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new 1c0f460 [Project called '任务空跑（前端）' for Li Junru_s20_220] (#181)
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commit 1c0f4609b2a7bc99bdc25cc3103eb1b78be5693c
Author: Winston9n78 <[email protected]>
AuthorDate: Wed Sep 30 22:28:04 2020 +0800
[Project called '任务空跑（前端）' for Li Junru_s20_220] (#181)
* Update docs1-3-1.js
* Add files via upload
---
docs/en-us/1.3.1/user_doc/architecture-design.md | 332 +++++++
docs/en-us/1.3.1/user_doc/configuration-file.md | 405 ++++++++
docs/en-us/1.3.1/user_doc/task-structure.md | 1136 ++++++++++++++++++++++
site_config/docs1-3-1.js | 12 +
4 files changed, 1885 insertions(+)
diff --git a/docs/en-us/1.3.1/user_doc/architecture-design.md
b/docs/en-us/1.3.1/user_doc/architecture-design.md
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+## System Architecture Design
+Before explaining the architecture of the scheduling system, let's first
understand the commonly used terms of the scheduling system
+
+### 1.Glossary
+**DAG：** The full name is Directed Acyclic Graph, referred to as DAG. Task
tasks in the workflow are assembled in the form of a directed acyclic graph,
and topological traversal is performed from nodes with zero degrees of entry
until there are no subsequent nodes. Examples are as follows:
+
+<p align="center">
+ <img src="/img/dag_examples_cn.jpg" alt="dag example" width="60%" />
+ <p align="center">
+ <em>dag example</em>
+ </p>
+</p>
+
+**Process definition**：Visualization formed by dragging task nodes and
establishing task node associations**DAG**
+
+**Process instance**：The process instance is the instantiation of the process
definition, which can be generated by manual start or scheduled scheduling.
Each time the process definition runs, a process instance is generated
+
+**Task instance**：The task instance is the instantiation of the task node in
the process definition, which identifies the specific task execution status
+
+**Task type**： Currently supports SHELL, SQL, SUB_PROCESS (sub-process),
PROCEDURE, MR, SPARK, PYTHON, DEPENDENT (depends), and plans to support dynamic
plug-in expansion, note: 其中子 **SUB_PROCESS** It is also a separate process
definition that can be started and executed separately
+
+**Scheduling method：** The system supports scheduled scheduling and manual
scheduling based on cron expressions. Command type support: start workflow,
start execution from current node, resume fault-tolerant workflow, resume pause
process, start execution from failed node, complement, timing, rerun, pause,
stop, resume waiting thread。Among them **Resume fault-tolerant workflow** 和
**Resume waiting thread** The two command types are used by the internal
control of scheduling, and cannot b [...]
+
+**Scheduled**：System adopts **quartz** distributed scheduler, and supports the
visual generation of cron expressions
+
+**Rely**：The system not only supports **DAG** simple dependencies between the
predecessor and successor nodes, but also provides **task dependent** nodes,
supporting **between processes**
+
+**Priority** ：Support the priority of process instances and task instances, if
the priority of process instances and task instances is not set, the default is
first-in first-out
+
+**Email alert**：Support **SQL task** Query result email sending, process
instance running result email alert and fault tolerance alert notification
+
+**Failure strategy**：For tasks running in parallel, if a task fails, two
failure strategy processing methods are provided. **Continue** refers to
regardless of the status of the task running in parallel until the end of the
process failure. **End** means that once a failed task is found, Kill will also
run the parallel task at the same time, and the process fails and ends
+
+**Complement**：Supplement historical data，Supports **interval parallel and
serial** two complement methods
+
+### 2.System Structure
+
+#### 2.1 System architecture diagram
+<p align="center">
+ <img src="/img/architecture-1.3.0.jpg" alt="System architecture diagram"
width="70%" />
+ <p align="center">
+ <em>System architecture diagram</em>
+ </p>
+</p>
+
+#### 2.2 Start process activity diagram
+<p align="center">
+ <img src="/img/process-start-flow-1.3.0.png" alt="Start process activity
diagram" width="70%" />
+ <p align="center">
+ <em>Start process activity diagram</em>
+ </p>
+</p>
+
+#### 2.3 Architecture description
+
+* **MasterServer**
+
+ MasterServer adopts a distributed and centerless design concept.
MasterServer is mainly responsible for DAG task segmentation, task submission
monitoring, and monitoring the health status of other MasterServer and
WorkerServer at the same time.
+ When the MasterServer service starts, register a temporary node with
Zookeeper, and perform fault tolerance by monitoring changes in the temporary
node of Zookeeper.
+ MasterServer provides monitoring services based on netty.
+
+ ##### The service mainly includes:
+
+ - **Distributed Quartz** distributed scheduling component, which is mainly
responsible for the start and stop operations of scheduled tasks. When Quartz
starts the task, there will be a thread pool inside the Master that is
specifically responsible for the follow-up operation of the processing task
+
+ - **MasterSchedulerThread** is a scanning thread that regularly scans the
**command** table in the database and performs different business operations
according to different **command types**
+
+ - **MasterExecThread** is mainly responsible for DAG task segmentation,
task submission monitoring, and logical processing of various command types
+
+ - **MasterTaskExecThread** is mainly responsible for the persistence of
tasks
+
+* **WorkerServer**
+
+ WorkerServer also adopts a distributed and decentralized design concept.
WorkerServer is mainly responsible for task execution and providing log
services.
+
+ When the WorkerServer service starts, register a temporary node with
Zookeeper and maintain a heartbeat.
+ Server provides monitoring services based on netty. Worker
+ ##### The service mainly includes:
+ - **Fetch TaskThread** is mainly responsible for continuously getting
tasks from **Task Queue**, and calling **TaskScheduleThread** corresponding
executor according to different task types.
+
+ - **LoggerServer** is an RPC service that provides functions such as log
fragment viewing, refreshing and downloading
+
+* **ZooKeeper**
+
+ ZooKeeper service, MasterServer and WorkerServer nodes in the system all
use ZooKeeper for cluster management and fault tolerance. In addition, the
system is based on ZooKeeper for event monitoring and distributed locks.
+
+ We have also implemented queues based on Redis, but we hope that
DolphinScheduler depends on as few components as possible, so we finally
removed the Redis implementation.
+
+* **Task Queue**
+
+ Provide task queue operation, the current queue is also implemented based
on Zookeeper. Because there is less information stored in the queue, there is
no need to worry about too much data in the queue. In fact, we have tested the
millions of data storage queues, which has no impact on system stability and
performance.
+
+* **Alert**
+
+ Provide alarm related interface, the interface mainly includes **alarm**
two types of alarm data storage, query and notification functions. Among them,
there are **email notification** and **SNMP (not yet implemented)**.
+
+* **API**
+
+ The API interface layer is mainly responsible for processing requests from
the front-end UI layer. The service uniformly provides RESTful APIs to provide
request services to the outside world. Interfaces include workflow creation,
definition, query, modification, release, logoff, manual start, stop, pause,
resume, start execution from the node and so on.
+
+* **UI**
+
+ The front-end page of the system provides various visual operation
interfaces of the system,See more at<a
href="/zh-cn/docs/user_doc/system-manual.html" target="_self"> System User
Manual </a>section。
+
+#### 2.3 Architecture design ideas
+
+##### One、Decentralization VS centralization
+
+###### Centralized thinking
+
+The centralized design concept is relatively simple. The nodes in the
distributed cluster are divided into roles according to roles, which are
roughly divided into two roles:
+<p align="center">
+ <img
src="https://analysys.github.io/easyscheduler_docs_cn/images/master_slave.png";
alt="master-slave character" width="50%" />
+ </p>
+
+- The role of the master is mainly responsible for task distribution and
monitoring the health status of the slave, and can dynamically balance the task
to the slave, so that the slave node will not be in a "busy dead" or "idle
dead" state.
+- The role of Worker is mainly responsible for task execution and maintenance
and Master's heartbeat, so that Master can assign tasks to Slave.
+
+
+
+Problems in centralized thought design:
+
+- Once there is a problem with the Master, the dragons are headless and the
entire cluster will collapse. In order to solve this problem, most of the
Master/Slave architecture models adopt the design scheme of active and standby
Master, which can be hot standby or cold standby, or automatic switching or
manual switching, and more and more new systems are beginning to have The
ability to automatically elect and switch Master to improve the availability of
the system.
+- Another problem is that if the Scheduler is on the Master, although it can
support different tasks in a DAG running on different machines, it will cause
the Master to be overloaded. If the Scheduler is on the slave, all tasks in a
DAG can only submit jobs on a certain machine. When there are more parallel
tasks, the pressure on the slave may be greater.
+
+
+
+###### Decentralized
+ <p align="center"
+ <img
src="https://analysys.github.io/easyscheduler_docs_cn/images/decentralization.png";
alt="Decentralization" width="50%" />
+ </p>
+
+- In the decentralized design, there is usually no concept of Master/Slave,
all roles are the same, the status is equal, the global Internet is a typical
decentralized distributed system, any node equipment connected to the network
is down, All will only affect a small range of functions.
+- The core design of decentralized design is that there is no "manager"
different from other nodes in the entire distributed system, so there is no
single point of failure. However, because there is no "manager" node, each node
needs to communicate with other nodes to obtain the necessary machine
information, and the unreliability of distributed system communication greatly
increases the difficulty of implementing the above functions.
+- In fact, truly decentralized distributed systems are rare. Instead, dynamic
centralized distributed systems are constantly pouring out. Under this
architecture, the managers in the cluster are dynamically selected, rather than
preset, and when the cluster fails, the nodes of the cluster will automatically
hold "meetings" to elect new "managers" To preside over the work. The most
typical case is Etcd implemented by ZooKeeper and Go language.
