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From gwens...@apache.org
Subject [1/3] kafka-site git commit: Add protocol guide
Date Thu, 10 Mar 2016 19:11:44 GMT
Repository: kafka-site
Updated Branches:
  refs/heads/asf-site 1bc5cd91c -> 14ffd37c0


http://git-wip-us.apache.org/repos/asf/kafka-site/blob/14ffd37c/090/producer_config.html
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-<table class="data-table"><tbody>
-<tr>
-<th>Name</th>
-<th>Description</th>
-<th>Type</th>
-<th>Default</th>
-<th>Valid Values</th>
-<th>Importance</th>
-</tr>
-<tr>
-<td>bootstrap.servers</td><td>A list of host/port pairs to use for establishing
the initial connection to the Kafka cluster. The client will make use of all servers irrespective
of which servers are specified here for bootstrapping&mdash;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).</td><td>list</td><td></td><td></td><td>high</td></tr>
-<tr>
-<td>key.serializer</td><td>Serializer class for key that implements the
<code>Serializer</code> interface.</td><td>class</td><td></td><td></td><td>high</td></tr>
-<tr>
-<td>value.serializer</td><td>Serializer class for value that implements
the <code>Serializer</code> interface.</td><td>class</td><td></td><td></td><td>high</td></tr>
-<tr>
-<td>acks</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
wil
 l 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.</td><td>string</td><td>1</td><td>[all,
-1, 0, 1]</td><td>high</td></tr>
-<tr>
-<td>buffer.memory</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><td>long</td><td>33554432</td><td>[0,...]</td><td>high</td></tr>
-<tr>
-<td>compression.type</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>, <code>snappy</code>, or <code>lz4</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><td>string</td><td>none</td><td></td><td>high</td></tr>
-<tr>
-<td>retries</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><td>int</td><td>0</td><td>[0,...,2147483647]</td><td>high</td></tr>
-<tr>
-<td>ssl.key.password</td><td>The password of the private key in the key
store file. This is optional for client.</td><td>password</td><td>null</td><td></td><td>high</td></tr>
-<tr>
-<td>ssl.keystore.location</td><td>The location of the key store file. This
is optional for client and can be used for two-way authentication for client.</td><td>string</td><td>null</td><td></td><td>high</td></tr>
-<tr>
-<td>ssl.keystore.password</td><td>The store password for the key store
file.This is optional for client and only needed if ssl.keystore.location is configured. </td><td>password</td><td>null</td><td></td><td>high</td></tr>
-<tr>
-<td>ssl.truststore.location</td><td>The location of the trust store file.
</td><td>string</td><td>null</td><td></td><td>high</td></tr>
-<tr>
-<td>ssl.truststore.password</td><td>The password for the trust store file.
</td><td>password</td><td>null</td><td></td><td>high</td></tr>
-<tr>
-<td>batch.size</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><td>int</td><td>16384</td><td>[0,...]</td><td>medium</td></tr>
-<tr>
-<td>client.id</td><td>An 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 in server-side request logging.</td><td>string</td><td>""</td><td></td><td>medium</td></tr>
-<tr>
-<td>connections.max.idle.ms</td><td>Close idle connections after the number
of milliseconds specified by this config.</td><td>long</td><td>540000</td><td></td><td>medium</td></tr>
-<tr>
-<td>linger.ms</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&mdash;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 specified 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><td>long</td><td>0</td><td>[0,...]</td><td>medium</td></tr>
-<tr>
-<td>max.block.ms</td><td>The configuration controls how long {@link KafkaProducer#send()}
and {@link KafkaProducer#partitionsFor} will block.These methods can be blocked either because
the buffer is full or metadata unavailable.Blocking in the user-supplied serializers or partitioner
will not be counted against this timeout.</td><td>long</td><td>60000</td><td>[0,...]</td><td>medium</td></tr>
-<tr>
-<td>max.request.size</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><td>int</td><td>1048576</td><td>[0,...]</td><td>medium</td></tr>
-<tr>
-<td>partitioner.class</td><td>Partitioner class that implements the <code>Partitioner</code>
interface.</td><td>class</td><td>class org.apache.kafka.clients.producer.internals.DefaultPartitioner</td><td></td><td>medium</td></tr>
-<tr>
-<td>receive.buffer.bytes</td><td>The size of the TCP receive buffer (SO_RCVBUF)
to use when reading data.</td><td>int</td><td>32768</td><td>[0,...]</td><td>medium</td></tr>
-<tr>
-<td>request.timeout.ms</td><td>The configuration controls the maximum amount
of time the client will wait for the response of a request. If the response is not received
before the timeout elapses the client will resend the request if necessary or fail the request
if retries are exhausted.</td><td>int</td><td>30000</td><td>[0,...]</td><td>medium</td></tr>
-<tr>
-<td>sasl.kerberos.service.name</td><td>The Kerberos principal name that
Kafka runs as. This can be defined either in Kafka's JAAS config or in Kafka's config.</td><td>string</td><td>null</td><td></td><td>medium</td></tr>
-<tr>
-<td>security.protocol</td><td>Protocol used to communicate with brokers.
