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zm&(=a6OwI~@eJttugfC_e^7X_+2cnZuu$!z>6)(Fs`f{iYv&-uo9O?O%IKjo(`~@^ zabrQ?$|MGIn`U|5?7Ar)MD5WV08Na91jnK63!Lr%dmwB(D>;4Tyn~-|>P>%2)?Cd# z+8DWFHBp(lxM+$${Z7T|&@H-`k?no{u}~9Odo($C<|Y+m_;_}!ACx-o+qv(-{kI99*Ym{NV4LLr3vR$c#>x^ uFKikU7^c1~)GGeRJNRy;nW@vUGx79+dpGX2bGe?kla*4EERZnx@;?9zfumjk literal 0 HcmV?d00001 diff --git a/docs/zh_CN/系统使用手册.md b/docs/zh_CN/系统使用手册.md index fc0e999118..595850bade 100644 --- a/docs/zh_CN/系统使用手册.md +++ b/docs/zh_CN/系统使用手册.md @@ -60,7 +60,7 @@ ### 执行流程定义 - **未上线状态的流程定义可以编辑,但是不可以运行**,所以先上线工作流 > 点击工作流定义,返回流程定义列表,点击”上线“图标,上线工作流定义。 - + > "下线"工作流之前,要先将定时管理的定时下线,才能成功下线工作流定义 - 点击”运行“,执行工作流。运行参数说明: @@ -98,28 +98,28 @@ ### 查看流程实例 > 点击“工作流实例”,查看流程实例列表。 - + > 点击工作流名称,查看任务执行状态。 - +

> 点击任务节点,点击“查看日志”,查看任务执行日志。 - +

- + > 点击任务实例节点,点击**查看历史**,可以查看该流程实例运行的该任务实例列表 - +

> 对工作流实例的操作: - +

@@ -165,7 +165,7 @@ - 密码:设置连接MySQL的密码 - 数据库名:输入连接MySQL的数据库名称 - Jdbc连接参数:用于MySQL连接的参数设置,以JSON形式填写 - +

@@ -191,7 +191,7 @@ #### 创建、编辑HIVE数据源 1.使用HiveServer2方式连接 - +

@@ -207,12 +207,19 @@ - Jdbc连接参数:用于HIVE连接的参数设置,以JSON形式填写 2.使用HiveServer2 HA Zookeeper方式连接 - +

+注意:如果开启了**kerberos**,则需要填写 **Principal** +

+ +

+ + + #### 创建、编辑Spark数据源

@@ -231,7 +238,7 @@ ### 上传资源 - 上传资源文件和udf函数,所有上传的文件和资源都会被存储到hdfs上,所以需要以下配置项: - + ``` conf/common/common.properties -- hdfs.startup.state=true @@ -242,7 +249,7 @@ conf/common/hadoop.properties ``` #### 文件管理 - + > 是对各种资源文件的管理,包括创建基本的txt/log/sh/conf等文件、上传jar包等各种类型文件,以及编辑、下载、删除等操作。

@@ -287,7 +294,7 @@ conf/common/hadoop.properties #### 资源管理 > 资源管理和文件管理功能类似,不同之处是资源管理是上传的UDF函数,文件管理上传的是用户程序,脚本及配置文件 - + * 上传udf资源 > 和上传文件相同。 @@ -303,7 +310,7 @@ conf/common/hadoop.properties - 参数:用来标注函数的输入参数 - 数据库名:预留字段,用于创建永久UDF函数 - UDF资源:设置创建的UDF对应的资源文件 - +

@@ -312,7 +319,7 @@ conf/common/hadoop.properties - 安全中心是只有管理员账户才有权限的功能,有队列管理、租户管理、用户管理、告警组管理、worker分组、令牌管理等功能,还可以对资源、数据源、项目等授权 - 管理员登录,默认用户名密码:admin/escheduler123 - + ### 创建队列 - 队列是在执行spark、mapreduce等程序,需要用到“队列”参数时使用的。 - “安全中心”->“队列管理”->“创建队列” @@ -357,7 +364,7 @@ conf/common/hadoop.properties ### 令牌管理 - 由于后端接口有登录检查,令牌管理,提供了一种可以通过调用接口的方式对系统进行各种操作。 - 调用示例: - + ```令牌调用示例 /** * test token @@ -477,15 +484,15 @@ conf/common/hadoop.properties ### 依赖(DEPENDENT)节点 - 依赖节点,就是**依赖检查节点**。比如A流程依赖昨天的B流程执行成功,依赖节点会去检查B流程在昨天是否有执行成功的实例。 - + > 拖动工具栏中的![PNG](https://analysys.github.io/easyscheduler_docs_cn/images/toolbar_DEPENDENT.png)任务节点到画板中,双击任务节点,如下图:

- + > 依赖节点提供了逻辑判断功能,比如检查昨天的B流程是否成功,或者C流程是否执行成功。 - +

@@ -536,7 +543,7 @@ conf/common/hadoop.properties ### SPARK节点 - 通过SPARK节点,可以直接直接执行SPARK程序,对于spark节点,worker会使用`spark-submit`方式提交任务 - + > 拖动工具栏中的![PNG](https://analysys.github.io/easyscheduler_docs_cn/images/toolbar_SPARK.png)任务节点到画板中,双击任务节点,如下图:

@@ -563,7 +570,7 @@ conf/common/hadoop.properties > 拖动工具栏中的![PNG](https://analysys.github.io/easyscheduler_docs_cn/images/toolbar_MR.png)任务节点到画板中,双击任务节点,如下图: 1. JAVA程序 - +

@@ -592,7 +599,7 @@ conf/common/hadoop.properties ### Python节点 - 使用python节点,可以直接执行python脚本,对于python节点,worker会使用`python **`方式提交任务。 - + > 拖动工具栏中的![PNG](https://analysys.github.io/easyscheduler_docs_cn/images/toolbar_PYTHON.png)任务节点到画板中,双击任务节点,如下图: