danny0405 commented on a change in pull request #2430: URL: https://github.com/apache/hudi/pull/2430#discussion_r561768669
########## File path: hudi-flink/src/main/java/org/apache/hudi/operator/StreamWriteFunction.java ########## @@ -0,0 +1,344 @@ +/* + * 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.operator; + +import org.apache.hudi.avro.HoodieAvroUtils; +import org.apache.hudi.client.FlinkTaskContextSupplier; +import org.apache.hudi.client.HoodieFlinkWriteClient; +import org.apache.hudi.client.WriteStatus; +import org.apache.hudi.client.common.HoodieFlinkEngineContext; +import org.apache.hudi.common.config.SerializableConfiguration; +import org.apache.hudi.common.model.HoodieRecord; +import org.apache.hudi.common.model.HoodieRecordPayload; +import org.apache.hudi.common.model.WriteOperationType; +import org.apache.hudi.common.util.ObjectSizeCalculator; +import org.apache.hudi.keygen.KeyGenerator; +import org.apache.hudi.operator.event.BatchWriteSuccessEvent; +import org.apache.hudi.util.StreamerUtil; + +import org.apache.avro.Schema; +import org.apache.avro.generic.GenericRecord; +import org.apache.flink.annotation.VisibleForTesting; +import org.apache.flink.configuration.Configuration; +import org.apache.flink.formats.avro.RowDataToAvroConverters; +import org.apache.flink.runtime.operators.coordination.OperatorEventGateway; +import org.apache.flink.runtime.state.FunctionInitializationContext; +import org.apache.flink.runtime.state.FunctionSnapshotContext; +import org.apache.flink.streaming.api.checkpoint.CheckpointedFunction; +import org.apache.flink.streaming.api.functions.KeyedProcessFunction; +import org.apache.flink.table.types.logical.RowType; +import org.apache.flink.util.Collector; +import org.apache.flink.util.Preconditions; +import org.slf4j.Logger; +import org.slf4j.LoggerFactory; + +import java.io.IOException; +import java.util.ArrayList; +import java.util.Collections; +import java.util.List; +import java.util.Random; +import java.util.concurrent.locks.Condition; +import java.util.concurrent.locks.ReentrantLock; +import java.util.function.BiFunction; + +/** + * Sink function to write the data to the underneath filesystem. + * + * <p><h2>Work Flow</h2> + * + * <p>The function firstly buffers the data as a batch of {@link HoodieRecord}s, + * It flushes(write) the records batch when a Flink checkpoint starts. After a batch has been written successfully, + * the function notifies its operator coordinator {@link StreamWriteOperatorCoordinator} to mark a successful write. + * + * <p><h2>Exactly-once Semantics</h2> + * + * <p>The task implements exactly-once semantics by buffering the data between checkpoints. The operator coordinator + * starts a new instant on the time line when a checkpoint triggers, the coordinator checkpoints always + * start before its operator, so when this function starts a checkpoint, a REQUESTED instant already exists. + * The function process thread then block data buffering and the checkpoint thread starts flushing the existing data buffer. + * When the existing data buffer write successfully, the process thread unblock and start buffering again for the next round checkpoint. + * Because any checkpoint failures would trigger the write rollback, it implements the exactly-once semantics. + * + * <p><h2>Fault Tolerance</h2> + * + * <p>The operator coordinator checks the validity for the last instant when it starts a new one. The operator rolls back + * the written data and throws when any error occurs. This means any checkpoint or task failure would trigger a failover. + * The operator coordinator would try several times when committing the writestatus. + * + * <p>Note: The function task requires the input stream be partitioned by the partition fields to avoid different write tasks + * write to the same file group that conflict. The general case for partition path is a datetime field, + * so the sink task is very possible to have IO bottleneck, the more flexible solution is to shuffle the + * data by the file group IDs. + * + * @param <I> Type of the input record + * @see StreamWriteOperatorCoordinator + */ +public class StreamWriteFunction<K, I, O> extends KeyedProcessFunction<K, I, O> implements CheckpointedFunction { + + private static final long serialVersionUID = 1L; + + private static final Logger LOG = LoggerFactory.getLogger(StreamWriteFunction.class); + + /** + * Write buffer for a checkpoint. + */ + private transient List<HoodieRecord> buffer; + + /** + * The buffer lock to control data buffering/flushing. + */ + private transient ReentrantLock bufferLock; + + /** + * The condition to decide