USDP使用笔记Flink配置及简单测试

Posted 2022-12-30 虎鲸不是鱼

tags:

篇首语：本文由小常识网(cha138.com)小编为大家整理，主要介绍了USDP使用笔记Flink配置及简单测试相关的知识，希望对你有一定的参考价值。

Flink配置Flink配置及简单测试

上一篇：https://lizhiyong.blog.csdn.net/article/details/123560865
将USDP2.0自带的Flink更换为Flink1.14后，还没有来得及改配置。不改配置用起来是有问题的，所以。。。本文主要就是改配置及简单测试效果。

USDP默认的配置

################################################################################
#  Licensed to the Apache Software Foundation (ASF) under one
#  or more contributor license agreements.  See the NOTICE file
#  distributed with this work for additional information
#  regarding copyright ownership.  The ASF licenses this file
#  to you under the Apache License, Version 2.0 (the
#  "License"); you may not use this file except in compliance
#  with the License.  You may obtain a copy of the License at
#
#      http://www.apache.org/licenses/LICENSE-2.0
#
#  Unless required by applicable law or agreed to in writing, software
#  distributed under the License is distributed on an "AS IS" BASIS,
#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
#  See the License for the specific language governing permissions and
# limitations under the License.
################################################################################


#==============================================================================
# Common
#==============================================================================

# The external address of the host on which the JobManager runs and can be
# reached by the TaskManagers and any clients which want to connect. This setting
# is only used in Standalone mode and may be overwritten on the JobManager side
# by specifying the --host <hostname> parameter of the bin/jobmanager.sh executable.
# In high availability mode, if you use the bin/start-cluster.sh script and setup
# the conf/masters file, this will be taken care of automatically. Yarn/Mesos
# automatically configure the host name based on the hostname of the node where the
# JobManager runs.

jobmanager.rpc.address: localhost

# The RPC port where the JobManager is reachable.

jobmanager.rpc.port: 6123


# The total process memory size for the JobManager.
#
# Note this accounts for all memory usage within the JobManager process, including JVM metaspace and other overhead.

jobmanager.memory.process.size: 1600m


# The total process memory size for the TaskManager.
#
# Note this accounts for all memory usage within the TaskManager process, including JVM metaspace and other overhead.

taskmanager.memory.process.size: 1728m

# To exclude JVM metaspace and overhead, please, use total Flink memory size instead of 'taskmanager.memory.process.size'.
# It is not recommended to set both 'taskmanager.memory.process.size' and Flink memory.
#
# taskmanager.memory.flink.size: 1280m

# The number of task slots that each TaskManager offers. Each slot runs one parallel pipeline.

taskmanager.numberOfTaskSlots: 1

# The parallelism used for programs that did not specify and other parallelism.

parallelism.default: 1

# The default file system scheme and authority.
#
# By default file paths without scheme are interpreted relative to the local
# root file system 'file:///'. Use this to override the default and interpret
# relative paths relative to a different file system,
# for example 'hdfs://mynamenode:12345'
#
# fs.default-scheme

#==============================================================================
# High Availability
#==============================================================================

# The high-availability mode. Possible options are 'NONE' or 'zookeeper'.
#
# high-availability: zookeeper

# The path where metadata for master recovery is persisted. While ZooKeeper stores
# the small ground truth for checkpoint and leader election, this location stores
# the larger objects, like persisted dataflow graphs.
#
# Must be a durable file system that is accessible from all nodes
# (like HDFS, S3, Ceph, nfs, ...)
#
# high-availability.storageDir: hdfs:///flink/ha/

# The list of ZooKeeper quorum peers that coordinate the high-availability
# setup. This must be a list of the form:
# "host1:clientPort,host2:clientPort,..." (default clientPort: 2181)
#
# high-availability.zookeeper.quorum: localhost:2181


# ACL options are based on https://zookeeper.apache.org/doc/r3.1.2/zookeeperProgrammers.html#sc_BuiltinACLSchemes
# It can be either "creator" (ZOO_CREATE_ALL_ACL) or "open" (ZOO_OPEN_ACL_UNSAFE)
# The default value is "open" and it can be changed to "creator" if ZK security is enabled
#
# high-availability.zookeeper.client.acl: open

