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+Kafka uses key-value pairs in the <a
href="http://en.wikipedia.org/wiki/.properties";>property file format</a> for
configuration. These values can be supplied either from a file or
programmatically.
+
+<h3><a id="brokerconfigs">3.1 Broker Configs</a></h3>
+
+The essential configurations are the following:
+<ul>
+ <li><code>broker.id</code>
+ <li><code>log.dirs</code>
+ <li><code>zookeeper.connect</code>
+</ul>
+
+Topic-level configurations and defaults are discussed in more detail <a
href="#topic-config">below</a>.
+
+<table class="data-table">
+<tbody><tr>
+ <th>Property</th>
+ <th>Default</th>
+ <th>Description</th>
+ </tr>
+ <tr>
+ <td>broker.id</td>
+ <td></td>
+ <td>Each broker is uniquely identified by a non-negative integer id.
This id serves as the broker's "name" and allows the broker to be moved to a
different host/port without confusing consumers. You can choose any number you
like so long as it is unique.
+ </td>
+ </tr>
+ <tr>
+ <td>log.dirs</td>
+ <td nowrap>/tmp/kafka-logs</td>
+ <td>A comma-separated list of one or more directories in which Kafka
data is stored. Each new partition that is created will be placed in the
directory which currently has the fewest partitions.</td>
+ </tr>
+ <tr>
+ <td>port</td>
+ <td>9092</td>
+ <td>The port on which the server accepts client connections.</td>
+ </tr>
+ <tr>
+ <td>zookeeper.connect</td>
+ <td>null</td>
+ <td>Specifies the ZooKeeper connection string in the form
<code>hostname:port</code>, where hostname and port are the host and port for a
node in your ZooKeeper cluster. To allow connecting through other ZooKeeper
nodes when that host is down you can also specify multiple hosts in the form
<code>hostname1:port1,hostname2:port2,hostname3:port3</code>.
+ <p>
+ZooKeeper also allows you to add a "chroot" path which will make all kafka
data for this cluster appear under a particular path. This is a way to setup
multiple Kafka clusters or other applications on the same ZooKeeper cluster. To
do this give a connection string in the form
<code>hostname1:port1,hostname2:port2,hostname3:port3/chroot/path</code> which
would put all this cluster's data under the path <code>/chroot/path</code>.
Note that consumers must use the same connection string.</td>
+ </tr>
+ <tr>
+ <td>message.max.bytes</td>
+ <td>1000000</td>
+ <td>The maximum size of a message that the server can receive. It is
important that this property be in sync with the maximum fetch size your
consumers use or else an unruly producer will be able to publish messages too
large for consumers to consume.</td>
+ </tr>
+ <tr>
+ <td>num.network.threads</td>
+ <td>3</td>
+ <td>The number of network threads that the server uses for handling
network requests. You probably don't need to change this.</td>
+ </tr>
+ <tr>
+ <td>num.io.threads</td>
+ <td>8</td>
+ <td>The number of I/O threads that the server uses for executing
requests. You should have at least as many threads as you have disks.</td>
+ </tr>
+ <tr>
+ <td>background.threads</td>
+ <td>10</td>
+ <td>The number of threads to use for various background processing tasks
such as file deletion. You should not need to change this.</td>
+ </tr>
+ <tr>
+ <td>queued.max.requests</td>
+ <td>500</td>
+ <td>The number of requests that can be queued up for processing by the
I/O threads before the network threads stop reading in new requests.</td>
+ </tr>
+ <tr>
+ <td>host.name</td>
+ <td>null</td>
+ <td>
+ <p>Hostname of broker. If this is set, it will only bind to this
address. If this is not set, it will bind to all interfaces, and publish one to
ZK.</p>
+ </td>
+ </tr>
+ <tr>
+ <td>advertised.host.name</td>
+ <td>null</td>
+ <td>
+ <p>If this is set this is the hostname that will be given out to
producers, consumers, and other brokers to connect to.</p>
+ </td>
+ </tr>
+ <tr>
+ <td>advertised.port</td>
+ <td>null</td>
+ <td>
+ <p>The port to give out to producers, consumers, and other brokers to
use in establishing connections. This only needs to be set if this port is
different from the port the server should bind to.</p>
+ </td>
+ </tr>
+ <tr>
+ <td>socket.send.buffer.bytes</td>
+ <td>100 * 1024</td>
+ <td>The SO_SNDBUFF buffer the server prefers for socket connections.</td>
+ </tr>
+ <tr>
+ <td>socket.receive.buffer.bytes</td>
+ <td>100 * 1024</td>
+ <td>The SO_RCVBUFF buffer the server prefers for socket connections.</td>
+ </tr>
+ <tr>
+ <td>socket.request.max.bytes</td>
+ <td>100 * 1024 * 1024</td>
+ <td>The maximum request size the server will allow. This prevents the
server from running out of memory and should be smaller than the Java heap
size.</td>
+ </tr>
+ <tr>
+ <td>num.partitions</td>
+ <td>1</td>
+ <td>The default number of partitions per topic if a partition count
isn't given at topic creation time.</td>
+ </tr>
+ <tr>
+ <td>log.segment.bytes</td>
+ <td nowrap>1024 * 1024 * 1024</td>
+ <td>The log for a topic partition is stored as a directory of segment
files. This setting controls the size to which a segment file will grow before
a new segment is rolled over in the log. This setting can be overridden on a
per-topic basis (see <a href="#topic-config">the per-topic configuration
section</a>).</td>
+ </tr>
+ <tr>
+ <td>log.roll.{ms,hours}</td>
+ <td>24 * 7 hours</td>
+ <td>This setting will force Kafka to roll a new log segment even if the
log.segment.bytes size has not been reached. This setting can be overridden on
a per-topic basis (see <a href="#topic-config">the per-topic configuration
section</a>).</td>
+ </tr>
+ <tr>
+ <td>log.cleanup.policy</td>
+ <td>delete</td>
+ <td>This can take either the value <i>delete</i> or <i>compact</i>. If
<i>delete</i> is set, log segments will be deleted when they reach the size or
time limits set. If <i>compact</i> is set <a href="#compaction">log
compaction</a> will be used to clean out obsolete records. This setting can be
overridden on a per-topic basis (see <a href="#topic-config">the per-topic
configuration section</a>).</td>
+ </tr>
+ <tr>
+ <td>log.retention.{ms,minutes,hours}</td>
+ <td>7 days</td>
+ <td>The amount of time to keep a log segment before it is deleted, i.e.
the default data retention window for all topics. Note that if both
log.retention.minutes and log.retention.bytes are both set we delete a segment
when either limit is exceeded. This setting can be overridden on a per-topic
basis (see <a href="#topic-config">the per-topic configuration
section</a>).</td>
+ </tr>
+ <tr>
+ <td>log.retention.bytes</td>
+ <td>-1</td>
+ <td>The amount of data to retain in the log for each topic-partitions.
