/*
 * Copyright 2016 Red Hat Inc.
 *
 * Licensed 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 io.vertx.kafka.client.consumer;

import io.vertx.codegen.annotations.Fluent;
import io.vertx.codegen.annotations.GenIgnore;
import io.vertx.codegen.annotations.VertxGen;
import io.vertx.core.AsyncResult;
import io.vertx.core.Handler;
import io.vertx.core.Vertx;
import io.vertx.core.streams.ReadStream;
import io.vertx.kafka.client.common.PartitionInfo;
import io.vertx.kafka.client.common.TopicPartition;
import io.vertx.kafka.client.consumer.impl.KafkaConsumerImpl;
import org.apache.kafka.clients.consumer.Consumer;

import java.util.HashMap;
import java.util.List;
import java.util.Map;
import java.util.Properties;
import java.util.Set;

/**
 * Vert.x Kafka consumer.
 * <p>
 * You receive Kafka records by providing a {@link KafkaConsumer#handler(Handler)}. As messages arrive the handler
 * will be called with the records.
 * <p>
 * The {@link #pause()} and {@link #resume()} provides global control over reading the records from the consumer.
 * <p>
 * The {@link #pause(Set)} and {@link #resume(Set)} provides finer grained control over reading records
 * for specific Topic/Partition, these are Kafka's specific operations.
 */
@VertxGen
public interface KafkaConsumer<K, V> extends ReadStream<KafkaConsumerRecord<K, V>> {

  /**
   * Create a new KafkaConsumer instance from a native {@link Consumer}.
   *
   * @param vertx Vert.x instance to use
   * @param consumer the Kafka consumer to wrap
   * @return  an instance of the KafkaConsumer
   */
  @GenIgnore
  static <K, V> KafkaConsumer<K, V> create(Vertx vertx, Consumer<K, V> consumer) {
    KafkaReadStream<K, V> stream = KafkaReadStream.create(vertx, consumer);
    return new KafkaConsumerImpl<K, V>(stream);
  }

  /**
   * Create a new KafkaConsumer instance
   *
   * @param vertx Vert.x instance to use
   * @param config Kafka consumer configuration
   * @return  an instance of the KafkaConsumer
   */
  static <K, V> KafkaConsumer<K, V> create(Vertx vertx, Map<String, String> config) {
    KafkaReadStream<K, V> stream = KafkaReadStream.create(vertx, new HashMap<>(config));
    return new KafkaConsumerImpl<>(stream).registerCloseHook();
  }

  /**
   * Create a new KafkaConsumer instance
   *
   * @param vertx Vert.x instance to use
   * @param config  Kafka consumer configuration
   * @param keyType class type for the key deserialization
   * @param valueType class type for the value deserialization
   * @return  an instance of the KafkaConsumer
   */
  static <K, V> KafkaConsumer<K, V> create(Vertx vertx, Map<String, String> config,
                                           Class<K> keyType, Class<V> valueType) {
    KafkaReadStream<K, V> stream = KafkaReadStream.create(vertx, new HashMap<>(config), keyType, valueType);
    return new KafkaConsumerImpl<>(stream).registerCloseHook();
  }

  /**
   * Create a new KafkaConsumer instance
   *
   * @param vertx Vert.x instance to use
   * @param config Kafka consumer configuration
   * @return  an instance of the KafkaConsumer
   */
  @GenIgnore
  static <K, V> KafkaConsumer<K, V> create(Vertx vertx, Properties config) {
    KafkaReadStream<K, V> stream = KafkaReadStream.create(vertx, config);
    return new KafkaConsumerImpl<>(stream).registerCloseHook();
  }

  /**
   * Create a new KafkaConsumer instance
   *
   * @param vertx Vert.x instance to use
   * @param config Kafka consumer configuration
   * @param keyType class type for the key deserialization
   * @param valueType class type for the value deserialization
   * @return  an instance of the KafkaConsumer
   */
  @GenIgnore
  static <K, V> KafkaConsumer<K, V> create(Vertx vertx, Properties config,
                                           Class<K> keyType, Class<V> valueType) {
    KafkaReadStream<K, V> stream = KafkaReadStream.create(vertx, config, keyType, valueType);
    return new KafkaConsumerImpl<>(stream).registerCloseHook();
  }

