>> partitionRecordKeyMap = new HashMap<>();
+    records.forEach(record -> {
+      if (partitionRecordKeyMap.containsKey(record.getPartitionPath())) {
+        partitionRecordKeyMap.get(record.getPartitionPath()).add(record.getRecordKey());
+      } else {
+        List<String> recordKeys = Lists.newArrayList();
+        recordKeys.add(record.getRecordKey());
+        partitionRecordKeyMap.put(record.getPartitionPath(), recordKeys);
+      }
+    });
+
+    // Step 2: Lookup indexes for all the partition/recordkey pair
+    Map<HoodieKey, HoodieRecordLocation> keyFilenamePairMap =
+        lookupIndex(partitionRecordKeyMap, context, hoodieTable);
+
+    if (LOG.isDebugEnabled()) {
+      long totalTaggedRecords = keyFilenamePairMap.values().size();
+      LOG.debug("Number of update records (ones tagged with a fileID): " + totalTaggedRecords);
+    }
+
+    // Step 3: Tag the incoming records, as inserts or updates, by joining with existing record keys
+    List<HoodieRecord<T>> taggedRecords = tagLocationBacktoRecords(keyFilenamePairMap, records);
+
+    return taggedRecords;
+  }
+
+  /**
+   * Lookup the location for each record key and return the pair<record_key,location> for all record keys already
+   * present and drop the record keys if not present.
+   */
+  private Map<HoodieKey, HoodieRecordLocation> lookupIndex(
+      Map<String, List<String>> partitionRecordKeyMap, final HoodieEngineContext context,
+      final HoodieTable hoodieTable) {
+    // Obtain records per partition, in the incoming records
+    Map<String, Long> recordsPerPartition = new HashMap<>();
+    partitionRecordKeyMap.keySet().forEach(k -> recordsPerPartition.put(k, Long.valueOf(partitionRecordKeyMap.get(k).size())));
+    List<String> affectedPartitionPathList = new ArrayList<>(recordsPerPartition.keySet());
+
+    // Step 2: Load all involved files as <Partition, filename> pairs
+    List<Tuple2<String, BloomIndexFileInfo>> fileInfoList =
+        loadInvolvedFiles(affectedPartitionPathList, context, hoodieTable);
+    final Map<String, List<BloomIndexFileInfo>> partitionToFileInfo =
+        fileInfoList.stream().collect(groupingBy(Tuple2::_1, mapping(Tuple2::_2, toList())));
+
+    // Step 3: Obtain a List, for each incoming record, that already exists, with the file id,
+    // that contains it.
+    List<Tuple2<String, HoodieKey>> fileComparisons =
+            explodeRecordsWithFileComparisons(partitionToFileInfo, partitionRecordKeyMap);
+    return findMatchingFilesForRecordKeys(fileComparisons, hoodieTable);
+  }
+
+  /**
+   * Load all involved files as <Partition, filename> pair List.
+   */
+  //TODO duplicate code with spark, we can optimize this method later
+  List<Tuple2<String, BloomIndexFileInfo>> loadInvolvedFiles(List<String> partitions, final HoodieEngineContext context,
+                                                             final HoodieTable hoodieTable) {
+    // Obtain the latest data files from all the partitions.
+    List<Pair<String, String>> partitionPathFileIDList = getLatestBaseFilesForAllPartitions(partitions, context, hoodieTable).stream()
+        .map(pair -> Pair.of(pair.getKey(), pair.getValue().getFileId()))
+        .collect(toList());
+
+    if (config.getBloomIndexPruneByRanges()) {
+      // also obtain file ranges, if range pruning is enabled
+      context.setJobStatus(this.getClass().getName(), "Obtain key ranges for file slices (range pruning=on)");
+      return context.map(partitionPathFileIDList, pf -> {
+        try {
+          HoodieRangeInfoHandle rangeInfoHandle = new HoodieRangeInfoHandle(config, hoodieTable, pf);
+          String[] minMaxKeys = rangeInfoHandle.getMinMaxKeys();
+          return new Tuple2<>(pf.getKey(), new BloomIndexFileInfo(pf.getValue(), minMaxKeys[0], minMaxKeys[1]));
+        } catch (MetadataNotFoundException me) {
+          LOG.warn("Unable to find range metadata in file :" + pf);
+          return new Tuple2<>(pf.getKey(), new BloomIndexFileInfo(pf.getValue()));
+        }
+      }, Math.max(partitionPathFileIDList.size(), 1));
+    } else {
+      return partitionPathFileIDList.stream()
+          .map(pf -> new Tuple2<>(pf.getKey(), new BloomIndexFileInfo(pf.getValue()))).collect(toList());
+    }
+  }
+
+  @Override
+  public boolean rollbackCommit(String instantTime) {
+    // Nope, don't need to do anything.
+    return true;
+  }
+
+  /**
+   * This is not global, since we depend on the partitionPath to do the lookup.
+   */
+  @Override
+  public boolean isGlobal() {
+    return false;
+  }
+
+  /**
+   * No indexes into log files yet.
+   */
+  @Override
+  public boolean canIndexLogFiles() {
+    return false;
+  }
+
+  /**
+   * Bloom filters are stored, into the same data files.
+   */
+  @Override
+  public boolean isImplicitWithStorage() {
+    return true;
+  }
+
+  /**
+   * For each incoming record, produce N output records, 1 each for each file against which the record's key needs to be
+   * checked. For tables, where the keys have a definite insert order (e.g: timestamp as prefix), the number of files
+   * to be compared gets cut down a lot from range pruning.
+   * <p>
+   * Sub-partition to ensure the records can be looked up against files & also prune file<=>record comparisons based on
+   * recordKey ranges in the index info.
+   */
+  List<Tuple2<String, HoodieKey>> explodeRecordsWithFileComparisons(
+      final Map<String, List<BloomIndexFileInfo>> partitionToFileIndexInfo,
+      Map<String, List<String>> partitionRecordKeyMap) {
+    IndexFileFilter indexFileFilter =
+        config.useBloomIndexTreebasedFilter() ? new IntervalTreeBasedIndexFileFilter(partitionToFileIndexInfo)
+            : new ListBasedIndexFileFilter(partitionToFileIndexInfo);
+
+    List<Tuple2<String, HoodieKey>> fileRecordPairs = new ArrayList<>();
+    partitionRecordKeyMap.keySet().forEach(partitionPath ->  {
+      List<String> hoodieRecordKeys = partitionRecordKeyMap.get(partitionPath);
+      hoodieRecordKeys.forEach(hoodieRecordKey -> {
+        indexFileFilter.getMatchingFilesAndPartition(partitionPath, hoodieRecordKey).forEach(partitionFileIdPair -> {
+          fileRecordPairs.add(new Tuple2<>(partitionFileIdPair.getRight(),
+                  new HoodieKey(hoodieRecordKey, partitionPath)));
+        });
+      });
+    });
+    return fileRecordPairs;
+  }
+
+  /**
+   * Find out <RowKey, filename> pair.
+   */
+  Map<HoodieKey, HoodieRecordLocation> findMatchingFilesForRecordKeys(
+      List<Tuple2<String, HoodieKey>> fileComparisons,
+      HoodieTable hoodieTable) {
+
+    fileComparisons = fileComparisons.stream().sorted((o1, o2) -> o1._1.compareTo(o2._1)).collect(toList());
+
+    List<HoodieKeyLookupHandle.KeyLookupResult> keyLookupResults = new ArrayList<>();
+
+    Iterator<List<HoodieKeyLookupHandle.KeyLookupResult>> iterator = new HoodieFlinkBloomIndexCheckFunction(hoodieTable, config).apply(fileComparisons.iterator());
+    while (iterator.hasNext()) {
+      keyLookupResults.addAll(iterator.next());
+    }
+
+    Map<HoodieKey, HoodieRecordLocation> hoodieRecordLocationMap = new HashMap<>();
+
+    keyLookupResults = keyLookupResults.stream().filter(lr -> lr.getMatchingRecordKeys().size() > 0).collect(toList());
+    keyLookupResults.forEach(lookupResult -> {
+      lookupResult.getMatchingRecordKeys().forEach(r -> {
+        hoodieRecordLocationMap.put(new HoodieKey(r, lookupResult.getPartitionPath()), new HoodieRecordLocation(lookupResult.getBaseInstantTime(), lookupResult.getFileId()));
+      });
+    });
+
+    return hoodieRecordLocationMap;
+  }
+
+
+  /**
+   * Tag the <rowKey, filename> back to the original HoodieRecord List.
+   */
+  protected List<HoodieRecord<T>> tagLocationBacktoRecords(
+          Map<HoodieKey, HoodieRecordLocation> keyFilenamePair, List<HoodieRecord<T>> records) {
+    Map<HoodieKey, HoodieRecord<T>> keyRecordPairMap = new HashMap<>();
+    records.forEach(r -> keyRecordPairMap.put(r.getKey(), r));
+    // Here as the record might have more data than rowKey (some rowKeys' fileId is null),
+    // so we do left outer join.
+    List<Tuple2<HoodieRecord<T>, HoodieRecordLocation>> newList = new ArrayList<>();
+    keyRecordPairMap.keySet().forEach(k -> {
+      if (keyFilenamePair.containsKey(k)) {
+        newList.add(new Tuple2(keyRecordPairMap.get(k), keyFilenamePair.get(k)));
+      } else {
+        newList.add(new Tuple2(keyRecordPairMap.get(k), null));
+      }
+    });
+    List<HoodieRecord<T>> res = Lists.newArrayList();
+    for (Tuple2<HoodieRecord<T>, HoodieRecordLocation> v : newList) {
+      res.add(HoodieIndexUtils.getTaggedRecord(v._1, Option.ofNullable(v._2)));
+    }
+    return res;
+  }
+
+  @Override
+  public List<WriteStatus> updateLocation(List<WriteStatus> writeStatusList, HoodieEngineContext context,
+                                          HoodieTable<T, List<HoodieRecord<T>>, List<HoodieKey>, List<WriteStatus>> hoodieTable) {
+    return writeStatusList;
+  }
+}