#==============================================================================
# Fault tolerance and checkpointing
#==============================================================================

# The backend that will be used to store operator state checkpoints if
# checkpointing is enabled.
#
# Supported backends are 'jobmanager', 'filesystem', 'rocksdb', or the
# <class-name-of-factory>.
#
# state.backend: filesystem

# Directory for checkpoints filesystem, when using any of the default bundled
# state backends.
#
# state.checkpoints.dir: hdfs://namenode-host:port/flink-checkpoints

# Default target directory for savepoints, optional.
#
# state.savepoints.dir: hdfs://namenode-host:port/flink-savepoints

# Flag to enable/disable incremental checkpoints for backends that
# support incremental checkpoints (like the RocksDB state backend).
#
# state.backend.incremental: false

# The failover strategy, i.e., how the job computation recovers from task failures.
# Only restart tasks that may have been affected by the task failure, which typically includes
# downstream tasks and potentially upstream tasks if their produced data is no longer available for consumption.

jobmanager.execution.failover-strategy: region

#==============================================================================
# Rest & web frontend
#==============================================================================

# The port to which the REST client connects to. If rest.bind-port has
# not been specified, then the server will bind to this port as well.
#
#rest.port: 8081

# The address to which the REST client will connect to
#
#rest.address: 0.0.0.0

# Port range for the REST and web server to bind to.
#
#rest.bind-port: 8080-8090

# The address that the REST & web server binds to
#
#rest.bind-address: 0.0.0.0

# Flag to specify whether job submission is enabled from the web-based
# runtime monitor. Uncomment to disable.

#web.submit.enable: false

#==============================================================================
# Advanced
#==============================================================================

# Override the directories for temporary files. If not specified, the
# system-specific Java temporary directory (java.io.tmpdir property) is taken.
#
# For framework setups on Yarn or Mesos, Flink will automatically pick up the
# containers' temp directories without any need for configuration.
#
# Add a delimited list for multiple directories, using the system directory
# delimiter (colon ':' on unix) or a comma, e.g.:
#     /data1/tmp:/data2/tmp:/data3/tmp
#
# Note: Each directory entry is read from and written to by a different I/O
# thread. You can include the same directory multiple times in order to create
# multiple I/O threads against that directory. This is for example relevant for
# high-throughput RAIDs.
#
# io.tmp.dirs: /tmp

# The classloading resolve order. Possible values are 'child-first' (Flink's default)
# and 'parent-first' (Java's default).
#
# Child first classloading allows users to use different dependency/library
# versions in their application than those in the classpath. Switching back
# to 'parent-first' may help with debugging dependency issues.
#
# classloader.resolve-order: child-first

# The amount of memory going to the network stack. These numbers usually need 
# no tuning. Adjusting them may be necessary in case of an "Insufficient number
# of network buffers" error. The default min is 64MB, the default max is 1GB.
# 
# taskmanager.memory.network.fraction: 0.1
# taskmanager.memory.network.min: 64mb
# taskmanager.memory.network.max: 1gb

#==============================================================================
# Flink Cluster Security Configuration
#==============================================================================

# Kerberos authentication for various components - Hadoop, ZooKeeper, and connectors -
# may be enabled in four steps:
# 1. configure the local krb5.conf file
# 2. provide Kerberos credentials (either a keytab or a ticket cache w/ kinit)
# 3. make the credentials available to various JAAS login contexts
# 4. configure the connector to use JAAS/SASL

# The below configure how Kerberos credentials are provided. A keytab will be used instead of
# a ticket cache if the keytab path and principal are set.

# security.kerberos.login.use-ticket-cache: true
# security.kerberos.login.keytab: /path/to/kerberos/keytab
# security.kerberos.login.principal: flink-user

# The configuration below defines which JAAS login contexts

# security.kerberos.login.contexts: Client,KafkaClient

#==============================================================================
# ZK Security Configuration
#==============================================================================

# Below configurations are applicable if ZK ensemble is configured for security

# Override below configuration to provide custom ZK service name if configured
# zookeeper.sasl.service-name: zookeeper

# The configuration below must match one of the values set in "security.kerberos.login.contexts"
# zookeeper.sasl.login-context-name: Client

#==============================================================================
# HistoryServer
#==============================================================================