  @Fluent
  @Override
  KafkaConsumer<K, V> exceptionHandler(Handler<Throwable> handler);

  @Fluent
  @Override
  KafkaConsumer<K, V> handler(Handler<KafkaConsumerRecord<K, V>> handler);

  @Fluent
  @Override
  KafkaConsumer<K, V> pause();

  @Fluent
  @Override
  KafkaConsumer<K, V> resume();

  @Fluent
  @Override
  KafkaConsumer<K, V> endHandler(Handler<Void> endHandler);

  /**
   * Subscribe to the given topic to get dynamically assigned partitions.
   *
   * @param topic  topic to subscribe to
   * @return  current KafkaConsumer instance
   */
  @Fluent
  KafkaConsumer<K, V> subscribe(String topic);

  /**
   * Subscribe to the given list of topics to get dynamically assigned partitions.
   *
   * @param topics  topics to subscribe to
   * @return  current KafkaConsumer instance
   */
  @Fluent
  KafkaConsumer<K, V> subscribe(Set<String> topics);

  /**
   * Subscribe to the given topic to get dynamically assigned partitions.
   * <p>
   * Due to internal buffering of messages, when changing the subscribed topic  
   * the old topic may remain in effect 
   * (as observed by the {@linkplain #handler(Handler)} record handler}) 
   * until some time <em>after</em> the given {@code completionHandler} 
   * is called. In contrast, the once the given {@code completionHandler} 
   * is called the {@link #batchHandler(Handler)} will only see messages 
   * consistent with the new topic.
   * 
   * @param topic  topic to subscribe to
   * @param completionHandler handler called on operation completed
   * @return  current KafkaConsumer instance
   */
  @Fluent
  KafkaConsumer<K, V> subscribe(String topic, Handler<AsyncResult<Void>> completionHandler);

  /**
   * Subscribe to the given list of topics to get dynamically assigned partitions.
   * <p>
   * Due to internal buffering of messages, when changing the subscribed topics  
   * the old set of topics may remain in effect 
   * (as observed by the {@linkplain #handler(Handler)} record handler}) 
   * until some time <em>after</em> the given {@code completionHandler} 
   * is called. In contrast, the once the given {@code completionHandler} 
   * is called the {@link #batchHandler(Handler)} will only see messages 
   * consistent with the new set of topics.
   * 
   * @param topics  topics to subscribe to
   * @param completionHandler handler called on operation completed
   * @return  current KafkaConsumer instance
   */
  @Fluent
  KafkaConsumer<K, V> subscribe(Set<String> topics, Handler<AsyncResult<Void>> completionHandler);

  /**
   * Manually assign a partition to this consumer.
   *
   * @param topicPartition  partition which want assigned
   * @return  current KafkaConsumer instance
   */
  @Fluent
  KafkaConsumer<K, V> assign(TopicPartition topicPartition);

  /**
   * Manually assign a list of partition to this consumer.
   *
   * @param topicPartitions  partitions which want assigned
   * @return  current KafkaConsumer instance
   */
  @Fluent
  KafkaConsumer<K, V> assign(Set<TopicPartition> topicPartitions);

  /**
   * Manually assign a partition to this consumer.
   * <p>
   * Due to internal buffering of messages, when reassigning
   * the old partition may remain in effect 
   * (as observed by the {@linkplain #handler(Handler)} record handler)} 
   * until some time <em>after</em> the given {@code completionHandler} 
   * is called. In contrast, the once the given {@code completionHandler} 
   * is called the {@link #batchHandler(Handler)} will only see messages 
   * consistent with the new partition.
   * 
   * @param topicPartition  partition which want assigned
   * @param completionHandler handler called on operation completed
   * @return  current KafkaConsumer instance
   */
  @Fluent
  KafkaConsumer<K, V> assign(TopicPartition topicPartition, Handler<AsyncResult<Void>> completionHandler);

  /**
   * Manually assign a list of partition to this consumer.
   * <p>
   * Due to internal buffering of messages, when reassigning
   * the old set of partitions may remain in effect 
   * (as observed by the {@linkplain #handler(Handler)} record handler)} 
   * until some time <em>after</em> the given {@code completionHandler} 
   * is called. In contrast, the once the given {@code completionHandler} 
   * is called the {@link #batchHandler(Handler)} will only see messages 
   * consistent with the new set of partitions.
   * 
   * @param topicPartitions  partitions which want assigned
   * @param completionHandler handler called on operation completed
   * @return  current KafkaConsumer instance
   */
  @Fluent
  KafkaConsumer<K, V> assign(Set<TopicPartition> topicPartitions, Handler<AsyncResult<Void>> completionHandler);

  /**
   * Get the set of partitions currently assigned to this consumer.
   *
   * @param handler handler called on operation completed
   * @return  current KafkaConsumer instance
   */
  @Fluent
  KafkaConsumer<K, V> assignment(Handler<AsyncResult<Set<TopicPartition>>> handler);

  /**
   * Get metadata about partitions for all topics that the user is authorized to view.
   *
   * @param handler handler called on operation completed
   * @return  current KafkaConsumer instance
   */
  @Fluent
  @GenIgnore
  KafkaConsumer<K, V> listTopics(Handler<AsyncResult<Map<String, List<PartitionInfo>>>> handler);

  /**
   * Unsubscribe from topics currently subscribed with subscribe.
   *
   * @return  current KafkaConsumer instance
   */
  @Fluent
  KafkaConsumer<K, V> unsubscribe();

  /**
   * Unsubscribe from topics currently subscribed with subscribe.
   *
   * @param completionHandler handler called on operation completed
   * @return  current KafkaConsumer instance
   */
  @Fluent
  KafkaConsumer<K, V> unsubscribe(Handler<AsyncResult<Void>> completionHandler);

  /**
   * Get the current subscription.
   *
   * @param handler handler called on operation completed
   * @return  current KafkaConsumer instance
   */
  @Fluent
  KafkaConsumer<K, V> subscription(Handler<AsyncResult<Set<String>>> handler);

  /**
   * Suspend fetching from the requested partition.
   *
   * @param topicPartition topic partition from which suspend fetching
   * @return  current KafkaConsumer instance
   */
  @Fluent
  KafkaConsumer<K, V> pause(TopicPartition topicPartition);

  /**
   * Suspend fetching from the requested partitions.
   *
   * @param topicPartitions topic partition from which suspend fetching
   * @return  current KafkaConsumer instance
   */
  @Fluent
  KafkaConsumer<K, V> pause(Set<TopicPartition> topicPartitions);

  /**
   * Suspend fetching from the requested partition.
   * <p>
   * Due to internal buffering of messages,
   * the {@linkplain #handler(Handler) record handler} will 
   * continue to observe messages from the given {@code topicParation} 
   * until some time <em>after</em> the given {@code completionHandler} 
   * is called. In contrast, the once the given {@code completionHandler} 
   * is called the {@link #batchHandler(Handler)} will not see messages 
   * from the given {@code topicParation}.
   * 
   * @param topicPartition topic partition from which suspend fetching
   * @param completionHandler handler called on operation completed
   * @return  current KafkaConsumer instance
   */
  @Fluent
  KafkaConsumer<K, V> pause(TopicPartition topicPartition, Handler<AsyncResult<Void>> completionHandler);

  /**
   * Suspend fetching from the requested partitions.
   * <p>
   * Due to internal buffering of messages,
   * the {@linkplain #handler(Handler) record handler} will 
   * continue to observe messages from the given {@code topicParations} 
   * until some time <em>after</em> the given {@code completionHandler} 
   * is called. In contrast, the once the given {@code completionHandler} 
   * is called the {@link #batchHandler(Handler)} will not see messages 
   * from the given {@code topicParations}.
   * 
   * @param topicPartitions topic partition from which suspend fetching
   * @param completionHandler handler called on operation completed
   * @return  current KafkaConsumer instance
   */
  @Fluent
  KafkaConsumer<K, V> pause(Set<TopicPartition> topicPartitions, Handler<AsyncResult<Void>> completionHandler);

  /**
   * Get the set of partitions that were previously paused by a call to pause(Set).
   *
   * @param handler handler called on operation completed
   */
  void paused(Handler<AsyncResult<Set<TopicPartition>>> handler);

  /**
   * Resume specified partition which have been paused with pause.
   *
   * @param topicPartition topic partition from which resume fetching
   * @return  current KafkaConsumer instance
   */
  @Fluent
  KafkaConsumer<K, V> resume(TopicPartition topicPartition);

