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https://issues.apache.org/jira/browse/BEAM-9977?focusedWorklogId=440900&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-440900
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ASF GitHub Bot logged work on BEAM-9977:
----------------------------------------
Author: ASF GitHub Bot
Created on: 03/Jun/20 17:35
Start Date: 03/Jun/20 17:35
Worklog Time Spent: 10m
Work Description: boyuanzz commented on a change in pull request #11749:
URL: https://github.com/apache/beam/pull/11749#discussion_r434739659
##########
File path:
sdks/java/io/kafka/src/main/java/org/apache/beam/sdk/io/kafka/ReadFromKafkaViaSDF.java
##########
@@ -0,0 +1,697 @@
+/*
+ * 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 com.google.auto.value.AutoValue;
+import java.util.Map;
+import javax.annotation.Nullable;
+import org.apache.beam.sdk.coders.Coder;
+import org.apache.beam.sdk.coders.CoderRegistry;
+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.Element;
+import org.apache.beam.sdk.transforms.DoFn.GetRestrictionCoder;
+import org.apache.beam.sdk.transforms.DoFn.OutputReceiver;
+import org.apache.beam.sdk.transforms.DoFn.ProcessElement;
+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.OffsetRangeTracker;
+import org.apache.beam.sdk.transforms.splittabledofn.RestrictionTracker;
+import org.apache.beam.sdk.transforms.splittabledofn.WatermarkEstimator;
+import
org.apache.beam.sdk.transforms.splittabledofn.WatermarkEstimators.MonotonicallyIncreasing;
+import org.apache.beam.sdk.values.PCollection;
+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 beam blog post: https://beam.apache.org/blog/splittable-do-fn/ and
design
+ * doc:https://s.apache.org/beam-fn-api. The major difference from {@link
KafkaIO.Read} is, {@link
+ * ReadFromKafkaViaSDF} 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
ReadFromKafkaViaSDF}.
+ *
+ * <h3>Common Kafka Consumer Configurations</h3>
+ *
+ * <p>Most Kafka consumer configurations are similar to {@link KafkaIO.Read}:
+ *
+ * <ul>
+ * <li>{@link ReadFromKafkaViaSDF#getConsumerConfig()} is the same as {@link
+ * KafkaIO.Read#getConsumerConfig()}.
+ * <li>{@link ReadFromKafkaViaSDF#getConsumerFactoryFn()} is the same as
{@link
+ * KafkaIO.Read#getConsumerFactoryFn()}.
+ * <li>{@link ReadFromKafkaViaSDF#getOffsetConsumerConfig()} is the same as
{@link
+ * KafkaIO.Read#getOffsetConsumerConfig()}.
+ * <li>{@link ReadFromKafkaViaSDF#getKeyCoder()} is the same as {@link
+ * KafkaIO.Read#getKeyCoder()}.
+ * <li>{@link ReadFromKafkaViaSDF#getValueCoder()} is the same as {@link
+ * KafkaIO.Read#getValueCoder()}.
+ * <li>{@link ReadFromKafkaViaSDF#getKeyDeserializerProvider()} is the same
as {@link
+ * KafkaIO.Read#getKeyDeserializerProvider()}.
+ * <li>{@link ReadFromKafkaViaSDF#getValueDeserializerProvider()} is the
same as {@link
+ * KafkaIO.Read#getValueDeserializerProvider()}.
+ * <li>{@link ReadFromKafkaViaSDF#isCommitOffsetEnabled()} means the same as
{@link
+ * KafkaIO.Read#isCommitOffsetsInFinalizeEnabled()}.
+ * </ul>
+ *
+ * <p>For example, to create a basic {@link ReadFromKafkaViaSDF} transform:
+ *
+ * <pre>{@code
+ * pipeline
+ * .apply(Create.of(KafkaSourceDescription.of(new TopicPartition("my_topic",
1))))
+ * .apply(ReadFromKafkaViaSDF.create()
+ * .withBootstrapServers("broker_1:9092,broker_2:9092")
+ * .withKeyDeserializer(LongDeserializer.class).
+ * .withValueDeserializer(StringDeserializer.class));
+ * }</pre>
+ *
+ * <h3>Configurations of {@link ReadFromKafkaViaSDF}</h3>
+ *
+ * <p>Except configurations of Kafka Consumer, there are some other
configurations which are related
+ * to processing records.
+ *
+ * <p>{@link ReadFromKafkaViaSDF#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
+ * ReadFromKafkaViaSDF#commitOffsets()} will be ignored.
+ *
+ * <p>{@link
ReadFromKafkaViaSDF#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
+ * ReadFromKafkaViaSDF#withProcessingTime()}, {@link
ReadFromKafkaViaSDF#withCreateTime()} and
+ * {@link ReadFromKafkaViaSDF#withLogAppendTime()}.
+ *
+ * <p>For example, to create a {@link ReadFromKafkaViaSDF} with these
configurations:
+ *
+ * <pre>{@code
+ * pipeline
+ * .apply(Create.of(KafkaSourceDescription.of(new TopicPartition("my_topic",
1))))
+ * .apply(ReadFromKafkaViaSDF.create()
+ * .withBootstrapServers("broker_1:9092,broker_2:9092")
+ * .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 {@link KafkaSourceDescription#getStartOffset()} is set, use this
offset as start.
+ * <li>If {@link KafkaSourceDescription#getStartReadTime()} 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 {@link
OffsetRangeTracker}
+ * 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 estimated watermark is computed by {@link MonotonicallyIncreasing}
based on output timestamps
+ * per {@link KafkaSourceDescription}.
+ */
+@AutoValue
+public abstract class ReadFromKafkaViaSDF<K, V>
Review comment:
Hi Ismaël, thanks for your review and comments!
Yes I thought about using `KafkaIO.Read` as element and there are some
pushbacks from my side:
1. `KafkaIO.Read` is kind of heavy. For me, `KafkaIO.Read` is more like a
configuration + element. For me, the element should be something you may only
know about it during the pipeline execution time. So I want to isolate
element-like into `KafkaSourceDescription`.
2. For the case you mentioned that reading from different clusters, I
thought about it and not sure whether it would be a common case for reading
from Kafka. So I sent out an email titled with `[Discuss] Build Kafka read
transform on top of SplittableDoFn` to our dev mailing list to figure what
could be an element in common. So far I didn't hear back from the community for
the need of reading from different clusters.
3. We also consider x-lang usage for `ReadFromKafkaViaSDF`, which requires
we can encode and decode the element over the wire. So I want to make the
element as low weight as possible.
For the concern of increasing needs of element, we want to have
`KafkaSourceDescription` easy to be extended, as well as the coder.
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Issue Time Tracking
-------------------
Worklog Id: (was: 440900)
Time Spent: 7h 40m (was: 7.5h)
> Build Kafka Read on top of Java SplittableDoFn
> ----------------------------------------------
>
> Key: BEAM-9977
> URL: https://issues.apache.org/jira/browse/BEAM-9977
> Project: Beam
> Issue Type: New Feature
> Components: io-java-kafka
> Reporter: Boyuan Zhang
> Assignee: Boyuan Zhang
> Priority: P2
> Time Spent: 7h 40m
> Remaining Estimate: 0h
>
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