/**
 * 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.kafka.clients.producer;

import java.io.Closeable;
import java.util.List;
import java.util.Map;
import java.util.concurrent.Future;
import java.util.concurrent.TimeUnit;

import org.apache.kafka.common.Metric;
import org.apache.kafka.common.PartitionInfo;
import org.apache.kafka.common.MetricName;


/**
 * The interface for the {@link KafkaProducer}
 * @see KafkaProducer
 * @see MockProducer
 */
public interface Producer<K, V> extends Closeable {

    /**
     * Send the given record asynchronously and return a future which will eventually contain the response information.
     * 
     * @param record The record to send
     * @return A future which will eventually contain the response information
     */
    public Future<RecordMetadata> send(ProducerRecord<K, V> record);

    /**
     * Send a record and invoke the given callback when the record has been acknowledged by the server
     */
    public Future<RecordMetadata> send(ProducerRecord<K, V> record, Callback callback);
    
    /**
     * Flush any accumulated records from the producer. Blocks until all sends are complete.
     */
    public void flush();

    /**
     * Get a list of partitions for the given topic for custom partition assignment. The partition metadata will change
     * over time so this list should not be cached.
     */
    public List<PartitionInfo> partitionsFor(String topic);

    /**
     * Return a map of metrics maintained by the producer
     */
    public Map<MetricName, ? extends Metric> metrics();

    /**
     * Close this producer
     */
    public void close();

    /**
     * Tries to close the producer cleanly within the specified timeout. If the close does not complete within the
     * timeout, fail any pending send requests and force close the producer.
     */
    public void close(long timeout, TimeUnit unit);

}

/**
 * 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.kafka.clients.producer;

import java.net.InetSocketAddress;
import java.util.Collections;
import java.util.LinkedHashMap;
import java.util.List;
import java.util.Map;
import java.util.Properties;
import java.util.concurrent.ExecutionException;
import java.util.concurrent.Future;
import java.util.concurrent.TimeUnit;
import java.util.concurrent.atomic.AtomicInteger;
import java.util.concurrent.atomic.AtomicReference;

import org.apache.kafka.clients.ClientUtils;
import org.apache.kafka.clients.Metadata;
import org.apache.kafka.clients.NetworkClient;
import org.apache.kafka.clients.producer.internals.RecordAccumulator;
import org.apache.kafka.clients.producer.internals.Sender;
import org.apache.kafka.clients.producer.internals.ProducerInterceptors;
import org.apache.kafka.common.Cluster;
import org.apache.kafka.common.KafkaException;
import org.apache.kafka.common.Metric;
import org.apache.kafka.common.PartitionInfo;
import org.apache.kafka.common.TopicPartition;
import org.apache.kafka.common.config.ConfigException;
import org.apache.kafka.common.errors.ApiException;
import org.apache.kafka.common.errors.InterruptException;
import org.apache.kafka.common.errors.RecordTooLargeException;
import org.apache.kafka.common.errors.SerializationException;
import org.apache.kafka.common.errors.TimeoutException;
import org.apache.kafka.common.errors.TopicAuthorizationException;
import org.apache.kafka.common.metrics.JmxReporter;
import org.apache.kafka.common.metrics.MetricConfig;
import org.apache.kafka.common.MetricName;
import org.apache.kafka.common.metrics.Metrics;
import org.apache.kafka.common.metrics.MetricsReporter;
import org.apache.kafka.common.metrics.Sensor;
import org.apache.kafka.common.network.Selector;
import org.apache.kafka.common.network.ChannelBuilder;
import org.apache.kafka.common.record.CompressionType;
import org.apache.kafka.common.record.Record;
import org.apache.kafka.common.record.Records;
import org.apache.kafka.common.serialization.Serializer;
import org.apache.kafka.common.utils.AppInfoParser;
import org.apache.kafka.common.utils.KafkaThread;
import org.apache.kafka.common.utils.SystemTime;
import org.apache.kafka.common.utils.Time;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;


/**
 * A Kafka client that publishes records to the Kafka cluster.
 * <P>
 * The producer is <i>thread safe</i> and sharing a single producer instance across threads will generally be faster than
 * having multiple instances.
 * <p>
 * Here is a simple example of using the producer to send records with strings containing sequential numbers as the key/value
 * pairs.
 * <pre>
 * {@code
 * Properties props = new Properties();
 * props.put("bootstrap.servers", "localhost:9092");
 * props.put("acks", "all");
 * props.put("retries", 0);
 * props.put("batch.size", 16384);
 * props.put("linger.ms", 1);
 * props.put("buffer.memory", 33554432);
 * props.put("key.serializer", "org.apache.kafka.common.serialization.StringSerializer");
 * props.put("value.serializer", "org.apache.kafka.common.serialization.StringSerializer");
 *
 * Producer<String, String> producer = new KafkaProducer<>(props);
 * for(int i = 0; i < 100; i++)
 *     producer.send(new ProducerRecord<String, String>("my-topic", Integer.toString(i), Integer.toString(i)));
 *
 * producer.close();
 * }</pre>
 * <p>
 * The producer consists of a pool of buffer space that holds records that haven‘t yet been transmitted to the server
 * as well as a background I/O thread that is responsible for turning these records into requests and transmitting them
 * to the cluster. Failure to close the producer after use will leak these resources.
 * <p>
 * The {@link #send(ProducerRecord) send()} method is asynchronous. When called it adds the record to a buffer of pending record sends
 * and immediately returns. This allows the producer to batch together individual records for efficiency.
 * <p>
 * The <code>acks</code> config controls the criteria under which requests are considered complete. The "all" setting
 * we have specified will result in blocking on the full commit of the record, the slowest but most durable setting.
 * <p>
 * If the request fails, the producer can automatically retry, though since we have specified <code>retries</code>
 * as 0 it won‘t. Enabling retries also opens up the possibility of duplicates (see the documentation on
 * <a href="http://www.mamicode.com/http://kafka.apache.org/documentation.html#semantics">message delivery semantics</a> for details).
 * <p>
 * The producer maintains buffers of unsent records for each partition. These buffers are of a size specified by
 * the <code>batch.size</code> config. Making this larger can result in more batching, but requires more memory (since we will
 * generally have one of these buffers for each active partition).
 * <p>
 * By default a buffer is available to send immediately even if there is additional unused space in the buffer. However if you
 * want to reduce the number of requests you can set <code>linger.ms</code> to something greater than 0. This will
 * instruct the producer to wait up to that number of milliseconds before sending a request in hope that more records will
 * arrive to fill up the same batch. This is analogous to Nagle‘s algorithm in TCP. For example, in the code snippet above,
 * likely all 100 records would be sent in a single request since we set our linger time to 1 millisecond. However this setting
 * would add 1 millisecond of latency to our request waiting for more records to arrive if we didn‘t fill up the buffer. Note that
 * records that arrive close together in time will generally batch together even with <code>linger.ms=0</code> so under heavy load
 * batching will occur regardless of the linger configuration; however setting this to something larger than 0 can lead to fewer, more
 * efficient requests when not under maximal load at the cost of a small amount of latency.
 * <p>
 * The <code>buffer.memory</code> controls the total amount of memory available to the producer for buffering. If records
 * are sent faster than they can be transmitted to the server then this buffer space will be exhausted. When the buffer space is
 * exhausted additional send calls will block. The threshold for time to block is determined by <code>max.block.ms</code> after which it throws
 * a TimeoutException.
 * <p>
 * The <code>key.serializer</code> and <code>value.serializer</code> instruct how to turn the key and value objects the user provides with
 * their <code>ProducerRecord</code> into bytes. You can use the included {@link org.apache.kafka.common.serialization.ByteArraySerializer} or
 * {@link org.apache.kafka.common.serialization.StringSerializer} for simple string or byte types.
 */
public class KafkaProducer<K, V> implements Producer<K, V> {