hudi-client/hudi-flink-client/src/main/java/org/apache/hudi/index/bloom/HoodieFlinkBloomIndexCheckFunction.java

@@ -0,0 +1,127 @@
+/*
+ * 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.index.bloom;
+
+import org.apache.hudi.client.utils.LazyIterableIterator;
+import org.apache.hudi.common.model.HoodieKey;
+import org.apache.hudi.common.util.collection.Pair;
+import org.apache.hudi.config.HoodieWriteConfig;
+import org.apache.hudi.exception.HoodieException;
+import org.apache.hudi.exception.HoodieIndexException;
+import org.apache.hudi.io.HoodieKeyLookupHandle;
+import org.apache.hudi.io.HoodieKeyLookupHandle.KeyLookupResult;
+import org.apache.hudi.table.HoodieTable;
+
+import java.util.function.Function;
+import java.util.ArrayList;
+import java.util.Iterator;
+import java.util.List;
+
+import scala.Tuple2;
+
+/**
+ * Function performing actual checking of list containing (fileId, hoodieKeys) against the actual files.
+ */
+//TODO we can move this class into the hudi-client-common and reuse it for spark client
+public class HoodieFlinkBloomIndexCheckFunction
+        implements Function<Iterator<Tuple2<String, HoodieKey>>, Iterator<List<KeyLookupResult>>> {
+
+  private final HoodieTable hoodieTable;
+
+  private final HoodieWriteConfig config;
+
+  public HoodieFlinkBloomIndexCheckFunction(HoodieTable hoodieTable, HoodieWriteConfig config) {
+    this.hoodieTable = hoodieTable;
+    this.config = config;
+  }
+
+  @Override
+  public Iterator<List<KeyLookupResult>> apply(Iterator<Tuple2<String, HoodieKey>> fileParitionRecordKeyTripletItr) {
+    return new LazyKeyCheckIterator(fileParitionRecordKeyTripletItr);
+  }
+
+  @Override
+  public <V> Function<V, Iterator<List<KeyLookupResult>>> compose(Function<? super V, ? extends Iterator<Tuple2<String, HoodieKey>>> before) {
+    return null;
+  }
+
+  @Override
+  public <V> Function<Iterator<Tuple2<String, HoodieKey>>, V> andThen(Function<? super Iterator<List<KeyLookupResult>>, ? extends V> after) {
+    return null;
+  }
+
+  class LazyKeyCheckIterator extends LazyIterableIterator<Tuple2<String, HoodieKey>, List<KeyLookupResult>> {
+
+    private HoodieKeyLookupHandle keyLookupHandle;
+
+    LazyKeyCheckIterator(Iterator<Tuple2<String, HoodieKey>> filePartitionRecordKeyTripletItr) {
+      super(filePartitionRecordKeyTripletItr);
+    }
+
+    @Override
+    protected void start() {
+    }
+
+    @Override
+    protected List<KeyLookupResult> computeNext() {
+      List<KeyLookupResult> ret = new ArrayList<>();
+      try {
+        // process one file in each go.
+        while (inputItr.hasNext()) {
+          Tuple2<String, HoodieKey> currentTuple = inputItr.next();
+          String fileId = currentTuple._1;
+          String partitionPath = currentTuple._2.getPartitionPath();
+          String recordKey = currentTuple._2.getRecordKey();
+          Pair<String, String> partitionPathFilePair = Pair.of(partitionPath, fileId);
+
+          // lazily init state
+          if (keyLookupHandle == null) {
+            keyLookupHandle = new HoodieKeyLookupHandle(config, hoodieTable, partitionPathFilePair);
+          }
+
+          // if continue on current file
+          if (keyLookupHandle.getPartitionPathFilePair().equals(partitionPathFilePair)) {
+            keyLookupHandle.addKey(recordKey);
+          } else {
+            // do the actual checking of file & break out
+            ret.add(keyLookupHandle.getLookupResult());
+            keyLookupHandle = new HoodieKeyLookupHandle(config, hoodieTable, partitionPathFilePair);
+            keyLookupHandle.addKey(recordKey);
+            break;
+          }
+        }
+
+        // handle case, where we ran out of input, close pending work, update return val
+        if (!inputItr.hasNext()) {
+          ret.add(keyLookupHandle.getLookupResult());
+        }
+      } catch (Throwable e) {
+        if (e instanceof HoodieException) {
+          throw e;
+        }
+        throw new HoodieIndexException("Error checking bloom filter index. ", e);
+      }
+      return ret;
+    }
+
+    @Override
+    protected void end() {
+    }
+  }
+}