Valid values are: PLAINTEXT, SSL, SASL_PLAINTEXT, SASL_SSL.</td><td>string</td><td>PLAINTEXT</td><td></td><td>medium</td></tr>
-<tr>
-<td>send.buffer.bytes</td><td>The size of the TCP send buffer (SO_SNDBUF)
to use when sending data.</td><td>int</td><td>131072</td><td>[0,...]</td><td>medium</td></tr>
-<tr>
-<td>ssl.enabled.protocols</td><td>The list of protocols enabled for SSL
connections.</td><td>list</td><td>[TLSv1.2, TLSv1.1, TLSv1]</td><td></td><td>medium</td></tr>
-<tr>
-<td>ssl.keystore.type</td><td>The file format of the key store file. This
is optional for client.</td><td>string</td><td>JKS</td><td></td><td>medium</td></tr>
-<tr>
-<td>ssl.protocol</td><td>The SSL protocol used to generate the SSLContext.
Default setting is TLS, which is fine for most cases. Allowed values in recent JVMs are TLS,
TLSv1.1 and TLSv1.2. SSL, SSLv2 and SSLv3 may be supported in older JVMs, but their usage
is discouraged due to known security vulnerabilities.</td><td>string</td><td>TLS</td><td></td><td>medium</td></tr>
-<tr>
-<td>ssl.provider</td><td>The name of the security provider used for SSL
connections. Default value is the default security provider of the JVM.</td><td>string</td><td>null</td><td></td><td>medium</td></tr>
-<tr>
-<td>ssl.truststore.type</td><td>The file format of the trust store file.</td><td>string</td><td>JKS</td><td></td><td>medium</td></tr>
-<tr>
-<td>timeout.ms</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><td>int</td><td>30000</td><td>[0,...]</td><td>medium</td></tr>
-<tr>
-<td>block.on.buffer.full</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><td>boolean</td><td>false</td><td></td><td>low</td></tr>
-<tr>
-<td>max.in.flight.requests.per.connection</td><td>The maximum number of
unacknowledged requests the client will send on a single connection before blocking. Note
that if this setting is set to be greater than 1 and there are failed sends, there is a risk
of message re-ordering due to retries (i.e., if retries are enabled).</td><td>int</td><td>5</td><td>[1,...]</td><td>low</td></tr>
-<tr>
-<td>metadata.fetch.timeout.ms</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 fetch to succeed before throwing an exception back to the client.</td><td>long</td><td>60000</td><td>[0,...]</td><td>low</td></tr>
-<tr>
-<td>metadata.max.age.ms</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><td>long</td><td>300000</td><td>[0,...]</td><td>low</td></tr>
-<tr>
-<td>metric.reporters</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><td>list</td><td>[]</td><td></td><td>low</td></tr>
-<tr>
-<td>metrics.num.samples</td><td>The number of samples maintained to compute
metrics.</td><td>int</td><td>2</td><td>[1,...]</td><td>low</td></tr>
-<tr>
-<td>metrics.sample.window.ms</td><td>The number of samples maintained to
compute metrics.</td><td>long</td><td>30000</td><td>[0,...]</td><td>low</td></tr>
-<tr>
-<td>reconnect.backoff.ms</td><td>The amount of time to wait before attempting
to reconnect to a given host. This avoids repeatedly connecting to a host in a tight loop.
