1. Introduction to flink
Flink is an open source stream processing framework built for distributed, high-performance, ready-to-use, and accurate stream processing applications
2. Environment configuration
export JAVA_HOME=/usr/local/jdk1.8.0_391 export JRE_HOME=/usr/local/jdk1.8.0_391/jre export HBASE_HOME=/usr/local/bigdata/hbase-2.5.6 export HADOOP_HOME=/usr/local/bigdata/hadoop-3.3.6 export FLINK_HOME=/usr/local/bigdata/flink-1.18.0 export CLASSPATH=.:$JAVA_HOME/lib/dt.jar:$JAVA_HOME/lib/tools.jar:$JAR_HOME/lib export PATH=.:$JAVA_HOME/bin:$JRE_HOME/bin:$FLINK_HOME/bin:$HADOOP_HOME/bin:$HBASE_HOME/bin:$PYTHON_HOME/bin:$PATH
3. Prepare three servers
192.168.42.139 node1 192.168.42.140node2 192.168.42.141node3
4. Create logs and data under flink, and create zk and tmp under data.
5. Modify the flink-conf.yaml configuration file
############################################## ################################# # 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. ################################################ ############################## # These parameters are required for Java 17 support. # They can be safely removed when using Java 8/11. env.java.opts.all: --add-exports=java.base/sun.net.util=ALL-UNNAMED --add-exports=java.rmi/sun.rmi.registry=ALL-UNNAMED --add- exports=jdk.compiler/com.sun.tools.javac.api=ALL-UNNAMED --add-exports=jdk.compiler/com.sun.tools.javac.file=ALL-UNNAMED --add-exports=jdk. compiler/com.sun.tools.javac.parser=ALL-UNNAMED --add-exports=jdk.compiler/com.sun.tools.javac.tree=ALL-UNNAMED --add-exports=jdk.compiler/com. sun.tools.javac.util=ALL-UNNAMED --add-exports=java.security.jgss/sun.security.krb5=ALL-UNNAMED --add-opens=java.base/java.lang=ALL-UNNAMED - -add-opens=java.base/java.net=ALL-UNNAMED --add-opens=java.base/java.io=ALL-UNNAMED --add-opens=java.base/java.nio=ALL-UNNAMED --add-opens=java.base/sun.nio.ch=ALL-UNNAMED --add-opens=java.base/java.lang.reflect=ALL-UNNAMED --add-opens=java.base/java. text=ALL-UNNAMED --add-opens=java.base/java.time=ALL-UNNAMED --add-opens=java.base/java.util=ALL-UNNAMED --add-opens=java.base/java .util.concurrent=ALL-UNNAMED --add-opens=java.base/java.util.concurrent.atomic=ALL-UNNAMED --add-opens=java.base/java.util.concurrent.locks=ALL-UNNAMED #================================================== ============================= # 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 # automatically configure the host name based on the hostname of the node where the # JobManager runs. jobmanager.rpc.address: node1 # The RPC port where the JobManager is reachable. jobmanager.rpc.port: 6123 # The host interface the JobManager will bind to. By default, this is localhost, and will prevent # the JobManager from communicating outside the machine/container it is running on. # On YARN this setting will be ignored if it is set to 'localhost', defaulting to 0.0.0.0. # On Kubernetes this setting will be ignored, defaulting to 0.0.0.0. # # To enable this, set the bind-host address to one that has access to an outside facing network # interface, such as 0.0.0.0. jobmanager.bind-host: 0.0.0.0 # 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 host interface the TaskManager will bind to. By default, this is localhost, and will prevent # the TaskManager from communicating outside the machine/container it is running on. # On YARN this setting will be ignored if it is set to 'localhost', defaulting to 0.0.0.0. # On Kubernetes this setting will be ignored, defaulting to 0.0.0.0. # # To enable this, set the bind-host address to one that has access to an outside facing network # interface, such as 0.0.0.0. taskmanager.bind-host: 0.0.0.0 # The address of the host on which the TaskManager runs and can be reached by the JobManager and # other TaskManagers. If not specified, the TaskManager will try different strategies to identify # the address. # # Note this address needs to be reachable by the JobManager and forward traffic to one of # the interfaces the TaskManager is bound to (see 'taskmanager.bind-host'). # # Note also that unless all