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From jun...@apache.org
Subject svn commit: r1672183 - /kafka/site/083/introduction.html
Date Wed, 08 Apr 2015 21:15:24 GMT
Author: junrao
Date: Wed Apr  8 21:15:24 2015
New Revision: 1672183

URL: http://svn.apache.org/r1672183
Log:
Clarify that max number of consumer instances is per consumer group

Modified:
    kafka/site/083/introduction.html

Modified: kafka/site/083/introduction.html
URL: http://svn.apache.org/viewvc/kafka/site/083/introduction.html?rev=1672183&r1=1672182&r2=1672183&view=diff
==============================================================================
--- kafka/site/083/introduction.html (original)
+++ kafka/site/083/introduction.html Wed Apr  8 21:15:24 2015
@@ -67,9 +67,9 @@ Kafka has stronger ordering guarantees t
 <p>
 A traditional queue retains messages in-order on the server, and if multiple consumers consume
from the queue then the server hands out messages in the order they are stored. However, although
the server hands out messages in order, the messages are delivered asynchronously to consumers,
so they may arrive out of order on different consumers. This effectively means the ordering
of the messages is lost in the presence of parallel consumption. Messaging systems often work
around this by having a notion of "exclusive consumer" that allows only one process to consume
from a queue, but of course this means that there is no parallelism in processing.
 <p>
-Kafka does it better. By having a notion of parallelism&mdash;the partition&mdash;within
the topics, Kafka is able to provide both ordering guarantees and load balancing over a pool
of consumer processes. This is achieved by assigning the partitions in the topic to the consumers
in the consumer group so that each partition is consumed by exactly one consumer in the group.
By doing this we ensure that the consumer is the only reader of that partition and consumes
the data in order. Since there are many partitions this still balances the load over many
consumer instances. Note however that there cannot be more consumer instances than partitions.
+Kafka does it better. By having a notion of parallelism&mdash;the partition&mdash;within
the topics, Kafka is able to provide both ordering guarantees and load balancing over a pool
of consumer processes. This is achieved by assigning the partitions in the topic to the consumers
in the consumer group so that each partition is consumed by exactly one consumer in the group.
By doing this we ensure that the consumer is the only reader of that partition and consumes
the data in order. Since there are many partitions this still balances the load over many
consumer instances. Note however that there cannot be more consumer instances in a consumer
group than partitions.
 <p>
-Kafka only provides a total order over messages <i>within</i> a partition, not
between different partitions in a topic. Per-partition ordering combined with the ability
to partition data by key is sufficient for most applications. However, if you require a total
order over messages this can be achieved with a topic that has only one partition, though
this will mean only one consumer process.
+Kafka only provides a total order over messages <i>within</i> a partition, not
between different partitions in a topic. Per-partition ordering combined with the ability
to partition data by key is sufficient for most applications. However, if you require a total
order over messages this can be achieved with a topic that has only one partition, though
this will mean only one consumer process per consumer group.
 
 <h4>Guarantees</h4>
 



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