# The HistoryServer is started and stopped via bin/historyserver.sh (start|stop)

# Directory to upload completed jobs to. Add this directory to the list of
# monitored directories of the HistoryServer as well (see below).
jobmanager.archive.fs.dir: hdfs://zhiyong-1/zhiyong-1/flink-completed-jobs/

# The address under which the web-based HistoryServer listens.
# historyserver.web.address: zhiyong3

# History Server所绑定的ip，0.0.0.0代表允许所有ip访问
historyserver.web.address: 0.0.0.0

# 指定History Server间隔多少毫秒扫描一次归档目录
historyserver.archive.fs.refresh-interval: 10000


# The port under which the web-based HistoryServer listens, default 8082.
historyserver.web.port: 8082

# Comma separated list of directories to monitor for completed jobs.
historyserver.archive.fs.dir: hdfs://zhiyong-1/zhiyong-1/flink-completed-jobs/

# Interval in milliseconds for refreshing the monitored directories, default 10000.
historyserver.archive.fs.refresh-interval: 10000
historyserver.web.tmpdir: /data/udp/2.0.0.0/flink
env.java.opts: -Dlog4j2.formatMsgNoLookups=true

开启HA

修改Yaml

################################################################################
#  Licensed to the Apache Software Foundation (ASF) under one
#  or more contributor license agreements.  See the NOTICE file
#  distributed with this work for additional information
#  regarding copyright ownership.  The ASF licenses this file
#  to you under the Apache License, Version 2.0 (the
#  "License"); you may not use this file except in compliance
#  with the License.  You may obtain a copy of the License at
#
#      http://www.apache.org/licenses/LICENSE-2.0
#
#  Unless required by applicable law or agreed to in writing, software
#  distributed under the License is distributed on an "AS IS" BASIS,
#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
#  See the License for the specific language governing permissions and
# limitations under the License.
################################################################################


#==============================================================================
# Common
#==============================================================================

# The external address of the host on which the JobManager runs and can be
# reached by the TaskManagers and any clients which want to connect. This setting
# is only used in Standalone mode and may be overwritten on the JobManager side
# by specifying the --host <hostname> parameter of the bin/jobmanager.sh executable.
# In high availability mode, if you use the bin/start-cluster.sh script and setup
# the conf/masters file, this will be taken care of automatically. Yarn/Mesos
# automatically configure the host name based on the hostname of the node where the
# JobManager runs.

jobmanager.rpc.address: zhiyong2

# The RPC port where the JobManager is reachable.

jobmanager.rpc.port: 6123


# The total process memory size for the JobManager.
#
# Note this accounts for all memory usage within the JobManager process, including JVM metaspace and other overhead.

jobmanager.memory.process.size: 1600m


# The total process memory size for the TaskManager.
#
# Note this accounts for all memory usage within the TaskManager process, including JVM metaspace and other overhead.

taskmanager.memory.process.size: 1728m

# To exclude JVM metaspace and overhead, please, use total Flink memory size instead of 'taskmanager.memory.process.size'.
# It is not recommended to set both 'taskmanager.memory.process.size' and Flink memory.
#
# taskmanager.memory.flink.size: 1280m

# The number of task slots that each TaskManager offers. Each slot runs one parallel pipeline.

taskmanager.numberOfTaskSlots: 1

# The parallelism used for programs that did not specify and other parallelism.

parallelism.default: 1

# The default file system scheme and authority.
#
# By default file paths without scheme are interpreted relative to the local
# root file system 'file:///'. Use this to override the default and interpret
# relative paths relative to a different file system,
# for example 'hdfs://mynamenode:12345'
#
# fs.default-scheme

#==============================================================================
# High Availability
#==============================================================================

# The high-availability mode. Possible options are 'NONE' or 'zookeeper'.
#
high-availability: zookeeper

# The path where metadata for master recovery is persisted. While ZooKeeper stores
# the small ground truth for checkpoint and leader election, this location stores
# the larger objects, like persisted dataflow graphs.
#
# Must be a durable file system that is accessible from all nodes
# (like HDFS, S3, Ceph, nfs, ...)
#
high-availability.storageDir: hdfs://zhiyong-1/flink/ha/