    private static final Logger log = LoggerFactory.getLogger(KafkaProducer.class);
    private static final AtomicInteger PRODUCER_CLIENT_ID_SEQUENCE = new AtomicInteger(1);
    private static final String JMX_PREFIX = "kafka.producer";

    private String clientId;
    private final Partitioner partitioner;
    private final int maxRequestSize;
    private final long totalMemorySize;
    private final Metadata metadata;
    private final RecordAccumulator accumulator;
    private final Sender sender;
    private final Metrics metrics;
    private final Thread ioThread;
    private final CompressionType compressionType;
    private final Sensor errors;
    private final Time time;
    private final Serializer<K> keySerializer;
    private final Serializer<V> valueSerializer;
    private final ProducerConfig producerConfig;
    private final long maxBlockTimeMs;
    private final int requestTimeoutMs;
    private final ProducerInterceptors<K, V> interceptors;

    /**
     * A producer is instantiated by providing a set of key-value pairs as configuration. Valid configuration strings
     * are documented <a href="http://www.mamicode.com/http://kafka.apache.org/documentation.html#producerconfigs">here</a>. Values can be
     * either strings or Objects of the appropriate type (for example a numeric configuration would accept either the
     * string "42" or the integer 42).
     * @param configs   The producer configs
     *
     */
    public KafkaProducer(Map<String, Object> configs) {
        this(new ProducerConfig(configs), null, null);
    }

    /**
     * A producer is instantiated by providing a set of key-value pairs as configuration, a key and a value {@link Serializer}.
     * Valid configuration strings are documented <a href="http://www.mamicode.com/http://kafka.apache.org/documentation.html#producerconfigs">here</a>.
     * Values can be either strings or Objects of the appropriate type (for example a numeric configuration would accept
     * either the string "42" or the integer 42).
     * @param configs   The producer configs
     * @param keySerializer  The serializer for key that implements {@link Serializer}. The configure() method won‘t be
     *                       called in the producer when the serializer is passed in directly.
     * @param valueSerializer  The serializer for value that implements {@link Serializer}. The configure() method won‘t
     *                         be called in the producer when the serializer is passed in directly.
     */
    public KafkaProducer(Map<String, Object> configs, Serializer<K> keySerializer, Serializer<V> valueSerializer) {
        this(new ProducerConfig(ProducerConfig.addSerializerToConfig(configs, keySerializer, valueSerializer)),
             keySerializer, valueSerializer);
    }

    /**
     * A producer is instantiated by providing a set of key-value pairs as configuration. Valid configuration strings
     * are documented <a href="http://www.mamicode.com/http://kafka.apache.org/documentation.html#producerconfigs">here</a>.
     * @param properties   The producer configs
     */
    public KafkaProducer(Properties properties) {
        this(new ProducerConfig(properties), null, null);
    }

    /**
     * A producer is instantiated by providing a set of key-value pairs as configuration, a key and a value {@link Serializer}.
     * Valid configuration strings are documented <a href="http://www.mamicode.com/http://kafka.apache.org/documentation.html#producerconfigs">here</a>.
     * @param properties   The producer configs
     * @param keySerializer  The serializer for key that implements {@link Serializer}. The configure() method won‘t be
     *                       called in the producer when the serializer is passed in directly.
     * @param valueSerializer  The serializer for value that implements {@link Serializer}. The configure() method won‘t
     *                         be called in the producer when the serializer is passed in directly.
     */
    public KafkaProducer(Properties properties, Serializer<K> keySerializer, Serializer<V> valueSerializer) {
        this(new ProducerConfig(ProducerConfig.addSerializerToConfig(properties, keySerializer, valueSerializer)),
             keySerializer, valueSerializer);
    }

    @SuppressWarnings({"unchecked", "deprecation"})
    private KafkaProducer(ProducerConfig config, Serializer<K> keySerializer, Serializer<V> valueSerializer) {
        try {
            log.trace("Starting the Kafka producer");
            Map<String, Object> userProvidedConfigs = config.originals();
            this.producerConfig = config;
            this.time = new SystemTime();