Note that this is the limit per-partition so multiply by the number of
partitions to get the total data retained for the topic. Also note that if both
log.retention.hours and log.retention.bytes are both set we delete a segment
when either limit is exceeded. This setting can be overridden on a per-topic
basis (see <a href="#topic-config">the per-topic configuration
section</a>).</td>
+ </tr>
+ <tr>
+ <td>log.retention.check.interval.ms</td>
+ <td>5 minutes</td>
+ <td>The period with which we check whether any log segment is eligible
for deletion to meet the retention policies.</td>
+ </tr>
+ <tr>
+ <td>log.cleaner.enable</td>
+ <td>false</td>
+ <td>This configuration must be set to true for log compaction to
run.</td>
+ </tr>
+ <tr>
+ <td>log.cleaner.threads</td>
+ <td>1</td>
+ <td>The number of threads to use for cleaning logs in log
compaction.</td>
+ </tr>
+ <tr>
+ <td>log.cleaner.io.max.bytes.per.second</td>
+ <td>Double.MaxValue</td>
+ <td>The maximum amount of I/O the log cleaner can do while performing
log compaction. This setting allows setting a limit for the cleaner to avoid
impacting live request serving.</td>
+ </tr>
+ <tr>
+ <td>log.cleaner.dedupe.buffer.size</td>
+ <td>500*1024*1024</td>
+ <td>The size of the buffer the log cleaner uses for indexing and
deduplicating logs during cleaning. Larger is better provided you have
sufficient memory.</td>
+ </tr>
+ <tr>
+ <td>log.cleaner.io.buffer.size</td>
+ <td>512*1024</td>
+ <td>The size of the I/O chunk used during log cleaning. You probably
don't need to change this.</td>
+ </tr>
+ <tr>
+ <td>log.cleaner.io.buffer.load.factor</td>
+ <td>0.9</td>
+ <td>The load factor of the hash table used in log cleaning. You probably
don't need to change this.</td>
+ </tr>
+ <tr>
+ <td>log.cleaner.backoff.ms</td>
+ <td>15000</td>
+ <td>The interval between checks to see if any logs need cleaning.</td>
+ </tr>
+ <tr>
+ <td>log.cleaner.min.cleanable.ratio</td>
+ <td>0.5</td>
+ <td>This configuration controls how frequently the log compactor will
attempt to clean the log (assuming <a href="#compaction">log compaction</a> is
enabled). By default we will avoid cleaning a log where more than 50% of the
log has been compacted. This ratio bounds the maximum space wasted in the log
by duplicates (at 50% at most 50% of the log could be duplicates). A higher
ratio will mean fewer, more efficient cleanings but will mean more wasted space
in the log. This setting can be overridden on a per-topic basis (see <a
href="#topic-config">the per-topic configuration section</a>).</td>
+ </tr>
+ <tr>
+ <td>log.cleaner.delete.retention.ms</td>
+ <td>1 day</td>
+ <td>The amount of time to retain delete tombstone markers for <a
href="#compaction">log compacted</a> topics. This setting also gives a bound on
the time in which a consumer must complete a read if they begin from offset 0
to ensure that they get a valid snapshot of the final stage (otherwise delete
tombstones may be collected before they complete their scan). This setting can
be overridden on a per-topic basis (see <a href="#topic-config">the per-topic
configuration section</a>).</td>
+ </tr>
+ <tr>
+ <td>log.index.size.max.bytes</td>
+ <td>10 * 1024 * 1024</td>
+ <td>The maximum size in bytes we allow for the offset index for each log
segment. Note that we will always pre-allocate a sparse file with this much
space and shrink it down when the log rolls. If the index fills up we will roll
a new log segment even if we haven't reached the log.segment.bytes limit. This
setting can be overridden on a per-topic basis (see <a href="#topic-config">the
per-topic configuration section</a>).</td>
+ </tr>
+ <tr>
+ <td>log.index.interval.bytes</td>
+ <td>4096</td>
+ <td>The byte interval at which we add an entry to the offset index. When
executing a fetch request the server must do a linear scan for up to this many
bytes to find the correct position in the log to begin and end the fetch. So
setting this value to be larger will mean larger index files (and a bit more
memory usage) but less scanning. However the server will never add more than
one index entry per log append (even if more than log.index.interval worth of
messages are appended). In general you probably don't need to mess with this
value.</td>
+ </tr>
+ <tr>
+ <td>log.flush.interval.messages</td>
+ <td>Long.MaxValue</td>
+ <td>The number of messages written to a log partition before we force an
fsync on the log. Setting this lower will sync data to disk more often but will
have a major impact on performance. We generally recommend that people make use
of replication for durability rather than depending on single-server fsync,
however this setting can be used to be extra certain.</td>
+ </tr>
+ <tr>
+ <td>log.flush.scheduler.interval.ms</td>
+ <td>Long.MaxValue</td>
+ <td>The frequency in ms that the log flusher checks whether any log is
eligible to be flushed to disk.</td>
+ </tr>
+ <tr>
+ <td>log.flush.interval.ms</td>
+ <td>Long.MaxValue</td>
+ <td>The maximum time between fsync calls on the log. If used in
conjuction with log.flush.interval.messages the log will be flushed when either
criteria is met.</td>
+ </tr>
+ <tr>
+ <td>log.delete.delay.ms</td>
+ <td>60000</td>
+ <td>The period of time we hold log files around after they are removed
from the in-memory segment index. This period of time allows any in-progress
reads to complete uninterrupted without locking. You generally don't need to
change this.</td>
+ </tr>
+ <tr>
+ <td>log.flush.offset.checkpoint.interval.ms</td>
+ <td>60000</td>
+ <td>The frequency with which we checkpoint the last flush point for logs
for recovery. You should not need to change this.</td>
+ </tr>
+ <tr>
+ <td>log.segment.delete.delay.ms</td>
+ <td>60000</td>
+ <td>the amount of time to wait before deleting a file from the
filesystem.</td>
+ </tr>
+ <tr>
+ <td>auto.create.topics.enable</td>
+ <td>true</td>
+ <td>Enable auto creation of topic on the server. If this is set to true
then attempts to produce data or fetch metadata for a non-existent topic will
automatically create it with the default replication factor and number of
partitions.</td>
+ </tr>
+ <tr>
+ <td>controller.socket.timeout.ms</td>
+ <td>30000</td>
+ <td>The socket timeout for commands from the partition management
controller to the replicas.</td>
+ </tr>
+ <tr>
+ <td>controller.message.queue.size</td>
+ <td>Int.MaxValue</td>
+ <td>The buffer size for controller-to-broker-channels</td>
+ </tr>
+ <tr>
+ <td>default.replication.factor</td>
+ <td>1</td>
+ <td>The default replication factor for automatically created topics.</td>
+ </tr>
+ <tr>
+ <td>replica.lag.time.max.ms</td>
+ <td>10000</td>
+ <td>If a follower hasn't sent any fetch requests for this window of
time, the leader will remove the follower from ISR (in-sync replicas) and treat
it as dead.</td>
+ </tr>
+ <tr>
+ <td>replica.socket.timeout.ms</td>
+ <td>30 * 1000</td>
+ <td>The socket timeout for network requests to the leader for
replicating data.</td>
+ </tr>
+ <tr>
+ <td>replica.socket.receive.buffer.bytes</td>
+ <td>64 * 1024</td>
+ <td>The socket receive buffer for network requests to the leader for
replicating data.</td>
+ </tr>
+ <tr>
+ <td>replica.fetch.max.bytes</td>
+ <td nowrap>1024 * 1024</td>
+ <td>The number of byes of messages to attempt to fetch for each
partition in the fetch requests the replicas send to the leader.</td>
+ </tr>
+ <tr>
+ <td>replica.fetch.wait.max.ms</td>
+ <td>500</td>
+ <td>The maximum amount of time to wait time for data to arrive on the
leader in the fetch requests sent by the replicas to the leader.</td>
+ </tr>
+ <tr>
+ <td>replica.fetch.min.bytes</td>
+ <td>1</td>
+ <td>Minimum bytes expected for each fetch response for the fetch
requests from the replica to the leader. If not enough bytes, wait up to
replica.fetch.wait.max.ms for this many bytes to arrive.</td>
+ </tr>
+ <tr>
+ <td>num.replica.fetchers</td>
+ <td>1</td>
+ <td>
+ <p>Number of threads used to replicate messages from leaders.