This backoff applies to all requests sent by the consumer to the broker.</td><td>long</td><td>50</td><td>[0,...]</td><td>low</td></tr>
-<tr>
-<td>retry.backoff.ms</td><td>The amount of time to wait before attempting
to retry a failed fetch request to a given topic partition. This avoids repeated fetching-and-failing
in a tight loop.</td><td>long</td><td>100</td><td>[0,...]</td><td>low</td></tr>
-<tr>
-<td>sasl.kerberos.kinit.cmd</td><td>Kerberos kinit command path.</td><td>string</td><td>/usr/bin/kinit</td><td></td><td>low</td></tr>
-<tr>
-<td>sasl.kerberos.min.time.before.relogin</td><td>Login thread sleep time
between refresh attempts.</td><td>long</td><td>60000</td><td></td><td>low</td></tr>
-<tr>
-<td>sasl.kerberos.ticket.renew.jitter</td><td>Percentage of random jitter
added to the renewal time.</td><td>double</td><td>0.05</td><td></td><td>low</td></tr>
-<tr>
-<td>sasl.kerberos.ticket.renew.window.factor</td><td>Login thread will
sleep until the specified window factor of time from last refresh to ticket's expiry has been
reached, at which time it will try to renew the ticket.</td><td>double</td><td>0.8</td><td></td><td>low</td></tr>
-<tr>
-<td>ssl.cipher.suites</td><td>A list of cipher suites. This is a named
combination of authentication, encryption, MAC and key exchange algorithm used to negotiate
the security settings for a network connection using TLS or SSL network protocol.By default
all the available cipher suites are supported.</td><td>list</td><td>null</td><td></td><td>low</td></tr>
-<tr>
-<td>ssl.endpoint.identification.algorithm</td><td>The endpoint identification
algorithm to validate server hostname using server certificate. </td><td>string</td><td>null</td><td></td><td>low</td></tr>
-<tr>
-<td>ssl.keymanager.algorithm</td><td>The algorithm used by key manager
factory for SSL connections. Default value is the key manager factory algorithm configured
for the Java Virtual Machine.</td><td>string</td><td>SunX509</td><td></td><td>low</td></tr>
-<tr>
-<td>ssl.trustmanager.algorithm</td><td>The algorithm used by trust manager
factory for SSL connections. Default value is the trust manager factory algorithm configured
for the Java Virtual Machine.</td><td>string</td><td>PKIX</td><td></td><td>low</td></tr>
-</tbody></table>

http://git-wip-us.apache.org/repos/asf/kafka-site/blob/14ffd37c/090/protocol.html
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+<!--
+ 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.
+-->
+
+<!--#include virtual="../includes/header.html" -->
+
+<h3><a id="protocol" href="#protocol">Kafka Wire Protocol</a></h3>
+
+<p>This document covers the wire protocol implemented in Kafka. It is meant to give
a readable guide to the protocol that covers the available requests, their binary format,
and the proper way to make use of them to implement a client. This document assumes you understand
the basic design and terminology described <a href="https://kafka.apache.org/documentation.html#design">here</a></p>
+
+<ul class="toc">
+    <li><a href="#protocol_preliminaries">Preliminaries</a>
+        <ul>
+            <li><a href="#protocol_network">Network</a>
+            <li><a href="#protocol_partitioning">Partitioning and bootstrapping</a>
+            <li><a href="#protocol_partitioning_strategies">Partitioning Strategies</a>
+            <li><a href="#protocol_batching">Batching</a>
+            <li><a href="#protocol_compatibility">Versioning and Compatibility</a>
+        </ul>
+    </li>
+    <li><a href="#protocol_details">The Protocol</a>
+        <ul>
+            <li><a href="#protocol_types">Protocol Primitive Types</a>
+            <li><a href="#protocol_grammar">Notes on reading the request format
grammars</a>
+            <li><a href="#protocol_common">Common Request and Response Structure</a>
+            <li><a href="#protocol_message_sets">Message Sets</a>
+        </ul>
+    </li>
+    <li><a href="#protocol_constants">Constants</a>
+        <ul>
+            <li><a href="#protocol_error_codes">Error Codes</a>
+            <li><a href="#protocol_api_keys">Api Keys</a>
+        </ul>
+    </li>
+    <li><a href="#protocol_messages">The Messages</a></li>
+    <li><a href="#protocol_philosophy">Some Common Philosophical Questions</a></li>
+</ul>
+
+<h4><a id="protocol_preliminaries" href="#protocol_preliminaries">Preliminaries</a></h4>
+
+<h5><a id="protocol_network" href="#protocol_network">Network</a></h5>
+
+<p>Kafka uses a binary protocol over TCP. The protocol defines all apis as request
response message pairs. All messages are size delimited and are made up of the following primitive
types.</p>
+
+<p>The client initiates a socket connection and then writes a sequence of request messages
and reads back the corresponding response message. No handshake is required on connection
or disconnection. TCP is happier if you maintain persistent connections used for many requests
to amortize the cost of the TCP handshake, but beyond this penalty connecting is pretty cheap.</p>
+
+<p>The client will likely need to maintain a connection to multiple brokers, as data
is partitioned and the clients will need to talk to the server that has their data. However
it should not generally be necessary to maintain multiple connections to a single broker from
a single client instance (i.e. connection pooling).</p>
+
