From b4ee0a5dcfdda3ff61878146f0d68628d41ce7ff Mon Sep 17 00:00:00 2001 From: easyscheduler Date: Wed, 17 Jul 2019 20:05:07 +0800 Subject: [PATCH] Update README.md --- README.md | 33 ++++++++++++++++++--------------- 1 file changed, 18 insertions(+), 15 deletions(-) diff --git a/README.md b/README.md index c5116d4948..9d45e887e1 100644 --- a/README.md +++ b/README.md @@ -4,22 +4,25 @@ Easy Scheduler > Easy Scheduler for Big Data -** Design features: ** A distributed and easy-to-expand visual DAG workflow scheduling system. Dedicated to solving the complex dependencies in the data processing process, making the scheduling system `out of the box` in the data processing process. +### Design features: + +A distributed and easy-to-expand visual DAG workflow scheduling system. Dedicated to solving the complex dependencies in the data processing process, making the scheduling system `out of the box` in the data processing process. Its main objectives are as follows: - - Associate the Tasks according to the dependencies of the tasks in a DAG graph, which can visualize the running state of task in real time. - - Support for many task types: Shell, MR, Spark, SQL (mysql, postgresql, hive, sparksql), Python, Sub_Process, Procedure, etc. - - Support process scheduling, dependency scheduling, manual scheduling, manual pause/stop/recovery, support for failed retry/alarm, recovery from specified nodes, Kill task, etc. - - Support process priority, task priority and task failover and task timeout alarm/failure - - Support process global parameters and node custom parameter settings - - Support online upload/download of resource files, management, etc. Support online file creation and editing - - Support task log online viewing and scrolling, online download log, etc. - - Implement cluster HA, decentralize Master cluster and Worker cluster through Zookeeper - - Support online viewing of `Master/Worker` cpu load, memory, cpu - - Support process running history tree/gantt chart display, support task status statistics, process status statistics - - Support for complement - - Support for multi-tenant - - Support internationalization - - There are more waiting partners to explore + + - Associate the Tasks according to the dependencies of the tasks in a DAG graph, which can visualize the running state of task in real time. + - Support for many task types: Shell, MR, Spark, SQL (mysql, postgresql, hive, sparksql), Python, Sub_Process, Procedure, etc. + - Support process scheduling, dependency scheduling, manual scheduling, manual pause/stop/recovery, support for failed retry/alarm, recovery from specified nodes, Kill task, etc. + - Support process priority, task priority and task failover and task timeout alarm/failure + - Support process global parameters and node custom parameter settings + - Support online upload/download of resource files, management, etc. Support online file creation and editing + - Support task log online viewing and scrolling, online download log, etc. + - Implement cluster HA, decentralize Master cluster and Worker cluster through Zookeeper + - Support online viewing of `Master/Worker` cpu load, memory, cpu + - Support process running history tree/gantt chart display, support task status statistics, process status statistics + - Support for complement + - Support for multi-tenant + - Support internationalization + - There are more waiting partners to explore ### Comparison with similar scheduler systems