hudi-client/hudi-flink-client/src/main/resources/log4j-surefire.properties

@@ -0,0 +1,31 @@
+###
+# 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.
+###
+log4j.rootLogger=WARN, CONSOLE
+log4j.logger.org.apache=INFO
+log4j.logger.org.apache.hudi=DEBUG
+log4j.logger.org.apache.hadoop.hbase=ERROR
+
+# A1 is set to be a ConsoleAppender.
+log4j.appender.CONSOLE=org.apache.log4j.ConsoleAppender
+# A1 uses PatternLayout.
+log4j.appender.CONSOLE.layout=org.apache.log4j.PatternLayout
+log4j.appender.CONSOLE.layout.ConversionPattern=%-4r [%t] %-5p %c %x - %m%n
+log4j.appender.CONSOLE.filter.a=org.apache.log4j.varia.LevelRangeFilter
+log4j.appender.CONSOLE.filter.a.AcceptOnMatch=true
+log4j.appender.CONSOLE.filter.a.LevelMin=WARN
+log4j.appender.CONSOLE.filter.a.LevelMax=FATAL

hudi-client/hudi-flink-client/src/test/java/org/apache/hudi/index/bloom/TestFlinkHoodieBloomIndex.java

@@ -0,0 +1,469 @@
+/*
+ * 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.index.bloom;
+
+import org.apache.hudi.common.bloom.BloomFilter;
+import org.apache.hudi.common.bloom.BloomFilterFactory;
+import org.apache.hudi.common.bloom.BloomFilterTypeCode;
+import org.apache.hudi.common.model.HoodieKey;
+import org.apache.hudi.common.model.HoodieRecord;
+import org.apache.hudi.common.table.HoodieTableMetaClient;
+import org.apache.hudi.common.testutils.RawTripTestPayload;
+import org.apache.hudi.common.util.Option;
+import org.apache.hudi.common.util.collection.Pair;
+import org.apache.hudi.config.HoodieIndexConfig;
+import org.apache.hudi.config.HoodieWriteConfig;
+import org.apache.hudi.io.HoodieKeyLookupHandle;
+import org.apache.hudi.table.HoodieFlinkTable;
+import org.apache.hudi.table.HoodieTable;
+import org.apache.hudi.testutils.HoodieFlinkClientTestHarness;
+import org.apache.hudi.testutils.HoodieFlinkWriteableTestTable;
+
+import org.apache.avro.Schema;
+import org.apache.hadoop.fs.Path;
+import org.junit.jupiter.api.AfterEach;
+import org.junit.jupiter.api.BeforeEach;
+import org.junit.jupiter.api.Test;
+import org.junit.jupiter.params.ParameterizedTest;
+import org.junit.jupiter.params.provider.Arguments;
+import org.junit.jupiter.params.provider.MethodSource;
+
+import java.util.ArrayList;
+import java.util.HashMap;
+import java.util.List;
+import java.util.Map;
+import java.util.stream.Stream;
+
+import scala.Tuple2;
+
+import static java.util.Arrays.asList;
+import static java.util.UUID.randomUUID;
+import static org.apache.hudi.common.testutils.SchemaTestUtil.getSchemaFromResource;
+import static org.junit.jupiter.api.Assertions.assertDoesNotThrow;
+import static org.junit.jupiter.api.Assertions.assertEquals;
+import static org.junit.jupiter.api.Assertions.assertFalse;
+import static org.junit.jupiter.api.Assertions.assertNotNull;
+import static org.junit.jupiter.api.Assertions.assertNull;
+import static org.junit.jupiter.api.Assertions.assertTrue;
+
+/**
+ * Unit test against FlinkHoodieBloomIndex.
+ */
+//TODO merge code with Spark Bloom index tests.
+public class TestFlinkHoodieBloomIndex extends HoodieFlinkClientTestHarness {
+
+  private static final Schema SCHEMA = getSchemaFromResource(TestFlinkHoodieBloomIndex.class, "/exampleSchema.avsc", true);
+  private static final String TEST_NAME_WITH_PARAMS = "[{index}] Test with rangePruning={0}, treeFiltering={1}, bucketizedChecking={2}";
+
+  public static Stream<Arguments> configParams() {
+    Object[][] data =
+        new Object[][] {{true, true, true}, {false, true, true}, {true, true, false}, {true, false, true}};
+    return Stream.of(data).map(Arguments::of);
+  }
+
+  @BeforeEach
+  public void setUp() throws Exception {
+    initPath();
+    initFileSystem();
+    // We have some records to be tagged (two different partitions)
+    initMetaClient();
+  }
+
+  @AfterEach
+  public void tearDown() throws Exception {
+    cleanupResources();
+  }
+
+  private HoodieWriteConfig makeConfig(boolean rangePruning, boolean treeFiltering, boolean bucketizedChecking) {
+    return HoodieWriteConfig.newBuilder().withPath(basePath)
+        .withIndexConfig(HoodieIndexConfig.newBuilder().bloomIndexPruneByRanges(rangePruning)
+            .bloomIndexTreebasedFilter(treeFiltering).bloomIndexBucketizedChecking(bucketizedChecking)
+            .bloomIndexKeysPerBucket(2).build())
+        .build();
+  }
+
+  @ParameterizedTest(name = TEST_NAME_WITH_PARAMS)
+  @MethodSource("configParams")
+  public void testLoadInvolvedFiles(boolean rangePruning, boolean treeFiltering, boolean bucketizedChecking) throws Exception {
+    HoodieWriteConfig config = makeConfig(rangePruning, treeFiltering, bucketizedChecking);
+    FlinkHoodieBloomIndex index = new FlinkHoodieBloomIndex(config);
+    HoodieTable hoodieTable = HoodieFlinkTable.create(config, context, metaClient);
+    HoodieFlinkWriteableTestTable testTable = HoodieFlinkWriteableTestTable.of(hoodieTable, SCHEMA);
+
+    // Create some partitions, and put some files
+    // "2016/01/21": 0 file
+    // "2016/04/01": 1 file (2_0_20160401010101.parquet)
+    // "2015/03/12": 3 files (1_0_20150312101010.parquet, 3_0_20150312101010.parquet, 4_0_20150312101010.parquet)
+    testTable.withPartitionMetaFiles("2016/01/21", "2016/04/01", "2015/03/12");
+
+    RawTripTestPayload rowChange1 =
+        new RawTripTestPayload("{\"_row_key\":\"000\",\"time\":\"2016-01-31T03:16:41.415Z\",\"number\":12}");
+    HoodieRecord record1 =
+        new HoodieRecord(new HoodieKey(rowChange1.getRowKey(), rowChange1.getPartitionPath()), rowChange1);
+    RawTripTestPayload rowChange2 =
+        new RawTripTestPayload("{\"_row_key\":\"001\",\"time\":\"2016-01-31T03:16:41.415Z\",\"number\":12}");
+    HoodieRecord record2 =
+        new HoodieRecord(new HoodieKey(rowChange2.getRowKey(), rowChange2.getPartitionPath()), rowChange2);
+    RawTripTestPayload rowChange3 =
+        new RawTripTestPayload("{\"_row_key\":\"002\",\"time\":\"2016-01-31T03:16:41.415Z\",\"number\":12}");
+    HoodieRecord record3 =
+        new HoodieRecord(new HoodieKey(rowChange3.getRowKey(), rowChange3.getPartitionPath()), rowChange3);
+    RawTripTestPayload rowChange4 =
+        new RawTripTestPayload("{\"_row_key\":\"003\",\"time\":\"2016-01-31T03:16:41.415Z\",\"number\":12}");
+    HoodieRecord record4 =
+        new HoodieRecord(new HoodieKey(rowChange4.getRowKey(), rowChange4.getPartitionPath()), rowChange4);
+
+    List<String> partitions = asList("2016/01/21", "2016/04/01", "2015/03/12");