+<p>The server guarantees that on a single TCP connection, requests will be processed
in the order they are sent and responses will return in that order as well. The broker's request
processing allows only a single in-flight request per connection in order to guarantee this
ordering. Note that clients can (and ideally should) use non-blocking IO to implement request
pipelining and achieve higher throughput. i.e., clients can send requests even while awaiting
responses for preceding requests since the outstanding requests will be buffered in the underlying
OS socket buffer. All requests are initiated by the client, and result in a corresponding
response message from the server except where noted.</p>
+
+<p>The server has a configurable maximum limit on request size and any request that
exceeds this limit will result in the socket being disconnected.</p>
+
+<h5><a id="protocol_partitioning" href="#protocol_partitioning">Partitioning
and bootstrapping</a></h5>
+
+<p>Kafka is a partitioned system so not all servers have the complete data set. Instead
recall that topics are split into a pre-defined number of partitions, P, and each partition
is replicated with some replication factor, N. Topic partitions themselves are just ordered
"commit logs" numbered 0, 1, ..., P.</p>
+
+<p>All systems of this nature have the question of how a particular piece of data is
assigned to a particular partition. Kafka clients directly control this assignment, the brokers
themselves enforce no particular semantics of which messages should be published to a particular
partition. Rather, to publish messages the client directly addresses messages to a particular
partition, and when fetching messages, fetches from a particular partition. If two clients
want to use the same partitioning scheme they must use the same method to compute the mapping
of key to partition.</p>
+
+<p>These requests to publish or fetch data must be sent to the broker that is currently
acting as the leader for a given partition. This condition is enforced by the broker, so a
request for a particular partition to the wrong broker will result in an the NotLeaderForPartition
error code (described below).</p>
+
+<p>How can the client find out which topics exist, what partitions they have, and which
brokers currently host those partitions so that it can direct its requests to the right hosts?
This information is dynamic, so you can't just configure each client with some static mapping
file. Instead all Kafka brokers can answer a metadata request that describes the current state
of the cluster: what topics there are, which partitions those topics have, which broker is
the leader for those partitions, and the host and port information for these brokers.</p>
+
+<p>In other words, the client needs to somehow find one broker and that broker will
tell the client about all the other brokers that exist and what partitions they host. This
first broker may itself go down so the best practice for a client implementation is to take
a list of two or three urls to bootstrap from. The user can then choose to use a load balancer
or just statically configure two or three of their kafka hosts in the clients.</p>
+
+<p>The client does not need to keep polling to see if the cluster has changed; it can
fetch metadata once when it is instantiated cache that metadata until it receives an error
indicating that the metadata is out of date. This error can come in two forms: (1) a socket
error indicating the client cannot communicate with a particular broker, (2) an error code
in the response to a request indicating that this broker no longer hosts the partition for
which data was requested.</p>
+<ol>
+    <li>Cycle through a list of "bootstrap" kafka urls until we find one we can connect
to. Fetch cluster metadata.</li>
+    <li>Process fetch or produce requests, directing them to the appropriate broker
based on the topic/partitions they send to or fetch from.</li>
+    <li>If we get an appropriate error, refresh the metadata and try again.</li>
+</ol>
+
+<h5><a id="protocol_partitioning_strategies" href="#protocol_partitioning_strategies">Partitioning
Strategies</a></h5>
+
+<p>As mentioned above the assignment of messages to partitions is something the producing
client controls. That said, how should this functionality be exposed to the end-user?</p>
+
+<p>Partitioning really serves two purposes in Kafka:</p>
+<ol>
+    <li>It balances data and request load over brokers</li>
+    <li>It serves as a way to divvy up processing among consumer processes while allowing
local state and preserving order within the partition. We call this semantic partitioning.</li>
+</ol>
+
+<p>For a given use case you may care about only one of these or both.</p>
+
+<p>To accomplish simple load balancing a simple approach would be for the client to
just round robin requests over all brokers. Another alternative, in an environment where there
are many more producers than brokers, would be to have each client chose a single partition
at random and publish to that. This later strategy will result in far fewer TCP connections.</p>
+
+<p>Semantic partitioning means using some key in the message to assign messages to
partitions. For example if you were processing a click message stream you might want to partition
the stream by the user id so that all data for a particular user would go to a single consumer.