Increasing this value can increase the degree of I/O parallelism in the
follower broker.</p>
+ </td>
+ </tr>
+ <tr>
+ <td>replica.high.watermark.checkpoint.interval.ms</td>
+ <td>5000</td>
+ <td>The frequency with which each replica saves its high watermark to
disk to handle recovery.</td>
+ </tr>
+ <tr>
+ <td>fetch.purgatory.purge.interval.requests</td>
+ <td>1000</td>
+ <td>The purge interval (in number of requests) of the fetch request
purgatory.</td>
+ </tr>
+ <tr>
+ <td>producer.purgatory.purge.interval.requests</td>
+ <td>1000</td>
+ <td>The purge interval (in number of requests) of the producer request
purgatory.</td>
+ </tr>
+ <tr>
+ <td>zookeeper.session.timeout.ms</td>
+ <td>6000</td>
+ <td>ZooKeeper session timeout. If the server fails to heartbeat to
ZooKeeper within this period of time it is considered dead. If you set this too
low the server may be falsely considered dead; if you set it too high it may
take too long to recognize a truly dead server.</td>
+ </tr>
+ <tr>
+ <td>zookeeper.connection.timeout.ms</td>
+ <td>6000</td>
+ <td>The maximum amount of time that the client waits to establish a
connection to zookeeper.</td>
+ </tr>
+ <tr>
+ <td>zookeeper.sync.time.ms</td>
+ <td>2000</td>
+ <td>How far a ZK follower can be behind a ZK leader.</td>
+ </tr>
+ <tr>
+ <td>controlled.shutdown.enable</td>
+ <td>true</td>
+ <td>Enable controlled shutdown of the broker. If enabled, the broker
will move all leaders on it to some other brokers before shutting itself down.
This reduces the unavailability window during shutdown.</td>
+ </tr>
+ <tr>
+ <td>controlled.shutdown.max.retries</td>
+ <td>3</td>
+ <td>Number of retries to complete the controlled shutdown successfully
before executing an unclean shutdown.</td>
+ </tr>
+ <tr>
+ <td>controlled.shutdown.retry.backoff.ms</td>
+ <td>5000</td>
+ <td>Backoff time between shutdown retries.</td>
+ </tr>
+ <tr>
+ <td>auto.leader.rebalance.enable</td>
+ <td>true</td>
+ <td>If this is enabled the controller will automatically try to balance
leadership for partitions among the brokers by periodically returning
leadership to the "preferred" replica for each partition if it is
available.</td>
+ </tr>
+ <tr>
+ <td>leader.imbalance.per.broker.percentage</td>
+ <td>10</td>
+ <td>The percentage of leader imbalance allowed per broker. The
controller will rebalance leadership if this ratio goes above
+ the configured value per broker.</td>
+ </tr>
+ <tr>
+ <td>leader.imbalance.check.interval.seconds</td>
+ <td>300</td>
+ <td>The frequency with which to check for leader imbalance.</td>
+ </tr>
+ <tr>
+ <td>offset.metadata.max.bytes</td>
+ <td>4096</td>
+ <td>The maximum amount of metadata to allow clients to save with their
offsets.</td>
+ </tr>
+ <tr>
+ <td>max.connections.per.ip</td>
+ <td>Int.MaxValue</td>
+ <td>The maximum number of connections that a broker allows from each ip
address.</td>
+ </tr>
+ <tr>
+ <td>max.connections.per.ip.overrides</td>
+ <td></td>
+ <td>Per-ip or hostname overrides to the default maximum number of
connections.</td>
+ </tr>
+ <tr>
+ <td>connections.max.idle.ms</td>
+ <td>600000</td>
+ <td>Idle connections timeout: the server socket processor threads close
the connections that idle more than this.</td>
+ </tr>
+ <tr>
+ <td>log.roll.jitter.{ms,hours}</td>
+ <td>0</td>
+ <td>The maximum jitter to subtract from logRollTimeMillis.</td>
+ </tr>
+ <tr>
+ <td>num.recovery.threads.per.data.dir</td>
+ <td>1</td>
+ <td>The number of threads per data directory to be used for log recovery
at startup and flushing at shutdown.</td>
+ </tr>
+ <tr>
+ <td>unclean.leader.election.enable</td>
+ <td>true</td>
+ <td>Indicates whether to enable replicas not in the ISR set to be
elected as leader as a last resort, even though doing so may result in data
loss.</td>
+ </tr>
+ <tr>
+ <td>delete.topic.enable</td>
+ <td>false</td>
+ <td>Enable delete topic.</td>
+ </tr>
+ <tr>
+ <td>offsets.topic.num.partitions</td>
+ <td>50</td>
+ <td>The number of partitions for the offset commit topic. Since changing
this after deployment is currently unsupported, we recommend using a higher
setting for production (e.g., 100-200).</td>
+ </tr>
+ <tr>
+ <td>offsets.topic.retention.minutes</td>
+ <td>1440</td>
+ <td>Offsets that are older than this age will be marked for deletion.