+    List<Tuple2<String, BloomIndexFileInfo>> filesList = index.loadInvolvedFiles(partitions, context, hoodieTable);
+    // Still 0, as no valid commit
+    assertEquals(0, filesList.size());
+
+    testTable.addCommit("20160401010101").withInserts("2016/04/01", "2");
+    testTable.addCommit("20150312101010").withInserts("2015/03/12", "1")
+        .withInserts("2015/03/12", "3", record1)
+        .withInserts("2015/03/12", "4", record2, record3, record4);
+    metaClient.reloadActiveTimeline();
+
+    filesList = index.loadInvolvedFiles(partitions, context, hoodieTable);
+    assertEquals(4, filesList.size());
+
+    if (rangePruning) {
+      // these files will not have the key ranges
+      assertNull(filesList.get(0)._2().getMaxRecordKey());
+      assertNull(filesList.get(0)._2().getMinRecordKey());
+      assertFalse(filesList.get(1)._2().hasKeyRanges());
+      assertNotNull(filesList.get(2)._2().getMaxRecordKey());
+      assertNotNull(filesList.get(2)._2().getMinRecordKey());
+      assertTrue(filesList.get(3)._2().hasKeyRanges());
+
+      // no longer sorted, but should have same files.
+
+      List<Tuple2<String, BloomIndexFileInfo>> expected =
+          asList(new Tuple2<>("2016/04/01", new BloomIndexFileInfo("2")),
+              new Tuple2<>("2015/03/12", new BloomIndexFileInfo("1")),
+              new Tuple2<>("2015/03/12", new BloomIndexFileInfo("3", "000", "000")),
+              new Tuple2<>("2015/03/12", new BloomIndexFileInfo("4", "001", "003")));
+      assertEquals(expected, filesList);
+    }
+  }
+
+  @ParameterizedTest(name = TEST_NAME_WITH_PARAMS)
+  @MethodSource("configParams")
+  public void testRangePruning(boolean rangePruning, boolean treeFiltering, boolean bucketizedChecking) {
+    HoodieWriteConfig config = makeConfig(rangePruning, treeFiltering, bucketizedChecking);
+    FlinkHoodieBloomIndex index = new FlinkHoodieBloomIndex(config);
+
+    final Map<String, List<BloomIndexFileInfo>> partitionToFileIndexInfo = new HashMap<>();
+    partitionToFileIndexInfo.put("2017/10/22",
+        asList(new BloomIndexFileInfo("f1"), new BloomIndexFileInfo("f2", "000", "000"),
+            new BloomIndexFileInfo("f3", "001", "003"), new BloomIndexFileInfo("f4", "002", "007"),
+            new BloomIndexFileInfo("f5", "009", "010")));
+
+    Map<String, List<String>> partitionRecordKeyMap = new HashMap<>();
+    asList(new Tuple2<>("2017/10/22", "003"), new Tuple2<>("2017/10/22", "002"),
+            new Tuple2<>("2017/10/22", "005"), new Tuple2<>("2017/10/22", "004"))
+            .forEach(t -> {
+              List<String> recordKeyList = partitionRecordKeyMap.getOrDefault(t._1, new ArrayList<>());
+              recordKeyList.add(t._2);
+              partitionRecordKeyMap.put(t._1, recordKeyList);
+            });
+
+    List<scala.Tuple2<String, HoodieKey>> comparisonKeyList =
+        index.explodeRecordsWithFileComparisons(partitionToFileIndexInfo, partitionRecordKeyMap);
+
+    assertEquals(10, comparisonKeyList.size());
+    java.util.Map<String, List<String>> recordKeyToFileComps = comparisonKeyList.stream()
+        .collect(java.util.stream.Collectors.groupingBy(t -> t._2.getRecordKey(), java.util.stream.Collectors.mapping(t -> t._1, java.util.stream.Collectors.toList())));
+
+    assertEquals(4, recordKeyToFileComps.size());
+    assertEquals(new java.util.HashSet<>(asList("f1", "f3", "f4")), new java.util.HashSet<>(recordKeyToFileComps.get("002")));
+    assertEquals(new java.util.HashSet<>(asList("f1", "f3", "f4")), new java.util.HashSet<>(recordKeyToFileComps.get("003")));
+    assertEquals(new java.util.HashSet<>(asList("f1", "f4")), new java.util.HashSet<>(recordKeyToFileComps.get("004")));
+    assertEquals(new java.util.HashSet<>(asList("f1", "f4")), new java.util.HashSet<>(recordKeyToFileComps.get("005")));
+  }
+
+  @Test
+  public void testCheckUUIDsAgainstOneFile() throws Exception {
+    final String partition = "2016/01/31";
+    // Create some records to use
+    String recordStr1 = "{\"_row_key\":\"1eb5b87a-1feh-4edd-87b4-6ec96dc405a0\","
+        + "\"time\":\"2016-01-31T03:16:41.415Z\",\"number\":12}";
+    String recordStr2 = "{\"_row_key\":\"2eb5b87b-1feu-4edd-87b4-6ec96dc405a0\","
+        + "\"time\":\"2016-01-31T03:20:41.415Z\",\"number\":100}";
+    String recordStr3 = "{\"_row_key\":\"3eb5b87c-1fej-4edd-87b4-6ec96dc405a0\","
+        + "\"time\":\"2016-01-31T03:16:41.415Z\",\"number\":15}";
+    String recordStr4 = "{\"_row_key\":\"4eb5b87c-1fej-4edd-87b4-6ec96dc405a0\","
+        + "\"time\":\"2016-01-31T03:16:41.415Z\",\"number\":32}";
+    RawTripTestPayload rowChange1 = new RawTripTestPayload(recordStr1);
+    HoodieRecord record1 =
+        new HoodieRecord(new HoodieKey(rowChange1.getRowKey(), rowChange1.getPartitionPath()), rowChange1);
+    RawTripTestPayload rowChange2 = new RawTripTestPayload(recordStr2);
+    HoodieRecord record2 =
+        new HoodieRecord(new HoodieKey(rowChange2.getRowKey(), rowChange2.getPartitionPath()), rowChange2);
+    RawTripTestPayload rowChange3 = new RawTripTestPayload(recordStr3);
+    HoodieRecord record3 =
+        new HoodieRecord(new HoodieKey(rowChange3.getRowKey(), rowChange3.getPartitionPath()), rowChange3);
+    RawTripTestPayload rowChange4 = new RawTripTestPayload(recordStr4);
+    HoodieRecord record4 =
+        new HoodieRecord(new HoodieKey(rowChange4.getRowKey(), rowChange4.getPartitionPath()), rowChange4);
+
+    // We write record1, record2 to a parquet file, but the bloom filter contains (record1,
+    // record2, record3).
+    BloomFilter filter = BloomFilterFactory.createBloomFilter(10000, 0.0000001, -1, BloomFilterTypeCode.SIMPLE.name());
+    filter.add(record3.getRecordKey());
+    HoodieFlinkWriteableTestTable testTable = HoodieFlinkWriteableTestTable.of(metaClient, SCHEMA, filter);
+    String fileId = testTable.addCommit("000").getFileIdWithInserts(partition, record1, record2);
+    String filename = testTable.getBaseFileNameById(fileId);
+
+    // The bloom filter contains 3 records
+    assertTrue(filter.mightContain(record1.getRecordKey()));
+    assertTrue(filter.mightContain(record2.getRecordKey()));
+    assertTrue(filter.mightContain(record3.getRecordKey()));
+    assertFalse(filter.mightContain(record4.getRecordKey()));
+
+    // Compare with file
+    List<String> uuids = asList(record1.getRecordKey(), record2.getRecordKey(), record3.getRecordKey(), record4.getRecordKey());
+
+    HoodieWriteConfig config = HoodieWriteConfig.newBuilder().withPath(basePath).build();
