/*
 * 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.core.AsyncResult;
import io.vertx.core.Handler;
import io.vertx.core.Vertx;
import io.vertx.core.streams.ReadStream;
import io.vertx.kafka.client.consumer.impl.KafkaReadStreamImpl;
import io.vertx.kafka.client.serialization.VertxSerdes;
import org.apache.kafka.clients.consumer.Consumer;
import org.apache.kafka.clients.consumer.ConsumerRecord;
import org.apache.kafka.clients.consumer.ConsumerRecords;
import org.apache.kafka.clients.consumer.OffsetAndMetadata;
import org.apache.kafka.clients.consumer.OffsetAndTimestamp;
import org.apache.kafka.common.PartitionInfo;
import org.apache.kafka.common.TopicPartition;
import org.apache.kafka.common.serialization.Deserializer;

import java.util.List;
import java.util.Map;
import java.util.Properties;
import java.util.Set;
import java.util.regex.Pattern;

A ReadStream for consuming Kafka ConsumerRecord. 
 The ReadStream.pause() and ReadStream.resume() provides global control over reading the records from the consumer. 
 The pause(Set) and resume(Set) provides finer grained control over reading records for specific Topic/Partition, these are Kafka's specific operations. /**
 * A {@link ReadStream} for consuming Kafka {@link ConsumerRecord}.
 * <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.
 *
 */
public interface KafkaReadStream<K, V> extends ReadStream<ConsumerRecord<K, V>> {

  
Create a new KafkaReadStream instance
Params:
vertx – Vert.x instance to use
config –  Kafka consumer configuration
Returns:
 an instance of the KafkaReadStream/**
   * Create a new KafkaReadStream instance
   *
   * @param vertx Vert.x instance to use
   * @param config  Kafka consumer configuration
   * @return  an instance of the KafkaReadStream
   */
  static <K, V> KafkaReadStream<K, V> create(Vertx vertx, Properties config) {
    return create(vertx, new org.apache.kafka.clients.consumer.KafkaConsumer<>(config));
  }

  
Create a new KafkaReadStream instance
Params:
vertx – Vert.x instance to use
config –  Kafka consumer configuration
keyType – class type for the key deserialization
valueType – class type for the value deserialization
Returns:
 an instance of the KafkaReadStream/**
   * Create a new KafkaReadStream 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 KafkaReadStream
   */
  static <K, V> KafkaReadStream<K, V> create(Vertx vertx, Properties config, Class<K> keyType, Class<V> valueType) {
    Deserializer<K> keyDeserializer = VertxSerdes.serdeFrom(keyType).deserializer();
    Deserializer<V> valueDeserializer = VertxSerdes.serdeFrom(valueType).deserializer();
    return create(vertx, config, keyDeserializer, valueDeserializer);
  }

  
Create a new KafkaReadStream instance
Params:
vertx – Vert.x instance to use
config –  Kafka consumer configuration
keyDeserializer – key deserializer
valueDeserializer – value deserializer
Returns:
 an instance of the KafkaReadStream/**
   * Create a new KafkaReadStream instance
   *
   * @param vertx Vert.x instance to use
   * @param config  Kafka consumer configuration
   * @param keyDeserializer key deserializer
   * @param valueDeserializer value deserializer
   * @return  an instance of the KafkaReadStream
   */
  static <K, V> KafkaReadStream<K, V> create(Vertx vertx, Properties config, Deserializer<K> keyDeserializer, Deserializer<V> valueDeserializer) {
    return create(vertx, new org.apache.kafka.clients.consumer.KafkaConsumer<>(config, keyDeserializer, valueDeserializer));
  }

  
Create a new KafkaReadStream instance
Params:
vertx – Vert.x instance to use
config –  Kafka consumer configuration
Returns:
 an instance of the KafkaReadStream/**
   * Create a new KafkaReadStream instance
   *
   * @param vertx Vert.x instance to use
   * @param config  Kafka consumer configuration
   * @return  an instance of the KafkaReadStream
   */
  static <K, V> KafkaReadStream<K, V> create(Vertx vertx, Map<String, Object> config) {
    return create(vertx, new org.apache.kafka.clients.consumer.KafkaConsumer<>(config));
  }