TaskManagers are running on the same machine, this address needs to be # configured separately for each TaskManager. taskmanager.host: node1 # 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 #================================================== ============================= #HighAvailability #================================================== ============================= # The high-availability mode. Possible options are 'NONE' or 'zookeeper'. # # high-availability.type: 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: node1:2181,node2:2181,node3:2181 # 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. Checkpointing is enabled when execution.checkpointing.interval > 0. # # Execution checkpointing related parameters. Please refer to CheckpointConfig and ExecutionCheckpointingOptions for more details. # # execution.checkpointing.interval: 3min # execution.checkpointing.externalized-checkpoint-retention: [DELETE_ON_CANCELLATION, RETAIN_ON_CANCELLATION] # execution.checkpointing.max-concurrent-checkpoints: 1 # execution.checkpointing.min-pause: 0 # execution.checkpointing.mode: [EXACTLY_ONCE, AT_LEAST_ONCE] # execution.checkpointing.timeout: 10min # execution.checkpointing.tolerable-failed-checkpoints: 0 # execution.checkpointing.unaligned: false # # Supported backends are 'hashmap', 'rocksdb', or the # <class-name-of-factory>. # # state.backend.type: hashmap # 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: node1 # 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 # By default, this is localhost, which prevents the REST & web server from # being able to communicate outside of the machine/container it is running on. # # To enable this, set the bind address to one that has access to outside-facing # network interface, such as 0.0.0.0. # 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 # Flag to specify whether job cancellation is enabled from the web-based # runtime monitor. Uncomment to disable. #web.cancel.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, 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 relevant for example # high-throughput RAIDs. # io.tmp.dirs: /usr/local/bigdata/flink-1.18.0/data/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:///completed-jobs/ # The address under which the web-based HistoryServer listens. #historyserver.web.address: 0.0.0.0 # The port under which the web-based HistoryServer listens. #historyserver.web.port: 8082 # Comma separated list of directories to monitor for completed jobs. #historyserver.archive.fs.dir: hdfs:///completed-jobs/ # Interval in milliseconds for refreshing the monitored directories. #historyserver.archive.fs.refresh-interval: 10000
6. Modify master
node1:8081
7. Modify workers
node1 node2 node3
8. Copy flink to other nodes, and modify taskmanager.host: node2, taskmanager.host: node3
9. Start flink
Starting cluster. [INFO] 1 instance(s) of standalonesession are already running on node1. Starting standalonesession daemon on host node1. [INFO] 1 instance(s) of taskexecutor are already running on node1. Starting taskexecutor daemon on host node1. [INFO] 1 instance(s) of taskexecutor are already running on node2. Starting taskexecutor daemon on host node2. [INFO] 1 instance(s) of taskexecutor are already running on node3. Starting taskexecutor daemon on host node3.
10. Visit flink
http://192.168.42.139:8081/
Execute tasks in flink
flink run /usr/local/bigdata/flink-1.18.0/examples/batch/WordCount.jar --input /usr/local/bigdata/words.txt
[root@node1 bigdata]# flink run /usr/local/bigdata/flink-1.18.0/examples/batch/WordCount.jar --input /usr/local/bigdata/words.txt Printing result to stdout. Use --output to specify output path. Job has been submitted with JobID 1c34e43b5dbdddc9023b4779e8d04bd3 Program execution finished Job with JobID 1c34e43b5dbdddc9023b4779e8d04bd3 has finished. Job runtime: 318 ms Accumulator Results: - 5457c3b30d7f7aa4a5778adeb8240a86 (java.util.ArrayList) [5 elements] (aaaaa,1) (flink,157) (hadoop,44) (link,19) (spark,107)
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