+    HoodieFlinkTable table = HoodieFlinkTable.create(config, context, metaClient);
+    HoodieKeyLookupHandle keyHandle = new HoodieKeyLookupHandle<>(config, table, Pair.of(partition, fileId));
+    List<String> results = keyHandle.checkCandidatesAgainstFile(hadoopConf, uuids,
+        new Path(java.nio.file.Paths.get(basePath, partition, filename).toString()));
+    assertEquals(results.size(), 2);
+    assertTrue(results.get(0).equals("1eb5b87a-1feh-4edd-87b4-6ec96dc405a0")
+        || results.get(1).equals("1eb5b87a-1feh-4edd-87b4-6ec96dc405a0"));
+    assertTrue(results.get(0).equals("2eb5b87b-1feu-4edd-87b4-6ec96dc405a0")
+        || results.get(1).equals("2eb5b87b-1feu-4edd-87b4-6ec96dc405a0"));
+    // TODO(vc): Need more coverage on actual filenames
+    // assertTrue(results.get(0)._2().equals(filename));
+    // assertTrue(results.get(1)._2().equals(filename));
+  }
+
+  @ParameterizedTest(name = TEST_NAME_WITH_PARAMS)
+  @MethodSource("configParams")
+  public void testTagLocationWithEmptyList(boolean rangePruning, boolean treeFiltering, boolean bucketizedChecking) {
+    // We have some records to be tagged (two different partitions)
+    List<HoodieRecord> records = new ArrayList<>();
+    // Also create the metadata and config
+    HoodieWriteConfig config = makeConfig(rangePruning, treeFiltering, bucketizedChecking);
+    metaClient = HoodieTableMetaClient.reload(metaClient);
+    HoodieFlinkTable table = HoodieFlinkTable.create(config, context, metaClient);
+
+    // Let's tag
+    FlinkHoodieBloomIndex bloomIndex = new FlinkHoodieBloomIndex(config);
+
+    assertDoesNotThrow(() -> {
+      bloomIndex.tagLocation(records, context, table);
+    }, "EmptyList should not result in IllegalArgumentException: Positive number of slices required");
+  }
+
+  @ParameterizedTest(name = TEST_NAME_WITH_PARAMS)
+  @MethodSource("configParams")
+  public void testTagLocation(boolean rangePruning, boolean treeFiltering, boolean bucketizedChecking) throws Exception {
+    // We have some records to be tagged (two different partitions)
+    String rowKey1 = randomUUID().toString();
+    String rowKey2 = randomUUID().toString();
+    String rowKey3 = randomUUID().toString();
+    String recordStr1 = "{\"_row_key\":\"" + rowKey1 + "\",\"time\":\"2016-01-31T03:16:41.415Z\",\"number\":12}";
+    String recordStr2 = "{\"_row_key\":\"" + rowKey2 + "\",\"time\":\"2016-01-31T03:20:41.415Z\",\"number\":100}";
+    String recordStr3 = "{\"_row_key\":\"" + rowKey3 + "\",\"time\":\"2016-01-31T03:16:41.415Z\",\"number\":15}";
+    // place same row key under a different partition.
+    String recordStr4 = "{\"_row_key\":\"" + rowKey1 + "\",\"time\":\"2015-01-31T03:16:41.415Z\",\"number\":32}";
+    RawTripTestPayload rowChange1 = new RawTripTestPayload(recordStr1);
+    HoodieRecord record1 =
+        new HoodieRecord(new HoodieKey(rowChange1.getRowKey(), rowChange1.getPartitionPath()), rowChange1);
+    RawTripTestPayload rowChange2 = new RawTripTestPayload(recordStr2);
+    HoodieRecord record2 =
+        new HoodieRecord(new HoodieKey(rowChange2.getRowKey(), rowChange2.getPartitionPath()), rowChange2);
+    RawTripTestPayload rowChange3 = new RawTripTestPayload(recordStr3);
+    HoodieRecord record3 =
+        new HoodieRecord(new HoodieKey(rowChange3.getRowKey(), rowChange3.getPartitionPath()), rowChange3);
+    RawTripTestPayload rowChange4 = new RawTripTestPayload(recordStr4);
+    HoodieRecord record4 =
+        new HoodieRecord(new HoodieKey(rowChange4.getRowKey(), rowChange4.getPartitionPath()), rowChange4);
+    List<HoodieRecord> records = asList(record1, record2, record3, record4);
+
+    // Also create the metadata and config
+    HoodieWriteConfig config = makeConfig(rangePruning, treeFiltering, bucketizedChecking);
+    HoodieFlinkTable hoodieTable = HoodieFlinkTable.create(config, context, metaClient);
+    HoodieFlinkWriteableTestTable testTable = HoodieFlinkWriteableTestTable.of(hoodieTable, SCHEMA);
+
+    // Let's tag
+    FlinkHoodieBloomIndex bloomIndex = new FlinkHoodieBloomIndex(config);
+    List<HoodieRecord> taggedRecords = bloomIndex.tagLocation(records, context, hoodieTable);
+
+    // Should not find any files
+    for (HoodieRecord record : taggedRecords) {
+      assertFalse(record.isCurrentLocationKnown());
+    }
+
+    // We create three parquet file, each having one record. (two different partitions)
+    String fileId1 = testTable.addCommit("001").getFileIdWithInserts("2016/01/31", record1);
+    String fileId2 = testTable.addCommit("002").getFileIdWithInserts("2016/01/31", record2);
+    String fileId3 = testTable.addCommit("003").getFileIdWithInserts("2015/01/31", record4);
+
+    metaClient.reloadActiveTimeline();
+
+    // We do the tag again
+    taggedRecords = bloomIndex.tagLocation(records, context, HoodieFlinkTable.create(config, context, metaClient));
+
+    // Check results
+    for (HoodieRecord record : taggedRecords) {
+      if (record.getRecordKey().equals(rowKey1)) {
+        if (record.getPartitionPath().equals("2015/01/31")) {
+          assertEquals(record.getCurrentLocation().getFileId(), fileId3);
+        } else {
+          assertEquals(record.getCurrentLocation().getFileId(), fileId1);
+        }
+      } else if (record.getRecordKey().equals(rowKey2)) {
+        assertEquals(record.getCurrentLocation().getFileId(), fileId2);
+      } else if (record.getRecordKey().equals(rowKey3)) {
+        assertFalse(record.isCurrentLocationKnown());
+      }
+    }
+  }
+
+  @ParameterizedTest(name = TEST_NAME_WITH_PARAMS)
+  @MethodSource("configParams")
+  public void testCheckExists(boolean rangePruning, boolean treeFiltering, boolean bucketizedChecking) throws Exception {
+    // We have some records to be tagged (two different partitions)
+
+    String recordStr1 = "{\"_row_key\":\"1eb5b87a-1feh-4edd-87b4-6ec96dc405a0\","
+        + "\"time\":\"2016-01-31T03:16:41.415Z\",\"number\":12}";
+    String recordStr2 = "{\"_row_key\":\"2eb5b87b-1feu-4edd-87b4-6ec96dc405a0\","
+        + "\"time\":\"2016-01-31T03:20:41.415Z\",\"number\":100}";
+    String recordStr3 = "{\"_row_key\":\"3eb5b87c-1fej-4edd-87b4-6ec96dc405a0\","
+        + "\"time\":\"2016-01-31T03:16:41.415Z\",\"number\":15}";
+    // record key same as recordStr2
+    String recordStr4 = "{\"_row_key\":\"2eb5b87b-1feu-4edd-87b4-6ec96dc405a0\","
+        + "\"time\":\"2015-01-31T03:16:41.415Z\",\"number\":32}";
+    RawTripTestPayload rowChange1 = new RawTripTestPayload(recordStr1);