+
+
+
+- The decentralization of DolphinScheduler is that the Master/Worker is
registered in Zookeeper, and the Master cluster and Worker cluster are
centerless, and the Zookeeper distributed lock is used to elect one of the
Master or Worker as the "manager" to perform the task.
+
+##### Two、Distributed lock practice
+
+DolphinScheduler uses ZooKeeper distributed lock to realize that only one
Master executes Scheduler at the same time, or only one Worker executes the
submission of tasks.
+1. The core process algorithm for acquiring distributed locks is as follows:
+ <p align="center">
+ <img
src="https://analysys.github.io/easyscheduler_docs_cn/images/distributed_lock.png";
alt="Obtain distributed lock process" width="50%" />
+ </p>
+
+2. Flow chart of implementation of Scheduler thread distributed lock in
DolphinScheduler:
+ <p align="center">
+ <img src="/img/distributed_lock_procss.png" alt="Obtain distributed lock
process" width="50%" />
+ </p>
+
+
+##### Three、Insufficient thread loop waiting problem
+
+- If there is no sub-process in a DAG, if the number of data in the Command
is greater than the threshold set by the thread pool, the process directly
waits or fails.
+- If many sub-processes are nested in a large DAG, the following figure will
produce a "dead" state:
+
+ <p align="center">
+ <img
src="https://analysys.github.io/easyscheduler_docs_cn/images/lack_thread.png";
alt="Insufficient threads waiting loop problem" width="50%" />
+ </p>
+In the above figure, MainFlowThread waits for the end of SubFlowThread1,
SubFlowThread1 waits for the end of SubFlowThread2, SubFlowThread2 waits for
the end of SubFlowThread3, and SubFlowThread3 waits for a new thread in the
thread pool, then the entire DAG process cannot end, so that the threads cannot
be released. In this way, the state of the child-parent process loop waiting is
formed. At this time, unless a new Master is started to add threads to break
such a "stalemate", the sched [...]
+
+It seems a bit unsatisfactory to start a new Master to break the deadlock, so
we proposed the following three solutions to reduce this risk:
+
+1. Calculate the sum of all Master threads, and then calculate the number of
threads required for each DAG, that is, pre-calculate before the DAG process is
executed. Because it is a multi-master thread pool, the total number of threads
is unlikely to be obtained in real time.
+2. Judge the single-master thread pool. If the thread pool is full, let the
thread fail directly.
+3. Add a Command type with insufficient resources. If the thread pool is
insufficient, suspend the main process. In this way, there are new threads in
the thread pool, which can make the process suspended by insufficient resources
wake up to execute again.
+
+note：The Master Scheduler thread is executed by FIFO when acquiring the
Command.
+
+So we chose the third way to solve the problem of insufficient threads.
+
+
+##### Four、Fault-tolerant design
+Fault tolerance is divided into service downtime fault tolerance and task
retry, and service downtime fault tolerance is divided into master fault
tolerance and worker fault tolerance.
+
+###### 1. Downtime fault tolerance
+
+The service fault-tolerance design relies on ZooKeeper's Watcher mechanism,
and the implementation principle is shown in the figure:
+
+ <p align="center">
+ <img
src="https://analysys.github.io/easyscheduler_docs_cn/images/fault-tolerant.png";
alt="DolphinScheduler fault-tolerant design" width="40%" />
+ </p>
+Among them, the Master monitors the directories of other Masters and Workers.
If the remove event is heard, fault tolerance of the process instance or task
instance will be performed according to the specific business logic.
+
+
+
+- Master fault tolerance flowchart：
+
+ <p align="center">
+ <img
src="https://analysys.github.io/easyscheduler_docs_cn/images/fault-tolerant_master.png";
alt="Master fault tolerance flowchart" width="40%" />
+ </p>
+After the fault tolerance of ZooKeeper Master is completed, it is re-scheduled
by the Scheduler thread in DolphinScheduler, traverses the DAG to find the
"running" and "submit successful" tasks, monitors the status of its task
instances for the "running" tasks, and "commits successful" tasks It is
necessary to determine whether the task queue already exists. If it exists, the
status of the task instance is also monitored. If it does not exist, resubmit
the task instance.
+
+
+
+- Worker fault tolerance flowchart：
+
+ <p align="center">
+ <img
src="https://analysys.github.io/easyscheduler_docs_cn/images/fault-tolerant_worker.png";
alt="Worker fault tolerance flow chart" width="40%" />
+ </p>
+
+Once the Master Scheduler thread finds that the task instance is in the "fault
tolerant" state, it takes over the task and resubmits it.
+
+ Note: Due to "network jitter", the node may lose its heartbeat with ZooKeeper
in a short period of time, and the node's remove event may occur. For this
situation, we use the simplest way, that is, once the node and ZooKeeper
timeout connection occurs, then directly stop the Master or Worker service.
+
+###### 2.Task failed and try again
+
+Here we must first distinguish the concepts of task failure retry, process
failure recovery, and process failure rerun:
+
+- Task failure retry is at the task level and is automatically performed by
the scheduling system. For example, if a Shell task is set to retry for 3
times, it will try to run it again up to 3 times after the Shell task fails.
+- Process failure recovery is at the process level and is performed manually.
Recovery can only be performed **from the failed node** or **from the current
node**
+- Process failure rerun is also at the process level and is performed
manually, rerun is performed from the start node
+
+
+
+Next to the topic, we divide the task nodes in the workflow into two types.
+
+- One is a business node, which corresponds to an actual script or processing
statement, such as Shell node, MR node, Spark node, and dependent node.
+
+- There is also a logical node, which does not do actual script or statement
processing, but only logical processing of the entire process flow, such as
sub-process sections.
+
+Each **business node** can be configured with the number of failed retries.
When the task node fails, it will automatically retry until it succeeds or
exceeds the configured number of retries. **Logical node** Failure retry is not
supported. But the tasks in the logical node support retry.
+
+If there is a task failure in the workflow that reaches the maximum number of
retries, the workflow will fail to stop, and the failed workflow can be
manually rerun or process recovery operation
+
+
+
+##### Five、Task priority design
+In the early scheduling design, if there is no priority design and the fair
scheduling design is used, the task submitted first may be completed at the
same time as the task submitted later, and the process or task priority cannot
be set, so We have redesigned this, and our current design is as follows:
+
+- According to **priority of different process instances** priority over
**priority of the same process instance** priority over **priority of tasks
within the same process**priority over **tasks within the same
process**submission order from high to Low task processing.
+ - The specific implementation is to parse the priority according to the
json of the task instance, and then save the **process instance
priority_process instance id_task priority_task id** information in the
ZooKeeper task queue, when obtained from the task queue, pass String comparison
can get the tasks that need to be executed first
+
+ - The priority of the process definition is to consider that some
processes need to be processed before other processes. This can be configured
when the process is started or scheduled to start. There are 5 levels in total,
which are HIGHEST, HIGH, MEDIUM, LOW, and LOWEST. As shown below
+ <p align="center">
+ <img
src="https://analysys.github.io/easyscheduler_docs_cn/images/process_priority.png";
alt="Process priority configuration" width="40%" />
+ </p>
+
+ - The priority of the task is also divided into 5 levels, followed by
HIGHEST, HIGH, MEDIUM, LOW, LOWEST. As shown below
+ <p align="center">
+ <img
src="https://analysys.github.io/easyscheduler_docs_cn/images/task_priority.png";
alt="Task priority configuration" width="35%" />
+ </p>
+
+
+##### Six、Logback and netty implement log access
+
+- Since Web (UI) and Worker are not necessarily on the same machine, viewing
the log cannot be like querying a local file. There are two options:
+ - Put logs on ES search engine
+ - Obtain remote log information through netty communication
+
+- In consideration of the lightness of DolphinScheduler as much as possible,
so I chose gRPC to achieve remote access to log information.
+
+ <p align="center">
+ <img src="https://analysys.github.io/easyscheduler_docs_cn/images/grpc.png";
alt="grpc remote access" width="50%" />
+ </p>
+
+
+- We use the FileAppender and Filter functions of the custom Logback to
realize that each task instance generates a log file.
+- FileAppender is mainly implemented as follows：
+
+ ```java
+ /**
+ * task log appender
+ */
+ public class TaskLogAppender extends FileAppender<ILoggingEvent {
+
+ ...
+
+ @Override
+ protected void append(ILoggingEvent event) {
+
+ if (currentlyActiveFile == null){
+ currentlyActiveFile = getFile();
+ }
+ String activeFile = currentlyActiveFile;
+ // thread name：
taskThreadName-processDefineId_processInstanceId_taskInstanceId
+ String threadName = event.getThreadName();
+ String[] threadNameArr = threadName.split("-");
+ // logId = processDefineId_processInstanceId_taskInstanceId
+ String logId = threadNameArr[1];
+ ...
+ super.subAppend(event);
+ }
+}
+ ```
+
+
+Generate logs in the form of /process definition id/process instance id/task
instance id.log
+
+- Filter to match the thread name starting with TaskLogInfo:
+
+- TaskLogFilter is implemented as follows：
+
+ ```java
+ /**
+ * task log filter
+ */
+public class TaskLogFilter extends Filter<ILoggingEvent {
+
+ @Override
+ public FilterReply decide(ILoggingEvent event) {
+ if (event.getThreadName().startsWith("TaskLogInfo-")){
+ return FilterReply.ACCEPT;
+ }
+ return FilterReply.DENY;
+ }
+}
+ ```
+
+### 3.Module introduction
+- dolphinscheduler-alert alarm module, providing AlertServer service.
