Dear folks,
I have run some basic tests using kafka. I have started 7 brokers,
created a topic with 21 partitions and 3 replicas.
2 producers are started with 5 threads each and pushed 2419200 messages of
50 bytes in total.
3 consumers with 2 in one group and 1 in other are started to fetch the
data at the same time. High level api is used to fetch the messages.
The whole process runs for about 3 hours. One group got 23991800 messages
and another group got 23911600 messages. I start the consumer again, no
messages are fetched later.
I try to catch the exceptions with send() and next() functions, however no
exceptions are thrown. I check the offset of zookeeper, but the offsets are
right.
Here is the most strangest thing that, I try to consume the same topic with
a different groupid, however on messages could be fetched. The offset of
this group jumps to the end of the offset.
So I think this maybe a configuration problem. Thanks for help in advance!
My configuration is listed as follows:
# The receive buffer (SO_RCVBUF) used by the socket server
socket.receive.buffer.bytes=5242880
# 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=/data1/kafka-logs,/data2/kafka-logs,/data3/kafka-logs,/data4/kafka-logs,/data5/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=2
############################# 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=48
# 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=536870912
# 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=60000
# By default the log cleaner is disabled and the log retention policy will
default to just delete segments after their retention expires.
# If log.cleaner.enable=true is set the cleaner will be enabled and
individual logs can then be marked for log compaction.
log.cleaner.enable=false
############################# 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=10.16.42.225:2199,10.16.42.226:2199,10.16.42.227:2199
# Timeout in ms for connecting to zookeeper
zookeeper.connection.timeout.ms=1000000
Shuo Chen
I have run some basic tests using kafka. I have started 7 brokers,
created a topic with 21 partitions and 3 replicas.
2 producers are started with 5 threads each and pushed 2419200 messages of
50 bytes in total.
3 consumers with 2 in one group and 1 in other are started to fetch the
data at the same time. High level api is used to fetch the messages.
The whole process runs for about 3 hours. One group got 23991800 messages
and another group got 23911600 messages. I start the consumer again, no
messages are fetched later.
I try to catch the exceptions with send() and next() functions, however no
exceptions are thrown. I check the offset of zookeeper, but the offsets are
right.
Here is the most strangest thing that, I try to consume the same topic with
a different groupid, however on messages could be fetched. The offset of
this group jumps to the end of the offset.
So I think this maybe a configuration problem. Thanks for help in advance!
My configuration is listed as follows:
# The receive buffer (SO_RCVBUF) used by the socket server
socket.receive.buffer.bytes=5242880
# 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=/data1/kafka-logs,/data2/kafka-logs,/data3/kafka-logs,/data4/kafka-logs,/data5/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=2
############################# 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=48
# 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=536870912
# 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=60000
# By default the log cleaner is disabled and the log retention policy will
default to just delete segments after their retention expires.
# If log.cleaner.enable=true is set the cleaner will be enabled and
individual logs can then be marked for log compaction.
log.cleaner.enable=false
############################# 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=10.16.42.225:2199,10.16.42.226:2199,10.16.42.227:2199
# Timeout in ms for connecting to zookeeper
zookeeper.connection.timeout.ms=1000000
Shuo Chen