+    HoodieKey key1 = new HoodieKey(rowChange1.getRowKey(), rowChange1.getPartitionPath());
+    HoodieRecord record1 = new HoodieRecord(key1, rowChange1);
+    RawTripTestPayload rowChange2 = new RawTripTestPayload(recordStr2);
+    HoodieKey key2 = new HoodieKey(rowChange2.getRowKey(), rowChange2.getPartitionPath());
+    HoodieRecord record2 = new HoodieRecord(key2, rowChange2);
+    RawTripTestPayload rowChange3 = new RawTripTestPayload(recordStr3);
+    HoodieKey key3 = new HoodieKey(rowChange3.getRowKey(), rowChange3.getPartitionPath());
+    RawTripTestPayload rowChange4 = new RawTripTestPayload(recordStr4);
+    HoodieKey key4 = new HoodieKey(rowChange4.getRowKey(), rowChange4.getPartitionPath());
+    HoodieRecord record4 = new HoodieRecord(key4, rowChange4);
+    List<HoodieKey> keys = asList(key1, key2, key3, key4);
+
+    // Also create the metadata and config
+    HoodieWriteConfig config = makeConfig(rangePruning, treeFiltering, bucketizedChecking);
+    HoodieTable hoodieTable = HoodieFlinkTable.create(config, context, metaClient);
+    HoodieFlinkWriteableTestTable testTable = HoodieFlinkWriteableTestTable.of(hoodieTable, SCHEMA);
+
+    // Let's tag
+    FlinkHoodieBloomIndex bloomIndex = new FlinkHoodieBloomIndex(config);
+    List<HoodieRecord> toTagRecords = new ArrayList<>();
+    toTagRecords.add(new HoodieRecord(record4.getKey(), null));
+    List<HoodieRecord> taggedRecords = bloomIndex.tagLocation(toTagRecords, context, hoodieTable);
+    Map<HoodieKey, Option<Pair<String, String>>> recordLocations = new HashMap<>();
+    for (HoodieRecord taggedRecord : taggedRecords) {
+      recordLocations.put(taggedRecord.getKey(), taggedRecord.isCurrentLocationKnown()
+                ? Option.of(Pair.of(taggedRecord.getPartitionPath(), taggedRecord.getCurrentLocation().getFileId()))
+                : Option.empty());
+    }
+    // Should not find any files
+    for (Option<Pair<String, String>> record : recordLocations.values()) {
+      assertTrue(!record.isPresent());
+    }
+
+    // We create three parquet file, each having one record. (two different partitions)
+    String fileId1 = testTable.addCommit("001").getFileIdWithInserts("2016/01/31", record1);
+    String fileId2 = testTable.addCommit("002").getFileIdWithInserts("2016/01/31", record2);
+    String fileId3 = testTable.addCommit("003").getFileIdWithInserts("2015/01/31", record4);
+
+    // We do the tag again
+    metaClient = HoodieTableMetaClient.reload(metaClient);
+    hoodieTable = HoodieFlinkTable.create(config, context, metaClient);
+    List<HoodieRecord> toTagRecords1 = new ArrayList<>();
+    for (HoodieKey key : keys) {
+      taggedRecords.add(new HoodieRecord(key, null));
+    }
+
+    taggedRecords = bloomIndex.tagLocation(toTagRecords1, context, hoodieTable);
+    recordLocations.clear();
+    for (HoodieRecord taggedRecord : taggedRecords) {
+      recordLocations.put(taggedRecord.getKey(), taggedRecord.isCurrentLocationKnown()
+                ? Option.of(Pair.of(taggedRecord.getPartitionPath(), taggedRecord.getCurrentLocation().getFileId()))
+                : Option.empty());
+    }
+
+    // Check results
+    for (Map.Entry<HoodieKey, Option<Pair<String, String>>> record : recordLocations.entrySet()) {
+      if (record.getKey().getRecordKey().equals("1eb5b87a-1feh-4edd-87b4-6ec96dc405a0")) {
+        assertTrue(record.getValue().isPresent());
+        assertEquals(fileId1, record.getValue().get().getRight());
+      } else if (record.getKey().getRecordKey().equals("2eb5b87b-1feu-4edd-87b4-6ec96dc405a0")) {
+        assertTrue(record.getValue().isPresent());
+        if (record.getKey().getPartitionPath().equals("2015/01/31")) {
+          assertEquals(fileId3, record.getValue().get().getRight());
+        } else {
+          assertEquals(fileId2, record.getValue().get().getRight());
+        }
+      } else if (record.getKey().getRecordKey().equals("3eb5b87c-1fej-4edd-87b4-6ec96dc405a0")) {
+        assertFalse(record.getValue().isPresent());
+      }
+    }
+  }
+
+  @ParameterizedTest(name = TEST_NAME_WITH_PARAMS)
+  @MethodSource("configParams")
+  public void testBloomFilterFalseError(boolean rangePruning, boolean treeFiltering, boolean bucketizedChecking) throws Exception {
+    // We have two hoodie records
+    String recordStr1 = "{\"_row_key\":\"1eb5b87a-1feh-4edd-87b4-6ec96dc405a0\","
+        + "\"time\":\"2016-01-31T03:16:41.415Z\",\"number\":12}";
+    String recordStr2 = "{\"_row_key\":\"2eb5b87b-1feu-4edd-87b4-6ec96dc405a0\","
+        + "\"time\":\"2016-01-31T03:20:41.415Z\",\"number\":100}";
+
+    // We write record1 to a parquet file, using a bloom filter having both records
+    RawTripTestPayload rowChange1 = new RawTripTestPayload(recordStr1);
+    HoodieRecord record1 = new HoodieRecord(new HoodieKey(rowChange1.getRowKey(), rowChange1.getPartitionPath()), rowChange1);
+    RawTripTestPayload rowChange2 = new RawTripTestPayload(recordStr2);
+    HoodieRecord record2 = new HoodieRecord(new HoodieKey(rowChange2.getRowKey(), rowChange2.getPartitionPath()), rowChange2);
+
+    BloomFilter filter = BloomFilterFactory.createBloomFilter(10000, 0.0000001, -1, BloomFilterTypeCode.SIMPLE.name());
+    filter.add(record2.getRecordKey());
+    HoodieFlinkWriteableTestTable testTable = HoodieFlinkWriteableTestTable.of(metaClient, SCHEMA, filter);
+    String fileId = testTable.addCommit("000").getFileIdWithInserts("2016/01/31", record1);
+    assertTrue(filter.mightContain(record1.getRecordKey()));
+    assertTrue(filter.mightContain(record2.getRecordKey()));
+
+    // We do the tag
+    List<HoodieRecord> records = asList(record1, record2);
+    HoodieWriteConfig config = makeConfig(rangePruning, treeFiltering, bucketizedChecking);
+    metaClient = HoodieTableMetaClient.reload(metaClient);
+    HoodieTable table = HoodieFlinkTable.create(config, context, metaClient);
+
+    FlinkHoodieBloomIndex bloomIndex = new FlinkHoodieBloomIndex(config);
+    List<HoodieRecord> taggedRecords = bloomIndex.tagLocation(records, context, table);
+
+    // Check results
+    for (HoodieRecord record : taggedRecords) {
+      if (record.getKey().equals("1eb5b87a-1feh-4edd-87b4-6ec96dc405a0")) {
+        assertEquals(record.getCurrentLocation().getFileId(), fileId);
+      } else if (record.getRecordKey().equals("2eb5b87b-1feu-4edd-87b4-6ec96dc405a0")) {
+        assertFalse(record.isCurrentLocationKnown());
+      }
+    }
+  }
+}