+
+- dolphinscheduler-api web application module, providing ApiServer service.
+
+- dolphinscheduler-common General constant enumeration, utility class, data
structure or base class
+
+- dolphinscheduler-dao provides operations such as database access.
+
+- dolphinscheduler-remote client and server based on netty
+
+- dolphinscheduler-server MasterServer and WorkerServer services
+
+- dolphinscheduler-service service module, including Quartz, Zookeeper, log
client access service, easy to call server module and api module
+
+- dolphinscheduler-ui front-end module
+### Sum up
+From the perspective of scheduling, this article preliminarily introduces the
architecture principles and implementation ideas of the big data distributed
workflow scheduling system-DolphinScheduler. To be continued
+
+
diff --git a/docs/en-us/1.3.1/user_doc/configuration-file.md
b/docs/en-us/1.3.1/user_doc/configuration-file.md
new file mode 100644
index 0000000..7c5bb2e
--- /dev/null
+++ b/docs/en-us/1.3.1/user_doc/configuration-file.md
@@ -0,0 +1,405 @@
+# Foreword
+This document is a description of the dolphinscheduler configuration file, and
the version is for dolphinscheduler-1.3.x.
+
+# Directory Structure
+All configuration files of dolphinscheduler are currently in the [conf]
directory.
+
+For a more intuitive understanding of the location of the [conf] directory and
the configuration files it contains, please see the simplified description of
the dolphinscheduler installation directory below.
+
+This article mainly talks about the configuration file of dolphinscheduler. I
won't go into details in other parts.
+
+[Note: The following dolphinscheduler is referred to as DS.]
+```
+
+├─bin DS command storage directory
+│ ├─dolphinscheduler-daemon.sh Activate/deactivate DS service script
+│ ├─start-all.sh Start all DS services according to the
configuration file
+│ ├─stop-all.sh Close all DS services according to the
configuration file
+├─conf Configuration file directory
+│ ├─application-api.properties api service configuration file
+│ ├─datasource.properties Database configuration file
+│ ├─zookeeper.properties zookeeper configuration file
+│ ├─master.properties Master service configuration file
+│ ├─worker.properties Worker service configuration file
+│ ├─quartz.properties Quartz service configuration file
+│ ├─common.properties Public service [storage] configuration
file
+│ ├─alert.properties alert service configuration file
+│ ├─config Environment variable configuration
folder
+│ ├─install_config.conf DS environment variable
configuration script [for DS installation/startup]
+│ ├─env Run script environment variable
configuration directory
+│ ├─dolphinscheduler_env.sh Run the script to load the
environment variable configuration file [such as: JAVA_HOME, HADOOP_HOME,
HIVE_HOME ...]
+│ ├─org mybatis mapper file directory
+│ ├─i18n i18n configuration file directory
+│ ├─logback-api.xml api service log configuration file
+│ ├─logback-master.xml Master service log configuration file
+│ ├─logback-worker.xml Worker service log configuration file
+│ ├─logback-alert.xml alert service log configuration file
+├─sql DS metadata creation and upgrade sql file
+│ ├─create Create SQL script directory
+│ ├─upgrade Upgrade SQL script directory
+│ ├─dolphinscheduler-postgre.sql Postgre database initialization script
+│ ├─dolphinscheduler_mysql.sql mysql database initialization version
+│ ├─soft_version Current DS version identification file
+├─script DS service deployment, database
creation/upgrade script directory
+│ ├─create-dolphinscheduler.sh DS database initialization script
+│ ├─upgrade-dolphinscheduler.sh DS database upgrade script
+│ ├─monitor-server.sh DS service monitoring startup script
+│ ├─scp-hosts.sh Install file transfer script
+│ ├─remove-zk-node.sh Clean Zookeeper cache file script
+├─ui Front-end WEB resource directory
+├─lib DS dependent jar storage directory
+├─install.sh Automatically install DS service script
+
+
+```
+
+
+# Detailed configuration file
+
+Serial number| Service classification | Configuration file|
+|--|--|--|
+1|Activate/deactivate DS service script|dolphinscheduler-daemon.sh
+2|Database connection configuration | datasource.properties
+3|Zookeeper connection configuration|zookeeper.properties
+4|Common [storage] configuration|common.properties
+5|API service configuration|application-api.properties
+6|Master service configuration|master.properties
+7|Worker service configuration|worker.properties
+8|Alert service configuration|alert.properties
+9|Quartz configuration|quartz.properties
+10|DS environment variable configuration script [for DS
installation/startup]|install_config.conf
+11|Run the script to load the environment variable configuration file <br
/>[for example: JAVA_HOME,HADOOP_HOME, HIVE_HOME ...|dolphinscheduler_env.sh
+12|Service log configuration files|api service log configuration file :
logback-api.xml <br /> Master service log configuration file :
logback-master.xml <br /> Worker service log configuration file :
logback-worker.xml <br /> alertService log configuration file :
logback-alert.xml
+
+
+## 1.dolphinscheduler-daemon.sh [Activate/deactivate DS service script]
+The dolphinscheduler-daemon.sh script is responsible for DS startup & shutdown
+start-all.sh/stop-all.sh eventually starts and shuts down the cluster through
dolphinscheduler-daemon.sh.
+At present, DS has only made a basic setting. Please set the JVM parameters
according to the actual situation of their resources.
+
+The default simplified parameters are as follows:
+```bash
+export DOLPHINSCHEDULER_OPTS="
+-server
+-Xmx16g
+-Xms1g
+-Xss512k
+-XX:+UseConcMarkSweepGC
+-XX:+CMSParallelRemarkEnabled
+-XX:+UseFastAccessorMethods
+-XX:+UseCMSInitiatingOccupancyOnly
+-XX:CMSInitiatingOccupancyFraction=70
+"
+```
+
+> It is not recommended to set "-XX:DisableExplicitGC", DS uses Netty for
communication. Setting this parameter may cause memory leaks.
+
+## 2.datasource.properties [Database Connectivity]
+Use Druid to manage the database connection in DS.The default simplified
configuration is as follows.
+|Parameter | Defaults| Description|
+|--|--|--|
+spring.datasource.driver-class-name| |Database driver
+spring.datasource.url||Database connection address
+spring.datasource.username||Database username
+spring.datasource.password||Database password
+spring.datasource.initialSize|5| Number of initial connection pools
+spring.datasource.minIdle|5| Minimum number of connection pools
+spring.datasource.maxActive|5| Maximum number of connection pools
+spring.datasource.maxWait|60000| Maximum waiting time
+spring.datasource.timeBetweenEvictionRunsMillis|60000| Connection detection
cycle
+spring.datasource.timeBetweenConnectErrorMillis|60000| Retry interval
+spring.datasource.minEvictableIdleTimeMillis|300000| The minimum time a
connection remains idle without being evicted
+spring.datasource.validationQuery|SELECT 1|SQL to check whether the connection
is valid
+spring.datasource.validationQueryTimeout|3| Timeout to check if the connection
is valid[seconds]
+spring.datasource.testWhileIdle|true| Check when applying for connection, if
idle time is greater than timeBetweenEvictionRunsMillis，Run validationQuery to
check whether the connection is valid.
+spring.datasource.testOnBorrow|true| Execute validationQuery to check whether
the connection is valid when applying for connection
+spring.datasource.testOnReturn|false| When returning the connection, execute
validationQuery to check whether the connection is valid
+spring.datasource.defaultAutoCommit|true| Whether to enable automatic
submission
+spring.datasource.keepAlive|true| For connections within the minIdle number in
the connection pool, if the idle time exceeds minEvictableIdleTimeMillis, the
keepAlive operation will be performed.
+spring.datasource.poolPreparedStatements|true| Open PSCache
+spring.datasource.maxPoolPreparedStatementPerConnectionSize|20| To enable
PSCache, you must configure greater than 0, when greater than
0,PoolPreparedStatements automatically trigger modification to true.
+
+
+## 3.zookeeper.properties [Zookeeper connection configuration]
+|Parameter |Defaults| Description|
+|--|--|--|
+zookeeper.quorum|localhost:2181| zk cluster connection information
+zookeeper.dolphinscheduler.root|/dolphinscheduler| DS stores root directory in
zookeeper
+zookeeper.session.timeout|60000| session time out
+zookeeper.connection.timeout|30000| Connection timed out
+zookeeper.retry.base.sleep|100| Basic retry time difference
+zookeeper.retry.max.sleep|30000| Maximum retry time
+zookeeper.retry.maxtime|10|Maximum number of retries
+
+
+## 4.common.properties [hadoop, s3, yarn configuration]
+The common.properties configuration file is currently mainly used to configure
hadoop/s3a related configurations.
+|Parameter |Defaults| Description|
+|--|--|--|
+resource.storage.type|NONE|Resource file storage type: HDFS,S3,NONE
+resource.upload.path|/dolphinscheduler|Resource file storage path
+data.basedir.path|/tmp/dolphinscheduler|Local working directory for storing
temporary files
+hadoop.security.authentication.startup.state|false|hadoop enable kerberos
permission
+java.security.krb5.conf.path|/opt/krb5.conf|kerberos configuration directory
+login.user.keytab.username|[email protected]|kerberos login user
+login.user.keytab.path|/opt/hdfs.headless.keytab|kerberos login user keytab
+resource.view.suffixs| txt,log,sh,conf,cfg,py,java,sql,hql,xml,properties|File
formats supported by the resource center
+hdfs.root.user|hdfs|If the storage type is HDFS, you need to configure users
with corresponding operation permissions
+fs.defaultFS|hdfs://mycluster:8020|Request address if resource.storage.type=S3
,the value is similar to: s3a://dolphinscheduler. If
resource.storage.type=HDFS, If hadoop configured HA, you need to copy the
core-site.xml and hdfs-site.xml files to the conf directory
+fs.s3a.endpoint||s3 endpoint address
+fs.s3a.access.key||s3 access key
+fs.s3a.secret.key| |s3 secret key
+yarn.resourcemanager.ha.rm.ids| |yarn resourcemanager address, If the
resourcemanager has HA turned on, enter the IP address of the HA (separated by
commas). If the resourcemanager is a single node, the value can be empty.