# The list of ZooKeeper quorum peers that coordinate the high-availability
# setup. This must be a list of the form:
# "host1:clientPort,host2:clientPort,..." (default clientPort: 2181)
#
high-availability.zookeeper.quorum: zhiyong2:2181,zhiyong3:2181,zhiyong4:2181


# ACL options are based on https://zookeeper.apache.org/doc/r3.1.2/zookeeperProgrammers.html#sc_BuiltinACLSchemes
# It can be either "creator" (ZOO_CREATE_ALL_ACL) or "open" (ZOO_OPEN_ACL_UNSAFE)
# The default value is "open" and it can be changed to "creator" if ZK security is enabled
#
# high-availability.zookeeper.client.acl: open

#==============================================================================
# Fault tolerance and checkpointing
#==============================================================================

# The backend that will be used to store operator state checkpoints if
# checkpointing is enabled.
#
# Supported backends are 'jobmanager', 'filesystem', 'rocksdb', or the
# <class-name-of-factory>.
#
state.backend: filesystem

# Directory for checkpoints filesystem, when using any of the default bundled
# state backends.
#
state.checkpoints.dir: hdfs://zhiyong-1/flink-checkpoints

# Default target directory for savepoints, optional.
#
state.savepoints.dir: hdfs://zhiyong-1/flink-savepoints

# Flag to enable/disable incremental checkpoints for backends that
# support incremental checkpoints (like the RocksDB state backend).
#
# state.backend.incremental: false

# The failover strategy, i.e., how the job computation recovers from task failures.
# Only restart tasks that may have been affected by the task failure, which typically includes
# downstream tasks and potentially upstream tasks if their produced data is no longer available for consumption.

jobmanager.execution.failover-strategy: region

#==============================================================================
# Rest & web frontend
#==============================================================================

# The port to which the REST client connects to. If rest.bind-port has
# not been specified, then the server will bind to this port as well.
#
#rest.port: 8081

# The address to which the REST client will connect to
#
#rest.address: 0.0.0.0

# Port range for the REST and web server to bind to.
#
#rest.bind-port: 8080-8090

# The address that the REST & web server binds to
#
#rest.bind-address: 0.0.0.0

# Flag to specify whether job submission is enabled from the web-based
# runtime monitor. Uncomment to disable.

web.submit.enable: true

#==============================================================================
# Advanced
#==============================================================================

# Override the directories for temporary files. If not specified, the
# system-specific Java temporary directory (java.io.tmpdir property) is taken.
#
# For framework setups on Yarn or Mesos, Flink will automatically pick up the
# containers' temp directories without any need for configuration.
#
# Add a delimited list for multiple directories, using the system directory
# delimiter (colon ':' on unix) or a comma, e.g.:
#     /data1/tmp:/data2/tmp:/data3/tmp
#
# Note: Each directory entry is read from and written to by a different I/O
# thread. You can include the same directory multiple times in order to create
# multiple I/O threads against that directory. This is for example relevant for
# high-throughput RAIDs.
#
# io.tmp.dirs: /tmp

# The classloading resolve order. Possible values are 'child-first' (Flink's default)
# and 'parent-first' (Java's default).
#
# Child first classloading allows users to use different dependency/library
# versions in their application than those in the classpath. Switching back
# to 'parent-first' may help with debugging dependency issues.
#
# classloader.resolve-order: child-first

# The amount of memory going to the network stack. These numbers usually need 
# no tuning. Adjusting them may be necessary in case of an "Insufficient number
# of network buffers" error. The default min is 64MB, the default max is 1GB.
# 
# taskmanager.memory.network.fraction: 0.1
# taskmanager.memory.network.min: 64mb
# taskmanager.memory.network.max: 1gb

#==============================================================================
# Flink Cluster Security Configuration
#==============================================================================

# Kerberos authentication for various components - Hadoop, ZooKeeper, and connectors -
# may be enabled in four steps:
# 1. configure the local krb5.conf file
# 2. provide Kerberos credentials (either a keytab or a ticket cache w/ kinit)
# 3. make the credentials available to various JAAS login contexts
# 4. configure the connector to use JAAS/SASL

# The below configure how Kerberos credentials are provided. A keytab will be used instead of
# a ticket cache if the keytab path and principal are set.

