boyuanzz commented on a change in pull request #11749: URL: https://github.com/apache/beam/pull/11749#discussion_r444564026
########## File path: sdks/java/io/kafka/src/main/java/org/apache/beam/sdk/io/kafka/ReadViaSDF.java ########## @@ -0,0 +1,861 @@ +/* + * 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.beam.sdk.io.kafka; + +import static org.apache.beam.vendor.guava.v26_0_jre.com.google.common.base.Preconditions.checkArgument; +import static org.apache.beam.vendor.guava.v26_0_jre.com.google.common.base.Preconditions.checkState; + +import com.google.auto.value.AutoValue; +import java.util.ArrayList; +import java.util.HashMap; +import java.util.Map; +import java.util.Optional; +import java.util.concurrent.TimeUnit; +import javax.annotation.Nullable; +import org.apache.beam.sdk.annotations.Experimental; +import org.apache.beam.sdk.annotations.Experimental.Kind; +import org.apache.beam.sdk.coders.Coder; +import org.apache.beam.sdk.coders.CoderRegistry; +import org.apache.beam.sdk.coders.KvCoder; +import org.apache.beam.sdk.io.kafka.KafkaIOUtils.MovingAvg; +import org.apache.beam.sdk.io.kafka.KafkaSourceDescription.Schemas; +import org.apache.beam.sdk.io.kafka.KafkaUnboundedReader.TimestampPolicyContext; +import org.apache.beam.sdk.io.range.OffsetRange; +import org.apache.beam.sdk.options.ExperimentalOptions; +import org.apache.beam.sdk.transforms.DoFn; +import org.apache.beam.sdk.transforms.DoFn.UnboundedPerElement; +import org.apache.beam.sdk.transforms.PTransform; +import org.apache.beam.sdk.transforms.ParDo; +import org.apache.beam.sdk.transforms.SerializableFunction; +import org.apache.beam.sdk.transforms.splittabledofn.GrowableOffsetRangeTracker; +import org.apache.beam.sdk.transforms.splittabledofn.ManualWatermarkEstimator; +import org.apache.beam.sdk.transforms.splittabledofn.OffsetRangeTracker; +import org.apache.beam.sdk.transforms.splittabledofn.RestrictionTracker; +import org.apache.beam.sdk.transforms.splittabledofn.RestrictionTracker.HasProgress; +import org.apache.beam.sdk.transforms.splittabledofn.WatermarkEstimator; +import org.apache.beam.sdk.transforms.splittabledofn.WatermarkEstimators.Manual; +import org.apache.beam.sdk.transforms.splittabledofn.WatermarkEstimators.MonotonicallyIncreasing; +import org.apache.beam.sdk.transforms.splittabledofn.WatermarkEstimators.WallTime; +import org.apache.beam.sdk.values.KV; +import org.apache.beam.sdk.values.PCollection; +import org.apache.beam.sdk.values.Row; +import org.apache.beam.vendor.guava.v26_0_jre.com.google.common.annotations.VisibleForTesting; +import org.apache.beam.vendor.guava.v26_0_jre.com.google.common.base.Supplier; +import org.apache.beam.vendor.guava.v26_0_jre.com.google.common.base.Suppliers; +import org.apache.beam.vendor.guava.v26_0_jre.com.google.common.collect.ImmutableList; +import org.apache.beam.vendor.guava.v26_0_jre.com.google.common.collect.ImmutableMap; +import org.apache.beam.vendor.guava.v26_0_jre.com.google.common.io.Closeables; +import org.apache.kafka.clients.consumer.Consumer; +import org.apache.kafka.clients.consumer.ConsumerConfig; +import org.apache.kafka.clients.consumer.ConsumerRecord; +import org.apache.kafka.clients.consumer.ConsumerRecords; +import org.apache.kafka.common.TopicPartition; +import org.apache.kafka.common.serialization.Deserializer; +import org.apache.kafka.common.utils.AppInfoParser; +import org.joda.time.Duration; +import org.joda.time.Instant; +import