+yarn.application.status.address|http://ds1:8088/ws/v1/cluster/apps/%s|If
resourcemanager has HA enabled or resourcemanager is not used, keep the default
value. If resourcemanager is a single node, you need to configure ds1 as the
hostname corresponding to resourcemanager
+dolphinscheduler.env.path|env/dolphinscheduler_env.sh|Run the script to load
the environment variable configuration file [eg: JAVA_HOME, HADOOP_HOME,
HIVE_HOME ...]
+development.state|false|Is it in development mode
+kerberos.expire.time|7|kerberos expiration time [hour]
+
+
+## 5.application-api.properties [API service configuration]
+|Parameter |Defaults| Description|
+|--|--|--|
+server.port|12345|API service communication port
+server.servlet.session.timeout|7200|session timeout
+server.servlet.context-path|/dolphinscheduler |Request path
+spring.servlet.multipart.max-file-size|1024MB|Maximum upload file size
+spring.servlet.multipart.max-request-size|1024MB|Maximum request size
+server.jetty.max-http-post-size|5000000|Jetty service maximum send request size
+spring.messages.encoding|UTF-8|Request encoding
+spring.jackson.time-zone|GMT+8|Set time zone
+spring.messages.basename|i18n/messages|i18n configuration
+security.authentication.type|PASSWORD|Permission verification type
+
+
+## 6.master.properties [Master service configuration]
+|Parameter |Defaults| Description|
+|--|--|--|
+master.listen.port|5678|master communication port
+master.exec.threads|100| Number of worker threads
+master.exec.task.num|20|Number of parallel tasks
+master.dispatch.task.num | 3|Number of distribution tasks
+master.heartbeat.interval|10|Heartbeat interval
+master.task.commit.retryTimes|5|Number of task retries
+master.task.commit.interval|1000|Task submission interval
+master.max.cpuload.avg|-1|When the CPU is less than this configuration, the
master service can work. The default value is -1 : cpu cores * 2
+master.reserved.memory|0.3|Memory threshold limit, the available memory is
greater than this value, the master service can work.
+
+
+## 7.worker.properties [Worker service configuration]
+|Parameter |Defaults| Description|
+|--|--|--|
+worker.listen.port|1234|worker communication port
+worker.exec.threads|100|Number of worker threads
+worker.heartbeat.interval|10|Heartbeat interval
+worker.max.cpuload.avg|-1|When the CPU is less than this configuration, the
worker service can work. The default value is -1 : cpu cores * 2
+worker.reserved.memory|0.3|Memory threshold limit, the available memory is
greater than this value, the worker service can work.
+worker.group|default|Workgroup grouping configuration. <br> When the worker
starts, it will automatically join the corresponding group according to the
configuration.
+
+
+## 8.alert.properties [Alert alert service configuration]
+|Parameter |Defaults| Description|
+|--|--|--|
+alert.type|EMAIL|Alarm type|
+mail.protocol|SMTP| Mail server protocol
+mail.server.host|xxx.xxx.com|Mail server address
+mail.server.port|25|Mail server port
+mail.sender|[email protected]|Sender mailbox
+mail.user|[email protected]|Sender's email name
+mail.passwd|111111|Sender email password
+mail.smtp.starttls.enable|true|Whether the mailbox opens tls
+mail.smtp.ssl.enable|false|Whether the mailbox opens ssl
+mail.smtp.ssl.trust|xxx.xxx.com|Email ssl whitelist
+xls.file.path|/tmp/xls|Temporary working directory for mailbox attachments
+||The following is the enterprise WeChat configuration[Optional]|
+enterprise.wechat.enable|false|Whether the enterprise WeChat is enabled
+enterprise.wechat.corp.id|xxxxxxx|
+enterprise.wechat.secret|xxxxxxx|
+enterprise.wechat.agent.id|xxxxxxx|
+enterprise.wechat.users|xxxxxxx|
+enterprise.wechat.token.url|https://qyapi.weixin.qq.com/cgi-bin/gettoken? <br
/> corpid=$corpId&corpsecret=$secret|
+enterprise.wechat.push.url|https://qyapi.weixin.qq.com/cgi-bin/message/send?
<br /> access_token=$token|
+enterprise.wechat.user.send.msg||Send message format
+enterprise.wechat.team.send.msg||Group message format
+plugin.dir|/Users/xx/your/path/to/plugin/dir|Plugin directory
+
+
+## 9.quartz.properties [Quartz configuration]
+This is mainly quartz configuration, please configure it in combination with
actual business scenarios & resources, this article will not be expanded for
the time being.
+|Parameter |Defaults| Description|
+|--|--|--|
+org.quartz.jobStore.driverDelegateClass |
org.quartz.impl.jdbcjobstore.StdJDBCDelegate
+org.quartz.jobStore.driverDelegateClass |
org.quartz.impl.jdbcjobstore.PostgreSQLDelegate
+org.quartz.scheduler.instanceName | DolphinScheduler
+org.quartz.scheduler.instanceId | AUTO
+org.quartz.scheduler.makeSchedulerThreadDaemon | true
+org.quartz.jobStore.useProperties | false
+org.quartz.threadPool.class | org.quartz.simpl.SimpleThreadPool
+org.quartz.threadPool.makeThreadsDaemons | true
+org.quartz.threadPool.threadCount | 25
+org.quartz.threadPool.threadPriority | 5
+org.quartz.jobStore.class | org.quartz.impl.jdbcjobstore.JobStoreTX
+org.quartz.jobStore.tablePrefix | QRTZ_
+org.quartz.jobStore.isClustered | true
+org.quartz.jobStore.misfireThreshold | 60000
+org.quartz.jobStore.clusterCheckinInterval | 5000
+org.quartz.jobStore.acquireTriggersWithinLock|true
+org.quartz.jobStore.dataSource | myDs
+org.quartz.dataSource.myDs.connectionProvider.class |
org.apache.dolphinscheduler.service.quartz.DruidConnectionProvider
+
+
+## 10.install_config.conf [DS environment variable configuration script [for
DS installation/startup]]
+The install_config.conf configuration file is more cumbersome.This file is
mainly used in two places.
+* 1.Automatic installation of DS cluster.
+
+> Calling the install.sh script will automatically load the configuration in
this file, and automatically configure the content in the above configuration
file according to the content in this file.
+> Such
as::dolphinscheduler-daemon.sh、datasource.properties、zookeeper.properties、common.properties、application-api.properties、master.properties、worker.properties、alert.properties、quartz.properties
Etc..
+
+
+* 2.DS cluster startup and shutdown.
+>When the DS cluster is started up and shut down, it will load the masters,
workers, alertServer, apiServers and other parameters in the configuration file
to start/close the DS cluster.
+
+The contents of the file are as follows:
+```bash
+
+# Note: If the configuration file contains special characters,such as:
`.*[]^${}\+?|()@#&`, Please escape,
+# Examples: `[` Escape to `\[`
+
+# Database type, currently only supports postgresql or mysql
+dbtype="mysql"
+
+# Database address & port
+dbhost="192.168.xx.xx:3306"
+
+# Database Name
+dbname="dolphinscheduler"
+
+
+# Database Username
+username="xx"
+
+# Database Password
+password="xx"
+
+# Zookeeper address
+zkQuorum="192.168.xx.xx:2181,192.168.xx.xx:2181,192.168.xx.xx:2181"
+
+# Where to install DS, such as: /data1_1T/dolphinscheduler，
+installPath="/data1_1T/dolphinscheduler"
+
+# Which user to use for deployment
+# Note: The deployment user needs sudo permissions and can operate hdfs.
+# If you use hdfs, the root directory must be created by the user.
Otherwise, there will be permissions related issues.
+deployUser="dolphinscheduler"
+
+
+# The following is the alarm service configuration
+# Mail server address
+mailServerHost="smtp.exmail.qq.com"
+
+# Mail Server Port
+mailServerPort="25"
+
+# Sender
+mailSender="xxxxxxxxxx"
+
+# Sending user
+mailUser="xxxxxxxxxx"
+
+# email Password
+mailPassword="xxxxxxxxxx"
+
+# TLS protocol mailbox is set to true, otherwise set to false
+starttlsEnable="true"
+
+# The mailbox with SSL protocol enabled is set to true, otherwise it is false.
Note: starttlsEnable and sslEnable cannot be true at the same time
+sslEnable="false"
+
+# Mail service address value, same as mailServerHost
+sslTrust="smtp.exmail.qq.com"
+
+#Where to upload resource files such as sql used for business, you can set:
HDFS, S3, NONE. If you want to upload to HDFS, please configure as HDFS; if you
do not need the resource upload function, please select NONE.
+resourceStorageType="NONE"
+
+# if S3，write S3 address，HA，for example ：s3a://dolphinscheduler，
+# Note，s3 be sure to create the root directory /dolphinscheduler
+defaultFS="hdfs://mycluster:8020"
+
+# If the resourceStorageType is S3, the parameters to be configured are as
follows:
+s3Endpoint="http://192.168.xx.xx:9010";
+s3AccessKey="xxxxxxxxxx"
+s3SecretKey="xxxxxxxxxx"
+
+# If the ResourceManager is HA, configure it as the primary and secondary ip
or hostname of the ResourceManager node, such as "192.168.xx.xx,
192.168.xx.xx", otherwise if it is a single ResourceManager or yarn is not used
at all, please configure yarnHaIps="" That’s it, if yarn is not used, configure
it as ""
+yarnHaIps="192.168.xx.xx,192.168.xx.xx"
+
+# If it is a single ResourceManager, configure it as the ResourceManager node
ip or host name, otherwise keep the default value.