  
Create a new KafkaReadStream instance
Params:
vertx – Vert.x instance to use
config –  Kafka consumer configuration
keyType – class type for the key deserialization
valueType – class type for the value deserialization
Returns:
 an instance of the KafkaReadStream/**
   * Create a new KafkaReadStream 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 KafkaReadStream
   */
  static <K, V> KafkaReadStream<K, V> create(Vertx vertx, Map<String, Object> config, Class<K> keyType, Class<V> valueType) {
    Deserializer<K> keyDeserializer = VertxSerdes.serdeFrom(keyType).deserializer();
    Deserializer<V> valueDeserializer = VertxSerdes.serdeFrom(valueType).deserializer();
    return create(vertx, config, keyDeserializer, valueDeserializer);
  }

  
Create a new KafkaReadStream instance
Params:
vertx – Vert.x instance to use
config –  Kafka consumer configuration
keyDeserializer – key deserializer
valueDeserializer – value deserializer
Returns:
 an instance of the KafkaReadStream/**
   * Create a new KafkaReadStream instance
   *
   * @param vertx Vert.x instance to use
   * @param config  Kafka consumer configuration
   * @param keyDeserializer key deserializer
   * @param valueDeserializer value deserializer
   * @return  an instance of the KafkaReadStream
   */
  static <K, V> KafkaReadStream<K, V> create(Vertx vertx, Map<String, Object> config, Deserializer<K> keyDeserializer, Deserializer<V> valueDeserializer) {
    return create(vertx, new org.apache.kafka.clients.consumer.KafkaConsumer<>(config, keyDeserializer, valueDeserializer));
  }

  
Create a new KafkaReadStream instance
Params:
vertx – Vert.x instance to use
consumer –  native Kafka consumer instance
Returns:
 an instance of the KafkaReadStream/**
   * Create a new KafkaReadStream instance
   *
   * @param vertx Vert.x instance to use
   * @param consumer  native Kafka consumer instance
   * @return  an instance of the KafkaReadStream
   */
  static <K, V> KafkaReadStream<K, V> create(Vertx vertx, Consumer<K, V> consumer) {
    return new KafkaReadStreamImpl<>(vertx.getOrCreateContext(), consumer);
  }

  
Get the last committed offset for the given partition (whether the commit happened by this process or another).
Params:
topicPartition –  topic partition for getting last committed offset
handler – handler called on operation completed/**
   * 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);

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

  
Suspend fetching from the requested partitions.
 Due to internal buffering of messages, the record handler will continue to observe messages from the given topicPartitions until some time after the given completionHandler is called. In contrast, the once the given completionHandler is called the batchHandler(Handler) will not see messages from the given topicPartitions. 
Params:
topicPartitions – topic partition from which suspend fetching
completionHandler – handler called on operation completed
Returns:
 current KafkaReadStream instance/**
   * 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 topicPartitions}
   * 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 topicPartitions}.
   *
   * @param topicPartitions topic partition from which suspend fetching
   * @param completionHandler handler called on operation completed
   * @return  current KafkaReadStream instance
   */
  KafkaReadStream<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). 
Params:
handler – handler called on operation completed/**
   * Get the set of partitions that were previously paused by a call to {@link #pause(Set)}.
   *
   * @param handler handler called on operation completed
   */
  void paused(Handler<AsyncResult<Set<TopicPartition>>> handler);

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

  
Resume specified partitions which have been paused with pause.
Params:
topicPartitions – topic partition from which resume fetching
completionHandler – handler called on operation completed
Returns:
 current KafkaReadStream instance/**
   * 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 KafkaReadStream instance
   */
  KafkaReadStream<K, V> resume(Set<TopicPartition> topicPartitions, Handler<AsyncResult<Void>> completionHandler);