  /**
   * Resume specified partitions which have been paused with pause.
   *
   * @param topicPartitions topic partition from which resume fetching
   * @return  current KafkaConsumer instance
   */
  @Fluent
  KafkaConsumer<K, V> resume(Set<TopicPartition> topicPartitions);

  /**
   * Resume specified partition which have been paused with pause.
   *
   * @param topicPartition topic partition from which resume fetching
   * @param completionHandler handler called on operation completed
   * @return  current KafkaConsumer instance
   */
  @Fluent
  KafkaConsumer<K, V> resume(TopicPartition topicPartition, Handler<AsyncResult<Void>> completionHandler);

  /**
   * Resume specified partitions which have been paused with pause.
   *
   * @param topicPartitions topic partition from which resume fetching
   * @param completionHandler handler called on operation completed
   * @return  current KafkaConsumer instance
   */
  @Fluent
  KafkaConsumer<K, V> resume(Set<TopicPartition> topicPartitions, Handler<AsyncResult<Void>> completionHandler);

  /**
   * Set the handler called when topic partitions are revoked to the consumer
   *
   * @param handler handler called on revoked topic partitions
   * @return  current KafkaConsumer instance
   */
  @Fluent
  KafkaConsumer<K, V> partitionsRevokedHandler(Handler<Set<TopicPartition>> handler);

  /**
   * Set the handler called when topic partitions are assigned to the consumer
   *
   * @param handler handler called on assigned topic partitions
   * @return  current KafkaConsumer instance
   */
  @Fluent
  KafkaConsumer<K, V> partitionsAssignedHandler(Handler<Set<TopicPartition>> handler);

  /**
   * Overrides the fetch offsets that the consumer will use on the next poll.
   *
   * @param topicPartition  topic partition for which seek
   * @param offset  offset to seek inside the topic partition
   * @return  current KafkaConsumer instance
   */
  @Fluent
  KafkaConsumer<K, V> seek(TopicPartition topicPartition, long offset);

  /**
   * Overrides the fetch offsets that the consumer will use on the next poll.
   * <p>
   * Due to internal buffering of messages,
   * the {@linkplain #handler(Handler) record handler} will 
   * continue to observe messages fetched with respect to the old offset  
   * until some time <em>after</em> the given {@code completionHandler} 
   * is called. In contrast, the once the given {@code completionHandler} 
   * is called the {@link #batchHandler(Handler)} will only see messages 
   * consistent with the new offset.
   * 
   * @param topicPartition  topic partition for which seek
   * @param offset  offset to seek inside the topic partition
   * @param completionHandler handler called on operation completed
   * @return  current KafkaConsumer instance
   */
  @Fluent
  KafkaConsumer<K, V> seek(TopicPartition topicPartition, long offset, Handler<AsyncResult<Void>> completionHandler);

  /**
   * Seek to the first offset for each of the given partition.
   *
   * @param topicPartition topic partition for which seek
   * @return  current KafkaConsumer instance
   */
  @Fluent
  KafkaConsumer<K, V> seekToBeginning(TopicPartition topicPartition);

  /**
   * Seek to the first offset for each of the given partitions.
   *
   * @param topicPartitions topic partition for which seek
   * @return  current KafkaConsumer instance
   */
  @Fluent
  KafkaConsumer<K, V> seekToBeginning(Set<TopicPartition> topicPartitions);

  /**
   * Seek to the first offset for each of the given partition.
   * <p>
   * Due to internal buffering of messages,
   * the {@linkplain #handler(Handler) record handler} will 
   * continue to observe messages fetched with respect to the old offset  
   * until some time <em>after</em> the given {@code completionHandler} 
   * is called. In contrast, the once the given {@code completionHandler} 
   * is called the {@link #batchHandler(Handler)} will only see messages 
   * consistent with the new offset.
   * 
   * @param topicPartition topic partition for which seek
   * @param completionHandler handler called on operation completed
   * @return  current KafkaConsumer instance
   */
  @Fluent
  KafkaConsumer<K, V> seekToBeginning(TopicPartition topicPartition, Handler<AsyncResult<Void>> completionHandler);

  /**
   * Seek to the first offset for each of the given partitions.
   * <p>
   * Due to internal buffering of messages,
   * the {@linkplain #handler(Handler) record handler} will 
   * continue to observe messages fetched with respect to the old offset  
   * until some time <em>after</em> the given {@code completionHandler} 
   * is called. In contrast, the once the given {@code completionHandler} 
   * is called the {@link #batchHandler(Handler)} will only see messages 
   * consistent with the new offset.
   * 
   * @param topicPartitions topic partition for which seek
   * @param completionHandler handler called on operation completed
   * @return  current KafkaConsumer instance
   */
  @Fluent
  KafkaConsumer<K, V> seekToBeginning(Set<TopicPartition> topicPartitions, Handler<AsyncResult<Void>> completionHandler);

  /**
   * Seek to the last offset for each of the given partition.
   *
   * @param topicPartition topic partition for which seek
   * @return  current KafkaConsumer instance
   */
  @Fluent
  KafkaConsumer<K, V> seekToEnd(TopicPartition topicPartition);

  /**
   * Seek to the last offset for each of the given partitions.
   *
   * @param topicPartitions topic partition for which seek
   * @return  current KafkaConsumer instance
   */
  @Fluent
  KafkaConsumer<K, V> seekToEnd(Set<TopicPartition> topicPartitions);

  /**
   * Seek to the last offset for each of the given partition.
   * <p>
   * Due to internal buffering of messages,
   * the {@linkplain #handler(Handler) record handler} will 
   * continue to observe messages fetched with respect to the old offset  
   * until some time <em>after</em> the given {@code completionHandler} 
   * is called. In contrast, the once the given {@code completionHandler} 
   * is called the {@link #batchHandler(Handler)} will only see messages 
   * consistent with the new offset.
   * 
   * @param topicPartition topic partition for which seek
   * @param completionHandler handler called on operation completed
   * @return  current KafkaConsumer instance
   */
  @Fluent
  KafkaConsumer<K, V> seekToEnd(TopicPartition topicPartition, Handler<AsyncResult<Void>> completionHandler);

  /**
   * Seek to the last offset for each of the given partitions.
   * <p>
   * Due to internal buffering of messages,
   * the {@linkplain #handler(Handler) record handler} will 
   * continue to observe messages fetched with respect to the old offset  
   * until some time <em>after</em> the given {@code completionHandler} 
   * is called. In contrast, the once the given {@code completionHandler} 
   * is called the {@link #batchHandler(Handler)} will only see messages 
   * consistent with the new offset.
   * 
   * @param topicPartitions topic partition for which seek
   * @param completionHandler handler called on operation completed
   * @return  current KafkaConsumer instance
   */
  @Fluent
  KafkaConsumer<K, V> seekToEnd(Set<TopicPartition> topicPartitions, Handler<AsyncResult<Void>> completionHandler);

  /**
   * Commit current offsets for all the subscribed list of topics and partition.
   */
  void commit();

  /**
   * Commit current offsets for all the subscribed list of topics and partition.
   *
   * @param completionHandler handler called on operation completed
   */
  void commit(Handler<AsyncResult<Void>> completionHandler);

  /**
   * Commit the specified offsets for the specified list of topics and partitions to Kafka.
   *
   * @param offsets offsets list to commit
   */
  @GenIgnore
  void commit(Map<TopicPartition, OffsetAndMetadata> offsets);

  /**
   * Commit the specified offsets for the specified list of topics and partitions to Kafka.
   *
   * @param offsets offsets list to commit
   * @param completionHandler handler called on operation completed
   */
  @GenIgnore
  void commit(Map<TopicPartition, OffsetAndMetadata> offsets, Handler<AsyncResult<Map<TopicPartition, OffsetAndMetadata>>> completionHandler);

  /**
   * Get the last committed offset for the given partition (whether the commit happened by this process or another).
   *
   * @param topicPartition  topic partition for getting last committed offset
   * @param handler handler called on operation completed
   */
  void committed(TopicPartition topicPartition, Handler<AsyncResult<OffsetAndMetadata>> handler);

  /**
   * Get metadata about the partitions for a given topic.
   *
   * @param topic topic partition for which getting partitions info
   * @param handler handler called on operation completed
   * @return  current KafkaConsumer instance
   */
  @Fluent
  KafkaConsumer<K, V> partitionsFor(String topic, Handler<AsyncResult<List<PartitionInfo>>> handler);

  /**
   * Set the handler to be used when batches of messages are fetched
   * from the Kafka server. Batch handlers need to take care not to block
   * the event loop when dealing with large batches. It is better to process
   * records individually using the {@link #handler(Handler) record handler}.
   * @param handler handler called when batches of messages are fetched
   * @return current KafkaConsumer instance
   */
  @Fluent
  KafkaConsumer<K, V> batchHandler(Handler<KafkaConsumerRecords<K, V>> handler);

  /**
   * Close the consumer
   */
  default void close() {
    close(null);
  }

  /**
   * Close the consumer
   *
   * @param completionHandler handler called on operation completed
   */
  void close(Handler<AsyncResult<Void>> completionHandler);

  /**
   * Get the offset of the next record that will be fetched (if a record with that offset exists).
   *
   * @param partition The partition to get the position for
   * @param handler handler called on operation completed
   */
  void position(TopicPartition partition, Handler<AsyncResult<Long>> handler);

  /**
   * Look up the offsets for the given partitions by timestamp. Note: the result might be empty in case
   * for the given timestamp no offset can be found -- e.g., when the timestamp refers to the future
   * @param topicPartitionTimestamps A map with pairs of (TopicPartition, Timestamp).
   * @param handler handler called on operation completed
   */
  @GenIgnore
  void offsetsForTimes(Map<TopicPartition, Long> topicPartitionTimestamps, Handler<AsyncResult<Map<TopicPartition, OffsetAndTimestamp>>> handler);

  /**
   * Look up the offset for the given partition by timestamp. Note: the result might be null in case
   * for the given timestamp no offset can be found -- e.g., when the timestamp refers to the future
   * @param topicPartition TopicPartition to query.
   * @param timestamp Timestamp to be used in the query.
   * @param handler handler called on operation completed
   */
  void offsetsForTimes(TopicPartition topicPartition, Long timestamp, Handler<AsyncResult<OffsetAndTimestamp>> handler);

  /**
   * Get the first offset for the given partitions.
   * @param topicPartitions the partitions to get the earliest offsets.
   * @param handler handler called on operation completed. Returns the earliest available offsets for the given partitions
   */
  @GenIgnore
  void beginningOffsets(Set<TopicPartition> topicPartitions, Handler<AsyncResult<Map<TopicPartition, Long>>> handler);

  /**
   * Get the first offset for the given partitions.
   * @param topicPartition the partition to get the earliest offset.
   * @param handler handler called on operation completed. Returns the earliest available offset for the given partition
   */
  void beginningOffsets(TopicPartition topicPartition, Handler<AsyncResult<Long>> handler);

  /**
   * Get the last offset for the given partitions. The last offset of a partition is the offset
   * of the upcoming message, i.e. the offset of the last available message + 1.
   * @param topicPartitions the partitions to get the end offsets.
   * @param handler handler called on operation completed. The end offsets for the given partitions.
   */
  @GenIgnore
  void endOffsets(Set<TopicPartition> topicPartitions, Handler<AsyncResult<Map<TopicPartition, Long>>> handler);

  /**
   * Get the last offset for the given partition. The last offset of a partition is the offset
   * of the upcoming message, i.e. the offset of the last available message + 1.
   * @param topicPartition the partition to get the end offset.
   * @param handler handler called on operation completed. The end offset for the given partition.
   */
  void endOffsets(TopicPartition topicPartition, Handler<AsyncResult<Long>> handler);

  /**
   * @return  underlying the {@link KafkaReadStream} instance
   */
  @GenIgnore
  KafkaReadStream<K, V> asStream();

  /**
   * @return the underlying consumer
   */
  @GenIgnore
  Consumer<K, V> unwrap();

  /**
   * Sets the poll timeout (in ms) for the underlying native Kafka Consumer. Defaults to 1000.
   * Setting timeout to a lower value results in a more 'responsive' client, because it will block for a shorter period
   * if no data is available in the assigned partition and therefore allows subsequent actions to be executed with a shorter
   * delay. At the same time, the client will poll more frequently and thus will potentially create a higher load on the Kafka Broker.
   *
   * @param timeout The time, in milliseconds, spent waiting in poll if data is not available in the buffer.
   * If 0, returns immediately with any records that are available currently in the native Kafka consumer's buffer,
   * else returns empty. Must not be negative.
   */
  KafkaConsumer<K, V> pollTimeout(long timeout);
}