+singleYarnIp="yarnIp1"
+
+# The storage path of resource files in HDFS/S3
+resourceUploadPath="/dolphinscheduler"
+
+
+# HDFS/S3 Operating user
+hdfsRootUser="hdfs"
+
+# The following is the kerberos configuration
+
+# Whether kerberos is turned on
+kerberosStartUp="false"
+# kdc krb5 config file path
+krb5ConfPath="$installPath/conf/krb5.conf"
+# keytab username
+keytabUserName="[email protected]"
+# username keytab path
+keytabPath="$installPath/conf/hdfs.headless.keytab"
+
+
+# api service port
+apiServerPort="12345"
+
+
+# Hostname of all hosts where DS is deployed
+ips="ds1,ds2,ds3,ds4,ds5"
+
+# ssh port, default 22
+sshPort="22"
+
+# Deploy master service host
+masters="ds1,ds2"
+
+# The host where the worker service is deployed
+# Note: Each worker needs to set a worker group name, the default value is
"default"
+workers="ds1:default,ds2:default,ds3:default,ds4:default,ds5:default"
+
+# Deploy the alert service host
+alertServer="ds3"
+
+# Deploy api service host
+apiServers="ds1"
+```
+
+## 11.dolphinscheduler_env.sh [Environment variable configuration]
+When submitting a task through a shell-like method, the environment variables
in the configuration file are loaded into the host.
+The types of tasks involved are: Shell tasks, Python tasks, Spark tasks, Flink
tasks, Datax tasks, etc.
+```bash
+export HADOOP_HOME=/opt/soft/hadoop
+export HADOOP_CONF_DIR=/opt/soft/hadoop/etc/hadoop
+export SPARK_HOME1=/opt/soft/spark1
+export SPARK_HOME2=/opt/soft/spark2
+export PYTHON_HOME=/opt/soft/python
+export JAVA_HOME=/opt/soft/java
+export HIVE_HOME=/opt/soft/hive
+export FLINK_HOME=/opt/soft/flink
+export DATAX_HOME=/opt/soft/datax/bin/datax.py
+
+export
PATH=$HADOOP_HOME/bin:$SPARK_HOME1/bin:$SPARK_HOME2/bin:$PYTHON_HOME:$JAVA_HOME/bin:$HIVE_HOME/bin:$PATH:$FLINK_HOME/bin:$DATAX_HOME:$PATH
+
+```
+
+## 12.Service log configuration files
+Correspondence service| Log file name |
+|--|--|--|
+api service log configuration file |logback-api.xml|
+Master service log configuration file|logback-master.xml |
+Worker service log configuration file|logback-worker.xml |
+alert service log configuration file|logback-alert.xml |
diff --git a/docs/en-us/1.3.1/user_doc/task-structure.md
b/docs/en-us/1.3.1/user_doc/task-structure.md
new file mode 100644
index 0000000..2442e7e
--- /dev/null
+++ b/docs/en-us/1.3.1/user_doc/task-structure.md
@@ -0,0 +1,1136 @@
+
+# Overall task storage structure
+All tasks created in dolphinscheduler are saved in the t_ds_process_definition
table.
+
+The database table structure is shown in the following table:
+
+
+Serial number | Field | Types | Description
+-------- | ---------| -------- | ---------
+1|id|int(11)|Primary key
+2|name|varchar(255)|Process definition name
+3|version|int(11)|Process definition version
+4|release_state|tinyint(4)|Release status of the process definition：0 not
online, 1 online
+5|project_id|int(11)|Project id
+6|user_id|int(11)|User id of the process definition
+7|process_definition_json|longtext|Process definition JSON
+8|description|text|Process definition description
+9|global_params|text|Global parameters
+10|flag|tinyint(4)|Whether the process is available: 0 is not available, 1 is
available
+11|locations|text|Node coordinate information
+12|connects|text|Node connection information
+13|receivers|text|Recipient
+14|receivers_cc|text|Cc
+15|create_time|datetime|Creation time
+16|timeout|int(11) |overtime time
+17|tenant_id|int(11) |Tenant id
+18|update_time|datetime|Update time
+19|modify_by|varchar(36)|Modify user
+20|resource_ids|varchar(255)|Resource ids
+
+The process_definition_json field is the core field, which defines the task
information in the DAG diagram. The data is stored in JSON.
+
+The public data structure is as follows.
+Serial number | Field | Types | Description
+-------- | ---------| -------- | ---------
+1|globalParams|Array|Global parameters
+2|tasks|Array|Task collection in the process [ Please refer to the following
chapters for the structure of each type]
+3|tenantId|int|Tenant id
+4|timeout|int|overtime time
+
+Data example:
+```bash
+{
+ "globalParams":[
+ {
+ "prop":"golbal_bizdate",
+ "direct":"IN",
+ "type":"VARCHAR",
+ "value":"${system.biz.date}"
+ }
+ ],
+ "tasks":Array[1],
+ "tenantId":0,
+ "timeout":0
+}
+```
+
+# Detailed explanation of the storage structure of each task type
+
+## Shell node
+**The node data structure is as follows:**
+Serial number|Field||Types|Description |Description
+-------- | ---------| ---------| -------- | --------- | ---------
+1|id | |String| Task code|
+2|type ||String |Type |SHELL
+3| name| |String|Name |
+4| params| |Object| Custom parameters |Json format
+5| |rawScript |String| Shell script |
+6| | localParams| Array|Custom parameters||
+7| | resourceList| Array|Resource||
+8|description | |String|Description | |
+9|runFlag | |String |Run ID| |
+10|conditionResult | |Object|Conditional branch | |
+11| | successNode| Array|Jump to node successfully| |
+12| | failedNode|Array|Failed jump node |
+13| dependence| |Object |Task dependency |Mutually exclusive with params
+14|maxRetryTimes | |String|Maximum number of retries | |
+15|retryInterval | |String |Retry interval| |
+16|timeout | |Object|Timeout control | |
+17| taskInstancePriority| |String|Task priority | |
+18|workerGroup | |String |Worker Grouping| |
+19|preTasks | |Array|Predecessor | |
+
+
+**Sample node data:**
+
+```bash
+{
+ "type":"SHELL",
+ "id":"tasks-80760",
+ "name":"Shell Task",
+ "params":{
+ "resourceList":[
+ {
+ "id":3,
+ "name":"run.sh",
+ "res":"run.sh"
+ }
+ ],
+ "localParams":[
+
+ ],
+ "rawScript":"echo "This is a shell script""
+ },
+ "description":"",
+ "runFlag":"NORMAL",
+ "conditionResult":{
+ "successNode":[
+ ""
+ ],
+ "failedNode":[
+ ""
+ ]
+ },
+ "dependence":{
+
+ },
+ "maxRetryTimes":"0",
+ "retryInterval":"1",
+ "timeout":{
+ "strategy":"",
+ "interval":null,
+ "enable":false
+ },
+ "taskInstancePriority":"MEDIUM",
+ "workerGroup":"default",
+ "preTasks":[
+
+ ]
+}
+
+```
+
+
+## SQL node
+Perform data query and update operations on the specified data source through
SQL.
+
+**The node data structure is as follows:**
+Serial number|Parameter name||Types|Description |Description
+-------- | ---------| ---------| -------- | --------- | ---------
+1|id | |String| Task code|
+2|type ||String |Type |SQL
+3| name| |String|Name |
+4| params| |Object| Custom parameters |Json 格式
+5| |type |String | Database type
+6| |datasource |Int | Data source id
+7| |sql |String | Query SQL statement
+8| |udfs | String| udf function|UDF function ids, separated by commas.