To accomplish this the client can take a key associated with the message and use some hash
of this key to choose the partition to which to deliver the message.</p>
+
+<h5><a id="protocol_batching" href="#protocol_batching">Batching</a></h5>
+
+<p>Our apis encourage batching small things together for efficiency. We have found
this is a very significant performance win. Both our API to send messages and our API to fetch
messages always work with a sequence of messages not a single message to encourage this. A
clever client can make use of this and support an "asynchronous" mode in which it batches
together messages sent individually and sends them in larger clumps. We go even further with
this and allow the batching across multiple topics and partitions, so a produce request may
contain data to append to many partitions and a fetch request may pull data from many partitions
all at once.</p>
+
+<p>The client implementer can choose to ignore this and send everything one at a time
if they like.</p>
+
+<h5><a id="protocol_compatibility" href="#protocol_compatibility">Versioning
and Compatibility</a></h5>
+
+<p>The protocol is designed to enable incremental evolution in a backward compatible
fashion. Our versioning is on a per-api basis, each version consisting of a request and response
pair. Each request contains an API key that identifies the API being invoked and a version
number that indicates the format of the request and the expected format of the response.</p>
+
+<p>The intention is that clients would implement a particular version of the protocol,
and indicate this version in their requests. Our goal is primarily to allow API evolution
in an environment where downtime is not allowed and clients and servers cannot all be changed
at once.</p>
+
+<p>The server will reject requests with a version it does not support, and will always
respond to the client with exactly the protocol format it expects based on the version it
included in its request. The intended upgrade path is that new features would first be rolled
out on the server (with the older clients not making use of them) and then as newer clients
are deployed these new features would gradually be taken advantage of.</p>
+
+<p>Currently all versions are baselined at 0, as we evolve these APIs we will indicate
the format for each version individually.</p>
+
+<h4><a id="protocol_details" href="#protocol_details">The Protocol</a></h4>
+
+<h5><a id="protocol_types" href="#protocol_types">Protocol Primitive Types</a></h5>
+
+<p>The protocol is built out of the following primitive types.</p>
+
+<p><b>Fixed Width Primitives</b><p>
+
+<p>int8, int16, int32, int64 - Signed integers with the given precision (in bits) stored
in big endian order.</p>
+
+<p><b>Variable Length Primitives</b><p>
+
+<p>bytes, string - These types consist of a signed integer giving a length N followed
by N bytes of content. A length of -1 indicates null. string uses an int16 for its size, and
bytes uses an int32.</p>
+
+<p><b>Arrays</b><p>
+
+<p>This is a notation for handling repeated structures. These will always be encoded
as an int32 size containing the length N followed by N repetitions of the structure which
can itself be made up of other primitive types. In the BNF grammars below we will show an
array of a structure foo as [foo].</p>
+
+<h5><a id="protocol_grammar" href="#protocol_grammar">Notes on reading the request
format grammars</a></h5>
+
+<p>The <a href="https://en.wikipedia.org/wiki/Backus%E2%80%93Naur_Form">BNF</a>s
below give an exact context free grammar for the request and response binary format. The BNF
is intentionally not compact in order to give human-readable name. As always in a BNF a sequence
of productions indicates concatenation. When there are multiple possible productions these
are separated with '|' and may be enclosed in parenthesis for grouping. The top-level definition
is always given first and subsequent sub-parts are indented.</p>
+
+<h5><a id="protocol_common" href="#protocol_common">Common Request and Response
Structure</a></h5>
+
+<p>All requests and responses originate from the following grammar which will be incrementally
describe through the rest of this document:</p>
+
+<pre>
+RequestOrResponse => Size (RequestMessage | ResponseMessage)
+Size => int32
+</pre>
+
+<table class="data-table"><tbody>
+<tr><th>Field</th><th>Description</th></tr>
+<tr><td>message_size</td><td>The message_size field gives the size
of the subsequent request or response message in bytes. The client can read requests by first
reading this 4 byte size as an integer N, and then reading and parsing the subsequent N bytes
of the request.</td></tr>
+</table>
+
+<h5><a id="protocol_message_sets" href="#protocol_message_sets">Message Sets</a></h5>
+
+<p>A description of the message set format can be found <a href="https://cwiki.apache.org/confluence/display/KAFKA/A+Guide+To+The+Kafka+Protocol#AGuideToTheKafkaProtocol-Messagesets">here</a>.
