1、flink-conf.yaml
jobmanager.rpc.address: hadoop-160
# 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: 2
# 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://hadoop-160:8020/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: hadoop-160:2181,hadoop-161:2181,hadoop-162:2181
# 在zookeeper下的根目录
high-availability.zookeeper.path.root: /flink
# 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://hadoop-160:8020/flink/checkpoints
# Default target directory for savepoints, optional.
#
state.savepoints.dir: hdfs://hadoop-160:8020/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: 9081
# 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: 9100-9124
# 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: /data/flink/tmp
env.log.dir: /data/logs/flink
# 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
fs.hdfs.hadoopconf: /opt/module/hadoop/etc/hadoop
#==============================================================================
# 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://hadoop-160:8020/flink/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: 9082
# Comma separated list of directories to monitor for completed jobs.
historyserver.archive.fs.dir: hdfs://hadoop-160:8020/flink/completed-jobs/
# Interval in milliseconds for refreshing the monitored directories.
historyserver.archive.fs.refresh-interval: 10000
2、masters
hadoop-160:8081
3、workers
hadoop-161
hadoop-162
hadoop-163
4、zoo.cfg
server.1=hadoop-160:2888:3888
server.2=hadoop-161:2888:3888
server.3=hadoop-162:2888:3888
5、sql-client-defaults.yaml
# Define catalogs here.
catalogs:
- name: myhive
type: hive
hive-conf-dir: /opt/module/hive-3.1.2/conf
hive-version: 3.1.2
default-database: default
# Execution properties
#==============================================================================
# Properties that change the fundamental execution behavior of a table program.
execution:
# select the implementation responsible for planning table programs
# possible values are 'blink' (used by default) or 'old'
planner: blink
# 'batch' or 'streaming' execution
type: streaming
# allow 'event-time' or only 'processing-time' in sources
time-characteristic: event-time
# interval in ms for emitting periodic watermarks
periodic-watermarks-interval: 200
# 'changelog', 'table' or 'tableau' presentation of results
result-mode: table
# maximum number of maintained rows in 'table' presentation of results
max-table-result-rows: 100
# parallelism of the program
parallelism: 1
# maximum parallelism
max-parallelism: 128
# minimum idle state retention in ms
min-idle-state-retention: 0
# maximum idle state retention in ms
max-idle-state-retention: 0
# current catalog ('default_catalog' by default)
current-catalog: default_catalog
# current database of the current catalog (default database of the catalog by default)
current-database: default_database
# controls how table programs are restarted in case of a failures
restart-strategy:
# strategy type
# possible values are "fixed-delay", "failure-rate", "none", or "fallback" (default)
type: fallback
# Configuration options
#==============================================================================
# Configuration options for adjusting and tuning table programs.
# A full list of options and their default values can be found
# on the dedicated "Configuration" web page.
# A configuration can look like:
# configuration:
# table.exec.spill-compression.enabled: true
# table.exec.spill-compression.block-size: 128kb
# table.optimizer.join-reorder-enabled: true
configuration:
table.sql-dialect: hive
# Deployment properties
#==============================================================================
# Properties that describe the cluster to which table programs are submitted to.
deployment:
# general cluster communication timeout in ms
response-timeout: 5000
# (optional) address from cluster to gateway
gateway-address: ""
# (optional) port from cluster to gateway
gateway-port: 0
6、jar包
#添加jar包到lib目录
flink-connector-hive_2.11-1.11.3.jar
flink-connector-jdbc_2.11-1.11.3.jar
flink-shaded-hadoop-2-uber-2.8.3-7.0.jar
flink-sql-connector-hive-3.1.2_2.11-1.11.3.jar
hive-exec-3.1.2.jar
libfb303-0.9.3.jar
mysql-connector-java-5.1.47.jar
7、启停集群
bin/start-cluster.sh
bin/stop-cluster.sh
8、作业运行模式
- Session模式
#在Flink On Yarn
bin/yarn-session.sh -n 3 -s 3 -jm 1024 -tm 1024 -d
#提交任务
./bin/flink run -yid application_xxx_xxx ./examples/batch/WordCount.jar
- Per-job模式
./bin/flink run -m yarn-cluster -yjm 1024 -ytm 1024 ./examples/batch/WordCount.jar
- Application模式
bin/flink run-application -t yarn-application ./MyApplication.jar
#用于指定 JobManager 和 TaskManager 的内存大小的命令如下所示：
bin/flink run-application -t yarn-application \
-Djobmanager.memory.process.size=2048m \
-Dtaskmanager.memory.process.size=4096m \
./MyApplication.jar
#为了进一步节省将Flink发行版运送到群集的带宽，可以把 Flink 的发行版预上传到 YARN 可访问的位置，并使用 yarn.provided.lib.dirs配置选项，如下所示：
bin/flink run-application -t yarn-application \
-Djobmanager.memory.process.size=2048m \
-Dtaskmanager.memory.process.size=4096m \
-Dyarn.provided.lib.dirs="hdfs://myhdfs/remote-flink-dist-dir" \
./MyApplication.jar
#为了进一步节省提交应用程序 jar 所需的带宽，还可以将其预上传到 HDFS，并指定指向的远程路径， ./MyApplication.jar如下所示：
bin/flink run-application -t yarn-application \
-Djobmanager.memory.process.size=2048m \
-Dtaskmanager.memory.process.size=4096m \
-Dyarn.provided.lib.dirs="hdfs://myhdfs/remote-flink-dist-dir" \
hdfs://myhdfs/jars/MyApplication.jar
-t参数用来指定部署目标，目前支持YARN（yarn-application）和K8S（kubernetes-application）
-D参数则用来指定与作业相关的各项参数
9、Flink-SQL查询Hive数据
bin/sql-client.sh embedded
show catalogs;
use catalog myhive;
#现在就可以用hive的语法进行查询了
show databases;