The actual purge will occur when the log cleaner compacts the offsets
topic.</td>
+ </tr>
+ <tr>
+ <td>offsets.retention.check.interval.ms</td>
+ <td>600000</td>
+ <td>The frequency at which the offset manager checks for stale
offsets.</td>
+ </tr>
+ <tr>
+ <td>offsets.topic.replication.factor</td>
+ <td>3</td>
+ <td>The replication factor for the offset commit topic. A higher setting
(e.g., three or four) is recommended in order to ensure higher availability. If
the offsets topic is created when fewer brokers than the replication factor
then the offsets topic will be created with fewer replicas.</td>
+ </tr>
+ <tr>
+ <td>offsets.topic.segment.bytes</td>
+ <td>104857600</td>
+ <td>Segment size for the offsets topic. Since it uses a compacted topic,
this should be kept relatively low in order to facilitate faster log compaction
and loads.</td>
+ </tr>
+ <tr>
+ <td>offsets.load.buffer.size</td>
+ <td>5242880</td>
+ <td>An offset load occurs when a broker becomes the offset manager for a
set of consumer groups (i.e., when it becomes a leader for an offsets topic
partition). This setting corresponds to the batch size (in bytes) to use when
reading from the offsets segments when loading offsets into the offset
manager's cache.</td>
+ </tr>
+<!--
+ <tr>
+ <td>offsets.topic.compression.codec</td>
+ <td>none</td>
+ <td>(Should not be used until KAFKA-1374 is implemented.) Compression
codec for the offsets topic. Compression should be enabled in order to achieve
"atomic" commits.</td>
+ </tr>
+-->
+ <tr>
+ <td>offsets.commit.required.acks</td>
+ <td>-1</td>
+ <td>The number of acknowledgements that are required before the offset
commit can be accepted. This is similar to the producer's acknowledgement
setting. In general, the default should not be overridden.</td>
+ </tr>
+ <tr>
+ <td>offsets.commit.timeout.ms</td>
+ <td>5000</td>
+ <td>The offset commit will be delayed until this timeout or the required
number of replicas have received the offset commit. This is similar to the
producer request timeout.</td>
+ </tr>
+ <tr>
+ <td>inter.broker.protocol.version</td>
+ <td>0.8.3</td>
+ <td>Version of the protocol brokers will use to communicate with each
other. This will default for the current version of the broker, but may need to
be set to older versions during a rolling upgrade process. In that scenario,
upgraded brokers will use the older version of the protocol and therefore will
be able to communicate with brokers that were not yet upgraded. See <a
href="#upgrade">upgrade section</a> for more details.</td>
+ </tr>
+</tbody></table>
+
+<p>More details about broker configuration can be found in the scala class
<code>kafka.server.KafkaConfig</code>.</p>
+
+<h4><a id="topic-config">Topic-level configuration</a></h3>
+
+Configurations pertinent to topics have both a global default as well an
optional per-topic override. If no per-topic configuration is given the global
default is used. The override can be set at topic creation time by giving one
or more <code>--config</code> options. This example creates a topic named
<i>my-topic</i> with a custom max message size and flush rate:
+<pre>
+<b> > bin/kafka-topics.sh --zookeeper localhost:2181 --create --topic
my-topic --partitions 1
+ --replication-factor 1 --config max.message.bytes=64000 --config
flush.messages=1</b>
+</pre>
+Overrides can also be changed or set later using the alter topic command. This
example updates the max message size for <i>my-topic</i>:
+<pre>
+<b> > bin/kafka-topics.sh --zookeeper localhost:2181 --alter --topic
my-topic
+ --config max.message.bytes=128000</b>
+</pre>
+
+To remove an override you can do
+<pre>
+<b> > bin/kafka-topics.sh --zookeeper localhost:2181 --alter --topic
my-topic
+ --deleteConfig max.message.bytes</b>
+</pre>
+
+The following are the topic-level configurations. The server's default
configuration for this property is given under the Server Default Property
heading, setting this default in the server config allows you to change the
default given to topics that have no override specified.
+<table class="data-table">
+<tbody>
+ <tr>
+ <th>Property</th>
+ <th>Default</th>
+ <th>Server Default Property</th>
+ <th>Description</th>
+ </tr>
+ <tr>
+ <td>cleanup.policy</td>
+ <td>delete</td>
+ <td>log.cleanup.policy</td>
+ <td>A string that is either "delete" or "compact". This string
designates the retention policy to use on old log segments. The default policy
("delete") will discard old segments when their retention time or size limit
has been reached. The "compact" setting will enable <a href="#compaction">log
compaction</a> on the topic.</td>
+ </tr>
+ <tr>
+ <td>delete.retention.ms</td>
+ <td>86400000 (24 hours)</td>
+ <td>log.cleaner.delete.retention.ms</td>
+ <td>The amount of time to retain delete tombstone markers for <a
href="#compaction">log compacted</a> topics. This setting also gives a bound on
the time in which a consumer must complete a read if they begin from offset 0
to ensure that they get a valid snapshot of the final stage (otherwise delete
tombstones may be collected before they complete their scan).</td>
+ </tr>
+ <tr>
+ <td>flush.messages</td>
+ <td>None</td>
+ <td>log.flush.interval.messages</td>
+ <td>This setting allows specifying an interval at which we will force an
fsync of data written to the log. For example if this was set to 1 we would
fsync after every message; if it were 5 we would fsync after every five
messages. In general we recommend you not set this and use replication for
durability and allow the operating system's background flush capabilities as it
is more efficient. This setting can be overridden on a per-topic basis (see <a
href="#topic-config">the per-topic configuration section</a>).</td>
+ </tr>
+ <tr>
+ <td>flush.ms</td>
+ <td>None</td>
+ <td>log.flush.interval.ms</td>
+ <td>This setting allows specifying a time interval at which we will
force an fsync of data written to the log. For example if this was set to 1000
we would fsync after 1000 ms had passed. In general we recommend you not set
this and use replication for durability and allow the operating system's
background flush capabilities as it is more efficient.</td>
+ </tr>
+ <tr>
+ <td>index.interval.bytes</td>
+ <td>4096</td>
+ <td>log.index.interval.bytes</td>
+ <td>This setting controls how frequently Kafka adds an index entry to
it's offset index. The default setting ensures that we index a message roughly
every 4096 bytes. More indexing allows reads to jump closer to the exact
position in the log but makes the index larger. You probably don't need to
change this.</td>
+ </tr>
+ <tr>
+ <td>max.message.bytes</td>
+ <td>1,000,000</td>
+ <td>message.max.bytes</td>
+ <td>This is largest message size Kafka will allow to be appended to this
topic. Note that if you increase this size you must also increase your
consumer's fetch size so they can fetch messages this large.</td>
+ </tr>
+ <tr>
+ <td>min.cleanable.dirty.ratio</td>
+ <td>0.5</td>
+ <td>log.cleaner.min.cleanable.ratio</td>
+ <td>This configuration controls how frequently the log compactor will
attempt to clean the log (assuming <a href="#compaction">log compaction</a> is
enabled). By default we will avoid cleaning a log where more than 50% of the
log has been compacted. This ratio bounds the maximum space wasted in the log
by duplicates (at 50% at most 50% of the log could be duplicates). A higher
ratio will mean fewer, more efficient cleanings but will mean more wasted space
in the log.</td>
+ </tr>
+ <tr>
+ <td>min.insync.replicas</td>
+ <td>1</td>
+ <td>min.insync.replicas</td>
+ <td>When a producer sets request.required.acks to -1,
min.insync.replicas specifies the minimum number of replicas that must
acknowledge a write for the write to be considered successful. If this minimum
cannot be met, then the producer will raise an exception (either
NotEnoughReplicas or NotEnoughReplicasAfterAppend). </br>
+ When used together, min.insync.replicas and request.required.acks allow
you to enforce greater durability guarantees. A typical scenario would be to
create a topic with a replication factor of 3, set min.insync.replicas to 2,
and produce with request.required.acks of -1. This will ensure that the
producer raises an exception if a majority of replicas do not receive a
write.</td>
+ </tr>
+ <tr>
+ <td>retention.bytes</td>
+ <td>None</td>
+ <td>log.retention.bytes</td>
+ <td>This configuration controls the maximum size a log can grow to
before we will discard old log segments to free up space if we are using the
"delete" retention policy. By default there is no size limit only a time
limit.</td>
+ </tr>
+ <tr>
+ <td>retention.ms</td>
+ <td>7 days</td>
+ <td>log.retention.minutes</td>
+ <td>This configuration controls the maximum time we will retain a log
before we will discard old log segments to free up space if we are using the
"delete" retention policy. This represents an SLA on how soon consumers must
read their data.</td>
+ </tr>
+ <tr>
+ <td>segment.bytes</td>
+ <td>1 GB</td>
+ <td>log.segment.bytes</td>
+ <td>This configuration controls the segment file size for the log.