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

  
Seek to the last offset for each of the given partitions.
 Due to internal buffering of messages, the record handler will continue to observe messages fetched with respect to the old offset until some time after the given completionHandler is called. In contrast, the once the given completionHandler is called the batchHandler(Handler) will only see messages consistent with the new offset. 
Params:
topicPartitions – topic partition for which seek
completionHandler – handler called on operation completed
Returns:
 current KafkaReadStream instance/**
   * 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 KafkaReadStream instance
   */
  KafkaReadStream<K, V> seekToEnd(Set<TopicPartition> topicPartitions, Handler<AsyncResult<Void>> completionHandler);

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

  
Seek to the first offset for each of the given partitions.
 Due to internal buffering of messages, the record handler will continue to observe messages fetched with respect to the old offset until some time after the given completionHandler is called. In contrast, the once the given completionHandler is called the batchHandler(Handler) will only see messages consistent with the new offset. 
Params:
topicPartitions – topic partition for which seek
completionHandler – handler called on operation completed
Returns:
 current KafkaReadStream instance/**
   * 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 KafkaReadStream instance
   */
  KafkaReadStream<K, V> seekToBeginning(Set<TopicPartition> topicPartitions, Handler<AsyncResult<Void>> completionHandler);

  
Overrides the fetch offsets that the consumer will use on the next poll.
Params:
topicPartition –  topic partition for which seek
offset –  offset to seek inside the topic partition
Returns:
 current KafkaReadStream instance/**
   * 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 KafkaReadStream instance
   */
  KafkaReadStream<K, V> seek(TopicPartition topicPartition, long offset);

  
Overrides the fetch offsets that the consumer will use on the next poll.
 Due to internal buffering of messages, the record handler will continue to observe messages fetched with respect to the old offset until some time after the given completionHandler is called. In contrast, the once the given completionHandler is called the batchHandler(Handler) will only see messages consistent with the new offset. 
Params:
topicPartition –  topic partition for which seek
offset –  offset to seek inside the topic partition
completionHandler – handler called on operation completed
Returns:
 current KafkaReadStream instance/**
   * 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 KafkaReadStream instance
   */
  KafkaReadStream<K, V> seek(TopicPartition topicPartition, long offset, Handler<AsyncResult<Void>> completionHandler);

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

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

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

  
Subscribe to the given list of topics to get dynamically assigned partitions.
 Due to internal buffering of messages, when changing the subscribed topics the old set of topics may remain in effect (as observed by the ReadStream.handler(Handler) record handler}) until some time after the given completionHandler is called. In contrast, the once the given completionHandler is called the batchHandler(Handler) will only see messages consistent with the new set of topics. 
Params:
topics –  topics to subscribe to
completionHandler – handler called on operation completed
Returns:
 current KafkaReadStream instance/**
   * 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 KafkaReadStream instance
   */
  KafkaReadStream<K, V> subscribe(Set<String> topics, Handler<AsyncResult<Void>> completionHandler);

  
Subscribe to all topics matching specified pattern to get dynamically assigned partitions.
 Due to internal buffering of messages, when changing the subscribed topics the old set of topics may remain in effect (as observed by the ReadStream.handler(Handler) record handler}) until some time after the given completionHandler is called. In contrast, the once the given completionHandler is called the batchHandler(Handler) will only see messages consistent with the new set of topics. 
Params:
pattern –  Pattern to subscribe to
completionHandler – handler called on operation completed
Returns:
 current KafkaReadStream instance/**
   * Subscribe to all topics matching specified pattern 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 pattern  Pattern to subscribe to
   * @param completionHandler handler called on operation completed
   * @return  current KafkaReadStream instance
   */
  KafkaReadStream<K, V> subscribe(Pattern pattern, Handler<AsyncResult<Void>> completionHandler);

