Author: jkreps
Date: Fri Apr 4 23:51:20 2014
New Revision: 1584942
URL: http://svn.apache.org/r1584942
Log:
Misc. tweaks to the producer config documentation.
Modified:
kafka/site/081/configuration.html
Modified: kafka/site/081/configuration.html
URL:
http://svn.apache.org/viewvc/kafka/site/081/configuration.html?rev=1584942&r1=1584941&r2=1584942&view=diff
==============================================================================
--- kafka/site/081/configuration.html (original)
+++ kafka/site/081/configuration.html Fri Apr 4 23:51:20 2014
@@ -718,21 +718,21 @@ We are working on a replacement for our
<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).</td></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 before considering a request complete.
This controls the durability of records that are sent. The following settings
are commonly useful: <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 message
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 i
t 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>
+ <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 message upon receiving the error. Allowing retries
will potentially change the ordering of messages because if two messages are
sent to a single partition, and the first fails and is retried but the second
succeeds, then the second message may appear first.</td></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 there is data for. <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 messages.</td></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 sends.
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 specified time
waiting for more records t
o show up. This setting defaults to 0 (i.e. no delay).</td></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>
@@ -740,17 +740,15 @@ We are working on a replacement for our
<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 ellipses 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>
+ <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.</td></tr>
- <tr>
-
<td>metadata.fetch.backoff.ms</td><td>long</td><td>50</td><td>low</td><td>The
minimum amount of time between metadata refreshes. The client refreshes
metadata whenever it realizes its internal metadata is out of sync with the
actual leadership of partitions. This configuration specifies a backoff to
prevent metadata refreshes from happening too frequently.</td></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 leadership changes to proactively discover any new
brokers or partitions.</td></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.</td></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>