whether to add new records into the buffer. + */ + private transient Condition addToBufferCondition; + + /** + * Flag saying whether there is an on-going checkpoint. + */ + private volatile boolean onCheckpointing = false; + + /** + * Config options. + */ + private final Configuration config; + + /** + * Id of current subtask. + */ + private int taskID; + + /** + * Write Client. + */ + private transient HoodieFlinkWriteClient writeClient; + + private transient BiFunction<List<HoodieRecord>, String, List<WriteStatus>> writeFunction; + + /** + * HoodieKey generator. + */ + private transient KeyGenerator keyGenerator; + + /** + * Row type of the input. + */ + private final RowType rowType; + + /** + * Avro schema of the input. + */ + private final Schema avroSchema; + + private transient RowDataToAvroConverters.RowDataToAvroConverter converter; + + /** + * The REQUESTED instant we write the data. + */ + private volatile String currentInstant; + + /** + * Gateway to send operator events to the operator coordinator. + */ + private transient OperatorEventGateway eventGateway; + + /** + * Constructs a StreamingSinkFunction. + * + * @param rowType The input row type + * @param config The config options + */ + public StreamWriteFunction(RowType rowType, Configuration config) { Review comment: Use row type has 2 benefits: 1. Use the all kinds of `DeserializationSchema` provided for `RowData`, such as `JsonRowDataDeserializationSchema`, there is no need to write converter code for every data format, `RowData` is a good data structure to bridge external raw format with `HoodieRecord` 2. `RowData` is internal data structure of `SQL` API, so that the codes for datastream can be reused. ########## File path: hudi-flink/src/main/java/org/apache/hudi/operator/StreamWriteFunction.java ########## @@ -0,0 +1,344 @@ +/* + * 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.operator; + +import org.apache.hudi.avro.HoodieAvroUtils; +import org.apache.hudi.client.FlinkTaskContextSupplier; +import org.apache.hudi.client.HoodieFlinkWriteClient; +import org.apache.hudi.client.WriteStatus; +import org.apache.hudi.client.common.HoodieFlinkEngineContext; +import org.apache.hudi.common.config.SerializableConfiguration; +import org.apache.hudi.common.model.HoodieRecord; +import org.apache.hudi.common.model.HoodieRecordPayload; +import org.apache.hudi.common.model.WriteOperationType; +import org.apache.hudi.common.util.ObjectSizeCalculator; +import org.apache.hudi.keygen.KeyGenerator; +import org.apache.hudi.operator.event.BatchWriteSuccessEvent; +import org.apache.hudi.util.StreamerUtil; + +import org.apache.avro.Schema; +import org.apache.avro.generic.GenericRecord; +import org.apache.flink.annotation.VisibleForTesting; +import org.apache.flink.configuration.Configuration; +import org.apache.flink.formats.avro.RowDataToAvroConverters; +import org.apache.flink.runtime.operators.coordination.OperatorEventGateway; +import org.apache.flink.runtime.state.FunctionInitializationContext; +import org.apache.flink.runtime.state.FunctionSnapshotContext; +import org.apache.flink.streaming.api.checkpoint.CheckpointedFunction; +import org.apache.flink.streaming.api.functions.KeyedProcessFunction; +import org.apache.flink.table.types.logical.RowType; +import org.apache.flink.util.Collector; +import org.apache.flink.util.Preconditions; +import org.slf4j.Logger; +import org.slf4j.LoggerFactory; + +import java.io.IOException; +import java.util.ArrayList; +import java.util.Collections; +import java.util.List; +import java.util.Random; +import java.util.concurrent.locks.Condition; +import java.util.concurrent.locks.ReentrantLock; +import java.util.function.BiFunction; + +/** + * Sink function to write the data to the underneath filesystem. + * + * <p><h2>Work Flow</h2> + * + * <p>The function firstly buffers the data as a batch of {@link HoodieRecord}s, + * It flushes(write) the records batch when a Flink checkpoint starts. After a batch has been written successfully, + * the function notifies its operator coordinator {@link StreamWriteOperatorCoordinator} to mark a successful write. + * + * <p><h2>Exactly-once Semantics</h2> + * + * <p>The task implements exactly-once semantics by buffering the data between checkpoints. The operator coordinator + * starts a new instant on the time line when a checkpoint triggers, the coordinator checkpoints always + * start before its operator, so when this function starts a checkpoint, a REQUESTED instant already exists. + * The function process thread then block data buffering and the checkpoint thread starts flushing the existing data buffer. + * When the existing data buffer write successfully, the process thread unblock and start buffering again for the next round checkpoint. + * Because any checkpoint failures would trigger the write rollback, it implements the exactly-once semantics. + * + * <p><h2>Fault Tolerance</h2> + * + * <p>The operator coordinator checks the validity for the last instant when it starts a new one. The operator rolls back + * the written data and throws when any error occurs. This means any checkpoint or task failure would trigger a failover. + * The operator coordinator would try several times when committing the writestatus. + * + * <p>Note: The function task requires the input stream be partitioned by the partition fields to avoid different write tasks + * write to the same file group that conflict. The general case for partition path is a datetime field, + * so the sink task is very possible to have IO bottleneck, the more flexible solution is to shuffle the + * data by the file group IDs. + * + * @param <I> Type of the input record + * @see StreamWriteOperatorCoordinator + */ +public class StreamWriteFunction<K, I, O> extends KeyedProcessFunction<K, I, O> implements CheckpointedFunction { + + private static final long serialVersionUID = 1L; + + private static final Logger LOG = LoggerFactory.getLogger(StreamWriteFunction.class); + + /** + * Write buffer for a checkpoint. + */ + private transient List<HoodieRecord> buffer; + + /** + * The buffer lock to control data buffering/flushing. + */ + private transient ReentrantLock bufferLock; + + /** + * The condition to decide whether to add new records into the buffer. + */ + private transient Condition addToBufferCondition; + + /** + * Flag saying whether there is an on-going checkpoint. + */ + private volatile boolean onCheckpointing = false; + + /** + * Config options. + */ + private final Configuration config; + + /** + * Id of current subtask. + */ + private int taskID; + + /** + * Write Client. + */ + private transient HoodieFlinkWriteClient writeClient; + + private transient BiFunction<List<HoodieRecord>, String, List<WriteStatus>> writeFunction; + + /** + * HoodieKey generator. + */ + private transient KeyGenerator keyGenerator; + + /** + * Row type of the input. + */ + private final RowType rowType; + + /** + * Avro schema of the input. + */ + private final Schema avroSchema; + + private transient RowDataToAvroConverters.RowDataToAvroConverter converter; + + /** + * The REQUESTED instant we write the data. + */ + private volatile String currentInstant; + + /** + * Gateway to send operator events to the operator coordinator. + */ + private transient OperatorEventGateway eventGateway; + + /** + * Constructs a StreamingSinkFunction. + * + * @param rowType The input row type + * @param config The config options + */ + public StreamWriteFunction(RowType rowType, Configuration config) { Review comment: > This brings an additional burden for sharing the same abstraction The main abstraction that we can share is the partitioning and micro-batching, not the source record parsing, so this should not be a concern. On the contrary, the `RowData` is very efficient in processing and it supports many data formats, e.g. `JSON`/`CSV`/`Avro` which are all complex and have many config options. > RowType makes the number of compatible Flink versions less The old pipeline does not use the `RowType`, so it should not have compatibility problem. BTW, the Hoodie `Spark` data source also use `Row` as the basic data structure, which is easy for `JSON`/`CSV`/`Avro` source data conversion and effective data handling in the pipeline. ########## File path: hudi-flink/src/main/java/org/apache/hudi/operator/StreamWriteFunction.java ########## @@ -0,0 +1,344 @@ +/* + * 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.operator; + +import org.apache.hudi.avro.HoodieAvroUtils; +import org.apache.hudi.client.FlinkTaskContextSupplier; +import org.apache.hudi.client.HoodieFlinkWriteClient; +import org.apache.hudi.client.WriteStatus; +import org.apache.hudi.client.common.HoodieFlinkEngineContext; +import org.apache.hudi.common.config.SerializableConfiguration; +import org.apache.hudi.common.model.HoodieRecord; +import org.apache.hudi.common.model.HoodieRecordPayload; +import org.apache.hudi.common.model.WriteOperationType; +import org.apache.hudi.common.util.ObjectSizeCalculator; +import org.apache.hudi.keygen.KeyGenerator; +import org.apache.hudi.operator.event.BatchWriteSuccessEvent; +import org.apache.hudi.util.StreamerUtil; + +import org.apache.avro.Schema; +import org.apache.avro.generic.GenericRecord; +import org.apache.flink.annotation.VisibleForTesting; +import org.apache.flink.configuration.Configuration; +import org.apache.flink.formats.avro.RowDataToAvroConverters; +import org.apache.flink.runtime.operators.coordination.OperatorEventGateway; +import org.apache.flink.runtime.state.FunctionInitializationContext; +import org.apache.flink.runtime.state.FunctionSnapshotContext; +import org.apache.flink.streaming.api.checkpoint.CheckpointedFunction; +import org.apache.flink.streaming.api.functions.KeyedProcessFunction; +import org.apache.flink.table.types.logical.RowType; +import org.apache.flink.util.Collector; +import org.apache.flink.util.Preconditions; +import org.slf4j.Logger; +import org.slf4j.LoggerFactory; + +import java.io.IOException; +import java.util.ArrayList; +import java.util.Collections; +import java.util.List; +import java.util.Random; +import java.util.concurrent.locks.Condition; +import java.util.concurrent.locks.ReentrantLock; +import java.util.function.BiFunction; + +/** + * Sink function to write the data to the underneath filesystem. + * + * <p><h2>Work Flow</h2> + * + * <p>The function firstly buffers the data as a batch of {@link HoodieRecord}s, + * It flushes(write) the records batch when a Flink checkpoint starts. After a batch has been written successfully, + * the function notifies its operator coordinator {@link StreamWriteOperatorCoordinator} to mark a successful write. + * + * <p><h2>Exactly-once Semantics</h2> + * + * <p>The task implements exactly-once semantics by buffering the data between checkpoints. The operator coordinator + * starts a new instant on the time line when a checkpoint triggers, the coordinator checkpoints always + * start before its operator, so when this function starts a checkpoint, a REQUESTED instant already exists. + * The function process thread then block data buffering and the checkpoint thread starts flushing the existing data buffer. + * When the existing data buffer write successfully, the process thread unblock and start buffering again for the next round checkpoint. + * Because any checkpoint failures would trigger the write rollback, it implements the exactly-once semantics. + * + * <p><h2>Fault Tolerance</h2> + * + * <p>The operator coordinator checks the validity for the last instant when it starts a new one. The operator rolls back + * the written data and throws when any error occurs. This means any checkpoint or task failure would trigger a failover. + * The operator coordinator would try several times when committing the writestatus. + * + * <p>Note: The function task requires the input stream be partitioned by the partition fields to avoid different write tasks + * write to the same file group that conflict. The general case for partition path is a datetime field, + * so the sink task is very possible to have IO bottleneck, the more flexible solution is to shuffle the + * data by the file group IDs. + * + * @param <I> Type of the input record + * @see StreamWriteOperatorCoordinator + */ +public class StreamWriteFunction<K, I, O> extends KeyedProcessFunction<K, I, O> implements CheckpointedFunction { + + private static final long serialVersionUID = 1L; + + private static final Logger LOG = LoggerFactory.getLogger(StreamWriteFunction.class); + + /** + * Write buffer for a checkpoint. + */ + private transient List<HoodieRecord> buffer; + + /** + * The buffer lock to control data buffering/flushing. + */ + private transient ReentrantLock bufferLock; + + /** + * The condition to decide whether to add new records into the buffer. + */ + private transient Condition addToBufferCondition; + + /** + * Flag saying whether there is an on-going checkpoint. + */ + private volatile boolean onCheckpointing = false; + + /** + * Config options. + */ + private final Configuration config; + + /** + * Id of current subtask. + */ + private int taskID; + + /** + * Write Client. + */ + private transient HoodieFlinkWriteClient writeClient; + + private transient BiFunction<List<HoodieRecord>, String, List<WriteStatus>> writeFunction; + + /** + * HoodieKey generator. + */ + private transient KeyGenerator keyGenerator; + + /** + * Row type of the input. + */ + private final RowType rowType; + + /** + * Avro schema of the input. + */ + private final Schema avroSchema; + + private transient RowDataToAvroConverters.RowDataToAvroConverter converter; + + /** + * The REQUESTED instant we write the data. + */ + private volatile String currentInstant; + + /** + * Gateway to send operator events to the operator coordinator. + */ + private transient OperatorEventGateway eventGateway; + + /** + * Constructs a StreamingSinkFunction. + * + * @param rowType