(KAFKA-3368)</p>
+
+<h4><a id="protocol_constants" href="#protocol_constants">Constants</a></h4>
+
+<h5><a id="protocol_error_codes" href="#protocol_error_codes">Error Codes</a></h5>
+<p>We use numeric codes to indicate what problem occurred on the server. These can
be translated by the client into exceptions or whatever the appropriate error handling mechanism
in the client language. Here is a table of the error codes currently in use:</p>
+<!--#include virtual="generated/protocol_errors.html" -->
+
+<h5><a id="protocol_api_keys" href="#protocol_api_keys">Api Keys</a></h5>
+<p>The following are the numeric codes that the ApiKey in the request can take for
each of the below request types.</p>
+<!--#include virtual="generated/protocol_api_keys.html" -->
+
+<h4><a id="protocol_messages" href="#protocol_messages">The Messages</a></h4>
+
+<p>This section gives details on each of the individual API Messages, their usage,
their binary format, and the meaning of their fields.</p>
+<!--#include virtual="generated/protocol_messages.html" -->
+
+<h4><a id="protocol_philosophy" href="#protocol_philosophy">Some Common Philosophical
Questions</a></h4>
+
+<p>Some people have asked why we don't use HTTP. There are a number of reasons, the
best is that client implementors can make use of some of the more advanced TCP features--the
ability to multiplex requests, the ability to simultaneously poll many connections, etc. We
have also found HTTP libraries in many languages to be surprisingly shabby.</p>
+
+<p>Others have asked if maybe we shouldn't support many different protocols. Prior
experience with this was that it makes it very hard to add and test new features if they have
to be ported across many protocol implementations. Our feeling is that most users don't really
see multiple protocols as a feature, they just want a good reliable client in the language
of their choice.</p>
+
+<p>Another question is why we don't adopt XMPP, STOMP, AMQP or an existing protocol.
The answer to this varies by protocol, but in general the problem is that the protocol does
determine large parts of the implementation and we couldn't do what we are doing if we didn't
have control over the protocol. Our belief is that it is possible to do better than existing
messaging systems have in providing a truly distributed messaging system, and to do this we
need to build something that works differently.</p>
+
+<p>A final question is why we don't use a system like Protocol Buffers or Thrift to
define our request messages. These packages excel at helping you to managing lots and lots
of serialized messages. However we have only a few messages. Support across languages is somewhat
spotty (depending on the package). Finally the mapping between binary log format and wire
protocol is something we manage somewhat carefully and this would not be possible with these
systems. Finally we prefer the style of versioning APIs explicitly and checking this to inferring
new values as nulls as it allows more nuanced control of compatibility.</p>
+
+<!--#include virtual="../includes/footer.html" -->

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 		<link rel="icon" type="image/gif" href="/images/apache_feather.gif">
 		<link href='http://fonts.googleapis.com/css?family=Source+Sans+Pro:400,400italic' rel='stylesheet'
type='text/css'>
 		<meta name="robots" content="index,follow" />
-		<meta name="language" content="en" /> 
+		<meta name="language" content="en" />
 		<meta name="keywords" content="apache kafka messaging queuing distributed stream processing">
 		<meta name="description" content="Apache Kafka: A high-throughput, distributed, publish-subscribe
messaging system.">
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@@ -68,6 +68,7 @@
 						<li><a href="http://cwiki.apache.org/confluence/display/KAFKA/Projects">projects</a></li>
 						<li><a href="/contributing.html">contributing</a></li>
 						<li><a href="/coding-guide.html">coding&nbsp;guide</a></li>
+						<li><a href="/protocol.html">protocol&nbsp;guide</a></li>
 						<li><a href="https://builds.apache.org">unit&nbsp;tests</a></li>
 					</ul>
 				</li>

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+<!-- should always link the the latest release's documentation -->
+<!--#include virtual="090/protocol.html" -->


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