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chore: update for release 1.5
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imbajin committed Nov 6, 2024
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2 changes: 1 addition & 1 deletion NOTICE
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Apache HugeGraph(incubating)
Copyright 2022-2023 The Apache Software Foundation
Copyright 2022-2024 The Apache Software Foundation

This product includes software developed at
The Apache Software Foundation (http://www.apache.org/).
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16 changes: 9 additions & 7 deletions README.md
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[![codecov](https://codecov.io/gh/apache/incubator-hugegraph-computer/branch/master/graph/badge.svg)](https://codecov.io/gh/apache/incubator-hugegraph-computer)
[![Docker Pulls](https://img.shields.io/docker/pulls/hugegraph/hugegraph-computer)](https://hub.docker.com/repository/docker/hugegraph/hugegraph-computer)

The [hugegraph-computer](./computer/README.md) is a distributed graph processing system for hugegraph.
The [hugegraph-computer](./computer/README.md) is a distributed graph processing system for hugegraph.
(Also, the in-memory computing engine(vermeer) is on the way 🚧)

## Learn More

The [project homepage](https://hugegraph.apache.org/docs/) contains more information about hugegraph-computer.
The [project homepage](https://hugegraph.apache.org/docs/quickstart/hugegraph-computer/) contains more information about hugegraph-computer.

And here are links of other repositories:
1. [hugegraph-server](https://github.com/apache/hugegraph) (graph's core component - OLTP server)
2. [hugegraph-toolchain](https://github.com/apache/hugegraph-toolchain) (include loader/dashboard/tool/client)
3. [hugegraph-commons](https://github.com/apache/hugegraph-commons) (include common & rpc module)
4. [hugegraph-website](https://github.com/apache/hugegraph-doc) (include doc & website code)
1. [hugegraph](https://github.com/apache/hugegraph) (graph's core component - Graph server + PD + Store)
2. [hugegraph-toolchain](https://github.com/apache/hugegraph-toolchain) (graph tools **[loader](https://github.com/apache/incubator-hugegraph-toolchain/tree/master/hugegraph-loader)/[dashboard](https://github.com/apache/incubator-hugegraph-toolchain/tree/master/hugegraph-hubble)/[tool](https://github.com/apache/incubator-hugegraph-toolchain/tree/master/hugegraph-tools)/[client](https://github.com/apache/incubator-hugegraph-toolchain/tree/master/hugegraph-client)**)
3. [hugegraph-ai](https://github.com/apache/incubator-hugegraph-ai) (integrated **Graph AI/LLM/KG** system)
4. [hugegraph-website](https://github.com/apache/hugegraph-doc) (**doc & website** code)


## Note

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- Feedback Email: [dev@hugegraph.apache.org](mailto:dev@hugegraph.apache.org) ([subscriber](https://hugegraph.apache.org/docs/contribution-guidelines/subscribe/) only)
- WeChat public account: Apache HugeGraph, welcome to scan this QR code to follow us.

<img src="https://github.com/apache/incubator-hugegraph-doc/blob/master/assets/images/wechat.png?raw=true" alt="QR png" width="350"/>
<img src="https://github.com/apache/hugegraph-doc/blob/master/assets/images/wechat.png?raw=true" alt="QR png" width="350"/>

6 changes: 3 additions & 3 deletions computer/README.md
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Expand Up @@ -5,8 +5,8 @@ The hugegraph-computer is a distributed graph processing system for hugegraph. I
## Features

- Support distributed MPP graph computing, and integrates with HugeGraph as graph input/output storage.
- Based on BSP(Bulk Synchronous Parallel) model, an algorithm performs computing through multiple parallel iterations, every iteration is a superstep.
- Based on BSP (Bulk Synchronous Parallel) model, an algorithm performs computing through multiple parallel iterations, every iteration is a superstep.
- Auto memory management. The framework will never be OOM(Out of Memory) since it will split some data to disk if it doesn't have enough memory to hold all the data.
- The part of edges or the messages of super node can be in memory, so you will never lose it.
- The part of edges or the messages of supernode can be in memory, so you will never lose it.
- You can load the data from HDFS or HugeGraph, output the results to HDFS or HugeGraph, or adapt any other systems manually as needed.
- Easy to develop a new algorithm. You just need to focus on a vertex only processing just like as in a single server, without worrying about message transfer and memory/storage management.
- Easy to develop a new algorithm. You need to focus on a vertex only processing just like as in a single server, without worrying about message transfer and memory/storage management.
17 changes: 7 additions & 10 deletions computer/pom.xml
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</prerequisites>

<properties>
<!-- TODO: update the version after toolchain v1.2 fixed -->
<revision>1.3.0</revision>
<hugegraph-common-version>1.3.0</hugegraph-common-version>
<hugegraph-client-version>1.3.0</hugegraph-client-version>
<hugegraph-rpc-version>1.3.0</hugegraph-rpc-version>
<hugegraph-loader-version>1.3.0</hugegraph-loader-version>
<revision>1.5.0</revision>
<hugegraph-commons-version>${revision}</hugegraph-commons-version>
<hugegraph-toolchain-version>${revision}</hugegraph-toolchain-version>
<project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
<top.level.dir>${project.basedir}/..</top.level.dir>
<release.name>hugegraph-computer</release.name>
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<dependency>
<groupId>org.apache.hugegraph</groupId>
<artifactId>hugegraph-common</artifactId>
<version>${hugegraph-common-version}</version>
<version>${hugegraph-commons-version}</version>
</dependency>
<dependency>
<groupId>org.apache.hugegraph</groupId>
<artifactId>hugegraph-rpc</artifactId>
<version>${hugegraph-rpc-version}</version>
<version>${hugegraph-commons-version}</version>
<exclusions>
<!-- conflict with etcd -->
<exclusion>
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<dependency>
<groupId>org.apache.hugegraph</groupId>
<artifactId>hugegraph-client</artifactId>
<version>${hugegraph-client-version}</version>
<version>${hugegraph-toolchain-version}</version>
</dependency>
<dependency>
<groupId>org.apache.hugegraph</groupId>
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<dependency>
<groupId>org.apache.hugegraph</groupId>
<artifactId>hugegraph-loader</artifactId>
<version>${hugegraph-loader-version}</version>
<version>${hugegraph-toolchain-version}</version>
<exclusions>
<exclusion>
<groupId>org.apache.hive</groupId>
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