以下配置是必須的

broker.id
log.dirs
zookeeper.connect

訊息保留策略

kafka有兩種“保留策略”：
1. 按時間，根據訊息保留的時間，當訊息在kafka中儲存的時間超過了指定時間，就可以被刪除；
2. 按空間，根據topic儲存的資料大小，當topic所佔的日誌檔案大小大於一個閥值，則可以開始刪除最舊的訊息

資料儲存的最大時間超過這個時間會根據log.cleanup.policy設定的策略處理資料，也就是消費端能夠多久去消費資料
log.retention.bytes和log.retention.hours任意一個達到要求，都會執行刪除，會被topic建立時的指定引數覆蓋。

# The minimum age of a log file to be eligible for deletion
log.retention.hours=168

# A size-based retention policy for logs. Segments are pruned from the log as long as the remaining
# segments don't drop below log.retention.bytes.
log.retention.bytes=1073741824

訊息可靠性機制

• 訊息傳送可靠性
  生產者傳送訊息到broker，有三種確認方式（request.required.acks）
  acks = 0: producer不會等待broker（leader）傳送ack 。因為傳送訊息網路超時或broker crash(1.Partition的Leader還沒有commit訊息 2.Leader與Follower資料不同步)，既有可能丟失也可能會重發。
  acks = 1: 當leader接收到訊息之後傳送ack，丟會重發，丟的概率很小
  acks = -1: 當所有的follower都同步訊息成功後傳送ack. 丟失訊息可能性比較低。
• 訊息儲存可靠性
  每一條訊息被髮送到broker中，會根據partition規則選擇被儲存到哪一個partition。如果partition規則設定的合理，所有訊息可以均勻分佈到不同的partition裡，這樣就實現了水平擴充套件。
  在建立topic時可以指定這個topic對應的partition的數量。在傳送一條訊息時，可以指定這條訊息的key，producer根據這個key和partition機制來判斷這個訊息傳送到哪個partition。
  kafka的高可靠性的保障來自於另一個叫副本（replication）策略，通過設定副本的相關引數，可以使kafka在效能和可靠性之間做不同的切換。

配置server.properties

# kafka.server.KafkaConfig for additional details and defaults
############################# Server Basics #############################
# broker的id，每一個broker必須設定成全域性唯一
broker.id=0
# 在啟動broker時候開啟刪除topic的開關，預設是關閉（false）的
delete.topic.enable=true
############################# Socket Server Settings #############################

# The address the socket server listens on. It will get the value returned from
# java.net.InetAddress.getCanonicalHostName() if not configured.
#   FORMAT:
#     listeners = security_protocol://host_name:port
#   EXAMPLE:
#     listeners = PLAINTEXT://your.host.name:9092
#listeners=PLAINTEXT://:9092
# Hostname and port the broker will advertise to producers and consumers. If not set,
# it uses the value for "listeners" if configured.  Otherwise, it will use the value
# returned from java.net.InetAddress.getCanonicalHostName().
advertised.listeners=PLAINTEXT://192.168.10.151:9092
advertised.host.name=192.168.10.151
advertised.port=9092

# The number of threads handling network requests
num.network.threads=3

# The number of threads doing disk I/O
num.io.threads=8

# The send buffer (SO_SNDBUF) used by the socket server
socket.send.buffer.bytes=102400

# The receive buffer (SO_RCVBUF) used by the socket server
socket.receive.buffer.bytes=102400

# The maximum size of a request that the socket server will accept (protection against OOM)
socket.request.max.bytes=104857600


############################# Log Basics #############################

# A comma seperated list of directories under which to store log files
log.dirs=/data/kafka/logs
# The default number of log partitions per topic. More partitions allow greater
# parallelism for consumption, but this will also result in more files across
# the brokers.
num.partitions=1

# The number of threads per data directory to be used for log recovery at startup and flushing at shutdown.
# This value is recommended to be increased for installations with data dirs located in RAID array.
num.recovery.threads.per.data.dir=1

############################# Log Flush Policy #############################

# Messages are immediately written to the filesystem but by default we only fsync() to sync
# the OS cache lazily. The following configurations control the flush of data to disk.
# There are a few important trade-offs here:
#    1. Durability: Unflushed data may be lost if you are not using replication.
#    2. Latency: Very large flush intervals may lead to latency spikes when the flush does occur as there will be a lot of data to flush.
#    3. Throughput: The flush is generally the most expensive operation, and a small flush interval may lead to exceessive seeks.
# The settings below allow one to configure the flush policy to flush data after a period of time or
# every N messages (or both). This can be done globally and overridden on a per-topic basis.

# The number of messages to accept before forcing a flush of data to disk
#log.flush.interval.messages=10000

# The maximum amount of time a message can sit in a log before we force a flush
#log.flush.interval.ms=1000

############################# Log Retention Policy #############################

# The following configurations control the disposal of log segments. The policy can
# be set to delete segments after a period of time, or after a given size has accumulated.
# A segment will be deleted whenever *either* of these criteria are met. Deletion always happens
# from the end of the log.

# The minimum age of a log file to be eligible for deletion
log.retention.hours=168

# A size-based retention policy for logs. Segments are pruned from the log as long as the remaining
# segments don't drop below log.retention.bytes.
#log.retention.bytes=1073741824

# The maximum size of a log segment file. When this size is reached a new log segment will be created.
log.segment.bytes=1073741824

# The interval at which log segments are checked to see if they can be deleted according
# to the retention policies
log.retention.check.interval.ms=300000

############################# Zookeeper #############################

# Zookeeper connection string (see zookeeper docs for details).
# This is a comma separated host:port pairs, each corresponding to a zk
# server. e.g. "127.0.0.1:3000,127.0.0.1:3001,127.0.0.1:3002".
# You can also append an optional chroot string to the urls to specify the
# root directory for all kafka znodes.
zookeeper.connect=192.168.10.151:2181

# Timeout in ms for connecting to zookeeper
zookeeper.connection.timeout.ms=6000

下面將更詳細地討論Topic級配置和約定

More details about broker configuration can be found in the scala class

kafka.server.KafkaConfig.