# security.kerberos.login.use-ticket-cache: true
# security.kerberos.login.keytab: /path/to/kerberos/keytab
# security.kerberos.login.principal: flink-user

# The configuration below defines which JAAS login contexts

# security.kerberos.login.contexts: Client,KafkaClient

#==============================================================================
# ZK Security Configuration
#==============================================================================

# Below configurations are applicable if ZK ensemble is configured for security

# Override below configuration to provide custom ZK service name if configured
# zookeeper.sasl.service-name: zookeeper

# The configuration below must match one of the values set in "security.kerberos.login.contexts"
# zookeeper.sasl.login-context-name: Client

#==============================================================================
# HistoryServer
#==============================================================================

# The HistoryServer is started and stopped via bin/historyserver.sh (start|stop)

# Directory to upload completed jobs to. Add this directory to the list of
# monitored directories of the HistoryServer as well (see below).
jobmanager.archive.fs.dir: hdfs://zhiyong-1/zhiyong-1/flink-completed-jobs/

# The address under which the web-based HistoryServer listens.
# historyserver.web.address: zhiyong3

# History Server所绑定的ip，0.0.0.0代表允许所有ip访问
historyserver.web.address: 0.0.0.0

# 指定History Server间隔多少毫秒扫描一次归档目录
historyserver.archive.fs.refresh-interval: 10000


# The port under which the web-based HistoryServer listens, default 8082.
historyserver.web.port: 8082

# Comma separated list of directories to monitor for completed jobs.
historyserver.archive.fs.dir: hdfs://zhiyong-1/zhiyong-1/flink-completed-jobs/

# Interval in milliseconds for refreshing the monitored directories, default 10000.
historyserver.archive.fs.refresh-interval: 10000
historyserver.web.tmpdir: /data/udp/2.0.0.0/flink
env.java.opts: -Dlog4j2.formatMsgNoLookups=true

修改后直接USDP确定，USDP会自动分发。

修改其它文件

masters

[root@zhiyong2 ~]# cd /srv/udp/2.0.0.0/flink/conf/
[root@zhiyong2 conf]# ll
总用量 60
-rwxrwxrwx 1 hadoop hadoop 10732 4月   1 11:29 flink-conf.yaml
-rwxr-xr-x 1 root   root    4469 4月   1 11:29 hive-site.xml
-rwxrwxrwx 1 hadoop hadoop  2917 3月  14 23:15 log4j-cli.properties
-rwxrwxrwx 1 hadoop hadoop  3041 3月  14 23:15 log4j-console.properties
-rwxrwxrwx 1 hadoop hadoop  2694 3月  14 23:15 log4j.properties
-rwxrwxrwx 1 hadoop hadoop  2041 3月  14 23:15 log4j-session.properties
-rwxrwxrwx 1 hadoop hadoop  2740 4月   1 11:29 logback-console.xml
-rwxrwxrwx 1 hadoop hadoop  1550 3月  14 23:15 logback-session.xml
-rwxrwxrwx 1 hadoop hadoop  2327 4月   1 11:29 logback.xml
-rwxrwxrwx 1 hadoop hadoop    15 3月  14 23:15 masters
drwxr-xr-x 2 root   root     300 4月   1 11:29 old
-rwxrwxrwx 1 hadoop hadoop    10 3月  14 23:15 workers
-rwxrwxrwx 1 hadoop hadoop  1434 3月  14 23:15 zoo.cfg
[root@zhiyong2 conf]# cat masters
localhost:8081
[root@zhiyong2 conf]# vim masters
[root@zhiyong2 conf]# cat masters
zhiyong3:8081
zhiyong4:8081

zoo.cfg

[root@zhiyong2 conf]# vim zoo.cfg
[root@zhiyong2 conf]# cat zoo.cfg
################################################################################
#  Licensed to the Apache Software Foundation (ASF) under one
#  or more contributor license agreements.  See the NOTICE file
#  distributed with this work for additional information
#  regarding copyright ownership.  The ASF licenses this file
#  to you under the Apache License, Version 2.0 (the
#  "License"); you may not use this file except in compliance
#  with the License.  You may obtain a copy of the License at
#
#      http://www.apache.org/licenses/LICENSE-2.0
#
#  Unless required by applicable law or agreed to in writing, software
#  distributed under the License is distributed on an "AS IS" BASIS,
#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
#  See the License for the specific language governing permissions and
# limitations under the License.
################################################################################