hudi-client/hudi-flink-client/src/test/java/org/apache/hudi/testutils/HoodieFlinkClientTestHarness.java

@@ -18,21 +18,31 @@
 
 package org.apache.hudi.testutils;
 
+import org.apache.hudi.client.FlinkTaskContextSupplier;
+import org.apache.hudi.client.HoodieFlinkWriteClient;
+import org.apache.hudi.client.common.HoodieFlinkEngineContext;
 import org.apache.hudi.common.fs.FSUtils;
 import org.apache.hudi.common.model.HoodieRecord;
 import org.apache.hudi.common.model.HoodieTableType;
 import org.apache.hudi.common.table.HoodieTableMetaClient;
+import org.apache.hudi.common.table.view.HoodieTableFileSystemView;
 import org.apache.hudi.common.testutils.HoodieCommonTestHarness;
 import org.apache.hudi.common.testutils.HoodieTestUtils;
+import org.apache.hudi.common.testutils.minicluster.HdfsTestService;
+import org.apache.hudi.index.bloom.TestFlinkHoodieBloomIndex;
 
+import org.apache.hadoop.hdfs.DistributedFileSystem;
+import org.apache.hadoop.hdfs.MiniDFSCluster;
 import org.apache.flink.runtime.testutils.MiniClusterResourceConfiguration;
 import org.apache.flink.streaming.api.functions.sink.SinkFunction;
 import org.apache.flink.test.util.MiniClusterWithClientResource;
 import org.apache.hadoop.conf.Configuration;
 import org.apache.hadoop.fs.FileSystem;
 import org.apache.hadoop.fs.LocalFileSystem;
+
 import org.apache.log4j.LogManager;
 import org.apache.log4j.Logger;
+
 import org.junit.jupiter.api.BeforeEach;
 import org.junit.jupiter.api.TestInfo;
 
@@ -40,7 +50,11 @@ import java.io.IOException;
 import java.io.Serializable;
 import java.util.ArrayList;
 import java.util.List;
+import java.util.concurrent.ExecutorService;
 
+/**
+ * The test harness for resource initialization and cleanup.
+ */
 public class HoodieFlinkClientTestHarness extends HoodieCommonTestHarness implements Serializable {
 
   protected static final Logger LOG = LogManager.getLogger(HoodieFlinkClientTestHarness.class);
@@ -48,6 +62,17 @@ public class HoodieFlinkClientTestHarness extends HoodieCommonTestHarness implem
   protected transient Configuration hadoopConf = null;
   protected transient FileSystem fs;
   protected transient MiniClusterWithClientResource flinkCluster = null;
+  protected transient HoodieFlinkEngineContext context = null;
+  protected transient ExecutorService executorService;
+  protected transient HoodieFlinkWriteClient writeClient;
+  protected transient HoodieTableFileSystemView tableView;
+
+  protected final FlinkTaskContextSupplier supplier = new FlinkTaskContextSupplier(null);
+
+  // dfs
+  protected transient HdfsTestService hdfsTestService;
+  protected transient MiniDFSCluster dfsCluster;
+  protected transient DistributedFileSystem dfs;
 
   @BeforeEach
   public void setTestMethodName(TestInfo testInfo) {
@@ -69,6 +94,7 @@ public class HoodieFlinkClientTestHarness extends HoodieCommonTestHarness implem
   protected void initFileSystem() {
     hadoopConf = new Configuration();
     initFileSystemWithConfiguration(hadoopConf);
+    context = new HoodieFlinkEngineContext(supplier);
   }
 
   private void initFileSystemWithConfiguration(Configuration configuration) {
@@ -116,6 +142,19 @@ public class HoodieFlinkClientTestHarness extends HoodieCommonTestHarness implem
     }
   }
 
+  /**
+   * Cleanups resource group for the subclasses of  {@link TestFlinkHoodieBloomIndex}.
+   */
+  public void cleanupResources() throws java.io.IOException {
+    cleanupClients();
+    cleanupFlinkContexts();
+    cleanupTestDataGenerator();
+    cleanupFileSystem();
+    cleanupDFS();
+    cleanupExecutorService();
+    System.gc();
+  }
+
   protected void cleanupFlinkMiniCluster() {
     if (flinkCluster != null) {
       flinkCluster.after();
@@ -133,4 +172,59 @@ public class HoodieFlinkClientTestHarness extends HoodieCommonTestHarness implem
       valuesList.add(value);
     }
   }
+
+  /**
+   * Cleanups hoodie clients.
+   */
+  protected void cleanupClients() throws java.io.IOException {
+    if (metaClient != null) {
+      metaClient = null;
+    }
+    if (writeClient != null) {
+      writeClient.close();
+      writeClient = null;
+    }
+    if (tableView != null) {
+      tableView.close();
+      tableView = null;
+    }
+  }
+
+  /**
+   * Cleanups the distributed file system.
+   *
+   * @throws IOException
+   */
+  protected void cleanupDFS() throws java.io.IOException {
+    if (hdfsTestService != null) {
+      hdfsTestService.stop();
+      dfsCluster.shutdown();
+      hdfsTestService = null;
+      dfsCluster = null;
+      dfs = null;
+    }
+    // Need to closeAll to clear FileSystem.Cache, required because DFS and LocalFS used in the
+    // same JVM
+    FileSystem.closeAll();
+  }
+
+  /**
+   * Cleanups the executor service.
+   */
+  protected void cleanupExecutorService() {
+    if (this.executorService != null) {
+      this.executorService.shutdownNow();
+      this.executorService = null;
+    }
+  }
+
+  /**
+   * Cleanups Flink contexts.
+   */
+  protected void cleanupFlinkContexts() {
+    if (context != null) {
+      LOG.info("Closing flink engine context used in previous test-case");
+      context = null;
+    }
+  }
 }

hudi-client/hudi-flink-client/src/test/java/org/apache/hudi/testutils/HoodieFlinkWriteableTestTable.java