            clientId = config.getString(ProducerConfig.CLIENT_ID_CONFIG);
            if (clientId.length() <= 0)
                clientId = "producer-" + PRODUCER_CLIENT_ID_SEQUENCE.getAndIncrement();
            Map<String, String> metricTags = new LinkedHashMap<String, String>();
            metricTags.put("client-id", clientId);
            MetricConfig metricConfig = new MetricConfig().samples(config.getInt(ProducerConfig.METRICS_NUM_SAMPLES_CONFIG))
                    .timeWindow(config.getLong(ProducerConfig.METRICS_SAMPLE_WINDOW_MS_CONFIG), TimeUnit.MILLISECONDS)
                    .tags(metricTags);
            List<MetricsReporter> reporters = config.getConfiguredInstances(ProducerConfig.METRIC_REPORTER_CLASSES_CONFIG,
                    MetricsReporter.class);
            reporters.add(new JmxReporter(JMX_PREFIX));
            this.metrics = new Metrics(metricConfig, reporters, time);
            this.partitioner = config.getConfiguredInstance(ProducerConfig.PARTITIONER_CLASS_CONFIG, Partitioner.class);
            long retryBackoffMs = config.getLong(ProducerConfig.RETRY_BACKOFF_MS_CONFIG);
            this.metadata = http://www.mamicode.com/new Metadata(retryBackoffMs, config.getLong(ProducerConfig.METADATA_MAX_AGE_CONFIG));
            this.maxRequestSize = config.getInt(ProducerConfig.MAX_REQUEST_SIZE_CONFIG);
            this.totalMemorySize = config.getLong(ProducerConfig.BUFFER_MEMORY_CONFIG);
            this.compressionType = CompressionType.forName(config.getString(ProducerConfig.COMPRESSION_TYPE_CONFIG));
            /* check for user defined settings.
             * If the BLOCK_ON_BUFFER_FULL is set to true,we do not honor METADATA_FETCH_TIMEOUT_CONFIG.
             * This should be removed with release 0.9 when the deprecated configs are removed.
             */
            if (userProvidedConfigs.containsKey(ProducerConfig.BLOCK_ON_BUFFER_FULL_CONFIG)) {
                log.warn(ProducerConfig.BLOCK_ON_BUFFER_FULL_CONFIG + " config is deprecated and will be removed soon. " +
                        "Please use " + ProducerConfig.MAX_BLOCK_MS_CONFIG);
                boolean blockOnBufferFull = config.getBoolean(ProducerConfig.BLOCK_ON_BUFFER_FULL_CONFIG);
                if (blockOnBufferFull) {
                    this.maxBlockTimeMs = Long.MAX_VALUE;
                } else if (userProvidedConfigs.containsKey(ProducerConfig.METADATA_FETCH_TIMEOUT_CONFIG)) {
                    log.warn(ProducerConfig.METADATA_FETCH_TIMEOUT_CONFIG + " config is deprecated and will be removed soon. " +
                            "Please use " + ProducerConfig.MAX_BLOCK_MS_CONFIG);
                    this.maxBlockTimeMs = config.getLong(ProducerConfig.METADATA_FETCH_TIMEOUT_CONFIG);
                } else {
                    this.maxBlockTimeMs = config.getLong(ProducerConfig.MAX_BLOCK_MS_CONFIG);
                }
            } else if (userProvidedConfigs.containsKey(ProducerConfig.METADATA_FETCH_TIMEOUT_CONFIG)) {
                log.warn(ProducerConfig.METADATA_FETCH_TIMEOUT_CONFIG + " config is deprecated and will be removed soon. " +
                        "Please use " + ProducerConfig.MAX_BLOCK_MS_CONFIG);
                this.maxBlockTimeMs = config.getLong(ProducerConfig.METADATA_FETCH_TIMEOUT_CONFIG);
            } else {
                this.maxBlockTimeMs = config.getLong(ProducerConfig.MAX_BLOCK_MS_CONFIG);
            }

            /* check for user defined settings.
             * If the TIME_OUT config is set use that for request timeout.
             * This should be removed with release 0.9
             */
            if (userProvidedConfigs.containsKey(ProducerConfig.TIMEOUT_CONFIG)) {
                log.warn(ProducerConfig.TIMEOUT_CONFIG + " config is deprecated and will be removed soon. Please use " +
                        ProducerConfig.REQUEST_TIMEOUT_MS_CONFIG);
                this.requestTimeoutMs = config.getInt(ProducerConfig.TIMEOUT_CONFIG);
            } else {
                this.requestTimeoutMs = config.getInt(ProducerConfig.REQUEST_TIMEOUT_MS_CONFIG);
            }

            this.accumulator = new RecordAccumulator(config.getInt(ProducerConfig.BATCH_SIZE_CONFIG),
                    this.totalMemorySize,
                    this.compressionType,
                    config.getLong(ProducerConfig.LINGER_MS_CONFIG),
                    retryBackoffMs,
                    metrics,
                    time);
            List<InetSocketAddress> addresses = ClientUtils.parseAndValidateAddresses(config.getList(ProducerConfig.BOOTSTRAP_SERVERS_CONFIG));
            this.metadata.update(Cluster.bootstrap(addresses), time.milliseconds());
            ChannelBuilder channelBuilder = ClientUtils.createChannelBuilder(config.values());
            NetworkClient client = new NetworkClient(
                    new Selector(config.getLong(ProducerConfig.CONNECTIONS_MAX_IDLE_MS_CONFIG), this.metrics, time, "producer", channelBuilder),
                    this.metadata,
                    clientId,
                    config.getInt(ProducerConfig.MAX_IN_FLIGHT_REQUESTS_PER_CONNECTION),
                    config.getLong(ProducerConfig.RECONNECT_BACKOFF_MS_CONFIG),
                    config.getInt(ProducerConfig.SEND_BUFFER_CONFIG),
                    config.getInt(ProducerConfig.RECEIVE_BUFFER_CONFIG),
                    this.requestTimeoutMs, time);
            this.sender = new Sender(client,
                    this.metadata,
                    this.accumulator,
                    config.getInt(ProducerConfig.MAX_IN_FLIGHT_REQUESTS_PER_CONNECTION) == 1,
                    config.getInt(ProducerConfig.MAX_REQUEST_SIZE_CONFIG),
                    (short) parseAcks(config.getString(ProducerConfig.ACKS_CONFIG)),
                    config.getInt(ProducerConfig.RETRIES_CONFIG),
                    this.metrics,
                    new SystemTime(),
                    clientId,
                    this.requestTimeoutMs);
            String ioThreadName = "kafka-producer-network-thread" + (clientId.length() > 0 ? " | " + clientId : "");
            this.ioThread = new KafkaThread(ioThreadName, this.sender, true);
            this.ioThread.start();

            this.errors = this.metrics.sensor("errors");

            if (keySerializer == null) {
                this.keySerializer = config.getConfiguredInstance(ProducerConfig.KEY_SERIALIZER_CLASS_CONFIG,
                        Serializer.class);
                this.keySerializer.configure(config.originals(), true);
            } else {
                config.ignore(ProducerConfig.KEY_SERIALIZER_CLASS_CONFIG);
                this.keySerializer = keySerializer;
            }
            if (valueSerializer == null) {
                this.valueSerializer = config.getConfiguredInstance(ProducerConfig.VALUE_SERIALIZER_CLASS_CONFIG,
                        Serializer.class);
                this.valueSerializer.configure(config.originals(), false);
            } else {
                config.ignore(ProducerConfig.VALUE_SERIALIZER_CLASS_CONFIG);
                this.valueSerializer = valueSerializer;
            }