Retention and cleaning is always done a file at a time so a larger segment size
means fewer files but less granular control over retention.</td>
+ </tr>
+ <tr>
+ <td>segment.index.bytes</td>
+ <td>10 MB</td>
+ <td>log.index.size.max.bytes</td>
+ <td>This configuration controls the size of the index that maps offsets
to file positions. We preallocate this index file and shrink it only after log
rolls. You generally should not need to change this setting.</td>
+ </tr>
+ <tr>
+ <td>segment.ms</td>
+ <td>7 days</td>
+ <td>log.roll.hours</td>
+ <td>This configuration controls the period of time after which Kafka
will force the log to roll even if the segment file isn't full to ensure that
retention can delete or compact old data.</td>
+ </tr>
+ <tr>
+ <td>segment.jitter.ms</td>
+ <td>0</td>
+ <td>log.roll.jitter.{ms,hours}</td>
+ <td>The maximum jitter to subtract from logRollTimeMillis.</td>
+ </tr>
+</table>
+
+<h3><a id="consumerconfigs">3.2 Consumer Configs</a></h3>
+The essential consumer configurations are the following:
+<ul>
+ <li><code>group.id</code>
+ <li><code>zookeeper.connect</code>
+</ul>
+
+<table class="data-table">
+<tbody><tr>
+ <th>Property</th>
+ <th>Default</th>
+ <th>Description</th>
+</tr>
+ <tr>
+ <td>group.id</td>
+ <td colspan="1"></td>
+ <td>A string that uniquely identifies the group of consumer processes to
which this consumer belongs. By setting the same group id multiple processes
indicate that they are all part of the same consumer group.</td>
+ </tr>
+ <tr>
+ <td>zookeeper.connect</td>
+ <td colspan="1"></td>
+ <td>Specifies the ZooKeeper connection string in the form
<code>hostname:port</code> where host and port are the host and port of a
ZooKeeper server. To allow connecting through other ZooKeeper nodes when that
ZooKeeper machine is down you can also specify multiple hosts in the form
<code>hostname1:port1,hostname2:port2,hostname3:port3</code>.
+ <p>
+ The server may also have a ZooKeeper chroot path as part of it's ZooKeeper
connection string which puts its data under some path in the global ZooKeeper
namespace. If so the consumer should use the same chroot path in its connection
string. For example to give a chroot path of <code>/chroot/path</code> you
would give the connection string as
<code>hostname1:port1,hostname2:port2,hostname3:port3/chroot/path</code>.</td>
+ </tr>
+ <tr>
+ <td>consumer.id</td>
+ <td colspan="1">null</td>
+ <td>
+ <p>Generated automatically if not set.</p>
+ </td>
+ </tr>
+ <tr>
+ <td>socket.timeout.ms</td>
+ <td colspan="1">30 * 1000</td>
+ <td>The socket timeout for network requests. The actual timeout set will
be max.fetch.wait + socket.timeout.ms.</td>
+ </tr>
+ <tr>
+ <td>socket.receive.buffer.bytes</td>
+ <td colspan="1">64 * 1024</td>
+ <td>The socket receive buffer for network requests</td>
+ </tr>
+ <tr>
+ <td>fetch.message.max.bytes</td>
+ <td nowrap>1024 * 1024</td>
+ <td>The number of byes of messages to attempt to fetch for each
topic-partition in each fetch request. These bytes will be read into memory for
each partition, so this helps control the memory used by the consumer. The
fetch request size must be at least as large as the maximum message size the
server allows or else it is possible for the producer to send messages larger
than the consumer can fetch.</td>
+ </tr>
+ <tr>
+ <td>num.consumer.fetchers</td>
+ <td colspan="1">1</td>
+ <td>The number fetcher threads used to fetch data.</td>
+ </tr>
+ <tr>
+ <td>auto.commit.enable</td>
+ <td colspan="1">true</td>
+ <td>If true, periodically commit to ZooKeeper the offset of messages
already fetched by the consumer. This committed offset will be used when the
process fails as the position from which the new consumer will begin.</td>
+ </tr>
+ <tr>
+ <td>auto.commit.interval.ms</td>
+ <td colspan="1">60 * 1000</td>
+ <td>The frequency in ms that the consumer offsets are committed to
zookeeper.</td>
+ </tr>
+ <tr>
+ <td>queued.max.message.chunks</td>
+ <td colspan="1">2</td>
+ <td>Max number of message chunks buffered for consumption. Each chunk
can be up to fetch.message.max.bytes.</td>
+ </tr>
+ <tr>
+ <td>rebalance.max.retries</td>
+ <td colspan="1">4</td>
+ <td>When a new consumer joins a consumer group the set of consumers
attempt to "rebalance" the load to assign partitions to each consumer. If the
set of consumers changes while this assignment is taking place the rebalance
will fail and retry. This setting controls the maximum number of attempts
before giving up.</td>
+ </tr>
+ <tr>
+ <td>fetch.min.bytes</td>
+ <td colspan="1">1</td>
+ <td>The minimum amount of data the server should return for a fetch
request. If insufficient data is available the request will wait for that much
data to accumulate before answering the request.</td>
+ </tr>
+ <tr>
+ <td>fetch.wait.max.ms</td>
+ <td colspan="1">100</td>
+ <td>The maximum amount of time the server will block before answering
the fetch request if there isn't sufficient data to immediately satisfy
fetch.min.bytes</td>
+ </tr>
+ <tr>
+ <td>rebalance.backoff.ms</td>
+ <td>2000</td>
+ <td>Backoff time between retries during rebalance.</td>
+ </tr>
+ <tr>
+ <td>refresh.leader.backoff.ms</td>
+ <td colspan="1">200</td>
+ <td>Backoff time to wait before trying to determine the leader of a
partition that has just lost its leader.</td>
+ </tr>
+ <tr>
+ <td>auto.offset.reset</td>
+ <td colspan="1">largest</td>
+ <td>
+ <p>What to do when there is no initial offset in ZooKeeper or if an
offset is out of range:<br/>* smallest : automatically reset the offset to the
smallest offset<br/>* largest : automatically reset the offset to the largest
offset<br/>* anything else: throw exception to the consumer</p>
+ </td>
+ </tr>
+ <tr>
+ <td>consumer.timeout.ms</td>
+ <td colspan="1">-1</td>
+ <td>Throw a timeout exception to the consumer if no message is available
for consumption after the specified interval</td>
+ </tr>
+ <tr>
+ <td>exclude.internal.topics</td>
+ <td colspan="1">true</td>
+ <td>Whether messages from internal topics (such as offsets) should be
exposed to the consumer.</td>
+ </tr>
+ <tr>
+ <td>partition.assignment.strategy</td>
+ <td colspan="1">range</td>
+ <td>Select a strategy for assigning partitions to consumer streams.