org.slf4j.Logger; +import org.slf4j.LoggerFactory; + +/** + * A {@link PTransform} that takes a PCollection of {@link KafkaSourceDescription} as input and + * outputs a PCollection of {@link KafkaRecord}. The core implementation is based on {@code + * SplittableDoFn}. For more details about the concept of {@code SplittableDoFn}, please refer to + * the <a href="https://beam.apache.org/blog/splittable-do-fn/";>blog post</a> and <a + * href="https://s.apache.org/beam-fn-api";>design doc</a>. The major difference from {@link + * KafkaIO.Read} is, {@link ReadViaSDF} doesn't require source descriptions(e.g., {@link + * KafkaIO.Read#getTopicPartitions()}, {@link KafkaIO.Read#getTopics()}, {@link + * KafkaIO.Read#getStartReadTime()}, etc.) during the pipeline construction time. Instead, the + * pipeline can populate these source descriptions during runtime. For example, the pipeline can + * query Kafka topics from BigQuery table and read these topics via {@link ReadViaSDF}. + * + * <h3>Common Kafka Consumer Configurations</h3> + * + * <p>Most Kafka consumer configurations are similar to {@link KafkaIO.Read}: + * + * <ul> + * <li>{@link ReadViaSDF#getConsumerConfig()} is the same as {@link + * KafkaIO.Read#getConsumerConfig()}. + * <li>{@link ReadViaSDF#getConsumerFactoryFn()} is the same as {@link + * KafkaIO.Read#getConsumerFactoryFn()}. + * <li>{@link ReadViaSDF#getOffsetConsumerConfig()} is the same as {@link + * KafkaIO.Read#getOffsetConsumerConfig()}. + * <li>{@link ReadViaSDF#getKeyCoder()} is the same as {@link KafkaIO.Read#getKeyCoder()}. + * <li>{@link ReadViaSDF#getValueCoder()} is the same as {@link KafkaIO.Read#getValueCoder()}. + * <li>{@link ReadViaSDF#getKeyDeserializerProvider()} is the same as {@link + * KafkaIO.Read#getKeyDeserializerProvider()}. + * <li>{@link ReadViaSDF#getValueDeserializerProvider()} is the same as {@link + * KafkaIO.Read#getValueDeserializerProvider()}. + * <li>{@link ReadViaSDF#isCommitOffsetEnabled()} means the same as {@link + * KafkaIO.Read#isCommitOffsetsInFinalizeEnabled()}. + * </ul> + * + * <p>For example, to create a basic {@link ReadViaSDF} transform: + * + * <pre>{@code + * pipeline + * .apply(Create.of(KafkaSourceDescription.of(new TopicPartition("topic", 1))) + * .apply(KafkaIO.readAll() + * .withBootstrapServers("broker_1:9092,broker_2:9092") + * .withKeyDeserializer(LongDeserializer.class). + * .withValueDeserializer(StringDeserializer.class)); + * + * Note that the {@code bootstrapServers} can also be populated from {@link KafkaSourceDescription}: + * pipeline + * .apply(Create.of( + * KafkaSourceDescription.of( + * new TopicPartition("topic", 1), + * null, + * null, + * ImmutableList.of("broker_1:9092", "broker_2:9092")) + * .apply(KafkaIO.readAll() + * .withKeyDeserializer(LongDeserializer.class). + * .withValueDeserializer(StringDeserializer.class)); + * + * }</pre> + * + * <h3>Configurations of {@link ReadViaSDF}</h3> + * + * <p>Except configurations of Kafka Consumer, there are some other configurations which are related + * to processing records. + * + * <p>{@link ReadViaSDF#commitOffsets()} enables committing offset after processing the record. Note + * that if {@code isolation.level} is set to "read_committed" or {@link + * ConsumerConfig#ENABLE_AUTO_COMMIT_CONFIG} is set in the consumer config, the {@link + * ReadViaSDF#commitOffsets()} will be ignored. + * + * <p>{@link ReadViaSDF#withExtractOutputTimestampFn(SerializableFunction)} asks