[GitHub] [incubator-hugegraph-computer] javeme commented on a diff in pull request #189: chore: update a string of ci configs & gitignore & REAME

[GitBox <gi...@apache.org>]

javeme commented on code in PR #189:
URL: https://github.com/apache/incubator-hugegraph-computer/pull/189#discussion_r1005812038


##########
.github/workflows/codeql-analysis.yml:
##########
@@ -7,7 +7,7 @@ on:
     branches: [ master, release-*, v0.* ]
   pull_request:
     # The branches below must be a subset of the branches above
-    branches: [ master ]
+    # branches: [ master ] # enable it in all PR

Review Comment:
   branches=empty means any pr? if so please update the comment at line 9



##########
.github/workflows/ci.yml:
##########
@@ -5,14 +5,8 @@ on:
     branches:
       - master
       - /^release-.*$/
-      - /^test-.*$/
       - /^v[0-9]\..*$/
   pull_request:
-    branches:

Review Comment:
   means any branch if keep none?



##########
README.md:
##########
@@ -5,19 +5,31 @@
 [![codecov](https://codecov.io/gh/hugegraph/hugegraph-computer/branch/master/graph/badge.svg)](https://codecov.io/gh/hugegraph/hugegraph-computer)
 [![Docker Pulls](https://img.shields.io/docker/pulls/hugegraph/hugegraph-builtin-algorithms)](https://hub.docker.com/repository/docker/hugegraph/hugegraph-builtin-algorithms)
 
-hugegraph-computer is a distributed graph processing system for hugegraph. It is an implementaion of [Pregel](https://kowshik.github.io/JPregel/pregel_paper.pdf). It runs on Kubernetes or YARN framework.
+hugegraph-computer is a distributed graph processing system for hugegraph. It is an implementation of [Pregel](https://kowshik.github.io/JPregel/pregel_paper.pdf). It runs on Kubernetes or YARN framework.
 
 ## Features
 
 - Based on BSP(Bulk Synchronous Parallel) model, every iteration is a superstep.
-- Auto memory management. The framework will spilt some data to disk, the framework will never OOM(Out of Memory).
-- The the part of edges or the messages of super node can be in memory, so you will never loss it.
+- Auto memory management. The framework will split some data to disk, the framework will never OOM(Out of Memory).
+- The part of edges or the messages of super node can be in memory, so you will never lose it.
 - You can output the result to HDFS or HugeGraph, or any other system.
-- Easy to develop a new algotirhm. You need to focus on a vertex only, not to worry about messages transfering and memory.
+- Easy to develop a new algorithm. You need to focus on a vertex only, not to worry about messages transferring and memory.
 
 ## Learn More
 
-The [project homepage](https://hugegraph.github.io/hugegraph-doc/) contains more information about hugegraph-computer. 
+The [project homepage](https://hugegraph.apache.org/docs/) contains more information about hugegraph-computer.
+
+And here are links of other repositories:
+1. [hugegraph-server](https://github.com/apache/incubator-hugegraph) (graph's core component - OLTP server)

Review Comment:
   ditto



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