@@ -0,0 +1,136 @@
+/*
+ * 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.testutils;
+
+import org.apache.hudi.avro.HoodieAvroUtils;
+import org.apache.hudi.common.bloom.BloomFilter;
+import org.apache.hudi.common.bloom.BloomFilterFactory;
+import org.apache.hudi.common.bloom.BloomFilterTypeCode;
+import org.apache.hudi.common.model.HoodieLogFile;
+import org.apache.hudi.common.model.HoodieRecord;
+import org.apache.hudi.common.model.HoodieRecordLocation;
+import org.apache.hudi.common.table.HoodieTableMetaClient;
+import org.apache.hudi.common.table.log.HoodieLogFormat;
+import org.apache.hudi.common.table.log.block.HoodieAvroDataBlock;
+import org.apache.hudi.common.table.log.block.HoodieLogBlock.HeaderMetadataType;
+import org.apache.hudi.table.HoodieTable;
+
+import org.apache.avro.Schema;
+import org.apache.avro.generic.GenericRecord;
+import org.apache.hadoop.fs.Path;
+import org.apache.log4j.LogManager;
+import org.apache.log4j.Logger;
+
+import java.util.Arrays;
+import java.util.List;
+import java.util.Map;
+import java.util.stream.Collectors;
+
+public class HoodieFlinkWriteableTestTable extends HoodieWriteableTestTable {
+  private static final Logger LOG = LogManager.getLogger(HoodieFlinkWriteableTestTable.class);
+
+  private HoodieFlinkWriteableTestTable(String basePath, org.apache.hadoop.fs.FileSystem fs, HoodieTableMetaClient metaClient, Schema schema, BloomFilter filter) {
+    super(basePath, fs, metaClient, schema, filter);
+  }
+
+  public static HoodieFlinkWriteableTestTable of(HoodieTableMetaClient metaClient, Schema schema, BloomFilter filter) {
+    return new HoodieFlinkWriteableTestTable(metaClient.getBasePath(), metaClient.getRawFs(), metaClient, schema, filter);
+  }
+
+  public static HoodieFlinkWriteableTestTable of(HoodieTableMetaClient metaClient, Schema schema) {
+    BloomFilter filter = BloomFilterFactory.createBloomFilter(10000, 0.0000001, -1, BloomFilterTypeCode.SIMPLE.name());
+    return of(metaClient, schema, filter);
+  }
+
+  public static HoodieFlinkWriteableTestTable of(HoodieTable hoodieTable, Schema schema) {
+    HoodieTableMetaClient metaClient = hoodieTable.getMetaClient();
+    return of(metaClient, schema);
+  }
+
+  public static HoodieFlinkWriteableTestTable of(HoodieTable hoodieTable, Schema schema, BloomFilter filter) {
+    HoodieTableMetaClient metaClient = hoodieTable.getMetaClient();
+    return of(metaClient, schema, filter);
+  }
+
+  @Override
+  public HoodieFlinkWriteableTestTable addCommit(String instantTime) throws Exception {
+    return (HoodieFlinkWriteableTestTable) super.addCommit(instantTime);
+  }
+
+  @Override
+  public HoodieFlinkWriteableTestTable forCommit(String instantTime) {
+    return (HoodieFlinkWriteableTestTable) super.forCommit(instantTime);
+  }
+
+  public String getFileIdWithInserts(String partition) throws Exception {
+    return getFileIdWithInserts(partition, new HoodieRecord[0]);
+  }
+
+  public String getFileIdWithInserts(String partition, HoodieRecord... records) throws Exception {
+    return getFileIdWithInserts(partition, Arrays.asList(records));
+  }
+
+  public String getFileIdWithInserts(String partition, List<HoodieRecord> records) throws Exception {
+    String fileId = java.util.UUID.randomUUID().toString();
+    withInserts(partition, fileId, records);
+    return fileId;
+  }
+
+  public HoodieFlinkWriteableTestTable withInserts(String partition, String fileId) throws Exception {
+    return withInserts(partition, fileId, new HoodieRecord[0]);
+  }
+
+  public HoodieFlinkWriteableTestTable withInserts(String partition, String fileId, HoodieRecord... records) throws Exception {
+    return withInserts(partition, fileId, Arrays.asList(records));
+  }
+
+  public HoodieFlinkWriteableTestTable withInserts(String partition, String fileId, List<HoodieRecord> records) throws Exception {
+    return (HoodieFlinkWriteableTestTable) withInserts(partition, fileId, records, new org.apache.hudi.client.FlinkTaskContextSupplier(null));
+  }
+
+  public HoodieFlinkWriteableTestTable withLogAppends(List<HoodieRecord> records) throws Exception {
+    for (List<HoodieRecord> groupedRecords: records.stream().collect(Collectors.groupingBy(HoodieRecord::getCurrentLocation)).values()) {
+      appendRecordsToLogFile(groupedRecords);
+    }
+    return this;
+  }
+
+  private void appendRecordsToLogFile(List<HoodieRecord> groupedRecords) throws Exception {
+    String partitionPath = groupedRecords.get(0).getPartitionPath();
+    HoodieRecordLocation location = groupedRecords.get(0).getCurrentLocation();
+    try (HoodieLogFormat.Writer logWriter = HoodieLogFormat.newWriterBuilder().onParentPath(new Path(basePath, partitionPath))
+        .withFileExtension(HoodieLogFile.DELTA_EXTENSION).withFileId(location.getFileId())
+        .overBaseCommit(location.getInstantTime()).withFs(fs).build()) {
+      Map<HeaderMetadataType, String> header = new java.util.HashMap<>();
+      header.put(HeaderMetadataType.INSTANT_TIME, location.getInstantTime());
+      header.put(HeaderMetadataType.SCHEMA, schema.toString());
+      logWriter.appendBlock(new HoodieAvroDataBlock(groupedRecords.stream().map(r -> {
+        try {
+          GenericRecord val = (GenericRecord) r.getData().getInsertValue(schema).get();
+          HoodieAvroUtils.addHoodieKeyToRecord(val, r.getRecordKey(), r.getPartitionPath(), "");
+          return (org.apache.avro.generic.IndexedRecord) val;
+        } catch (java.io.IOException e) {
+          LOG.warn("Failed to convert record " + r.toString(), e);
+          return null;
+        }
+      }).collect(Collectors.toList()), header));
+    }
+  }
+}