for a function + * which takes a {@link KafkaRecord} as input and outputs outputTimestamp. This function is used to + * produce output timestamp per {@link KafkaRecord}. There are three built-in types: {@link + * ReadViaSDF#withProcessingTime()}, {@link ReadViaSDF#withCreateTime()} and {@link + * ReadViaSDF#withLogAppendTime()}. + * + * <p>For example, to create a {@link ReadViaSDF} with these configurations: + * + * <pre>{@code + * pipeline + * .apply(Create.of( + * KafkaSourceDescription.of( + * new TopicPartition("topic", 1), + * null, + * null, + * ImmutableList.of("broker_1:9092", "broker_2:9092")) + * .apply(KafkaIO.readAll() + * .withKeyDeserializer(LongDeserializer.class). + * .withValueDeserializer(StringDeserializer.class) + * .withProcessingTime() + * .commitOffsets()); + * + * }</pre> + * + * <h3>Read from {@link KafkaSourceDescription}</h3> + * + * {@link ReadFromKafkaDoFn} implements the logic of reading from Kafka. The element is a {@link + * KafkaSourceDescription}, and the restriction is an {@link OffsetRange} which represents record + * offset. A {@link GrowableOffsetRangeTracker} is used to track an {@link OffsetRange} ended with + * {@code Long.MAX_VALUE}. For a finite range, a {@link OffsetRangeTracker} is created. + * + * <h4>Initialize Restriction</h4> + * + * {@link ReadFromKafkaDoFn#initialRestriction(KafkaSourceDescription)} creates an initial range for + * a input element {@link KafkaSourceDescription}. The end of range will be initialized as {@code + * Long.MAX_VALUE}. For the start of the range: + * + * <ul> + * <li>If {@code startReadOffset} in {@link KafkaSourceDescription} is set, use this offset as + * start. + * <li>If {@code startReadTime} in {@link KafkaSourceDescription} is set, seek the start offset + * based on this time. + * <li>Otherwise, the last committed offset + 1 will be returned by {@link + * Consumer#position(TopicPartition)} as the start. + * </ul> + * + * <h4>Initial Split</h4> + * + * <p>There is no initial split for now. + * + * <h4>Checkpoint and Resume Processing</h4> + * + * <p>There are 2 types of checkpoint here: self-checkpoint which invokes by the DoFn and + * system-checkpoint which is issued by the runner via {@link + * org.apache.beam.model.fnexecution.v1.BeamFnApi.ProcessBundleSplitRequest}. Every time the + * consumer gets empty response from {@link Consumer#poll(long)}, {@link ReadFromKafkaDoFn} will + * checkpoint at current {@link KafkaSourceDescription} and move to process the next element. These + * deferred elements will be resumed by the runner as soon as possible. + * + * <h4>Progress and Size</h4> + * + * <p>The progress is provided by {@link GrowableOffsetRangeTracker} or per {@link + * KafkaSourceDescription}. For an infinite {@link OffsetRange}, a Kafka {@link Consumer} is used in + * the {@link GrowableOffsetRangeTracker} as the {@link + * GrowableOffsetRangeTracker.RangeEndEstimator} to poll the latest offset. Please refer to {@link + * ReadFromKafkaDoFn.KafkaLatestOffsetEstimator} for details. + * + * <p>The size is computed by {@link ReadFromKafkaDoFn#getSize(KafkaSourceDescription, + * OffsetRange).