+9| |sqlType | String| SQL node type |0 query, 1 non query
+10| |title |String | Mail title
+11| |receivers |String | Recipient
+12| |receiversCc |String | Cc
+13| |showType | String| Mail display type|TABLE table , ATTACHMENT attachment
+14| |connParams | String| Connection parameters
+15| |preStatements | Array| Pre-SQL
+16| | postStatements| Array|Post SQL||
+17| | localParams| Array|Custom parameters||
+18|description | |String|Dscription | |
+19|runFlag | |String |Run ID| |
+20|conditionResult | |Object|Conditional branch | |
+21| | successNode| Array|Jump to node successfully| |
+22| | failedNode|Array|Failed jump node |
+23| dependence| |Object |Task dependency |Mutually exclusive with params
+24|maxRetryTimes | |String|Maximum number of retries | |
+25|retryInterval | |String |Retry interval| |
+26|timeout | |Object|Timeout control | |
+27| taskInstancePriority| |String|Task priority | |
+28|workerGroup | |String |Worker Grouping| |
+29|preTasks | |Array|Predecessor | |
+
+
+**Sample node data:**
+
+```bash
+{
+ "type":"SQL",
+ "id":"tasks-95648",
+ "name":"SqlTask-Query",
+ "params":{
+ "type":"MYSQL",
+ "datasource":1,
+ "sql":"select id , namge , age from emp where id = ${id}",
+ "udfs":"",
+ "sqlType":"0",
+ "title":"[email protected]",
+ "receivers":"[email protected]",
+ "receiversCc":"",
+ "showType":"TABLE",
+ "localParams":[
+ {
+ "prop":"id",
+ "direct":"IN",
+ "type":"INTEGER",
+ "value":"1"
+ }
+ ],
+ "connParams":"",
+ "preStatements":[
+ "insert into emp ( id,name ) value (1,'Li' )"
+ ],
+ "postStatements":[
+
+ ]
+ },
+ "description":"",
+ "runFlag":"NORMAL",
+ "conditionResult":{
+ "successNode":[
+ ""
+ ],
+ "failedNode":[
+ ""
+ ]
+ },
+ "dependence":{
+
+ },
+ "maxRetryTimes":"0",
+ "retryInterval":"1",
+ "timeout":{
+ "strategy":"",
+ "interval":null,
+ "enable":false
+ },
+ "taskInstancePriority":"MEDIUM",
+ "workerGroup":"default",
+ "preTasks":[
+
+ ]
+}
+```
+
+
+## PROCEDURE [stored procedure] node
+**The node data structure is as follows:**
+**Sample node data:**
+
+## SPARK node
+**The node data structure is as follows:**
+
+Serial number|Parameter name||Types|Description |Description
+-------- | ---------| ---------| -------- | --------- | ---------
+1|id | |String| Task code|
+2|type ||String |Types of |SPARK
+3| name| |String|Name |
+4| params| |Object| Custom parameters |Json format
+5| |mainClass |String | Run the main class
+6| |mainArgs | String| Operating parameters
+7| |others | String| Other parameters
+8| |mainJar |Object | Program jar package
+9| |deployMode |String | Deployment mode |local,client,cluster
+10| |driverCores | String| Driver core
+11| |driverMemory | String| Driver memory
+12| |numExecutors |String | Number of executors
+13| |executorMemory |String | Executor memory
+14| |executorCores |String | Number of executor cores
+15| |programType | String| Type program|JAVA,SCALA,PYTHON
+16| | sparkVersion| String| Spark version| SPARK1 , SPARK2
+17| | localParams| Array|Custom parameters
+18| | resourceList| Array|Resource
+19|description | |String|Description | |
+20|runFlag | |String |Run ID| |
+21|conditionResult | |Object|Conditional branch | |
+22| | successNode| Array|Jump to node successfully| |
+23| | failedNode|Array|Failed jump node |
+24| dependence| |Object |Task dependency |Mutually exclusive with params
+25|maxRetryTimes | |String|Maximum number of retries | |
+26|retryInterval | |String |Retry interval| |
+27|timeout | |Object|Timeout control | |
+28| taskInstancePriority| |String|Task priority | |
+29|workerGroup | |String |Worker Grouping| |
+30|preTasks | |Array|Predecessor | |
+
+
+**Sample node data:**
+
+```bash
+{
+ "type":"SPARK",
+ "id":"tasks-87430",
+ "name":"SparkTask",
+ "params":{
+ "mainClass":"org.apache.spark.examples.SparkPi",
+ "mainJar":{
+ "id":4
+ },
+ "deployMode":"cluster",
+ "resourceList":[
+ {
+ "id":3,
+ "name":"run.sh",
+ "res":"run.sh"
+ }
+ ],
+ "localParams":[
+
+ ],
+ "driverCores":1,
+ "driverMemory":"512M",
+ "numExecutors":2,
+ "executorMemory":"2G",
+ "executorCores":2,
+ "mainArgs":"10",
+ "others":"",
+ "programType":"SCALA",
+ "sparkVersion":"SPARK2"
+ },
+ "description":"",
+ "runFlag":"NORMAL",
+ "conditionResult":{
+ "successNode":[
+ ""
+ ],
+ "failedNode":[
+ ""
+ ]
+ },
+ "dependence":{
+
+ },
+ "maxRetryTimes":"0",
+ "retryInterval":"1",
+ "timeout":{
+ "strategy":"",
+ "interval":null,
+ "enable":false
+ },
+ "taskInstancePriority":"MEDIUM",
+ "workerGroup":"default",
+ "preTasks":[
+
+ ]
+}
+```
+
+
+
+## MapReduce (MR) node
+**The node data structure is as follows:**
+
+Serial number|Parameter name||Types|Description |描Description述
+-------- | ---------| ---------| -------- | --------- | ---------
+1|id | |String| Task code|
+2|type ||String |Type |MR
+3| name| |String|Name |
+4| params| |Object| Custom parameters |Json format
+5| |mainClass |String | Run the main class
+6| |mainArgs | String| Operating parameters
+7| |others | String| Other parameters
+8| |mainJar |Object | Program jar package
+9| |programType | String| Program type|JAVA,PYTHON
+10| | localParams| Array|Custom parameters
+11| | resourceList| Array|Resource
+12|description | |String|Description | |
+13|runFlag | |String |Run ID| |
+14|conditionResult | |Object|Conditional branch | |
+15| | successNode| Array|Jump to node successfully| |
+16| | failedNode|Array|Failed jump node |
+17| dependence| |Object |Task dependency |Mutually exclusive with params
+18|maxRetryTimes | |String|Maximum number of retries | |
+19|retryInterval | |String |Retry interval| |
+20|timeout | |Object|Timeout control | |
+21| taskInstancePriority| |String|Task priority | |
+22|workerGroup | |String |Worker Grouping| |
+23|preTasks | |Array|Predecessor | |
+
+
+
+**Sample node data:**
+
+```bash
+{
+ "type":"MR",
+ "id":"tasks-28997",
+ "name":"MRTask",
+ "params":{
+ "mainClass":"wordcount",
+ "mainJar":{
+ "id":5
+ },
+ "resourceList":[
+ {
+ "id":3,
+ "name":"run.sh",
+ "res":"run.sh"
+ }
+ ],
+ "localParams":[
+
+ ],
+ "mainArgs":"/tmp/wordcount/input /tmp/wordcount/output/",
+ "others":"",
+ "programType":"JAVA"
+ },
+ "description":"",
+ "runFlag":"NORMAL",
+ "conditionResult":{
+ "successNode":[
+ ""
+ ],
+ "failedNode":[
+ ""
+ ]
+ },
+ "dependence":{
+
+ },
+ "maxRetryTimes":"0",
+ "retryInterval":"1",
+ "timeout":{
+ "strategy":"",
+ "interval":null,
+ "enable":false
+ },
+ "taskInstancePriority":"MEDIUM",
+ "workerGroup":"default",
+ "preTasks":[
+
+ ]
+}
+```
+
+
+## Python node
+**The node data structure is as follows:**
+Serial number|parameter name||Types|Description |Description
+-------- | ---------| ---------| -------- | --------- | ---------
+1|id | |String| Task code|
+2|type ||String |Type |PYTHON
+3| name| |String|Name |
+4| params| |Object| Custom parameters |Json format
+5| |rawScript |String| Python script |
+6| | localParams| Array|Custom parameters||
+7| | resourceList| Array|Resource||
+8|description | |String|Description | |
+9|runFlag | |String |Run ID| |
+10|conditionResult | |Object|Conditional branch | |
+11| | successNode| Array|Jump to node successfully| |
+12| | failedNode|Array|Failed jump node |
+13| dependence| |Object |Task dependency |Mutually exclusive with params
+14|maxRetryTimes | |String|Maximum number of retries | |
+15|retryInterval | |String |Retry interval| |
+16|timeout | |Object|Timeout control | |
+17| taskInstancePriority| |String|Task priority | |
+18|workerGroup | |String |Worker Grouping| |
+19|preTasks | |Array|Predecessor | |
+
+
+**Sample node data:**
+
+```bash
+{
+ "type":"PYTHON",
+ "id":"tasks-5463",
+ "name":"Python Task",
+ "params":{
+ "resourceList":[
+ {
+ "id":3,
+ "name":"run.sh",
+ "res":"run.sh"
+ }
+ ],
+ "localParams":[
+
+ ],
+ "rawScript":"print("This is a python script")"
+ },
+ "description":"",
+ "runFlag":"NORMAL",
+ "conditionResult":{
+ "successNode":[
+ ""
+ ],
+ "failedNode":[
+ ""
+ ]
+ },
+ "dependence":{
+
+ },
+ "maxRetryTimes":"0",
+ "retryInterval":"1",
+ "timeout":{
+ "strategy":"",
+ "interval":null,
+ "enable":false
+ },
+ "taskInstancePriority":"MEDIUM",
+ "workerGroup":"default",
+ "preTasks":[
+
+ ]
+}
+```
+
+
+
+
+## Flink node
+**The node data structure is as follows:**
+
+Serial number|Parameter name||Types|Description |Description
+-------- | ---------| ---------| -------- | --------- | ---------
+1|id | |String| Task code|
+2|type ||String |Type |FLINK
+3| name| |String|Name |
+4| params| |Object| Custom parameters |Json format
+5| |mainClass |String | Run the main class
+6| |mainArgs | String| Operating parameters
+7| |others | String| Other parameters
+8| |mainJar |Object | Program jar package
+9| |deployMode |String | Deployment mode |local,client,cluster
+10| |slot | String| Number of slots
+11| |taskManager |String | Number of taskManage
+12| |taskManagerMemory |String | TaskManager memory
+13| |jobManagerMemory |String | JobManager memory number
+14| |programType | String| Program type|JAVA,SCALA,PYTHON
+15| | localParams| Array|Custom parameters
+16| | resourceList| Array|Resource
+17|description | |String|Description | |
+18|runFlag | |String |Run ID| |
+19|conditionResult | |Object|Conditional branch | |
+20| | successNode| Array|Jump to node successfully| |
+21| | failedNode|Array|Failed jump node |
+22| dependence| |Object |Task dependency |Mutually exclusive with params
+23|maxRetryTimes | |String|Maximum number of retries | |
+24|retryInterval | |String |Retry interval| |
+25|timeout | |Object|Timeout control | |
+26| taskInstancePriority| |String|Task priority | |
+27|workerGroup | |String |Worker Grouping| |
+38|preTasks | |Array|Predecessor | |
+
+
+**Sample node data:**
+
+```bash
+{
+ "type":"FLINK",
+ "id":"tasks-17135",
+ "name":"FlinkTask",
+ "params":{
+ "mainClass":"com.flink.demo",
+ "mainJar":{
+ "id":6
+ },
+ "deployMode":"cluster",
+ "resourceList":[
+ {
+ "id":3,
+ "name":"run.sh",
+ "res":"run.sh"
+ }
+ ],
+ "localParams":[
+
+ ],
+ "slot":1,
+ "taskManager":"2",
+ "jobManagerMemory":"1G",
+ "taskManagerMemory":"2G",
+ "executorCores":2,
+ "mainArgs":"100",
+ "others":"",
+ "programType":"SCALA"
+ },
+ "description":"",
+ "runFlag":"NORMAL",
+ "conditionResult":{
+ "successNode":[
+ ""
+ ],
+ "failedNode":[
+ ""
+ ]
+ },
+ "dependence":{
+
+ },
+ "maxRetryTimes":"0",
+ "retryInterval":"1",
+ "timeout":{
+ "strategy":"",
+ "interval":null,
+ "enable":false
+ },
+ "taskInstancePriority":"MEDIUM",
+ "workerGroup":"default",
+ "preTasks":[
+
+ ]
+}
+```
+
+## HTTP node
+**The node data structure is as follows:**
+
+Serial number|Parameter name||Type|Description |Description
+-------- | ---------| ---------| -------- | --------- | ---------
+1|id | |String| Task code|
+2|type ||String |Type |HTTP
+3| name| |String|Name |
+4| params| |Object| Custom parameters |Json format
+5| |url |String | Request address
+6| |httpMethod | String| Request method|GET,POST,HEAD,PUT,DELETE
+7| | httpParams| Array|Request parameter
+8| |httpCheckCondition | String| Check conditions|Default response code 200
+9| |condition |String | Check content
+10| | localParams| Array|Custom parameters
+11|description | |String|Description | |
+12|runFlag | |String |Run ID| |
+13|conditionResult | |Object|Conditional branch | |
+14| | successNode| Array|Jump to node successfully| |
+15| | failedNode|Array|Failed jump node |
+16| dependence| |Object |Task dependency |Mutually exclusive with params
+17|maxRetryTimes | |String|Maximum number of retries | |
+18|retryInterval | |String |Retry interval| |
+19|timeout | |Object|Timeout control | |
+20| taskInstancePriority| |String|Task priority | |
+21|workerGroup | |String |Worker Grouping| |
+22|preTasks | |Array|Predecessor | |
+
+
+**Sample node data:**
+
+```bash
+{
+ "type":"HTTP",
+ "id":"tasks-60499",
+ "name":"HttpTask",
+ "params":{
+ "localParams":[
+
+ ],
+ "httpParams":[
+ {
+ "prop":"id",
+ "httpParametersType":"PARAMETER",
+ "value":"1"
+ },
+ {
+ "prop":"name",
+ "httpParametersType":"PARAMETER",
+ "value":"Bo"
+ }
+ ],
+ "url":"https://www.xxxxx.com:9012";,
+ "httpMethod":"POST",
+ "httpCheckCondition":"STATUS_CODE_DEFAULT",
+ "condition":""
+ },
+ "description":"",
+ "runFlag":"NORMAL",
+ "conditionResult":{
+ "successNode":[
+ ""
+ ],
+ "failedNode":[
+ ""
+ ]
+ },
+ "dependence":{
+
+ },
+ "maxRetryTimes":"0",
+ "retryInterval":"1",
+ "timeout":{
+ "strategy":"",
+ "interval":null,
+ "enable":false
+ },
+ "taskInstancePriority":"MEDIUM",
+ "workerGroup":"default",
+ "preTasks":[
+
+ ]
+}
+```
+
+
+
+## DataX node
+
+**The node data structure is as follows:**
+Serial number|Parameter name||Types|Description |Description
+-------- | ---------| ---------| -------- | --------- | ---------
+1|id | |String| Task code|
+2|type ||String |Type |DATAX
+3| name| |String|Name |
+4| params| |Object| Custom parameters |Json format
+5| |customConfig |Int | Custom type| 0 custom, 1 custom
+6| |dsType |String | Source database type
+7| |dataSource |Int | Source database ID
+8| |dtType | String| Target database type
+9| |dataTarget | Int| Target database ID
+10| |sql |String | SQL statement
+11| |targetTable |String | Target table
+12| |jobSpeedByte |Int | Current limit (bytes)
+13| |jobSpeedRecord | Int| Current limit (number of records)
+14| |preStatements | Array| Pre-SQL
+15| | postStatements| Array|Post SQL
+16| | json| String|Custom configuration|Effective when customConfig=1
+17| | localParams| Array|Custom parameters|Effective when customConfig=1
+18|description | |String|Description | |
+19|runFlag | |String |Run ID| |
+20|conditionResult | |Object|Conditional branch | |
+21| | successNode| Array|Jump to node successfully| |
+22| | failedNode|Array|Failed jump node |
+23| dependence| |Object |Task dependency |Mutually exclusive with params
+24|maxRetryTimes | |String|Maximum number of retries | |
+25|retryInterval | |String |Retry interval| |
+26|timeout | |Object|Timeout control | |
+27| taskInstancePriority| |String|Task priority | |
+28|workerGroup | |String |Worker Grouping| |
+29|preTasks | |Array|Predecessor | |
+
+
+
+**Sample node data:**
+
+
+```bash
+{
+ "type":"DATAX",
+ "id":"tasks-91196",
+ "name":"DataxTask-DB",
+ "params":{
+ "customConfig":0,
+ "dsType":"MYSQL",
+ "dataSource":1,
+ "dtType":"MYSQL",
+ "dataTarget":1,
+ "sql":"select id, name ,age from user ",
+ "targetTable":"emp",
+ "jobSpeedByte":524288,
+ "jobSpeedRecord":500,
+ "preStatements":[
+ "truncate table emp "
+ ],
+ "postStatements":[
+ "truncate table user"
+ ]
+ },
+ "description":"",
+ "runFlag":"NORMAL",
+ "conditionResult":{
+ "successNode":[
+ ""
+ ],
+ "failedNode":[
+ ""
+ ]
+ },
+ "dependence":{
+
+ },
+ "maxRetryTimes":"0",
+ "retryInterval":"1",
+ "timeout":{
+ "strategy":"",
+ "interval":null,
+ "enable":false
+ },
+ "taskInstancePriority":"MEDIUM",
+ "workerGroup":"default",
+ "preTasks":[
+
+ ]
+}
+```
+
+## Sqoop node
+
+**The node data structure is as follows:**
+Serial number|parameter name||Types|Description |Description
+-------- | ---------| ---------| -------- | --------- | ---------
+1|id | |String| Task code|
+2|type ||String |Type |SQOOP
+3| name| |String|Name |
+4| params| |Object| Custom parameters |JSON format
+5| | concurrency| Int|Concurrency
+6| | modelType|String |Flow direction|import,export
+7| |sourceType|String |Data source type |
+8| |sourceParams |String| Data source parameters| JSON format
+9| | targetType|String |Target data type
+10| |targetParams | String|Target data parameters|JSON format
+11| |localParams |Array |Custom parameters
+12|description | |String|Description | |
+13|runFlag | |String |Run ID| |
+14|conditionResult | |Object|Conditional branch | |
+15| | successNode| Array|Jump to node successfully| |
+16| | failedNode|Array|Failed jump node |
+17| dependence| |Object |Task dependency |Mutually exclusive with params
+18|maxRetryTimes | |String|Maximum number of retries | |
+19|retryInterval | |String |Retry interval| |
+20|timeout | |Object|Timeout control | |
+21| taskInstancePriority| |String|Task priority | |
+22|workerGroup | |String |Worker Grouping| |
+23|preTasks | |Array|Predecessor | |
+
+
+
+
+**Sample node data:**
+
+```bash
+{
+ "type":"SQOOP",
+ "id":"tasks-82041",
+ "name":"Sqoop Task",
+ "params":{
+ "concurrency":1,
+ "modelType":"import",
+ "sourceType":"MYSQL",
+ "targetType":"HDFS",
+
"sourceParams":"{"srcType":"MYSQL","srcDatasource":1,"srcTable":"","srcQueryType":"1","srcQuerySql":"selec
id , name from
user","srcColumnType":"0","srcColumns":"","srcConditionList":[],"mapColumnHive":[{"prop":"hivetype-key","direct":"IN","type":"VARCHAR","value":"hivetype-value"}],"mapColumnJava":[{"prop":"javatype-key","direct":"IN","type":"VARCHAR","value":"javatype-value"}]}",
