分布式调度框架。

7.2 KiB

Raw Blame History

Backend Deployment Document

There are two deployment modes for the backend:

automatic deployment
source code compile and then deployment

Preparations

Download the latest version of the installation package, download address： gitee download or github download, download escheduler-backend-x.x.x.tar.gz(back-end referred to as escheduler-backend),escheduler-ui-x.x.x.tar.gz(front-end referred to as escheduler-ui)

Preparations 1: Installation of basic software (self-installation of required items)

Mysql (5.5+) : Mandatory
JDK (1.8+) : Mandatory
ZooKeeper(3.4.6+) ：Mandatory
Hadoop(2.6+) ：Optionally, if you need to use the resource upload function, MapReduce task submission needs to configure Hadoop (uploaded resource files are currently stored on Hdfs)
Hive(1.2.1) : Optional, hive task submission needs to be installed
Spark(1.x,2.x) : Optional, Spark task submission needs to be installed
PostgreSQL(8.2.15+) : Optional, PostgreSQL PostgreSQL stored procedures need to be installed

 Note: Easy Scheduler itself does not rely on Hadoop, Hive, Spark, PostgreSQL, but only calls their Client to run the corresponding tasks.

Preparations 2: Create deployment users

Deployment users are created on all machines that require deployment scheduling, because the worker service executes jobs in sudo-u {linux-user}, so deployment users need sudo privileges and are confidential.

vi /etc/sudoers

# For example, the deployment user is an escheduler account
escheduler  ALL=(ALL)       NOPASSWD: NOPASSWD: ALL

# And you need to comment out the Default requiretty line
#Default requiretty

Preparations 3: SSH Secret-Free Configuration

Configure SSH secret-free login on deployment machines and other installation machines. If you want to install easyscheduler on deployment machines, you need to configure native password-free login itself.

Connect the host and other machines SSH

Preparations 4: database initialization

Create databases and accounts

Execute the following command to create database and account

CREATE DATABASE escheduler DEFAULT CHARACTER SET utf8 DEFAULT COLLATE utf8_general_ci;
GRANT ALL PRIVILEGES ON escheduler.* TO '{user}'@'%' IDENTIFIED BY '{password}';
GRANT ALL PRIVILEGES ON escheduler.* TO '{user}'@'localhost' IDENTIFIED BY '{password}';
flush privileges;

creates tables and imports basic data Modify the following attributes in ./conf/dao/data_source.properties
```
    spring.datasource.url
    spring.datasource.username
    spring.datasource.password
```
Execute scripts for creating tables and importing basic data
```
sh ./script/create_escheduler.sh
```

Preparations 5: Modify the deployment directory permissions and operation parameters

 instruction of escheduler-backend directory

bin : Basic service startup script
conf : Project Profile
lib : The project relies on jar packages, including individual module jars and third-party jars
script :  Cluster Start, Stop and Service Monitor Start and Stop scripts
sql : The project relies on SQL files
install.sh :  One-click deployment script

Modify permissions (please modify the 'deployUser' to the corresponding deployment user) so that the deployment user has operational privileges on the escheduler-backend directory

sudo chown -R deployUser:deployUser escheduler-backend
Modify the .escheduler_env.sh environment variable in the conf/env/directory
Modify deployment parameters (depending on your server and business situation):
Modify the parameters in install.sh to replace the values required by your business
- MonitorServerState switch variable, added in version 1.0.3, controls whether to start the self-start script (monitor master, worker status, if off-line will start automatically). The default value of "false" means that the self-start script is not started, and if it needs to start, it is changed to "true".
- 'hdfsStartupSate' switch variable controls whether to start hdfs The default value of "false" means not to start hdfs Change the variable to 'true' if you want to use hdfs, you also need to create the hdfs root path by yourself, that 'hdfsPath' in install.sh.
If you use hdfs-related functions, you need to copyhdfs-site.xml and core-site.xml to the conf directory

Deployment

Automated deployment is recommended, and experienced partners can use source deployment as well.

Automated Deployment

Install zookeeper tools

pip install kazoo
Switch to deployment user, one-click deployment

sh install.sh
Use the jps command to check if the services are started (jps comes from Java JDK)

    MasterServer         ----- Master Service
    WorkerServer         ----- Worker Service
    LoggerServer         ----- Logger Service
    ApiApplicationServer ----- API Service
    AlertServer          ----- Alert Service

If all services are normal, the automatic deployment is successful

After successful deployment, the log can be viewed and stored in a specified folder.

 logs/
    ├── escheduler-alert-server.log
    ├── escheduler-master-server.log
    |—— escheduler-worker-server.log
    |—— escheduler-api-server.log
    |—— escheduler-logger-server.log

Compile source code to deploy

After downloading the release version of the source package, unzip it into the root directory

Execute the compilation command：

 mvn -U clean package assembly:assembly -Dmaven.test.skip=true

View directory

After normal compilation, ./target/escheduler-{version}/ is generated in the current directory

Start-and-stop services commonly used in systems (for service purposes, please refer to System Architecture Design for details)

stop all services in the cluster

sh ./bin/stop_all.sh
start all services in the cluster

sh ./bin/start_all.sh
start and stop one master server

sh ./bin/escheduler-daemon.sh start master-server
sh ./bin/escheduler-daemon.sh stop master-server

start and stop one worker server

sh ./bin/escheduler-daemon.sh start worker-server
sh ./bin/escheduler-daemon.sh stop worker-server

start and stop api server

sh ./bin/escheduler-daemon.sh start api-server
sh ./bin/escheduler-daemon.sh stop api-server

start and stop logger server

sh ./bin/escheduler-daemon.sh start logger-server
sh ./bin/escheduler-daemon.sh stop logger-server

start and stop alert server

sh ./bin/escheduler-daemon.sh start alert-server
sh ./bin/escheduler-daemon.sh stop alert-server

Database Upgrade

Database upgrade is a function added in version 1.0.2. The database can be upgraded automatically by executing the following command:

sh ./script/upgrade_escheduler.sh

7.2 KiB Raw Blame History