The input row type + * @param config The config options + */ + public StreamWriteFunction(RowType rowType, Configuration config) { Review comment: > This brings an additional burden for sharing the same abstraction The main abstraction that we can share is the partitioning and micro-batching, not the source record parsing, so this should not be a concern. On the contrary, the `RowData` is very efficient in processing and it supports many data formats, e.g. `JSON`/`CSV`/`Avro` which are all complex and have many config options. > RowType makes the number of compatible Flink versions less The old pipeline does not use the `RowType`, so it should not have compatibility problem. BTW, the Hoodie `Spark` data source also use `Row` as the basic data structure, which is easy for `JSON`/`CSV`/`Avro` source data conversion and effective data handling in the pipeline. ########## File path: hudi-flink/src/main/java/org/apache/hudi/operator/event/BatchWriteSuccessEvent.java ########## @@ -0,0 +1,64 @@ +/* + * 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.operator.event; + +import org.apache.flink.runtime.operators.coordination.OperatorEvent; + +import org.apache.hudi.client.WriteStatus; + +import java.util.List; + +/** + * An operator even to mark successful checkpoint batch write. + */ +public class BatchWriteSuccessEvent implements OperatorEvent { + private static final long serialVersionUID = 1L; + + private final List<WriteStatus> writeStatuses; + private final int taskID; + private final String instantTime; + + /** + * Creates an event. + * + * @param taskID The task ID + * @param instantTime The instant time under which to write the data + * @param writeStatuses The write statues list + */ + public BatchWriteSuccessEvent( Review comment: Removed. ########## File path: hudi-flink/src/main/java/org/apache/hudi/streamer/FlinkStreamerConfig.java ########## @@ -0,0 +1,124 @@ +/* + * 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.streamer; + +import org.apache.hudi.common.model.OverwriteWithLatestAvroPayload; +import org.apache.hudi.common.model.WriteOperationType; +import org.apache.hudi.keygen.SimpleAvroKeyGenerator; + +import com.beust.jcommander.Parameter; +import org.apache.flink.configuration.Configuration; + +import java.util.ArrayList; +import java.util.List; + +/** + * Configurations for Hoodie Flink streamer. + */ +public class FlinkStreamerConfig extends Configuration { + @Parameter(names = {"--kafka-topic"}, description = "Kafka topic name.", required = true) + public String kafkaTopic; + + @Parameter(names = {"--kafka-group-id"}, description = "Kafka consumer group id.", required = true) + public String kafkaGroupId; + + @Parameter(names = {"--kafka-bootstrap-servers"}, description = "Kafka bootstrap.servers.", required = true) + public String kafkaBootstrapServers; + + @Parameter(names = {"--flink-checkpoint-path"}, description = "Flink checkpoint path.") + public String flinkCheckPointPath; + + @Parameter(names = {"--flink-block-retry-times"}, description = "Times to retry when latest instant has not completed.") Review comment: Copied from the old code, how about `instant-retry-times` ? ########## File path: hudi-flink/src/main/java/org/apache/hudi/streamer/HoodieFlinkStreamerV2.java ########## @@ -0,0 +1,103 @@ +/* + * 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.streamer; + +import org.apache.hudi.operator.FlinkOptions; +import org.apache.hudi.operator.StreamWriteOperatorFactory; +import org.apache.hudi.util.StreamerUtil; + +import com.beust.jcommander.JCommander; +import org.apache.flink.configuration.Configuration; +import org.apache.flink.formats.avro.typeutils.AvroSchemaConverter; +import org.apache.flink.formats.json.JsonRowDataDeserializationSchema; +import org.apache.flink.formats.json.TimestampFormat; +import org.apache.flink.runtime.state.filesystem.FsStateBackend; +import org.apache.flink.streaming.api.datastream.DataStream; +import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment; +import org.apache.flink.streaming.connectors.kafka.FlinkKafkaConsumer; +import org.apache.flink.table.data.RowData; +import org.apache.flink.table.runtime.typeutils.InternalTypeInfo; +import org.apache.flink.table.types.logical.LogicalType; +import org.apache.flink.table.types.logical.RowType; + +import java.util.Properties; + +/** + * An Utility which can incrementally consume data from Kafka and apply it to the target table. + * currently, it only support COW table and insert, upsert operation. + */ +public class HoodieFlinkStreamerV2 { + public static void main(String[] args) throws Exception { + StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment(); + + final FlinkStreamerConfig cfg = new FlinkStreamerConfig(); + JCommander cmd = new JCommander(cfg, null, args); + if (cfg.help || args.length == 0) { + cmd.usage(); + System.exit(1); + } + env.enableCheckpointing(cfg.checkpointInterval); + env.getConfig().setGlobalJobParameters(cfg); + // We use checkpoint to trigger write operation, including instant generating and committing, + // There can only be one checkpoint at one time. + env.getCheckpointConfig().setMaxConcurrentCheckpoints(1); + env.disableOperatorChaining(); Review comment: Not necessary, removed. ########## File path: hudi-flink/src/main/java/org/apache/hudi/operator/FlinkOptions.java ########## @@ -0,0 +1,249 @@ +/* + * 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.operator; + +import org.apache.hudi.config.HoodieWriteConfig; +import org.apache.hudi.streamer.FlinkStreamerConfig; +import org.apache.hudi.common.model.OverwriteWithLatestAvroPayload; +import org.apache.hudi.keygen.SimpleAvroKeyGenerator; +import org.apache.hudi.keygen.constant.KeyGeneratorOptions; +import org.apache.hudi.util.StreamerUtil; + +import org.apache.flink.configuration.ConfigOption; +import org.apache.flink.configuration.ConfigOptions; +import org.apache.flink.configuration.Configuration; + +import java.util.Arrays; +import java.util.HashMap; +import java.util.List; +import java.util.Map; + +/** + * Hoodie Flink config options. + * + * <p>It has the options for Hoodie table read and write. It also defines some utilities. + */ +public class FlinkOptions { + private FlinkOptions() { + } + + // ------------------------------------------------------------------------ + // Base Options + // ------------------------------------------------------------------------ + public static final ConfigOption<String> PATH = ConfigOptions + .key("path") + .stringType() + .noDefaultValue() + .withDescription("Base path for the target hoodie table." + + "\nThe path would be created if it does not exist,\n" + + "otherwise a Hoodie table expects to be initialized successfully"); + + public static final ConfigOption<String> PROPS_FILE_PATH = ConfigOptions + .key("properties-file.path") + .stringType() + .noDefaultValue() + .withDescription("Path to properties file on local-fs or dfs, with configurations for \n" + + "hoodie client, schema provider, key generator and data source. For hoodie client props, sane defaults are\n" + + "used, but recommend use to provide basic things like metrics endpoints, hive configs etc. For sources, refer\n" + + "to individual classes, for supported properties"); + + // ------------------------------------------------------------------------ + // Read Options + // ------------------------------------------------------------------------ + public static final ConfigOption<String> READ_SCHEMA_FILE_PATH = ConfigOptions + .key("read.schema.file.path") + .stringType() + .noDefaultValue() + .withDescription("Avro schema file path, the parsed schema is used for deserializing"); + + // ------------------------------------------------------------------------ + // Write Options + // ------------------------------------------------------------------------ + public static final ConfigOption<String> TABLE_NAME = ConfigOptions + .key(HoodieWriteConfig.TABLE_NAME) + .stringType() + .noDefaultValue() + .withDescription("Table name to register to Hive metastore"); + + public static final ConfigOption<String> TABLE_TYPE = ConfigOptions + .key("write.table.type") + .stringType() + .defaultValue("COPY_ON_WRITE") + .withDescription("Type of table to write. COPY_ON_WRITE (or) MERGE_ON_READ"); + + public static final ConfigOption<String> OPERATION = ConfigOptions + .key("write.operation") + .stringType() + .defaultValue("upsert") + .withDescription("The write operation, that this write should do"); + + public static final ConfigOption<String> PRECOMBINE_FIELD = ConfigOptions + .key("write.precombine.field") Review comment: We can, but i would suggest to do this is a separate issue, we need to define some rules for config option name. ########## File path: hudi-flink/src/main/java/org/apache/hudi/operator/StreamWriteFunction.java ########## @@ -0,0 +1,342 @@ +/* + * 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.operator; + +import org.apache.hudi.avro.HoodieAvroUtils; +import org.apache.hudi.client.FlinkTaskContextSupplier; +import org.apache.hudi.client.HoodieFlinkWriteClient; +import org.apache.hudi.client.WriteStatus; +import org.apache.hudi.client.common.HoodieFlinkEngineContext; +import org.apache.hudi.common.config.SerializableConfiguration; +import