+
"targetParams":"{"targetPath":"/user/hive/warehouse/ods.db/user","deleteTargetDir":false,"fileType":"--as-avrodatafile","compressionCodec":"snappy","fieldsTerminated":",","linesTerminated":"@"}",
+ "localParams":[
+
+ ]
+ },
+ "description":"",
+ "runFlag":"NORMAL",
+ "conditionResult":{
+ "successNode":[
+ ""
+ ],
+ "failedNode":[
+ ""
+ ]
+ },
+ "dependence":{
+
+ },
+ "maxRetryTimes":"0",
+ "retryInterval":"1",
+ "timeout":{
+ "strategy":"",
+ "interval":null,
+ "enable":false
+ },
+ "taskInstancePriority":"MEDIUM",
+ "workerGroup":"default",
+ "preTasks":[
+
+ ]
+ }
+```
+
+## Conditional branch node
+
+**The node data structure is as follows:**
+Serial number|Parameter name||Types|Description |Description
+-------- | ---------| ---------| -------- | --------- | ---------
+1|id | |String| Task code|
+2|type ||String |Type |SHELL
+3| name| |String|Name |
+4| params| |Object| Custom parameters | null
+5|description | |String|Description | |
+6|runFlag | |String |Run ID| |
+7|conditionResult | |Object|Conditional branch | |
+8| | successNode| Array|Jump to node successfully| |
+9| | failedNode|Array|Failed jump node |
+10| dependence| |Object |Task dependency |Mutually exclusive with params
+11|maxRetryTimes | |String|Maximum number of retries | |
+12|retryInterval | |String |Retry interval| |
+13|timeout | |Object|Timeout control | |
+14| taskInstancePriority| |String|Task priority | |
+15|workerGroup | |String |Worker Grouping| |
+16|preTasks | |Array|Predecessor | |
+
+
+**Sample node data:**
+
+```bash
+{
+ "type":"CONDITIONS",
+ "id":"tasks-96189",
+ "name":"条件",
+ "params":{
+
+ },
+ "description":"",
+ "runFlag":"NORMAL",
+ "conditionResult":{
+ "successNode":[
+ "test04"
+ ],
+ "failedNode":[
+ "test05"
+ ]
+ },
+ "dependence":{
+ "relation":"AND",
+ "dependTaskList":[
+
+ ]
+ },
+ "maxRetryTimes":"0",
+ "retryInterval":"1",
+ "timeout":{
+ "strategy":"",
+ "interval":null,
+ "enable":false
+ },
+ "taskInstancePriority":"MEDIUM",
+ "workerGroup":"default",
+ "preTasks":[
+ "test01",
+ "test02"
+ ]
+}
+```
+
+
+## Subprocess node
+**The node data structure is as follows:**
+Serial number|Parameter name||Types|Description |Description
+-------- | ---------| ---------| -------- | --------- | ---------
+1|id | |String| Task code|
+2|type ||String |Type |SHELL
+3| name| |String|Name |
+4| params| |Object| Custom parameters |Json format
+5| |processDefinitionId |Int| Process definition id
+6|description | |String|Description | |
+7|runFlag | |String |Run ID| |
+8|conditionResult | |Object|Conditional branch | |
+9| | successNode| Array|Jump to node successfully| |
+10| | failedNode|Array|Failed jump node |
+11| dependence| |Object |Task dependency |Mutually exclusive with params
+12|maxRetryTimes | |String|Maximum number of retries | |
+13|retryInterval | |String |Retry interval| |
+14|timeout | |Object|Timeout control | |
+15| taskInstancePriority| |String|Task priority | |
+16|workerGroup | |String |Worker Grouping| |
+17|preTasks | |Array|Predecessor | |
+
+
+**Sample node data:**
+
+```bash
+{
+ "type":"SUB_PROCESS",
+ "id":"tasks-14806",
+ "name":"SubProcessTask",
+ "params":{
+ "processDefinitionId":2
+ },
+ "description":"",
+ "runFlag":"NORMAL",
+ "conditionResult":{
+ "successNode":[
+ ""
+ ],
+ "failedNode":[
+ ""
+ ]
+ },
+ "dependence":{
+
+ },
+ "timeout":{
+ "strategy":"",
+ "interval":null,
+ "enable":false
+ },
+ "taskInstancePriority":"MEDIUM",
+ "workerGroup":"default",
+ "preTasks":[
+
+ ]
+ }
+```
+
+
+
+## DEPENDENT node
+**The node data structure is as follows:**
+
+**The node data structure is as follows:**
+Serial number|parameter name||Types|Description |Description
+-------- | ---------| ---------| -------- | --------- | ---------
+1|id | |String| Task code|
+2|type ||String |Type |DEPENDENT
+3| name| |String|Name |
+4| params| |Object| Custom parameters |Json format
+5| |rawScript |String| Shell script |
+6| | localParams| Array|Custom parameters||
+7| | resourceList| Array|Resource||
+8|description | |String|Description | |
+9|runFlag | |String |Run ID| |
+10|conditionResult | |Object|Conditional branch | |
+11| | successNode| Array|Jump to node successfully| |
+12| | failedNode|Array|Failed jump node |
+13| dependence| |Object |Task dependency |Mutually exclusive with params
+14| | relation|String |Relationship |AND,OR
+15| | dependTaskList|Array |Dependent task list |
+16|maxRetryTimes | |String|Maximum number of retries | |
+17|retryInterval | |String |Retry interval| |
+18|timeout | |Object|Timeout control | |
+19| taskInstancePriority| |String|Task priority | |
+20|workerGroup | |String |Worker Grouping| |
+21|preTasks | |Array|Predecessor | |
+
+
+**Sample node data:**
+
+```bash
+{
+ "type":"DEPENDENT",
+ "id":"tasks-57057",
+ "name":"DenpendentTask",
+ "params":{
+
+ },
+ "description":"",
+ "runFlag":"NORMAL",
+ "conditionResult":{
+ "successNode":[
+ ""
+ ],
+ "failedNode":[
+ ""
+ ]
+ },
+ "dependence":{
+ "relation":"AND",
+ "dependTaskList":[
+ {
+ "relation":"AND",
+ "dependItemList":[
+ {
+ "projectId":1,
+ "definitionId":7,
+ "definitionList":[
+ {
+ "value":8,
+ "label":"MRTask"
+ },
+ {
+ "value":7,
+ "label":"FlinkTask"
+ },
+ {
+ "value":6,
+ "label":"SparkTask"
+ },
+ {
+ "value":5,
+ "label":"SqlTask-Update"
+ },
+ {
+ "value":4,
+ "label":"SqlTask-Query"
+ },
+ {
+ "value":3,
+ "label":"SubProcessTask"
+ },
+ {
+ "value":2,
+ "label":"Python Task"
+ },
+ {
+ "value":1,
+ "label":"Shell Task"
+ }
+ ],
+ "depTasks":"ALL",
+ "cycle":"day",
+ "dateValue":"today"
+ }
+ ]
+ },
+ {
+ "relation":"AND",
+ "dependItemList":[
+ {
+ "projectId":1,
+ "definitionId":5,
+ "definitionList":[
+ {
+ "value":8,
+ "label":"MRTask"
+ },
+ {
+ "value":7,
+ "label":"FlinkTask"
+ },
+ {
+ "value":6,
+ "label":"SparkTask"
+ },
+ {
+ "value":5,
+ "label":"SqlTask-Update"
+ },
+ {
+ "value":4,
+ "label":"SqlTask-Query"
+ },
+ {
+ "value":3,
+ "label":"SubProcessTask"
+ },
+ {
+ "value":2,
+ "label":"Python Task"
+ },
+ {
+ "value":1,
+ "label":"Shell Task"
+ }
+ ],
+ "depTasks":"SqlTask-Update",
+ "cycle":"day",
+ "dateValue":"today"
+ }
+ ]
+ }
+ ]
+ },
+ "maxRetryTimes":"0",
+ "retryInterval":"1",
+ "timeout":{
+ "strategy":"",
+ "interval":null,
+ "enable":false
+ },
+ "taskInstancePriority":"MEDIUM",
+ "workerGroup":"default",
+ "preTasks":[
+
+ ]
+ }
+```
diff --git a/site_config/docs1-3-1.js b/site_config/docs1-3-1.js
index 9a93677..d9360e1 100644
--- a/site_config/docs1-3-1.js
+++ b/site_config/docs1-3-1.js
@@ -15,6 +15,10 @@ export default {
{
title: 'Frontend deploy',
link:
'/en-us/docs/1.3.1/user_doc/frontend-deployment.html',
+ },
+ {
+ tltle: 'Configration file',
+ link:
'/en-us/docs/1.3.1/user_doc/configration-file.html'
}
]
},
@@ -33,6 +37,14 @@ export default {
title: 'Metadata',
link: '/en-us/docs/1.3.1/user_doc/metadata-1.3.html'
},
+ {
+ title: 'Architecture design',
+ link:
'/en-us/docs/1.3.1/user_doc/architecture-design.html'
+ },
+ {
+ title: 'task structure',
+ link: '/en-us/docs/1.3.1/user_doc/task-structure.html'
+ }
]
},
{
![https://analysys.github.io/easyscheduler_docs_cn/images/master_slave.png"](https://analysys.github.io/easyscheduler_docs_cn/images/master_slave.png"){kind=link}
![https://analysys.github.io/easyscheduler_docs_cn/images/decentralization.png"](https://analysys.github.io/easyscheduler_docs_cn/images/decentralization.png"){kind=link}
![https://analysys.github.io/easyscheduler_docs_cn/images/distributed_lock.png"](https://analysys.github.io/easyscheduler_docs_cn/images/distributed_lock.png"){kind=link}
![https://analysys.github.io/easyscheduler_docs_cn/images/lack_thread.png"](https://analysys.github.io/easyscheduler_docs_cn/images/lack_thread.png"){kind=link}
![https://analysys.github.io/easyscheduler_docs_cn/images/fault-tolerant.png"](https://analysys.github.io/easyscheduler_docs_cn/images/fault-tolerant.png"){kind=link}
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![https://analysys.github.io/easyscheduler_docs_cn/images/task_priority.png"](https://analysys.github.io/easyscheduler_docs_cn/images/task_priority.png"){kind=link}
![https://analysys.github.io/easyscheduler_docs_cn/images/grpc.png"](https://analysys.github.io/easyscheduler_docs_cn/images/grpc.png"){kind=link}