Possible values: range, roundrobin.</td>
+ </tr>
+ <tr>
+ <td>client.id</td>
+ <td colspan="1">group id value</td>
+ <td>The client id is a user-specified string sent in each request to
help trace calls. It should logically identify the application making the
request.</td>
+ </tr>
+ <tr>
+ <td>zookeeper.session.timeout.ms </td>
+ <td colspan="1">6000</td>
+ <td>ZooKeeper session timeout. If the consumer fails to heartbeat to
ZooKeeper for this period of time it is considered dead and a rebalance will
occur.</td>
+ </tr>
+ <tr>
+ <td>zookeeper.connection.timeout.ms</td>
+ <td colspan="1">6000</td>
+ <td>The max time that the client waits while establishing a connection
to zookeeper.</td>
+ </tr>
+ <tr>
+ <td>zookeeper.sync.time.ms </td>
+ <td colspan="1">2000</td>
+ <td>How far a ZK follower can be behind a ZK leader</td>
+ </tr>
+ <tr>
+ <td>offsets.storage</td>
+ <td colspan="1">zookeeper</td>
+ <td>Select where offsets should be stored (zookeeper or kafka).</td>
+ </tr>
+ <tr>
+ <td>offsets.channel.backoff.ms</td>
+ <td colspan="1">1000</td>
+ <td>The backoff period when reconnecting the offsets channel or retrying
failed offset fetch/commit requests.</td>
+ </tr>
+ <tr>
+ <td>offsets.channel.socket.timeout.ms</td>
+ <td colspan="1">10000</td>
+ <td>Socket timeout when reading responses for offset fetch/commit
requests. This timeout is also used for ConsumerMetadata requests that are used
to query for the offset manager.</td>
+ </tr>
+ <tr>
+ <td>offsets.commit.max.retries</td>
+ <td colspan="1">5</td>
+ <td>Retry the offset commit up to this many times on failure. This retry
count only applies to offset commits during shut-down. It does not apply to
commits originating from the auto-commit thread. It also does not apply to
attempts to query for the offset coordinator before committing offsets. i.e.,
if a consumer metadata request fails for any reason, it will be retried and
that retry does not count toward this limit.</td>
+ </tr>
+ <tr>
+ <td>dual.commit.enabled</td>
+ <td colspan="1">true</td>
+ <td>If you are using "kafka" as offsets.storage, you can dual commit
offsets to ZooKeeper (in addition to Kafka). This is required during migration
from zookeeper-based offset storage to kafka-based offset storage. With respect
to any given consumer group, it is safe to turn this off after all instances
within that group have been migrated to the new version that commits offsets to
the broker (instead of directly to ZooKeeper).</td>
+ </tr>
+ <tr>
+ <td>partition.assignment.strategy</td>
+ <td colspan="1">range</td>
+ <td><p>Select between the "range" or "roundrobin" strategy for assigning
partitions to consumer streams.<p>The round-robin partition assignor lays out
all the available partitions and all the available consumer threads. It then
proceeds to do a round-robin assignment from partition to consumer thread. If
the subscriptions of all consumer instances are identical, then the partitions
will be uniformly distributed. (i.e., the partition ownership counts will be
within a delta of exactly one across all consumer threads.) Round-robin
assignment is permitted only if: (a) Every topic has the same number of streams
within a consumer instance (b) The set of subscribed topics is identical for
every consumer instance within the group.<p> Range partitioning works on a
per-topic basis. For each topic, we lay out the available partitions in numeric
order and the consumer threads in lexicographic order. We then divide the
number of partitions by the total number of consumer streams (threads)
to determine the number of partitions to assign to each consumer. If it does
not evenly divide, then the first few consumers will have one extra
partition.</td>
+ </tr>
+</tbody>
+</table>
+
+
+<p>More details about consumer configuration can be found in the scala class
<code>kafka.consumer.ConsumerConfig</code>.</p>
+<h3><a id="producerconfigs">3.3 Producer Configs</a></h3>
+Essential configuration properties for the producer include:
+<ul>
+ <li><code>metadata.broker.list</code>
+ <li><code>request.required.acks</code>
+ <li><code>producer.type</code>
+ <li><code>serializer.class</code>
+</ul>
+
+<table class="data-table">
+<tbody><tr>
+ <th>Property</th>
+ <th>Default</th>
+ <th>Description</th>
+ </tr>
+ <tr>
+ <td>metadata.broker.list</td>
+ <td colspan="1"></td>
+ <td>
+ <p>This is for bootstrapping and the producer will only use it for
getting metadata (topics, partitions and replicas). The socket connections for
sending the actual data will be established based on the broker information
returned in the metadata. The format is host1:port1,host2:port2, and the list
can be a subset of brokers or a VIP pointing to a subset of brokers.</p>
+ </td>
+ </tr>
+ <tr>
+ <td>request.required.acks</td>
+ <td colspan="1">0</td>
+ <td>
+ <p>This value controls when a produce request is considered completed.
Specifically, how many other brokers must have committed the data to their log
and acknowledged this to the leader? Typical values are
+ <ul>
+ <li>0, which means that the producer never waits for an
acknowledgement from the broker (the same behavior as 0.7). This option
provides the lowest latency but the weakest durability guarantees (some data
will be lost when a server fails).
+ <li> 1, which means that the producer gets an acknowledgement
after the leader replica has received the data. This option provides better
durability as the client waits until the server acknowledges the request as
successful (only messages that were written to the now-dead leader but not yet
replicated will be lost).
+ <li> -1, The producer gets an acknowledgement after all in-sync
replicas have received the data. This option provides the greatest level of
durability. However, it does not completely eliminate the risk of message loss
because the number of in sync replicas may, in rare cases, shrink to 1. If you
want to ensure that some minimum number of replicas (typically a majority)
receive a write, then you must set the topic-level min.insync.replicas setting.
Please read the Replication section of the design documentation for a more
in-depth discussion.