  
Subscribe to all topics matching specified pattern to get dynamically assigned partitions.
Params:
pattern –  Pattern to subscribe to
Returns:
 current KafkaReadStream instance/**
   * Subscribe to all topics matching specified pattern to get dynamically assigned partitions.
   *
   * @param pattern  Pattern to subscribe to
   * @return  current KafkaReadStream instance
   */
  KafkaReadStream<K, V> subscribe(Pattern pattern);

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

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

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

  
Manually assign a set of partitions to this consumer.
Params:
partitions –  partitions which want assigned
Returns:
 current KafkaReadStream instance/**
   * Manually assign a set of partitions to this consumer.
   *
   * @param partitions  partitions which want assigned
   * @return  current KafkaReadStream instance
   */
  KafkaReadStream<K, V> assign(Set<TopicPartition> partitions);

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

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

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

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

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

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

  
Get metadata about the partitions for a given topic.
Params:
topic – topic partition for which getting partitions info
handler – handler called on operation completed
Returns:
 current KafkaReadStream instance/**
   * 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 KafkaReadStream instance
   */
  KafkaReadStream<K, V> partitionsFor(String topic, Handler<AsyncResult<List<PartitionInfo>>> handler);

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

  
Close the stream
Params:
completionHandler – handler called on operation completed/**
   * Close the stream
   *
   * @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).
Params:
partition – The partition to get the position for
handler – handler called on operation completed/**
   * 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.
Params:
topicPartitionTimestamps – A map with pairs of (TopicPartition, Timestamp).
handler – handler called on operation completed/**
   * Look up the offsets for the given partitions by timestamp.
   * @param topicPartitionTimestamps A map with pairs of (TopicPartition, Timestamp).
   * @param handler handler called on operation completed
   */
  void offsetsForTimes(Map<TopicPartition, Long> topicPartitionTimestamps, Handler<AsyncResult<Map<TopicPartition, OffsetAndTimestamp>>> handler);

  
 * Look up the offset for the given partition by timestamp.
Params:
topicPartition – Partition to query.
timestamp – Timestamp used to determine the offset.
handler – handler called on operation completed/**
   * * Look up the offset for the given partition by timestamp.
   * @param topicPartition Partition to query.
   * @param timestamp Timestamp used to determine the offset.
   * @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.
Params:
topicPartitions – the partitions to get the earliest offsets.
handler – handler called on operation completed. Returns the earliest available offsets for the given partitions/**
   * 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
   */
  void beginningOffsets(Set<TopicPartition> topicPartitions, Handler<AsyncResult<Map<TopicPartition, Long>>> handler);

  
Get the first offset for the given partition.
Params:
topicPartition – the partition to get the earliest offset.
handler – handler called on operation completed. Returns the earliest available offset for the given partition/**
   * Get the first offset for the given partition.
   * @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.
Params:
topicPartitions – the partitions to get the end offsets.
handler – handler called on operation completed. The end offsets for the given partitions./**
   * 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.
   */
  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.
Params:
topicPartition – the partition to get the end offset.
handler – handler called on operation completed. The end offset for the given partition./**
   * 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);


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

  
Set the handler that will be called when a new batch of records is returned from Kafka. 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 record handler. 
Params:
handler – handler called each time Kafka returns a batch of records.
Returns:
current KafkaReadStream instance./**
   * Set the handler that will be called when a new batch of records is
   * returned from Kafka. 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 each time Kafka returns a batch of records.
   * @return current KafkaReadStream instance.
   */
  KafkaReadStream<K, V> batchHandler(Handler<ConsumerRecords<K, V>> handler);

  
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.
Params:
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./**
   * 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.
   */
  KafkaReadStream<K, V> pollTimeout(long timeout);

  
Executes a poll for getting messages from Kafka
Params:
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.
handler – handler called after the poll with batch of records (can be empty)./**
   * Executes a poll for getting messages from Kafka
   *
   * @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.
   * @param handler handler called after the poll with batch of records (can be empty).
   */
  void poll(long timeout, Handler<AsyncResult<ConsumerRecords<K, V>>> handler);
}