org.apache.hudi.common.model.HoodieRecord; +import org.apache.hudi.common.model.HoodieRecordPayload; +import org.apache.hudi.common.model.WriteOperationType; +import org.apache.hudi.common.util.ObjectSizeCalculator; +import org.apache.hudi.keygen.KeyGenerator; +import org.apache.hudi.operator.event.BatchWriteSuccessEvent; +import org.apache.hudi.util.StreamerUtil; + +import org.apache.avro.Schema; +import org.apache.avro.generic.GenericRecord; +import org.apache.flink.annotation.VisibleForTesting; +import org.apache.flink.configuration.Configuration; +import org.apache.flink.formats.avro.RowDataToAvroConverters; +import org.apache.flink.runtime.operators.coordination.OperatorEventGateway; +import org.apache.flink.runtime.state.FunctionInitializationContext; +import org.apache.flink.runtime.state.FunctionSnapshotContext; +import org.apache.flink.streaming.api.checkpoint.CheckpointedFunction; +import org.apache.flink.streaming.api.functions.KeyedProcessFunction; +import org.apache.flink.table.types.logical.RowType; +import org.apache.flink.util.Collector; +import org.apache.flink.util.Preconditions; +import org.slf4j.Logger; +import org.slf4j.LoggerFactory; + +import java.io.IOException; +import java.util.ArrayList; +import java.util.Collections; +import java.util.List; +import java.util.Random; +import java.util.concurrent.locks.Condition; +import java.util.concurrent.locks.ReentrantLock; +import java.util.function.BiFunction; + +/** + * Sink function to write the data to the underneath filesystem. + * + * <p><h2>Work Flow</h2> + * + * <p>The function firstly buffers the data as a batch of {@link HoodieRecord}s, + * It flushes(write) the records batch when a Flink checkpoint starts. After a batch has been written successfully, + * the function notifies its operator coordinator {@link StreamWriteOperatorCoordinator} to mark a successful write. + * + * <p><h2>Exactly-once Semantics</h2> + * + * <p>The task implements exactly-once semantics by buffering the data between checkpoints. The operator coordinator + * starts a new instant on the time line when a checkpoint triggers, the coordinator checkpoints always + * start before its operator, so when this function starts a checkpoint, a REQUESTED instant already exists. + * The function process thread then block data buffering and the checkpoint thread starts flushing the existing data buffer. + * When the existing data buffer write successfully, the process thread unblock and start buffering again for the next round checkpoint. + * Because any checkpoint failures would trigger the write rollback, it implements the exactly-once semantics. + * + * <p><h2>Fault Tolerance</h2> + * + * <p>The operator coordinator checks the validity for the last instant when it starts a new one. The operator rolls back + * the written data and throws when any error occurs. This means any checkpoint or task failure would trigger a failover. + * The operator coordinator would try several times when committing the writestatus. + * + * <p>Note: The function task requires the input stream be partitioned by the partition fields to avoid different write tasks + * write to the same file group that conflict. The general case for partition path is a datetime field, + * so the sink task is very possible to have IO bottleneck, the more flexible solution is to shuffle the + * data by the file group IDs. + * + * @param <I> Type of the input record + * @see StreamWriteOperatorCoordinator + */ +public class StreamWriteFunction<K, I, O> + extends KeyedProcessFunction<K, I, O> + implements CheckpointedFunction { + + private static final long serialVersionUID = 1L; + + private static final Logger LOG = LoggerFactory.getLogger(StreamWriteFunction.class); + + /** + * Write buffer for a checkpoint. + */ + private transient List<HoodieRecord> buffer; + + /** + * The buffer lock to control data buffering/flushing. + */ + private transient ReentrantLock bufferLock; + + /** + * The condition to decide whether to add new records into the buffer. + */ + private transient Condition addToBufferCondition; + + /** + * Flag saying whether there is an on-going checkpoint. + */ + private volatile boolean onCheckpointing = false; + + /** + * Config options. + */ + private final Configuration config; + + /** + * Id of current subtask. + */ + private int taskID; + + /** + * Write Client. + */ + private transient HoodieFlinkWriteClient writeClient; + + private transient BiFunction<List<HoodieRecord>, String, List<WriteStatus>> writeFunction; + + /** + * HoodieKey generator. + */ + private transient KeyGenerator keyGenerator; + + /** + * Row type of the input. + */ + private