<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>HugeGraph Computing (OLAP) on Apache HugeGraph</title><link>https://hugegraph.apache.org/versions/1.7/docs/quickstart/computing/</link><description>Recent content in HugeGraph Computing (OLAP) on Apache HugeGraph</description><generator>Hugo</generator><language>en-US</language><lastBuildDate>Wed, 19 Nov 2025 15:15:54 +0800</lastBuildDate><atom:link href="https://hugegraph.apache.org/versions/1.7/docs/quickstart/computing/index.xml" rel="self" type="application/rss+xml"/><item><title>HugeGraph-Vermeer Quick Start</title><link>https://hugegraph.apache.org/versions/1.7/docs/quickstart/computing/hugegraph-vermeer/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://hugegraph.apache.org/versions/1.7/docs/quickstart/computing/hugegraph-vermeer/</guid><description>&lt;h2 id="1-overview-of-vermeer"&gt;1. Overview of Vermeer&#10;&lt;/h2&gt;&#10;&lt;h3 id="11-architecture"&gt;1.1 Architecture&#10;&lt;/h3&gt;&#10;&lt;p&gt;Vermeer is a high-performance, memory-first graph computing framework written in &lt;code&gt;Go&lt;/code&gt; (start once, execute any task), supporting ultra-fast computation of 15+ OLAP graph algorithms (most tasks complete in seconds to minutes), with master and worker roles. Currently, there is only one master (HA can be added), and there can be multiple workers.&lt;/p&gt;&#10;&lt;p&gt;The master is responsible for communication, forwarding, and aggregation, with minimal computation and resource usage. Workers are computation nodes used to store graph data and run computation tasks, consuming a large amount of memory and CPU. The grpc and rest modules handle internal communication and external calls, respectively.&lt;/p&gt;</description></item><item><title>HugeGraph-Computer Quick Start</title><link>https://hugegraph.apache.org/versions/1.7/docs/quickstart/computing/hugegraph-computer/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://hugegraph.apache.org/versions/1.7/docs/quickstart/computing/hugegraph-computer/</guid><description>&lt;h2 id="1-hugegraph-computer-overview"&gt;1 HugeGraph-Computer Overview&#10;&lt;/h2&gt;&#10;&lt;p&gt;The &lt;a href="https://github.com/apache/incubator-hugegraph-computer"&gt;&lt;code&gt;HugeGraph-Computer&lt;/code&gt;&lt;/a&gt; is a distributed graph processing system for HugeGraph (OLAP). It is an implementation of &lt;a href="https://kowshik.github.io/JPregel/pregel_paper.pdf"&gt;Pregel&lt;/a&gt;. It runs on a Kubernetes(K8s) framework.(It focuses on supporting graph data volumes of hundreds of billions to trillions, using disk for sorting and acceleration, which is one of the biggest differences from Vermeer)&lt;/p&gt;&#10;&lt;h3 id="features"&gt;Features&#10;&lt;/h3&gt;&#10;&lt;ul&gt;&#10;&lt;li&gt;Support distributed MPP graph computing, and integrates with HugeGraph as graph input/output storage.&lt;/li&gt;&#10;&lt;li&gt;Based on the BSP (Bulk Synchronous Parallel) model, an algorithm performs computing through multiple parallel iterations; every iteration is a superstep.&lt;/li&gt;&#10;&lt;li&gt;Auto memory management. The framework will never be OOM(Out of Memory) since it will split some data to disk if it doesn&amp;rsquo;t have enough memory to hold all the data.&lt;/li&gt;&#10;&lt;li&gt;The part of edges or the messages of super node can be in memory, so you will never lose it.&lt;/li&gt;&#10;&lt;li&gt;You can load the data from HDFS or HugeGraph, or any other system.&lt;/li&gt;&#10;&lt;li&gt;You can output the results to HDFS or HugeGraph, or any other system.&lt;/li&gt;&#10;&lt;li&gt;Easy to develop a new algorithm. You just need to focus on vertex-only processing just like as in a single server, without worrying about message transfer and memory/storage management.&lt;/li&gt;&#10;&lt;/ul&gt;&#10;&lt;h2 id="2-dependency-for-buildingrunning"&gt;2 Dependency for Building/Running&#10;&lt;/h2&gt;&#10;&lt;h3 id="21-install-java-11-jdk-11"&gt;2.1 Install Java 11 (JDK 11)&#10;&lt;/h3&gt;&#10;&lt;p&gt;&lt;strong&gt;Must&lt;/strong&gt; use ≥ &lt;code&gt;Java 11&lt;/code&gt; to run &lt;code&gt;Computer&lt;/code&gt;, and configure by yourself.&lt;/p&gt;</description></item></channel></rss>