} A {@link KafkaIOUtils.MovingAvg} is used to track the average size of kafka + * records. + * + * <h4>Track Watermark</h4> + * + * The {@link WatermarkEstimator} is created by {@link #getCreateWatermarkEstimatorFn()}. The + * estimated watermark is computed by this {@link WatermarkEstimator} based on output timestamps + * computed by {@link #getExtractOutputTimestampFn()} (SerializableFunction)}. The default + * configuration is using {@link #withProcessingTime()} as {@code extractTimestampFn} and {@link + * #withMonotonicallyIncreasingWatermarkEstimator()} as {@link WatermarkEstimator}. + */ +@Experimental(Kind.PORTABILITY) +@AutoValue +abstract class ReadViaSDF<K, V, WatermarkEstimatorT extends WatermarkEstimator<Instant>> + extends PTransform<PCollection<KafkaSourceDescription>, PCollection<KafkaRecord<K, V>>> { + + private static final Logger LOG = LoggerFactory.getLogger(ReadViaSDF.class); + + abstract Map<String, Object> getConsumerConfig(); + + @Nullable + abstract Map<String, Object> getOffsetConsumerConfig(); + + @Nullable + abstract DeserializerProvider getKeyDeserializerProvider(); + + @Nullable + abstract DeserializerProvider getValueDeserializerProvider(); + + @Nullable + abstract Coder<K> getKeyCoder(); + + @Nullable + abstract Coder<V> getValueCoder(); + + abstract SerializableFunction<Map<String, Object>, Consumer<byte[], byte[]>> + getConsumerFactoryFn(); + + @Nullable + abstract SerializableFunction<KafkaRecord<K, V>, Instant> getExtractOutputTimestampFn(); + + @Nullable + abstract SerializableFunction<Instant, WatermarkEstimatorT> getCreateWatermarkEstimatorFn(); + + abstract boolean isCommitOffsetEnabled(); + + @Nullable + abstract TimestampPolicyFactory<K, V> getTimestampPolicyFactory(); + + abstract Builder<K, V, WatermarkEstimatorT> toBuilder(); + + @AutoValue.Builder + abstract static class Builder<K, V, WatermarkEstimatorT extends WatermarkEstimator<Instant>> { + abstract Builder<K, V, WatermarkEstimatorT> setConsumerConfig(Map<String, Object> config); + + abstract Builder<K, V, WatermarkEstimatorT> setOffsetConsumerConfig( + Map<String, Object> offsetConsumerConfig); + + abstract Builder<K, V, WatermarkEstimatorT> setConsumerFactoryFn( + SerializableFunction<Map<String, Object>, Consumer<byte[], byte[]>> consumerFactoryFn); + + abstract Builder<K, V, WatermarkEstimatorT> setKeyDeserializerProvider( + DeserializerProvider deserializerProvider); + + abstract Builder<K, V, WatermarkEstimatorT> setValueDeserializerProvider( + DeserializerProvider deserializerProvider); + + abstract Builder<K, V, WatermarkEstimatorT> setKeyCoder(Coder<K> keyCoder); + + abstract Builder<K, V, WatermarkEstimatorT> setValueCoder(Coder<V> valueCoder); + + abstract Builder<K, V, WatermarkEstimatorT> setExtractOutputTimestampFn( + SerializableFunction<KafkaRecord<K, V>, Instant> fn); + + abstract Builder<K, V, WatermarkEstimatorT> setCreateWatermarkEstimatorFn( + SerializableFunction<Instant, WatermarkEstimatorT> fn); + + abstract Builder<K, V, WatermarkEstimatorT> setCommitOffsetEnabled(boolean commitOffsetEnabled); + + abstract Builder<K, V, WatermarkEstimatorT> setTimestampPolicyFactory( + TimestampPolicyFactory<K, V> policy); + + abstract ReadViaSDF<K, V, WatermarkEstimatorT> build(); + } + + public static <K, V, WatermarkEstimatorT extends WatermarkEstimator<Instant>> + ReadViaSDF<K, V, WatermarkEstimatorT> read() { + return new AutoValue_ReadViaSDF.Builder<K, V, WatermarkEstimatorT>() + .setConsumerFactoryFn(KafkaIOUtils.KAFKA_CONSUMER_FACTORY_FN) + .setConsumerConfig(KafkaIOUtils.DEFAULT_CONSUMER_PROPERTIES) + .setCommitOffsetEnabled(false) + .build() + .withProcessingTime() + .withMonotonicallyIncreasingWatermarkEstimator(); + } + + // Note