chamikaramj commented on code in PR #24799:
URL: https://github.com/apache/beam/pull/24799#discussion_r1092648906


##########
examples/java/src/main/java/org/apache/beam/examples/io/examplekafkaread/ExampleKafkaReadIO.java:
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@@ -0,0 +1,134 @@
+/*
+ * 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.examples.io.examplekafkaread;
+
+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.ArrayList;
+import java.util.List;
+import java.util.Map;
+import org.apache.beam.sdk.annotations.Experimental;
+import org.apache.beam.sdk.annotations.Experimental.Kind;
+import org.apache.beam.sdk.transforms.Impulse;
+import org.apache.beam.sdk.transforms.PTransform;
+import org.apache.beam.sdk.transforms.ParDo;
+import org.apache.beam.sdk.values.KV;
+import org.apache.beam.sdk.values.PBegin;
+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.kafka.clients.consumer.ConsumerConfig;
+import org.checkerframework.checker.nullness.qual.NonNull;
+import org.checkerframework.dataflow.qual.Pure;
+
+/**
+ * An example unbounded SDF IO, using Kafka as an underlying source. This IO 
deliberately has a
+ * minimal set of Kafka features, and exists as an example of how to write an 
unbounded SDF source.
+ *
+ * <p>This IO should not be used in pipelines, and has no guarantees for 
quality, correctness, or
+ * performance.
+ *
+ * <p>This IO was generated as a pared down version of KafkaIO, and should act 
to consume
+ * KV<byte[],byte[]> pairs from Kafka In practice, this IO would be used 
thusly: pipeline
+ * .apply(ExampleKafkaReadIO.read() 
.withBootstrapServers("broker_1:9092,broker_2:9092")
+ * .withTopics(ImmutableList.of("my_topic"))) .apply(Some Other Transforms);
+ */
+public class ExampleKafkaReadIO {
+
+  public static Read read() {
+    return new AutoValue_ExampleKafkaReadIO_Read.Builder()
+        .setTopics(new ArrayList<>())
+        .setConsumerConfig(ExampleKafkaReadIOUtils.DEFAULT_CONSUMER_PROPERTIES)
+        .build();
+  }
+
+  @AutoValue
+  @AutoValue.CopyAnnotations
+  public abstract static class Read extends PTransform<PBegin, 
PCollection<KV<byte[], byte[]>>> {
+
+    @Pure
+    abstract Map<String, Object> getConsumerConfig();
+
+    @Pure
+    abstract List<String> getTopics();
+
+    abstract Read.Builder toBuilder();
+
+    @Experimental(Kind.PORTABILITY)
+    @AutoValue.Builder
+    abstract static class Builder {
+      abstract Builder setConsumerConfig(Map<String, Object> config);
+
+      abstract Builder setTopics(List<String> topics);
+
+      abstract Read build();
+    }
+
+    /**
+     * This expand method is characteristic of many top level expands for IOs. 
It validates required
+     * parameters and configurations, and then it applies a series of DoFns to 
actually execute the
+     * read or write. It is typical to have multiple DoFns here, as frequently 
an IO needs to

Review Comment:
   How about:
   s\\
   "It is typical to have multiple DoFns here , as frequently an IO needs to 
determine what to read from the configuration before it actually reads"
   \\"It's typical for I/O connector transforms to be composite transforms 
since I/O connectors usually requires multiple computation units that have to 
be separated out for correctness or efficiency"



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