final RowType rowType; + + /** + * Avro schema of the input. + */ + private final Schema avroSchema; + + private transient RowDataToAvroConverters.RowDataToAvroConverter converter; + + /** + * The REQUESTED instant we write the data. + */ + private volatile String currentInstant; + + /** + * Gateway to send operator events to the operator coordinator. + */ + private transient OperatorEventGateway eventGateway; + + /** + * Constructs a StreamingSinkFunction. + * + * @param rowType The input row type + * @param config The config options + */ + public StreamWriteFunction(RowType rowType, Configuration config) { + this.rowType = rowType; + this.avroSchema = org.apache.flink.formats.avro.typeutils + .AvroSchemaConverter.convertToSchema(rowType); + this.config = config; + } + + @Override + public void open(Configuration parameters) throws IOException { + this.taskID = getRuntimeContext().getIndexOfThisSubtask(); + this.keyGenerator = StreamerUtil.createKeyGenerator(HoodieOptions.flatOptions(this.config)); + this.converter = RowDataToAvroConverters.createConverter(this.rowType); + initBuffer(); + initWriteClient(); + initWriteFunction(); + } + + @Override + public void initializeState(FunctionInitializationContext context) { + // no operation + } + + @Override + public void snapshotState(FunctionSnapshotContext functionSnapshotContext) { + bufferLock.lock(); + try { + // Based on the fact that the coordinator starts the checkpoint first, + // it would check the validity. + this.onCheckpointing = true; + this.currentInstant = this.writeClient.getInflightAndRequestedInstant(this.config.get(HoodieOptions.TABLE_TYPE)); + Preconditions.checkNotNull(this.currentInstant, + "No inflight instant when flushing data"); + // wait for the buffer data flush out and request a new instant + flushBuffer(); + // signal the task thread to start buffering + addToBufferCondition.signal(); + } finally { + this.onCheckpointing = false; + bufferLock.unlock(); + } + } + + @Override + public void processElement(I value, KeyedProcessFunction<K, I, O>.Context ctx, Collector<O> out) throws Exception { + bufferLock.lock(); + try { + if (onCheckpointing) { + addToBufferCondition.await(); + } + this.buffer.add(toHoodie(value)); + } finally { + bufferLock.unlock(); + } + } + + @Override + public void close() { + if (this.writeClient != null) { + this.writeClient.close(); + } + } + + // ------------------------------------------------------------------------- + // Getter/Setter + // ------------------------------------------------------------------------- + + @VisibleForTesting + @SuppressWarnings("rawtypes") + public List<HoodieRecord> getBuffer() { + return buffer; + } + + @VisibleForTesting + @SuppressWarnings("rawtypes") + public HoodieFlinkWriteClient getWriteClient() { + return writeClient; + } + + public void setOperatorEventGateway(OperatorEventGateway operatorEventGateway) { + this.eventGateway = operatorEventGateway; + } + + // ------------------------------------------------------------------------- + // Utilities + // ------------------------------------------------------------------------- + + private void initBuffer() { + this.buffer = new ArrayList<>(); + this.bufferLock = new ReentrantLock(); + this.addToBufferCondition = this.bufferLock.newCondition(); + } + + private void initWriteClient() { + HoodieFlinkEngineContext context = + new HoodieFlinkEngineContext( + new SerializableConfiguration(StreamerUtil.getHadoopConf()), + new FlinkTaskContextSupplier(getRuntimeContext())); + + writeClient = new HoodieFlinkWriteClient<>(context, StreamerUtil.getHoodieClientConfig(this.config)); + } + + private void initWriteFunction() { + final String writeOperation = this.config.get(HoodieOptions.OPERATION); + switch (WriteOperationType.fromValue(writeOperation)) { + case INSERT: + this.writeFunction = (records, instantTime) -> this.writeClient.insert(records, instantTime); + break; + case UPSERT: + this.writeFunction = (records, instantTime) -> this.writeClient.upsert(records, instantTime); + break; + default: + throw new RuntimeException("Unsupported write operation : " + writeOperation); + } + } + + // Keep for mini-batch write. + private static class BufferSizeEstimator { Review comment: Removed. ########## File path: hudi-flink/src/test/resources/test_source.data ########## @@ -0,0 +1,8 @@ +{"uuid": "id1", "name": "Danny", "age": 23, "ts": "1970-01-01T00:00:01", "partition": "par1"} Review comment: No, i'm old ---------------------------------------------------------------- This is an automated message from the Apache Git Service. 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