            // load interceptors and make sure they get clientId
            userProvidedConfigs.put(ProducerConfig.CLIENT_ID_CONFIG, clientId);
            List<ProducerInterceptor<K, V>> interceptorList = (List) (new ProducerConfig(userProvidedConfigs)).getConfiguredInstances(ProducerConfig.INTERCEPTOR_CLASSES_CONFIG,
                    ProducerInterceptor.class);
            this.interceptors = interceptorList.isEmpty() ? null : new ProducerInterceptors<>(interceptorList);

            config.logUnused();
            AppInfoParser.registerAppInfo(JMX_PREFIX, clientId);
            log.debug("Kafka producer started");
        } catch (Throwable t) {
            // call close methods if internal objects are already constructed
            // this is to prevent resource leak. see KAFKA-2121
            close(0, TimeUnit.MILLISECONDS, true);
            // now propagate the exception
            throw new KafkaException("Failed to construct kafka producer", t);
        }
    }

    private static int parseAcks(String acksString) {
        try {
            return acksString.trim().equalsIgnoreCase("all") ? -1 : Integer.parseInt(acksString.trim());
        } catch (NumberFormatException e) {
            throw new ConfigException("Invalid configuration value for ‘acks‘: " + acksString);
        }
    }

    /**
     * Asynchronously send a record to a topic. Equivalent to <code>send(record, null)</code>.
     * See {@link #send(ProducerRecord, Callback)} for details.
     */
    @Override
    public Future<RecordMetadata> send(ProducerRecord<K, V> record) {
        return send(record, null);
    }

    /**
     * Asynchronously send a record to a topic and invoke the provided callback when the send has been acknowledged.
     * <p>
     * The send is asynchronous and this method will return immediately once the record has been stored in the buffer of
     * records waiting to be sent. This allows sending many records in parallel without blocking to wait for the
     * response after each one.
     * <p>
     * The result of the send is a {@link RecordMetadata} specifying the partition the record was sent to, the offset
     * it was assigned and the timestamp of the record. If
     * {@link org.apache.kafka.common.record.TimestampType#CREATE_TIME CreateTime} is used by the topic, the timestamp
     * will be the user provided timestamp or the record send time if the user did not specify a timestamp for the
     * record. If {@link org.apache.kafka.common.record.TimestampType#LOG_APPEND_TIME LogAppendTime} is used for the
     * topic, the timestamp will be the Kafka broker local time when the message is appended.
     * <p>
     * Since the send call is asynchronous it returns a {@link java.util.concurrent.Future Future} for the
     * {@link RecordMetadata} that will be assigned to this record. Invoking {@link java.util.concurrent.Future#get()
     * get()} on this future will block until the associated request completes and then return the metadata for the record
     * or throw any exception that occurred while sending the record.
     * <p>
     * If you want to simulate a simple blocking call you can call the <code>get()</code> method immediately:
     *
     * <pre>
     * {@code
     * byte[] key = "key".getBytes();
     * byte[] http://www.mamicode.com/value = "value".getBytes();
     * ProducerRecord<byte[],byte[]> record = new ProducerRecord<byte[],byte[]>("my-topic", key, value)
     * producer.send(record).get();
     * }</pre>
     * <p>
     * Fully non-blocking usage can make use of the {@link Callback} parameter to provide a callback that
     * will be invoked when the request is complete.
     *
     * <pre>
     * {@code
     * ProducerRecord<byte[],byte[]> record = new ProducerRecord<byte[],byte[]>("the-topic", key, value);
     * producer.send(myRecord,
     *               new Callback() {
     *                   public void onCompletion(RecordMetadata metadata, Exception e) {
     *                       if(e != null)
     *                           e.printStackTrace();
     *                       System.out.println("The offset of the record we just sent is: " + metadata.offset());
     *                   }
     *               });
     * }
     * </pre>
     *
     * Callbacks for records being sent to the same partition are guaranteed to execute in order. That is, in the
     * following example <code>callback1</code> is guaranteed to execute before <code>callback2</code>:
     *
     * <pre>
     * {@code
     * producer.send(new ProducerRecord<byte[],byte[]>(topic, partition, key1, value1), callback1);
     * producer.send(new ProducerRecord<byte[],byte[]>(topic, partition, key2, value2), callback2);
     * }
     * </pre>
     * <p>
     * Note that callbacks will generally execute in the I/O thread of the producer and so should be reasonably fast or
     * they will delay the sending of messages from other threads. If you want to execute blocking or computationally
     * expensive callbacks it is recommended to use your own {@link java.util.concurrent.Executor} in the callback body
     * to parallelize processing.
     *
     * @param record The record to send
     * @param callback A user-supplied callback to execute when the record has been acknowledged by the server (null
     *        indicates no callback)
     *
     * @throws InterruptException If the thread is interrupted while blocked
     * @throws SerializationException If the key or value are not valid objects given the configured serializers
     * @throws TimeoutException if the time taken for fetching metadata or allocating memory for the record has surpassed <code>max.block.ms</code>.
     *
     */
    @Override
    public Future<RecordMetadata> send(ProducerRecord<K, V> record, Callback callback) {
        // intercept the record, which can be potentially modified; this method does not throw exceptions
        ProducerRecord<K, V> interceptedRecord = this.interceptors == null ? record : this.interceptors.onSend(record);
        return doSend(interceptedRecord, callback);
    }