that if the bootstrapServers is set here but also populated with the element, the element + // will override the bootstrapServers from the config. + public ReadViaSDF<K, V, WatermarkEstimatorT> withBootstrapServers(String bootstrapServers) { + return withConsumerConfigUpdates( + ImmutableMap.of(ConsumerConfig.BOOTSTRAP_SERVERS_CONFIG, bootstrapServers)); + } + + public ReadViaSDF<K, V, WatermarkEstimatorT> withKeyDeserializerProvider( + DeserializerProvider<K> deserializerProvider) { + return toBuilder().setKeyDeserializerProvider(deserializerProvider).build(); + } + + public ReadViaSDF<K, V, WatermarkEstimatorT> withValueDeserializerProvider( + DeserializerProvider<V> deserializerProvider) { + return toBuilder().setValueDeserializerProvider(deserializerProvider).build(); + } + + public ReadViaSDF<K, V, WatermarkEstimatorT> withKeyDeserializer( + Class<? extends Deserializer<K>> keyDeserializer) { + return withKeyDeserializerProvider(LocalDeserializerProvider.of(keyDeserializer)); + } + + public ReadViaSDF<K, V, WatermarkEstimatorT> withValueDeserializer( + Class<? extends Deserializer<V>> valueDeserializer) { + return withValueDeserializerProvider(LocalDeserializerProvider.of(valueDeserializer)); + } + + public ReadViaSDF<K, V, WatermarkEstimatorT> withKeyDeserializerAndCoder( + Class<? extends Deserializer<K>> keyDeserializer, Coder<K> keyCoder) { + return withKeyDeserializer(keyDeserializer).toBuilder().setKeyCoder(keyCoder).build(); + } + + public ReadViaSDF<K, V, WatermarkEstimatorT> withValueDeserializerAndCoder( + Class<? extends Deserializer<V>> valueDeserializer, Coder<V> valueCoder) { + return withValueDeserializer(valueDeserializer).toBuilder().setValueCoder(valueCoder).build(); + } + + public ReadViaSDF<K, V, WatermarkEstimatorT> withConsumerFactoryFn( + SerializableFunction<Map<String, Object>, Consumer<byte[], byte[]>> consumerFactoryFn) { + return toBuilder().setConsumerFactoryFn(consumerFactoryFn).build(); + } + + public ReadViaSDF<K, V, WatermarkEstimatorT> withConsumerConfigUpdates( + Map<String, Object> configUpdates) { + Map<String, Object> config = + KafkaIOUtils.updateKafkaProperties(getConsumerConfig(), configUpdates); + return toBuilder().setConsumerConfig(config).build(); + } + + public ReadViaSDF<K, V, WatermarkEstimatorT> withExtractOutputTimestampFn( + SerializableFunction<KafkaRecord<K, V>, Instant> fn) { + return toBuilder().setExtractOutputTimestampFn(fn).build(); + } + + public ReadViaSDF<K, V, WatermarkEstimatorT> withCreatWatermarkEstimatorFn( + SerializableFunction<Instant, WatermarkEstimatorT> fn) { + return toBuilder().setCreateWatermarkEstimatorFn(fn).build(); + } + + public ReadViaSDF<K, V, WatermarkEstimatorT> withLogAppendTime() { + return withExtractOutputTimestampFn(ExtractOutputTimestampFns.useLogAppendTime()); + } + + public ReadViaSDF<K, V, WatermarkEstimatorT> withProcessingTime() { + return withExtractOutputTimestampFn(ExtractOutputTimestampFns.useProcessingTime()); + } + + public ReadViaSDF<K, V, WatermarkEstimatorT> withCreateTime() { + return withExtractOutputTimestampFn(ExtractOutputTimestampFns.useCreateTime()); + } + + public ReadViaSDF<K, V, WatermarkEstimatorT> withWallTimeWatermarkEstimator() { + return withCreatWatermarkEstimatorFn( + state -> { + return (WatermarkEstimatorT) new WallTime(state); + }); + } + + public ReadViaSDF<K, V, WatermarkEstimatorT> withMonotonicallyIncreasingWatermarkEstimator() { + return