svn commit: r1584942 - /kafka/site/081/configuration.html

[jk...@apache.org]

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&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></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&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). 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&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 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&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 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>