    /**
     * Implementation of asynchronously send a record to a topic. Equivalent to <code>send(record, null)</code>.
     * See {@link #send(ProducerRecord, Callback)} for details.
     */
    private Future<RecordMetadata> doSend(ProducerRecord<K, V> record, Callback callback) {
        TopicPartition tp = null;
        try {
            // first make sure the metadata for the topic is available
            long waitedOnMetadataMs = waitOnMetadata(record.topic(), this.maxBlockTimeMs);
            long remainingWaitMs = Math.max(0, this.maxBlockTimeMs - waitedOnMetadataMs);
            byte[] serializedKey;
            try {
                serializedKey = keySerializer.serialize(record.topic(), record.key());
            } catch (ClassCastException cce) {
                throw new SerializationException("Can‘t convert key of class " + record.key().getClass().getName() +
                        " to class " + producerConfig.getClass(ProducerConfig.KEY_SERIALIZER_CLASS_CONFIG).getName() +
                        " specified in key.serializer");
            }
            byte[] serializedValue;
            try {
                serializedValue = valueSerializer.serialize(record.topic(), record.value());
            } catch (ClassCastException cce) {
                throw new SerializationException("Can‘t convert value of class " + record.value().getClass().getName() +
                        " to class " + producerConfig.getClass(ProducerConfig.VALUE_SERIALIZER_CLASS_CONFIG).getName() +
                        " specified in value.serializer");
            }
            int partition = partition(record, serializedKey, serializedValue, metadata.fetch());
            int serializedSize = Records.LOG_OVERHEAD + Record.recordSize(serializedKey, serializedValue);
            ensureValidRecordSize(serializedSize);
            tp = new TopicPartition(record.topic(), partition);
            long timestamp = record.timestamp() == null ? time.milliseconds() : record.timestamp();
            log.trace("Sending record {} with callback {} to topic {} partition {}", record, callback, record.topic(), partition);
            // producer callback will make sure to call both ‘callback‘ and interceptor callback
            Callback interceptCallback = this.interceptors == null ? callback : new InterceptorCallback<>(callback, this.interceptors, tp);
            RecordAccumulator.RecordAppendResult result = accumulator.append(tp, timestamp, serializedKey, serializedValue, interceptCallback, remainingWaitMs);
            if (result.batchIsFull || result.newBatchCreated) {
                log.trace("Waking up the sender since topic {} partition {} is either full or getting a new batch", record.topic(), partition);
                this.sender.wakeup();
            }
            return result.future;
            // handling exceptions and record the errors;
            // for API exceptions return them in the future,
            // for other exceptions throw directly
        } catch (ApiException e) {
            log.debug("Exception occurred during message send:", e);
            if (callback != null)
                callback.onCompletion(null, e);
            this.errors.record();
            if (this.interceptors != null)
                this.interceptors.onSendError(record, tp, e);
            return new FutureFailure(e);
        } catch (InterruptedException e) {
            this.errors.record();
            if (this.interceptors != null)
                this.interceptors.onSendError(record, tp, e);
            throw new InterruptException(e);
        } catch (BufferExhaustedException e) {
            this.errors.record();
            this.metrics.sensor("buffer-exhausted-records").record();
            if (this.interceptors != null)
                this.interceptors.onSendError(record, tp, e);
            throw e;
        } catch (KafkaException e) {
            this.errors.record();
            if (this.interceptors != null)
                this.interceptors.onSendError(record, tp, e);
            throw e;
        } catch (Exception e) {
            // we notify interceptor about all exceptions, since onSend is called before anything else in this method
            if (this.interceptors != null)
                this.interceptors.onSendError(record, tp, e);
            throw e;
        }
    }

    /**
     * Wait for cluster metadata including partitions for the given topic to be available.
     * @param topic The topic we want metadata for
     * @param maxWaitMs The maximum time in ms for waiting on the metadata
     * @return The amount of time we waited in ms
     */
    private long waitOnMetadata(String topic, long maxWaitMs) throws InterruptedException {
        // add topic to metadata topic list if it is not there already.
        if (!this.metadata.containsTopic(topic))
            this.metadata.add(topic);

        if (metadata.fetch().partitionsForTopic(topic) != null)
            return 0;

        long begin = time.milliseconds();
        long remainingWaitMs = maxWaitMs;
        while (metadata.fetch().partitionsForTopic(topic) == null) {
            log.trace("Requesting metadata update for topic {}.", topic);
            int version = metadata.requestUpdate();
            sender.wakeup();
            metadata.awaitUpdate(version, remainingWaitMs);
            long elapsed = time.milliseconds() - begin;
            if (elapsed >= maxWaitMs)
                throw new TimeoutException("Failed to update metadata after " + maxWaitMs + " ms.");
            if (metadata.fetch().unauthorizedTopics().contains(topic))
                throw new TopicAuthorizationException(topic);
            remainingWaitMs = maxWaitMs - elapsed;
        }
        return time.milliseconds() - begin;
    }

    /**
     * Validate that the record size isn‘t too large
     */
    private void ensureValidRecordSize(int size) {
        if (size > this.maxRequestSize)
            throw new RecordTooLargeException("The message is " + size +
                                              " bytes when serialized which is larger than the maximum request size you have configured with the " +
                                              ProducerConfig.MAX_REQUEST_SIZE_CONFIG +
                                              " configuration.");
        if (size > this.totalMemorySize)
            throw new RecordTooLargeException("The message is " + size +
                                              " bytes when serialized which is larger than the total memory buffer you have configured with the " +
                                              ProducerConfig.BUFFER_MEMORY_CONFIG +
                                              " configuration.");
    }

    /**
     * Invoking this method makes all buffered records immediately available to send (even if <code>linger.ms</code> is
     * greater than 0) and blocks on the completion of the requests associated with these records. The post-condition
     * of <code>flush()</code> is that any previously sent record will have completed (e.g. <code>Future.isDone() == true</code>).
     * A request is considered completed when it is successfully acknowledged
     * according to the <code>acks</code> configuration you have specified or else it results in an error.
     * <p>
     * Other threads can continue sending records while one thread is blocked waiting for a flush call to complete,
     * however no guarantee is made about the completion of records sent after the flush call begins.
     * <p>
     * This method can be useful when consuming from some input system and producing into Kafka. The <code>flush()</code> call
     * gives a convenient way to ensure all previously sent messages have actually completed.
     * <p>
     * This example shows how to consume from one Kafka topic and produce to another Kafka topic:
     * <pre>
     * {@code
     * for(ConsumerRecord<String, String> record: consumer.poll(100))
     *     producer.send(new ProducerRecord("my-topic", record.key(), record.value());
     * producer.flush();
     * consumer.commit();
     * }
     * </pre>
     *
     * Note that the above example may drop records if the produce request fails. If we want to ensure that this does not occur
     * we need to set <code>retries=&lt;large_number&gt;</code> in our config.
     *
     * @throws InterruptException If the thread is interrupted while blocked
     */
    @Override
    public void flush() {
        log.trace("Flushing accumulated records in producer.");
        this.accumulator.beginFlush();
        this.sender.wakeup();
        try {
            this.accumulator.awaitFlushCompletion();
        } catch (InterruptedException e) {
            throw new InterruptException("Flush interrupted.", e);
        }
    }

