gustavodemorais commented on code in PR #26313: URL: https://github.com/apache/flink/pull/26313#discussion_r2111544565
########## flink-table/flink-table-runtime/src/main/java/org/apache/flink/table/runtime/operators/join/stream/state/MultiJoinStateViews.java: ########## @@ -0,0 +1,359 @@ +/* + * 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.flink.table.runtime.operators.join.stream.state; + +import org.apache.flink.api.common.functions.RuntimeContext; +import org.apache.flink.api.common.state.MapState; +import org.apache.flink.api.common.state.MapStateDescriptor; +import org.apache.flink.api.common.state.StateTtlConfig; +import org.apache.flink.api.common.typeinfo.TypeInformation; +import org.apache.flink.api.common.typeinfo.Types; +import org.apache.flink.api.java.functions.KeySelector; +import org.apache.flink.table.data.RowData; +import org.apache.flink.table.runtime.operators.join.stream.utils.JoinInputSideSpec; +import org.apache.flink.table.runtime.typeutils.InternalTypeInfo; +import org.apache.flink.types.RowKind; +import org.apache.flink.util.IterableIterator; + +import java.util.ArrayList; +import java.util.Collections; +import java.util.HashMap; +import java.util.Iterator; +import java.util.List; +import java.util.Map; +import java.util.NoSuchElementException; + +import static org.apache.flink.table.runtime.util.StateConfigUtil.createTtlConfig; +import static org.apache.flink.util.Preconditions.checkNotNull; + +/** + * Factory class to create different implementations of {@link MultiJoinStateView} based on the + * characteristics described in {@link JoinInputSideSpec}. + * + * <p>Each state view uses a {@link MapState} where the primary key is the `mapKey` derived from the + * join conditions (via {@link + * org.apache.flink.table.runtime.operators.join.stream.keyselector.JoinKeyExtractor}). The value + * stored within this map depends on whether the input side has a unique key and how it relates to + * the join key, optimizing storage and access patterns. + */ +public final class MultiJoinStateViews { + + /** Creates a {@link MultiJoinStateView} depends on {@link JoinInputSideSpec}. */ + public static MultiJoinStateView create( + RuntimeContext ctx, + String stateName, + JoinInputSideSpec inputSideSpec, + InternalTypeInfo<RowData> mapKeyType, // Type info for the outer map key + InternalTypeInfo<RowData> recordType, + long retentionTime) { + StateTtlConfig ttlConfig = createTtlConfig(retentionTime); + + if (inputSideSpec.hasUniqueKey()) { + if (inputSideSpec.joinKeyContainsUniqueKey()) { + return new JoinKeyContainsUniqueKey( + ctx, stateName, mapKeyType, recordType, ttlConfig); + } else { + return new InputSideHasUniqueKey( + ctx, + stateName, + mapKeyType, + recordType, + inputSideSpec.getUniqueKeyType(), + inputSideSpec.getUniqueKeySelector(), + ttlConfig); + } + } else { + return new InputSideHasNoUniqueKey(ctx, stateName, mapKeyType, recordType, ttlConfig); + } + } + + /** + * Creates a {@link MapStateDescriptor} with the given parameters and applies TTL configuration. + * + * @param <K> Key type + * @param <V> Value type + * @param stateName Unique name for the state + * @param keyTypeInfo Type information for the key + * @param valueTypeInfo Type information for the value + * @param ttlConfig State TTL configuration + * @return Configured MapStateDescriptor + */ + private static <K, V> MapStateDescriptor<K, V> createStateDescriptor( + String stateName, + TypeInformation<K> keyTypeInfo, + TypeInformation<V> valueTypeInfo, + StateTtlConfig ttlConfig) { + MapStateDescriptor<K, V> descriptor = + new MapStateDescriptor<>(stateName, keyTypeInfo, valueTypeInfo); + if (ttlConfig.isEnabled()) { + descriptor.enableTimeToLive(ttlConfig); + } + return descriptor; + } + + // ------------------------------------------------------------------------------------ + // Multi Join State View Implementations + // ------------------------------------------------------------------------------------ + + /** + * State view for input sides where the unique key is fully contained within the join key. + * + * <p>Stores data as {@code MapState<MapKey, Record>}. + */ + private static final class JoinKeyContainsUniqueKey implements MultiJoinStateView { + + // stores record in the mapping <MapKey, Record> + private final MapState<RowData, RowData> recordState; + private final List<RowData> reusedList; + + private JoinKeyContainsUniqueKey( + RuntimeContext ctx, + final String stateName, + final InternalTypeInfo<RowData> mapKeyType, + final InternalTypeInfo<RowData> recordType, + final StateTtlConfig ttlConfig) { + + MapStateDescriptor<RowData, RowData> recordStateDesc = + createStateDescriptor(stateName, mapKeyType, recordType, ttlConfig); + + this.recordState = ctx.getMapState(recordStateDesc); + // the result records always not more than 1 per mapKey + this.reusedList = new ArrayList<>(1); + } + + @Override + public void addRecord(RowData mapKey, RowData record) throws Exception { + recordState.put(mapKey, record); + } + + @Override + public void retractRecord(RowData mapKey, RowData record) throws Exception { + // Only one record is kept per mapKey, remove it directly. + recordState.remove(mapKey); + } + + @Override + public Iterable<RowData> getRecords(RowData mapKey) throws Exception { + reusedList.clear(); + RowData record = recordState.get(mapKey); + if (record != null) { + reusedList.add(record); + } + return reusedList; + } + + @Override + public void cleanup(RowData mapKey) throws Exception { + recordState.remove(mapKey); + } + } + + /** + * State view for input sides that have a unique key, but it differs from the join key. + * + * <p>Stores data as {@code MapState<MapKey, Map<UK, Record>>}. + */ + private static final class InputSideHasUniqueKey implements MultiJoinStateView { + + // stores map in the mapping <MapKey, Map<UK, Record>> + private final MapState<RowData, Map<RowData, RowData>> recordState; + private final KeySelector<RowData, RowData> uniqueKeySelector; + + private InputSideHasUniqueKey( + RuntimeContext ctx, + final String stateName, + final InternalTypeInfo<RowData> mapKeyType, + final InternalTypeInfo<RowData> recordType, + final InternalTypeInfo<RowData> uniqueKeyType, + final KeySelector<RowData, RowData> uniqueKeySelector, + final StateTtlConfig ttlConfig) { + checkNotNull(uniqueKeyType); + checkNotNull(uniqueKeySelector); + this.uniqueKeySelector = uniqueKeySelector; + + TypeInformation<Map<RowData, RowData>> mapValueTypeInfo = + Types.MAP(uniqueKeyType, recordType); // UK is the key in the inner map + + MapStateDescriptor<RowData, Map<RowData, RowData>> recordStateDesc = + createStateDescriptor(stateName, mapKeyType, mapValueTypeInfo, ttlConfig); + + this.recordState = ctx.getMapState(recordStateDesc); + } + + @Override + public void addRecord(RowData mapKey, RowData record) throws Exception { + RowData uniqueKey = uniqueKeySelector.getKey(record); + Map<RowData, RowData> uniqueKeyToRecordMap = recordState.get(mapKey); + if (uniqueKeyToRecordMap == null) { + uniqueKeyToRecordMap = new HashMap<>(); + } + uniqueKeyToRecordMap.put(uniqueKey, record); + recordState.put(mapKey, uniqueKeyToRecordMap); + } + + @Override + public void retractRecord(RowData mapKey, RowData record) throws Exception { + RowData uniqueKey = uniqueKeySelector.getKey(record); + Map<RowData, RowData> uniqueKeyToRecordMap = recordState.get(mapKey); + if (uniqueKeyToRecordMap != null) { + uniqueKeyToRecordMap.remove(uniqueKey); + if (uniqueKeyToRecordMap.isEmpty()) { + // Clean up the entry for mapKey if the inner map becomes empty + recordState.remove(mapKey); + } else { + recordState.put(mapKey, uniqueKeyToRecordMap); + } + } + // ignore uniqueKeyToRecordMap == null + } + + @Override + public Iterable<RowData> getRecords(RowData mapKey) throws Exception { + Map<RowData, RowData> uniqueKeyToRecordMap = recordState.get(mapKey); + if (uniqueKeyToRecordMap == null) { + return Collections.emptyList(); + } else { + // Return the values (records) from the inner map + return uniqueKeyToRecordMap.values(); + } + } + + @Override + public void cleanup(RowData mapKey) throws Exception { + recordState.remove(mapKey); + } + } + + /** + * State view for input sides that do not have a unique key (multi-set semantics). + * + * <p>Stores data as {@code MapState<MapKey, Map<Record, Count>>}. + */ + private static final class InputSideHasNoUniqueKey implements MultiJoinStateView { + + // stores map in the mapping <MapKey, Map<Record, Count>> + private final MapState<RowData, Map<RowData, Integer>> recordState; Review Comment: Hey @rovboyko, thanks for the comment. I've synced with Dawid and Roman on this. > And if we receive the input data from T1 (with particular values of T1.k1 and T1.k98) we need first to get all data from T2 I think there might be some misalignment. It's not necessary to get all the data from T2. In the most common case, where queries use primary keys (**JoinKeyContainsUniqueKey**), we can get the associated record from T2 for the incoming T1 record directly. In this case, if having a primary key on T1.K1 or T1.k98, if we get a record on T1, we'll perform getRecords on T2 for(T1.K1, T1.k9 8) which will return us only one record. In the case where **we do not join on primary keys**, we have two cases: **InputSideHasUniqueKey** and **InputSideHasNoUniqueKey**. For these, we'll only retrieve the records from state for the `commonJoinKey`. In this case, records for a specific T1.K1, does that make sense? For InputSideHasUniqueKey, we'll only deserialize the key to filter them accordingly and not the value necessarily. For these two, there's one more optimization mapped here that would also make this quite efficient, see https://github.com/apache/flink/pull/26313#discussion_r2107592699. > future optimization which might be used for MJ is changing state order in runtime would not be possible to use if the JoinKey != CommonKey. We can still apply this optimization. For example, for `SELECT * FROM T1 JOIN T2 on T1.k1 = T2.k1 AND T1.k98 = T2.k98 JOIN T3 on T2.k1 = T3.k1 AND T2.k99 == T3.k99` we could start at any position. This has too be done carefully though and can't be applied to all use cases - but can be applied to all the cases when joinKey = commonKey. Why do you think we can't apply this? > Or we can use parallel requests to different states in future For different common join keys, we can access state in parallel. If commonJoinKey=joinKey, you'll be able to access state in parallel for each joinKey. On what kind of optimizations were you thinking about? -- 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: issues-unsubscr...@flink.apache.org For queries about this service, please contact Infrastructure at: us...@infra.apache.org