+ </ul>
+ </p>
+ </td>
+ </tr>
+ <tr>
+ <td>request.timeout.ms</td>
+ <td colspan="1">10000</td>
+ <td>The amount of time the broker will wait trying to meet the
request.required.acks requirement before sending back an error to the
client.</td>
+ </tr>
+ <tr>
+ <td>producer.type</td>
+ <td colspan="1">sync</td>
+ <td>
+ <p>This parameter specifies whether the messages are sent
asynchronously in a background thread. Valid values are (1) async for
asynchronous send and (2) sync for synchronous send. By setting the producer to
async we allow batching together of requests (which is great for throughput)
but open the possibility of a failure of the client machine dropping unsent
data.</p>
+ </td>
+ <tr>
+ <td>serializer.class</td>
+ <td colspan="1">kafka.serializer.DefaultEncoder</td>
+ <td>The serializer class for messages. The default encoder takes a
byte[] and returns the same byte[].</td>
+ </tr>
+ <tr>
+ <td>key.serializer.class</td>
+ <td colspan="1"></td>
+ <td>The serializer class for keys (defaults to the same as for messages
if nothing is given).</td>
+ </tr>
+ <tr>
+ <td>partitioner.class</td>
+ <td colspan="1">kafka.producer.DefaultPartitioner</td>
+ <td>The partitioner class for partitioning messages amongst sub-topics.
The default partitioner is based on the hash of the key.</td>
+ </tr>
+ <tr>
+ <td>compression.codec</td>
+ <td colspan="1">none</td>
+ <td>
+ <p>This parameter allows you to specify the compression codec for all
data generated by this producer. Valid values are "none", "gzip" and
"snappy".</p>
+ </td>
+ </tr>
+ <tr>
+ <td>compressed.topics</td>
+ <td colspan="1">null</td>
+ <td>
+ <p>This parameter allows you to set whether compression should be
turned on for particular topics. If the compression codec is anything other
than NoCompressionCodec, enable compression only for specified topics if any.
If the list of compressed topics is empty, then enable the specified
compression codec for all topics. If the compression codec is
NoCompressionCodec, compression is disabled for all topics</p>
+ </td>
+ </tr>
+ <tr>
+ <td>message.send.max.retries</td>
+ <td colspan="1">3</td>
+ <td>
+ <p>This property will cause the producer to automatically retry a
failed send request. This property specifies the number of retries when such
failures occur. Note that setting a non-zero value here can lead to duplicates
in the case of network errors that cause a message to be sent but the
acknowledgement to be lost.</p>
+ </td>
+ </tr>
+ <tr>
+ <td>retry.backoff.ms</td>
+ <td colspan="1">100</td>
+ <td>
+ <p>Before each retry, the producer refreshes the metadata of relevant
topics to see if a new leader has been elected. Since leader election takes a
bit of time, this property specifies the amount of time that the producer waits
before refreshing the metadata.</p>
+ </td>
+ </tr>
+ <tr>
+ <td>topic.metadata.refresh.interval.ms</td>
+ <td colspan="1">600 * 1000</td>
+ <td>
+ <p>The producer generally refreshes the topic metadata from brokers
when there is a failure (partition missing, leader not available...). It will
also poll regularly (default: every 10min so 600000ms). If you set this to a
negative value, metadata will only get refreshed on failure. If you set this to
zero, the metadata will get refreshed after each message sent (not
recommended). Important note: the refresh happen only AFTER the message is
sent, so if the producer never sends a message the metadata is never
refreshed</p>
+ </td>
+ </tr>
+ <tr>
+ <td>queue.buffering.max.ms</td>
+ <td colspan="1">5000</td>
+ <td>Maximum time to buffer data when using async mode. For example a
setting of 100 will try to batch together 100ms of messages to send at once.
This will improve throughput but adds message delivery latency due to the
buffering.</td>
+ </tr>
+ <tr>
+ <td>queue.buffering.max.messages</td>
+ <td colspan="1">10000</td>
+ <td>The maximum number of unsent messages that can be queued up the
producer when using async mode before either the producer must be blocked or
data must be dropped.</td>
+ </tr>
+ <tr>
+ <td>queue.enqueue.timeout.ms</td>
+ <td colspan="1">-1</td>
+ <td>
+ <p>The amount of time to block before dropping messages when running
in async mode and the buffer has reached queue.buffering.max.messages. If set
to 0 events will be enqueued immediately or dropped if the queue is full (the
producer send call will never block). If set to -1 the producer will block
indefinitely and never willingly drop a send.</p>
+ </td>
+ </tr>
+ <tr>
+ <td>batch.num.messages</td>
+ <td colspan="1">200</td>
+ <td>The number of messages to send in one batch when using async mode.
The producer will wait until either this number of messages are ready to send
or queue.buffer.max.ms is reached.</td>
+ </tr>
+ <tr>
+ <td>send.buffer.bytes</td>
+ <td colspan="1">100 * 1024</td>
+ <td>Socket write buffer size</td>
+ </tr>
+ <tr>
+ <td>client.id</td>
+ <td colspan="1">""</td>
+ <td>The client id is a user-specified string sent in each request to
help trace calls. It should logically identify the application making the
request.</td>
+ </tr>
+</tbody></table>
+<p>More details about producer configuration can be found in the scala class
<code>kafka.producer.ProducerConfig</code>.</p>
+
+<h3><a id="newproducerconfigs">3.4 New Producer Configs</a></h3>
+
+We are working on a replacement for our existing producer. The code is
available in trunk now and can be considered beta quality. Below is the
configuration for the new producer.