    /**
     * Get the partition metadata for the give topic. This can be used for custom partitioning.
     * @throws InterruptException If the thread is interrupted while blocked
     */
    @Override
    public List<PartitionInfo> partitionsFor(String topic) {
        try {
            waitOnMetadata(topic, this.maxBlockTimeMs);
        } catch (InterruptedException e) {
            throw new InterruptException(e);
        }
        return this.metadata.fetch().partitionsForTopic(topic);
    }

    /**
     * Get the full set of internal metrics maintained by the producer.
     */
    @Override
    public Map<MetricName, ? extends Metric> metrics() {
        return Collections.unmodifiableMap(this.metrics.metrics());
    }

    /**
     * Close this producer. This method blocks until all previously sent requests complete.
     * This method is equivalent to <code>close(Long.MAX_VALUE, TimeUnit.MILLISECONDS)</code>.
     * <p>
     * <strong>If close() is called from {@link Callback}, a warning message will be logged and close(0, TimeUnit.MILLISECONDS)
     * will be called instead. We do this because the sender thread would otherwise try to join itself and
     * block forever.</strong>
     * <p>
     *
     * @throws InterruptException If the thread is interrupted while blocked
     */
    @Override
    public void close() {
        close(Long.MAX_VALUE, TimeUnit.MILLISECONDS);
    }

    /**
     * This method waits up to <code>timeout</code> for the producer to complete the sending of all incomplete requests.
     * <p>
     * If the producer is unable to complete all requests before the timeout expires, this method will fail
     * any unsent and unacknowledged records immediately.
     * <p>
     * If invoked from within a {@link Callback} this method will not block and will be equivalent to
     * <code>close(0, TimeUnit.MILLISECONDS)</code>. This is done since no further sending will happen while
     * blocking the I/O thread of the producer.
     *
     * @param timeout The maximum time to wait for producer to complete any pending requests. The value should be
     *                non-negative. Specifying a timeout of zero means do not wait for pending send requests to complete.
     * @param timeUnit The time unit for the <code>timeout</code>
     * @throws InterruptException If the thread is interrupted while blocked
     * @throws IllegalArgumentException If the <code>timeout</code> is negative.
     */
    @Override
    public void close(long timeout, TimeUnit timeUnit) {
        close(timeout, timeUnit, false);
    }

    private void close(long timeout, TimeUnit timeUnit, boolean swallowException) {
        if (timeout < 0)
            throw new IllegalArgumentException("The timeout cannot be negative.");

        log.info("Closing the Kafka producer with timeoutMillis = {} ms.", timeUnit.toMillis(timeout));
        // this will keep track of the first encountered exception
        AtomicReference<Throwable> firstException = new AtomicReference<Throwable>();
        boolean invokedFromCallback = Thread.currentThread() == this.ioThread;
        if (timeout > 0) {
            if (invokedFromCallback) {
                log.warn("Overriding close timeout {} ms to 0 ms in order to prevent useless blocking due to self-join. " +
                    "This means you have incorrectly invoked close with a non-zero timeout from the producer call-back.", timeout);
            } else {
                // Try to close gracefully.
                if (this.sender != null)
                    this.sender.initiateClose();
                if (this.ioThread != null) {
                    try {
                        this.ioThread.join(timeUnit.toMillis(timeout));
                    } catch (InterruptedException t) {
                        firstException.compareAndSet(null, t);
                        log.error("Interrupted while joining ioThread", t);
                    }
                }
            }
        }

        if (this.sender != null && this.ioThread != null && this.ioThread.isAlive()) {
            log.info("Proceeding to force close the producer since pending requests could not be completed " +
                "within timeout {} ms.", timeout);
            this.sender.forceClose();
            // Only join the sender thread when not calling from callback.
            if (!invokedFromCallback) {
                try {
                    this.ioThread.join();
                } catch (InterruptedException e) {
                    firstException.compareAndSet(null, e);
                }
            }
        }

        ClientUtils.closeQuietly(interceptors, "producer interceptors", firstException);
        ClientUtils.closeQuietly(metrics, "producer metrics", firstException);
        ClientUtils.closeQuietly(keySerializer, "producer keySerializer", firstException);
        ClientUtils.closeQuietly(valueSerializer, "producer valueSerializer", firstException);
        AppInfoParser.unregisterAppInfo(JMX_PREFIX, clientId);
        log.debug("The Kafka producer has closed.");
        if (firstException.get() != null && !swallowException)
            throw new KafkaException("Failed to close kafka producer", firstException.get());
    }

    /**
     * computes partition for given record.
     * if the record has partition returns the value otherwise
     * calls configured partitioner class to compute the partition.
     */
    private int partition(ProducerRecord<K, V> record, byte[] serializedKey , byte[] serializedValue, Cluster cluster) {
        Integer partition = record.partition();
        if (partition != null) {
            List<PartitionInfo> partitions = cluster.partitionsForTopic(record.topic());
            int lastPartition = partitions.size() - 1;
            // they have given us a partition, use it
            if (partition < 0 || partition > lastPartition) {
                throw new IllegalArgumentException(String.format("Invalid partition given with record: %d is not in the range [0...%d].", partition, lastPartition));
            }
            return partition;
        }
        return this.partitioner.partition(record.topic(), record.key(), serializedKey, record.value(), serializedValue,
            cluster);
    }

    private static class FutureFailure implements Future<RecordMetadata> {

        private final ExecutionException exception;

        public FutureFailure(Exception exception) {
            this.exception = new ExecutionException(exception);
        }

        @Override
        public boolean cancel(boolean interrupt) {
            return false;
        }

        @Override
        public RecordMetadata get() throws ExecutionException {
            throw this.exception;
        }

        @Override
        public RecordMetadata get(long timeout, TimeUnit unit) throws ExecutionException {
            throw this.exception;
        }

        @Override
        public boolean isCancelled() {
            return false;
        }