# The number of milliseconds of each tick
tickTime=2000

# The number of ticks that the initial  synchronization phase can take
initLimit=10

# The number of ticks that can pass between  sending a request and getting an acknowledgement
syncLimit=5

# The directory where the snapshot is stored.
# dataDir=/tmp/zookeeper

# The port at which the clients will connect
clientPort=2181

# ZooKeeper quorum peers
server.1=zhiyong2:2888:3888
server.2=zhiyong3:2888:3888
server.3=zhiyong4:2888:3888
# server.2=host:peer-port:leader-port

workers

[root@zhiyong2 conf]# cat workers
localhost
[root@zhiyong2 conf]# vim workers
[root@zhiyong2 conf]# cat workers
zhiyong2
zhiyong3
zhiyong4

分发

[root@zhiyong2 conf]# pwd
/srv/udp/2.0.0.0/flink/conf
[root@zhiyong2 conf]# scp ./masters root@zhiyong3:$PWD
masters                                                                                                                     100%   28    11.5KB/s   00:00
[root@zhiyong2 conf]# scp ./masters root@zhiyong4:$PWD
masters                                                                                                                     100%   28     9.0KB/s   00:00
[root@zhiyong2 conf]# scp ./zoo.cfg root@zhiyong3:$PWD
zoo.cfg                                                                                                                     100% 1489   759.7KB/s   00:00
[root@zhiyong2 conf]# scp ./zoo.cfg root@zhiyong4:$PWD
zoo.cfg                                                                                                                     100% 1489   530.4KB/s   00:00
[root@zhiyong2 conf]# scp ./workers root@zhiyong3:$PWD
workers                                                                                                                     100%   27     7.0KB/s   00:00
[root@zhiyong2 conf]# scp ./workers root@zhiyong4:$PWD
workers                                                                                                                     100%   27     8.9KB/s   00:00
[root@zhiyong2 conf]#

测试on Yarn

在Yarn做资源容器的情况下，主要是3种模式：Session模式，Per-Job模式，Application模式。

Session模式适用于频繁交互的小任务【比如当即席查询来用的sql-client】。这种模式随便玩玩就好，生产环境不合适。

Per-Job好处就是资源隔离的比较彻底，坏处当然就是资源占用率可能不高，没办法充分压榨CPU的算力。

Application模式是后来新增的，当然也就先进一些。

已经白底黑字清清楚楚地写了：

Per-job mode is only supported by YARN and has been deprecated in Flink 1.15. It will be dropped in FLINK-26000. Please consider application mode to launch a dedicated cluster per-job on YARN.

从Flink1.15开始Per-Job模式就要淘汰了，所以之后的新版本Flink应该逐步切换位Application模式。如果有必要，那也是基于Application模式构建专用集群模拟出Per-Job的效果。

Session模式

提交任务：

./bin/flink run -t yarn-session \\
  -Dyarn.application.id=application_XXXX_YY \\
  ./examples/streaming/TopSpeedWindowing.jar

或者指定Yarn的ID：

./bin/yarn-session.sh -id application_XXXX_YY

Per-Job模式

这是我们prod使用的部署模式，用法简单：

./bin/flink run -t yarn-per-job --detached ./examples/streaming/TopSpeedWindowing.jar

查看和cancel掉任务也很简单：

# List running job on the cluster
./bin/flink list -t yarn-per-job -Dyarn.application.id=application_XXXX_YY
# Cancel running job
./bin/flink cancel -t yarn-per-job -Dyarn.application.id=application_XXXX_YY <jobId>

Application模式

提交任务：

./bin/flink run-application -t yarn-application ./examples/streaming/TopSpeedWindowing.jar

查看和Cancel任务：

# List running job on the cluster
./bin/flink list USDP使用笔记Flink配置及简单测试
 USDP使用笔记使用Flink1.14.3替换自带的老版Flink1.13
 USDP使用笔记使用Flink1.14.3替换自带的老版Flink1.13
 USDP使用笔记大数据集群及组件启停
 USDP使用笔记大数据集群及组件启停
 学习笔记Flink—— Flink开发环境配置及运行实例(单词计数)