使用Kafka服务启动订购者失败

时间:2018-08-17 08:47:10

标签: apache-kafka hyperledger-fabric hyperledger

我尝试在一组物理节点上部署具有2个对等点,2个订购者,4个kafka和3个zookeeper的Hyperledger Fabric集群。 我的部署基于给定的docker example

我下载kafka_2.11-1.0.0.tgz并使用以下命令在四个节点中启动该过程(3个zookeeper节点也是属性设置)。

kafka-server-start.sh kafka-config/server-0.properties
kafka-server-start.sh kafka-config/server-1.properties 
kafka-server-start.sh kafka-config/server-2.properties 
kafka-server-start.sh kafka-config/server-3.properties 

server-0.properties中的配置如下(文件头的自定义配置注意)。除broker.id外,其他三个相同。

############################# Server Basics #############################

# The id of the broker. This must be set to a unique integer for each broker.
broker.id=0
message.max.bytes=103809024
replica.fetch.max.bytes=103809024
unclean.leader.election.enable=false 
min.insync.replicas=2
default.replication.factor=3
############################# 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 = listener_name://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://your.host.name:9092

# Maps listener names to security protocols, the default is for them to be the same. See the config documentation for more details
#listener.security.protocol.map=PLAINTEXT:PLAINTEXT,SSL:SSL,SASL_PLAINTEXT:SASL_PLAINTEXT,SASL_SSL:SASL_SSL

# The number of threads that the server uses for receiving requests from the network and sending responses to the network
num.network.threads=3

# The number of threads that the server uses for processing requests, which may include 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 separated list of directories under which to store log files
log.dirs=/tmp/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

############################# Internal Topic Settings  #############################
# The replication factor for the group metadata internal topics "__consumer_offsets" and "__transaction_state"
# For anything other than development testing, a value greater than 1 is recommended for to ensure availability such as 3.
offsets.topic.replication.factor=1
transaction.state.log.replication.factor=1
transaction.state.log.min.isr=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 excessive 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 due to age
log.retention.hours=168

# A size-based retention policy for logs. Segments are pruned from the log unless the remaining
# segments drop below log.retention.bytes. Functions independently of log.retention.hours.
#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=slave-10:2181,slave-11:2181,slave-12:2181

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


############################# Group Coordinator Settings #############################

# The following configuration specifies the time, in milliseconds, that the GroupCoordinator will delay the initial consumer rebalance.
# The rebalance will be further delayed by the value of group.initial.rebalance.delay.ms as new members join the group, up to a maximum of max.poll.interval.ms.
# The default value for this is 3 seconds.
# We override this to 0 here as it makes for a better out-of-the-box experience for development and testing.
# However, in production environments the default value of 3 seconds is more suitable as this will help to avoid unnecessary, and potentially expensive, rebalances during application startup.
group.initial.rebalance.delay.ms=0

四个Kafka节点可以平稳运行。但是,当我通过cmd启动订购程序时

export FABRIC_CFG_PATH=/users/ruanpc/fabric-1.0-exp/fabric-config
export ORDERER_GENERAL_LOGLEVEL=INFO  
export ORDERER_GENERAL_LISTENADDRESS=0.0.0.0 
export ORDERER_GENERAL_GENESISMETHOD=file 
export ORDERER_GENERAL_GENESISFILE=/users/ruanpc/fabric-1.0-exp/channel-artifacts/genesis.block
export ORDERER_GENERAL_LOCALMSPID=OrdererMSP 
export ORDERER_GENERAL_LOCALMSPDIR=/users/ruanpc/fabric-1.0-exp/crypto-config/ordererOrganizations/example.com/orderers/orderer0.example.com/msp
export ORDERER_KAFKA_RETRY_SHORTINTERVAL=1s
export ORDERER_KAFKA_RETRY_SHORTTOTAL=30s
export ORDERER_KAFKA_VERBOSE=true
export ORDERER_FILELEDGER_LOCATION="/tmp/hyperledger/production/orderer"
orderer

订购过程不断报告

2018-08-17 08:24:46.324 UTC [orderer/consensus/kafka/sarama] eachPartition -> DEBU 2e4 producer/broker/3 state change to [retrying] on testchainid/0 because kafka server: Messages are rejected since there are fewer in-sync replicas than required.

与此同时,我的第四个kafka节点不断报告

org.apache.kafka.common.errors.NotEnoughReplicasException: Number of insync replicas for partition testchainid-0 is [1], below required minimum [2]
[2018-08-17 08:24:39,529] ERROR [ReplicaManager broker=3] Error processing append operation on partition testchainid-0 (kafka.server.ReplicaManager)

其他三个kafka节点似乎正常工作。

以下是我的kafka主题的说明:

kafka-topics.sh --zookeeper localhost:2181 --describe --topic testchainid 
Topic:testchainid PartitionCount:1  ReplicationFactor:1 Configs: Topic: testchainid Partition: 0    Leader: 3   Replicas: 3 Isr: 3 

有人知道发生了什么吗?谢谢!

1 个答案:

答案 0 :(得分:2)

主题testchainid的复制因子设置为1,小于min.insync.replicas=2

您需要通过运行

增加复制因子的数量
kafka-topics --zookeeper localhost:2181 --alter --topic testchainid --replication-factor 2

我还建议检查主题testchainid为何只有一个副本,因为在您的kafka代理配置中,默认复制因子设置为3:

default.replication.factor=3