        @Override
        public boolean isDone() {
            return true;
        }

    }

    /**
     * A callback called when producer request is complete. It in turn calls user-supplied callback (if given) and
     * notifies producer interceptors about the request completion.
     */
    private static class InterceptorCallback<K, V> implements Callback {
        private final Callback userCallback;
        private final ProducerInterceptors<K, V> interceptors;
        private final TopicPartition tp;

        public InterceptorCallback(Callback userCallback, ProducerInterceptors<K, V> interceptors,
                                   TopicPartition tp) {
            this.userCallback = userCallback;
            this.interceptors = interceptors;
            this.tp = tp;
        }

        public void onCompletion(RecordMetadata metadata, Exception exception) {
            if (this.interceptors != null) {
                if (metadata =http://www.mamicode.com/= null) {
                    this.interceptors.onAcknowledgement(new RecordMetadata(tp, -1, -1, Record.NO_TIMESTAMP, -1, -1, -1),
                                                        exception);
                } else {
                    this.interceptors.onAcknowledgement(metadata, exception);
                }
            }
            if (this.userCallback != null)
                this.userCallback.onCompletion(metadata, exception);
        }
    }
}

/**
 * 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.kafka.clients.producer;

import java.util.ArrayDeque;
import java.util.ArrayList;
import java.util.Collections;
import java.util.Deque;
import java.util.HashMap;
import java.util.List;
import java.util.Map;
import java.util.concurrent.Future;
import java.util.concurrent.TimeUnit;

import org.apache.kafka.clients.producer.internals.FutureRecordMetadata;
import org.apache.kafka.clients.producer.internals.DefaultPartitioner;
import org.apache.kafka.clients.producer.internals.ProduceRequestResult;
import org.apache.kafka.common.Cluster;
import org.apache.kafka.common.Metric;
import org.apache.kafka.common.MetricName;
import org.apache.kafka.common.PartitionInfo;
import org.apache.kafka.common.TopicPartition;
import org.apache.kafka.common.record.Record;
import org.apache.kafka.common.serialization.Serializer;


/**
 * A mock of the producer interface you can use for testing code that uses Kafka.
 * <p>
 * By default this mock will synchronously complete each send call successfully. However it can be configured to allow
 * the user to control the completion of the call and supply an optional error for the producer to throw.
 */
public class MockProducer<K, V> implements Producer<K, V> {

    private final Cluster cluster;
    private final Partitioner partitioner;
    private final List<ProducerRecord<K, V>> sent;
    private final Deque<Completion> completions;
    private boolean autoComplete;
    private Map<TopicPartition, Long> offsets;
    private final Serializer<K> keySerializer;
    private final Serializer<V> valueSerializer;

    /**
     * Create a mock producer
     *
     * @param cluster The cluster holding metadata for this producer
     * @param autoComplete If true automatically complete all requests successfully and execute the callback. Otherwise
     *        the user must call {@link #completeNext()} or {@link #errorNext(RuntimeException)} after
     *        {@link #send(ProducerRecord) send()} to complete the call and unblock the @{link
     *        java.util.concurrent.Future Future&lt;RecordMetadata&gt;} that is returned.
     * @param partitioner The partition strategy
     * @param keySerializer The serializer for key that implements {@link Serializer}.
     * @param valueSerializer The serializer for value that implements {@link Serializer}.
     */
    public MockProducer(Cluster cluster, boolean autoComplete, Partitioner partitioner, Serializer<K> keySerializer, Serializer<V> valueSerializer) {
        this.cluster = cluster;
        this.autoComplete = autoComplete;
        this.partitioner = partitioner;
        this.keySerializer = keySerializer;
        this.valueSerializer = valueSerializer;
        this.offsets = new HashMap<TopicPartition, Long>();
        this.sent = new ArrayList<ProducerRecord<K, V>>();
        this.completions = new ArrayDeque<Completion>();
    }

    /**
     * Create a new mock producer with invented metadata the given autoComplete setting and key\value serializers
     *
     * Equivalent to {@link #MockProducer(Cluster, boolean, Partitioner, Serializer, Serializer)} new MockProducer(Cluster.empty(), autoComplete, new DefaultPartitioner(), keySerializer, valueSerializer)}
     */
    public MockProducer(boolean autoComplete, Serializer<K> keySerializer, Serializer<V> valueSerializer) {
        this(Cluster.empty(), autoComplete, new DefaultPartitioner(), keySerializer, valueSerializer);
    }

    /**
     * Create a new mock producer with invented metadata the given autoComplete setting, partitioner and key\value serializers
     *
     * Equivalent to {@link #MockProducer(Cluster, boolean, Partitioner, Serializer, Serializer)} new MockProducer(Cluster.empty(), autoComplete, partitioner, keySerializer, valueSerializer)}
     */
    public MockProducer(boolean autoComplete, Partitioner partitioner, Serializer<K> keySerializer, Serializer<V> valueSerializer) {
        this(Cluster.empty(), autoComplete, partitioner, keySerializer, valueSerializer);
    }

    /**
     * Adds the record to the list of sent records. The {@link RecordMetadata} returned will be immediately satisfied.
     * 
     * @see #history()
     */
    @Override
    public synchronized Future<RecordMetadata> send(ProducerRecord<K, V> record) {
        return send(record, null);
    }

    /**
     * Adds the record to the list of sent records.
     *
     * @see #history()
     */
    @Override
    public synchronized Future<RecordMetadata> send(ProducerRecord<K, V> record, Callback callback) {
        int partition = 0;
        if (this.cluster.partitionsForTopic(record.topic()) != null)
            partition = partition(record, this.cluster);
        ProduceRequestResult result = new ProduceRequestResult();
        FutureRecordMetadata future = new FutureRecordMetadata(result, 0, Record.NO_TIMESTAMP, 0, 0, 0);
        TopicPartition topicPartition = new TopicPartition(record.topic(), partition);
        long offset = nextOffset(topicPartition);
        Completion completion = new Completion(topicPartition, offset,
                                               new RecordMetadata(topicPartition, 0, offset, Record.NO_TIMESTAMP, 0, 0, 0),
                                               result, callback);
        this.sent.add(record);
        if (autoComplete)
            completion.complete(null);
        else
            this.completions.addLast(completion);
        return future;
    }

