cshuo commented on code in PR #17490: URL: https://github.com/apache/hudi/pull/17490#discussion_r2614039149
########## hudi-flink-datasource/hudi-flink/src/main/java/org/apache/hudi/source/stats/RecordLevelIndex.java: ########## @@ -0,0 +1,263 @@ +/* + * 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.source.stats; + +import org.apache.hudi.client.common.HoodieFlinkEngineContext; +import org.apache.hudi.common.data.HoodieListData; +import org.apache.hudi.common.data.HoodiePairData; +import org.apache.hudi.common.model.FileSlice; +import org.apache.hudi.common.model.HoodieRecordGlobalLocation; +import org.apache.hudi.common.table.HoodieTableMetaClient; +import org.apache.hudi.common.util.HoodieDataUtils; +import org.apache.hudi.common.util.Option; +import org.apache.hudi.common.util.VisibleForTesting; +import org.apache.hudi.common.util.collection.Pair; +import org.apache.hudi.configuration.FlinkOptions; +import org.apache.hudi.configuration.OptionsResolver; +import org.apache.hudi.keygen.KeyGenUtils; +import org.apache.hudi.keygen.KeyGenerator; +import org.apache.hudi.metadata.HoodieTableMetadata; +import org.apache.hudi.metadata.HoodieTableMetadataUtil; +import org.apache.hudi.sink.bulk.RowDataKeyGen; +import org.apache.hudi.source.ExpressionEvaluators; +import org.apache.hudi.util.StreamerUtil; + +import org.apache.flink.configuration.Configuration; +import org.apache.flink.table.data.TimestampData; +import org.apache.flink.table.types.logical.DecimalType; +import org.apache.flink.table.types.logical.LogicalType; +import org.apache.flink.table.types.logical.RowType; +import org.slf4j.Logger; +import org.slf4j.LoggerFactory; + +import java.math.BigDecimal; +import java.util.ArrayList; +import java.util.Arrays; +import java.util.Collections; +import java.util.List; +import java.util.Objects; +import java.util.Set; +import java.util.stream.Collectors; + +/** + * An index support implementation that leverages Record Level Index to prune file slices. + */ +public class RecordLevelIndex implements FlinkMetadataIndex { + private static final long serialVersionUID = 1L; + private static final Logger LOG = LoggerFactory.getLogger(RecordLevelIndex.class); + + private final String basePath; + private final Configuration conf; + private final List<String> hoodieKeysFromFilter; + private final HoodieTableMetaClient metaClient; + private HoodieTableMetadata metadataTable; + + private RecordLevelIndex( + String basePath, + Configuration conf, + HoodieTableMetaClient metaClient, + List<String> hoodieKeysFromFilter) { + this.basePath = basePath; + this.conf = conf; + this.metaClient = metaClient; + this.hoodieKeysFromFilter = hoodieKeysFromFilter; + } + + @Override + public String getIndexPartitionName() { + return HoodieTableMetadataUtil.PARTITION_NAME_RECORD_INDEX; + } + + @Override + public boolean isIndexAvailable() { + return metaClient.getTableConfig().isMetadataTableAvailable() + && metaClient.getTableConfig().getMetadataPartitions().contains(HoodieTableMetadataUtil.PARTITION_NAME_RECORD_INDEX); + } + + public HoodieTableMetadata getMetadataTable() { + // initialize the metadata table lazily + if (this.metadataTable == null) { + this.metadataTable = metaClient.getTableFormat().getMetadataFactory().create( + HoodieFlinkEngineContext.DEFAULT, + metaClient.getStorage(), + StreamerUtil.metadataConfig(conf), + basePath); + } + return this.metadataTable; + } + + public List<FileSlice> computeCandidateFileSlices(List<FileSlice> fileSlices) { + if (!isIndexAvailable()) { + return fileSlices; + } + HoodiePairData<String, HoodieRecordGlobalLocation> recordIndexData = + getMetadataTable().readRecordIndexLocationsWithKeys(HoodieListData.eager(hoodieKeysFromFilter)); + try { + List<Pair<String, HoodieRecordGlobalLocation>> recordIndexLocations = HoodieDataUtils.dedupeAndCollectAsList(recordIndexData); + Set<String> fileIds = recordIndexLocations.stream() + .map(pair -> pair.getValue().getFileId()).collect(Collectors.toSet()); + return fileSlices.stream().filter(fileSlice -> fileIds.contains(fileSlice.getFileId())).collect(Collectors.toList()); + } finally { + // Clean up the RDD to avoid memory leaks + recordIndexData.unpersistWithDependencies(); + } + } + + public static Option<RecordLevelIndex> create( + String basePath, + Configuration conf, + HoodieTableMetaClient metaClient, + List<ExpressionEvaluators.Evaluator> evaluators, + RowType rowType) { + if (evaluators.isEmpty() || !FlinkOptions.QUERY_TYPE_SNAPSHOT.equalsIgnoreCase(conf.get(FlinkOptions.QUERY_TYPE))) { + return Option.empty(); + } + if (metaClient == null) { + metaClient = StreamerUtil.createMetaClient(conf); + } + if (KeyGenUtils.mayUseNewEncodingForComplexKeyGen(metaClient.getTableConfig())) { + return Option.empty(); + } + + String[] recordKeyFields = metaClient.getTableConfig().getRecordKeyFields().orElse(new String[0]); + if (recordKeyFields.length == 0) { + LOG.warn("The table do not have record keys, skipping the rli pruning."); + return Option.empty(); + } + boolean consistentLogicalTimestampEnabled = OptionsResolver.isConsistentLogicalTimestampEnabled(conf); + List<String> hoodieKeysFromFilter = computeHoodieKeyFromFilters(conf, metaClient, evaluators, recordKeyFields, rowType, consistentLogicalTimestampEnabled); + if (hoodieKeysFromFilter.isEmpty()) { + LOG.warn("The number of keys from query predicate is empty, skipping the rli pruning."); + return Option.empty(); + } + int maxKeyNum = conf.get(FlinkOptions.READ_DATA_SKIPPING_RLI_KEYS_MAX_NUM); + if (hoodieKeysFromFilter.size() > maxKeyNum) { + LOG.warn("The number of keys from query predicate: {} exceeds the upper threshold: {}, skipping the rli pruning, the keys: {}", + hoodieKeysFromFilter.size(), maxKeyNum, hoodieKeysFromFilter); + return Option.empty(); + } + return Option.of(new RecordLevelIndex(basePath, conf, metaClient, hoodieKeysFromFilter)); + } + + /** + * Given query filters, it filters the EqualTo, IN and OR queries on record key columns and + * returns the list of record key literals present in the query, for example: + * <p> + * filter1: `key1` = 'val1', returns {"val1"} + * filter2: `key1` in ('val1', 'val2', 'val3'), returns {"val1", "vale", "val3"} + * filter3: `key1` = 'val1' OR `key1` = 'val2' or `key1` = 'val3', returns {"val1", "vale", "val3"} + * filter4: `key1` = 'val1' AND `key2` in ('val2', 'val3'), returns {"key1:val1,key2:val2", "key1:val1,key2:val3"} + */ + @VisibleForTesting + public static List<String> computeHoodieKeyFromFilters( + Configuration conf, + HoodieTableMetaClient metaClient, + List<ExpressionEvaluators.Evaluator> evaluators, + String[] keyFields, + RowType rowType, + boolean consistentLogicalTimestampEnabled) { + String[] partitionFields = metaClient.getTableConfig().getPartitionFields().orElse(new String[0]); + // align with the check logic in RowDataKeyGen + boolean isComplexRecordKey = keyFields.length > 1 || partitionFields.length > 1 && !OptionsResolver.useComplexKeygenNewEncoding(conf); + List<String> hoodieKeys = new ArrayList<>(); + List<String> fieldNames = rowType.getFieldNames(); + for (String keyField: keyFields) { + List<String> recordKeys = new ArrayList<>(); + LogicalType fieldType = rowType.getTypeAt(fieldNames.indexOf(keyField)); + for (ExpressionEvaluators.Evaluator evaluator: evaluators) { + // if there exists multiple ref fields in an evaluator, ignore this evaluator, e.g., key = 'key1' or age = 20 + List<Object> literals = collectLiterals(evaluator, keyField); + literals.forEach(val -> recordKeys.add(isComplexRecordKey + ? keyField + KeyGenerator.DEFAULT_COLUMN_VALUE_SEPARATOR + normalizeLiteral(val, keyField, fieldType, consistentLogicalTimestampEnabled) + : normalizeLiteral(val, keyField, fieldType, consistentLogicalTimestampEnabled))); + } + if (recordKeys.isEmpty()) { + LOG.info("No literals found for the record key: {}, therefore filtering can not be performed", keyField); + return Collections.emptyList(); + } else if (!isComplexRecordKey || hoodieKeys.isEmpty()) { + hoodieKeys = recordKeys; + } else { + // Combine literals for this configured record key with literals for the other configured record keys + // If there are two literals for rk1, rk2, rk3 each. A total of 8 combinations will be generated + List<String> tmpHoodieKeys = new ArrayList<>(); + for (String compositeKey: hoodieKeys) { + for (String recordKey: recordKeys) { + tmpHoodieKeys.add(compositeKey + KeyGenerator.DEFAULT_RECORD_KEY_PARTS_SEPARATOR + recordKey); + } + } + hoodieKeys = tmpHoodieKeys; + } + } + return hoodieKeys; + } + + /** + * Collect literal values for record key fields from the predicate. + */ + private static List<Object> collectLiterals(ExpressionEvaluators.Evaluator evaluator, String refName) { Review Comment: We do not have common Expression shared among different engines yet, so it's hard to trying reusing codes now. -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected]