+
+<table class="data-table">
+ <tr>
+ <th>Name</th>
+ <th>Type</th>
+ <th>Default</th>
+ <th>Importance</th>
+ <th>Description</th>
+ </tr>
+ <tr>
+ <td>bootstrap.servers</td><td>list</td><td></td><td>high</td><td>A list
of host/port pairs to use for establishing the initial connection to the Kafka
cluster. Data will be load balanced over all servers irrespective of which
servers are specified here for bootstrapping—this list only impacts the
initial hosts used to discover the full set of servers. This list should be in
the form <code>host1:port1,host2:port2,...</code>. Since these servers are just
used for the initial connection to discover the full cluster membership (which
may change dynamically), this list need not contain the full set of servers
(you may want more than one, though, in case a server is down). If no server in
this list is available sending data will fail until on becomes
available.</td></tr>
+ <tr>
+ <td>acks</td><td>string</td><td>1</td><td>high</td><td>The number of
acknowledgments the producer requires the leader to have received before
considering a request complete. This controls the durability of records that
are sent. The following settings are common: <ul> <li><code>acks=0</code> If
set to zero then the producer will not wait for any acknowledgment from the
server at all. The record will be immediately added to the socket buffer and
considered sent. No guarantee can be made that the server has received the
record in this case, and the <code>retries</code> configuration will not take
effect (as the client won't generally know of any failures). The offset given
back for each record will always be set to -1. <li><code>acks=1</code> This
will mean the leader will write the record to its local log but will respond
without awaiting full acknowledgement from all followers. In this case should
the leader fail immediately after acknowledging the record but before the
followers
have replicated it then the record will be lost. <li><code>acks=all</code>
This means the leader will wait for the full set of in-sync replicas to
acknowledge the record. This guarantees that the record will not be lost as
long as at least one in-sync replica remains alive. This is the strongest
available guarantee. <li>Other settings such as <code>acks=2</code> are also
possible, and will require the given number of acknowledgements but this is
generally less useful.</td></tr>
+ <tr>
+
<td>buffer.memory</td><td>long</td><td>33554432</td><td>high</td><td>The total
bytes of memory the producer can use to buffer records waiting to be sent to
the server. If records are sent faster than they can be delivered to the server
the producer will either block or throw an exception based on the preference
specified by <code>block.on.buffer.full</code>. <p>This setting should
correspond roughly to the total memory the producer will use, but is not a hard
bound since not all memory the producer uses is used for buffering. Some
additional memory will be used for compression (if compression is enabled) as
well as for maintaining in-flight requests.</td></tr>
+ <tr>
+
<td>compression.type</td><td>string</td><td>none</td><td>high</td><td>The
compression type for all data generated by the producer. The default is none
(i.e. no compression). Valid values are <code>none</code>, <code>gzip</code>,
or <code>snappy</code>. Compression is of full batches of data, so the
efficacy of batching will also impact the compression ratio (more batching
means better compression).</td></tr>
+ <tr>
+ <td>retries</td><td>int</td><td>0</td><td>high</td><td>Setting a value
greater than zero will cause the client to resend any record whose send fails
with a potentially transient error. Note that this retry is no different than
if the client resent the record upon receiving the error. Allowing retries will
potentially change the ordering of records because if two records are sent to a
single partition, and the first fails and is retried but the second succeeds,
then the second record may appear first.</td></tr>
+ <tr>
+ <td>batch.size</td><td>int</td><td>16384</td><td>medium</td><td>The
producer will attempt to batch records together into fewer requests whenever
multiple records are being sent to the same partition. This helps performance
on both the client and the server. This configuration controls the default
batch size in bytes. <p>No attempt will be made to batch records larger than
this size. <p>Requests sent to brokers will contain multiple batches, one for
each partition with data available to be sent. <p>A small batch size will make
batching less common and may reduce throughput (a batch size of zero will
disable batching entirely). A very large batch size may use memory a bit more
wastefully as we will always allocate a buffer of the specified batch size in
anticipation of additional records.</td></tr>
+ <tr>
+ <td>client.id</td><td>string</td><td></td><td>medium</td><td>The id
string to pass to the server when making requests. The purpose of this is to be
able to track the source of requests beyond just ip/port by allowing a logical
application name to be included with the request. The application can set any
string it wants as this has no functional purpose other than in logging and
metrics.</td></tr>
+ <tr>
+ <td>linger.ms</td><td>long</td><td>0</td><td>medium</td><td>The
producer groups together any records that arrive in between request
transmissions into a single batched request. Normally this occurs only under
load when records arrive faster than they can be sent out. However in some
circumstances the client may want to reduce the number of requests even under
moderate load. This setting accomplishes this by adding a small amount of
artificial delay—that is, rather than immediately sending out a record
the producer will wait for up to the given delay to allow other records to be
sent so that the sends can be batched together. This can be thought of as
analogous to Nagle's algorithm in TCP. This setting gives the upper bound on
the delay for batching: once we get <code>batch.size</code> worth of records
for a partition it will be sent immediately regardless of this setting, however
if we have fewer than this many bytes accumulated for this partition we will
'linger' for the spe
cified time waiting for more records to show up. This setting defaults to 0
(i.e. no delay). Setting <code>linger.ms=5</code>, for example, would have the
effect of reducing the number of requests sent but would add up to 5ms of
latency to records sent in the absense of load.</td></tr>
+ <tr>
+
<td>max.request.size</td><td>int</td><td>1048576</td><td>medium</td><td>The
maximum size of a request. This is also effectively a cap on the maximum record
size. Note that the server has its own cap on record size which may be
different from this. This setting will limit the number of record batches the
producer will send in a single request to avoid sending huge requests.</td></tr>
+ <tr>
+
<td>receive.buffer.bytes</td><td>int</td><td>32768</td><td>medium</td><td>The
size of the TCP receive buffer to use when reading data</td></tr>
+ <tr>
+
<td>send.buffer.bytes</td><td>int</td><td>131072</td><td>medium</td><td>The
size of the TCP send buffer to use when sending data</td></tr>
+ <tr>
+ <td>timeout.ms</td><td>int</td><td>30000</td><td>medium</td><td>The
configuration controls the maximum amount of time the server will wait for
acknowledgments from followers to meet the acknowledgment requirements the
producer has specified with the <code>acks</code> configuration. If the
requested number of acknowledgments are not met when the timeout elapses an
error will be returned. This timeout is measured on the server side and does
not include the network latency of the request.</td></tr>
+ <tr>
+
<td>block.on.buffer.full</td><td>boolean</td><td>true</td><td>low</td><td>When
our memory buffer is exhausted we must either stop accepting new records
(block) or throw errors. By default this setting is true and we block, however
in some scenarios blocking is not desirable and it is better to immediately
give an error. Setting this to <code>false</code> will accomplish that: the
producer will throw a BufferExhaustedException if a recrord is sent and the
buffer space is full.</td></tr>
+ <tr>
+
<td>metadata.fetch.timeout.ms</td><td>long</td><td>60000</td><td>low</td><td>The
first time data is sent to a topic we must fetch metadata about that topic to
know which servers host the topic's partitions. This configuration controls the
maximum amount of time we will block waiting for the metadata fetch to succeed
before throwing an exception back to the client.</td></tr>
+ <tr>
+
<td>metadata.max.age.ms</td><td>long</td><td>300000</td><td>low</td><td>The
period of time in milliseconds after which we force a refresh of metadata even
if we haven't seen any partition leadership changes to proactively discover
any new brokers or partitions.</td></tr>
+ <tr>
+ <td>metric.reporters</td><td>list</td><td>[]</td><td>low</td><td>A list
of classes to use as metrics reporters. Implementing the
<code>MetricReporter</code> interface allows plugging in classes that will be
notified of new metric creation. The JmxReporter is always included to register
JMX statistics.</td></tr>
+ <tr>
+ <td>metrics.num.samples</td><td>int</td><td>2</td><td>low</td><td>The
number of samples maintained to compute metrics.</td></tr>
+ <tr>
+
<td>metrics.sample.window.ms</td><td>long</td><td>30000</td><td>low</td><td>The
metrics system maintains a configurable number of samples over a fixed window
size. This configuration controls the size of the window. For example we might
maintain two samples each measured over a 30 second period. When a window
expires we erase and overwrite the oldest window.</td></tr>
+ <tr>
+
<td>reconnect.backoff.ms</td><td>long</td><td>10</td><td>low</td><td>The amount
of time to wait before attempting to reconnect to a given host when a
connection fails. This avoids a scenario where the client repeatedly attempts
to connect to a host in a tight loop.</td></tr>
+ <tr>
+ <td>retry.backoff.ms</td><td>long</td><td>100</td><td>low</td><td>The
amount of time to wait before attempting to retry a failed produce request to a
given topic partition. This avoids repeated sending-and-failing in a tight
loop.</td></tr>
+ </table>