    /**
     * Get the next offset for this topic/partition
     */
    private long nextOffset(TopicPartition tp) {
        Long offset = this.offsets.get(tp);
        if (offset == null) {
            this.offsets.put(tp, 1L);
            return 0L;
        } else {
            Long next = offset + 1;
            this.offsets.put(tp, next);
            return offset;
        }
    }

    public synchronized void flush() {
        while (!this.completions.isEmpty())
            completeNext();
    }

    public List<PartitionInfo> partitionsFor(String topic) {
        return this.cluster.partitionsForTopic(topic);
    }

    public Map<MetricName, Metric> metrics() {
        return Collections.emptyMap();
    }

    @Override
    public void close() {
    }

    @Override
    public void close(long timeout, TimeUnit timeUnit) {
    }

    /**
     * Get the list of sent records since the last call to {@link #clear()}
     */
    public synchronized List<ProducerRecord<K, V>> history() {
        return new ArrayList<ProducerRecord<K, V>>(this.sent);
    }

    /**
     * Clear the stored history of sent records
     */
    public synchronized void clear() {
        this.sent.clear();
        this.completions.clear();
    }

    /**
     * Complete the earliest uncompleted call successfully.
     *
     * @return true if there was an uncompleted call to complete
     */
    public synchronized boolean completeNext() {
        return errorNext(null);
    }

    /**
     * Complete the earliest uncompleted call with the given error.
     *
     * @return true if there was an uncompleted call to complete
     */
    public synchronized boolean errorNext(RuntimeException e) {
        Completion completion = this.completions.pollFirst();
        if (completion != null) {
            completion.complete(e);
            return true;
        } else {
            return false;
        }
    }

    /**
     * computes partition for given record.
     */
    private int partition(ProducerRecord<K, V> record, Cluster cluster) {
        Integer partition = record.partition();
        String topic = record.topic();
        if (partition != null) {
            List<PartitionInfo> partitions = cluster.partitionsForTopic(topic);
            int numPartitions = partitions.size();
            // they have given us a partition, use it
            if (partition < 0 || partition >= numPartitions)
                throw new IllegalArgumentException("Invalid partition given with record: " + partition
                                                   + " is not in the range [0..."
                                                   + numPartitions
                                                   + "].");
            return partition;
        }
        byte[] keyBytes = keySerializer.serialize(topic, record.key());
        byte[] valueBytes = valueSerializer.serialize(topic, record.value());
        return this.partitioner.partition(topic, record.key(), keyBytes, record.value(), valueBytes, cluster);
    }

    private static class Completion {
        private final long offset;
        private final RecordMetadata metadata;
        private final ProduceRequestResult result;
        private final Callback callback;
        private final TopicPartition topicPartition;

        public Completion(TopicPartition topicPartition,
                          long offset,
                          RecordMetadata metadata,
                          ProduceRequestResult result,
                          Callback callback) {
            this.metadata =http://www.mamicode.com/ metadata;
            this.offset = offset;
            this.result = result;
            this.callback = callback;
            this.topicPartition = topicPartition;
        }

        public void complete(RuntimeException e) {
            result.done(topicPartition, e == null ? offset : -1L, e);
            if (callback != null) {
                if (e == null)
                    callback.onCompletion(metadata, null);
                else
                    callback.onCompletion(null, e);
            }
        }
    }

}

/**
 * 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.kafka.clients.producer;

import org.apache.kafka.common.Configurable;
import org.apache.kafka.common.Cluster;

/**
 * Partitioner Interface
 */

public interface Partitioner extends Configurable {

    /**
     * Compute the partition for the given record.
     *
     * @param topic The topic name
     * @param key The key to partition on (or null if no key)
     * @param keyBytes The serialized key to partition on( or null if no key)
     * @param value The value to partition on or null
     * @param valueBytes The serialized value to partition on or null
     * @param cluster The current cluster metadata
     */
    public int partition(String topic, Object key, byte[] keyBytes, Object value, byte[] valueBytes, Cluster cluster);

    /**
     * This is called when partitioner is closed.
     */
    public void close();

}

/**
 * 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.kafka.clients.producer.internals;

import java.util.List;
import java.util.Map;
import java.util.Random;
import java.util.concurrent.atomic.AtomicInteger;

import org.apache.kafka.clients.producer.Partitioner;
import org.apache.kafka.common.Cluster;
import org.apache.kafka.common.PartitionInfo;
import org.apache.kafka.common.utils.Utils;

/**
 * The default partitioning strategy:
 * <ul>
 * <li>If a partition is specified in the record, use it
 * <li>If no partition is specified but a key is present choose a partition based on a hash of the key
 * <li>If no partition or key is present choose a partition in a round-robin fashion
 */
public class DefaultPartitioner implements Partitioner {

    private final AtomicInteger counter = new AtomicInteger(new Random().nextInt());

    /**
     * A cheap way to deterministically convert a number to a positive value. When the input is
     * positive, the original value is returned. When the input number is negative, the returned
     * positive value is the original value bit AND against 0x7fffffff which is not its absolutely
     * value.
     *
     * Note: changing this method in the future will possibly cause partition selection not to be
     * compatible with the existing messages already placed on a partition.
     *
     * @param number a given number
     * @return a positive number.
     */
    private static int toPositive(int number) {
        return number & 0x7fffffff;
    }

    public void configure(Map<String, ?> configs) {}

    /**
     * Compute the partition for the given record.
     *
     * @param topic The topic name
     * @param key The key to partition on (or null if no key)
     * @param keyBytes serialized key to partition on (or null if no key)
     * @param value The value to partition on or null
     * @param valueBytes serialized value to partition on or null
     * @param cluster The current cluster metadata
     */
    public int partition(String topic, Object key, byte[] keyBytes, Object value, byte[] valueBytes, Cluster cluster) {
        List<PartitionInfo> partitions = cluster.partitionsForTopic(topic);
        int numPartitions = partitions.size();
        if (keyBytes == null) {
            int nextValue =http://www.mamicode.com/ counter.getAndIncrement();
            List<PartitionInfo> availablePartitions = cluster.availablePartitionsForTopic(topic);
            if (availablePartitions.size() > 0) {
                int part = DefaultPartitioner.toPositive(nextValue) % availablePartitions.size();
                return availablePartitions.get(part).partition();
            } else {
                // no partitions are available, give a non-available partition
                return DefaultPartitioner.toPositive(nextValue) % numPartitions;
            }
        } else {
            // hash the keyBytes to choose a partition
            return DefaultPartitioner.toPositive(Utils.murmur2(keyBytes)) % numPartitions;
        }
    }

    public void close() {}

}