withCreatWatermarkEstimatorFn( + state -> { + return (WatermarkEstimatorT) new MonotonicallyIncreasing(state); + }); + } + + public ReadViaSDF<K, V, WatermarkEstimatorT> withManualWatermarkEstimator() { + return withCreatWatermarkEstimatorFn( + state -> { + return (WatermarkEstimatorT) new Manual(state); + }); + } + + // If a transactional producer is used and it's desired to only read records from committed + // transaction, it's recommended to set read_committed. Otherwise, read_uncommitted is the default + // value. + public ReadViaSDF<K, V, WatermarkEstimatorT> withReadCommitted() { + return withConsumerConfigUpdates(ImmutableMap.of("isolation.level", "read_committed")); + } + + public ReadViaSDF<K, V, WatermarkEstimatorT> commitOffsets() { + return toBuilder().setCommitOffsetEnabled(true).build(); + } + + public ReadViaSDF<K, V, WatermarkEstimatorT> withOffsetConsumerConfigOverrides( + Map<String, Object> offsetConsumerConfig) { + return toBuilder().setOffsetConsumerConfig(offsetConsumerConfig).build(); + } + + public ReadViaSDF<K, V, WatermarkEstimatorT> withConsumerConfigOverrides( + Map<String, Object> consumerConfig) { + return toBuilder().setConsumerConfig(consumerConfig).build(); + } + + ReadViaSDFExternally forExternalBuild() { + return new ReadViaSDFExternally(this); + } + + private static class ReadViaSDFExternally< + K, V, WatermarkEstimatorT extends WatermarkEstimator<Instant>> + extends PTransform<PCollection<Row>, PCollection<KV<K, V>>> { + + private final ReadViaSDF<K, V, WatermarkEstimatorT> readViaSDF; + + ReadViaSDFExternally(ReadViaSDF read) { + readViaSDF = read; + } + + @Override + public PCollection<KV<K, V>> expand(PCollection<Row> input) { + return input + .apply( + ParDo.of( + new DoFn<Row, KafkaSourceDescription>() { + @ProcessElement + public void processElement( + @Element Row row, OutputReceiver<KafkaSourceDescription> outputReceiver) { + TopicPartition topicPartition = + new TopicPartition( + row.getString(Schemas.TOPIC), row.getInt32(Schemas.PARTITION)); + Instant startReadTime = + row.getInt64(Schemas.START_READ_TIME) != null + ? Instant.ofEpochMilli(row.getInt64(Schemas.START_READ_TIME)) + : null; + outputReceiver.output( + KafkaSourceDescription.of( + topicPartition, + row.getInt64(Schemas.START_READ_OFFSET), + startReadTime, + new ArrayList<>(row.getArray(Schemas.BOOTSTRAP_SERVERS)))); + } + })) + .apply(readViaSDF) + .apply( + ParDo.of( + new DoFn<KafkaRecord<K, V>, KV<K, V>>() { + @ProcessElement + public void processElement( + @Element KafkaRecord element, OutputReceiver<KV<K, V>> outputReceiver) { + outputReceiver.output(element.getKV()); + } + })) + .setCoder(KvCoder.<K, V>of(readViaSDF.getKeyCoder(), readViaSDF.getValueCoder())); + } + } + + ReadViaSDF<K, V, WatermarkEstimatorT> withTimestampPolicyFactory( + TimestampPolicyFactory<K, V> timestampPolicyFactory) { + return toBuilder().setTimestampPolicyFactory(timestampPolicyFactory).build(); + } + + @Override + public PCollection<KafkaRecord<K, V>> expand(PCollection<KafkaSourceDescription> input) { + checkArgument( + ExperimentalOptions.hasExperiment(input.getPipeline().getOptions(), "beam_fn_api"), + "The ReadFromKafkaViaSDF can only used when beam_fn_api is enabled."); Review comment: It should be `ReadAll`. ---------------------------------------------------------------- This is an automated message from the Apache Git Service. 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