Trilobita is a Pregel-like distributed graph processing system implemented to handle large-scale graph processing tasks in a distributed environment efficiently. This is the 50.041 Distributive System group project.

Trilobita is built to handle distributed graph processing tasks, providing a robust and fault-tolerant framework for efficient graph computation. We follow the ideas presented by Pregel,

Throughout the development of Trilobita, we adhere to the following guiding principles.

1. Fault Tolerance: the system should be able to gracefully manage failures of both the master and worker servers, ensuring continuity in task execution and failure handling.
2. Flexibility: users of Trilobita should be empowered to customize their graph processing tasks and assemble operational clusters by using their personal laptops.
3. Consistency: the system should guarantee causal consistency during the computation and fault-handling process, providing a reliable and predictable environment for users.
4. Efficiency: the connection and communication between different machines should be efficient and adapt to varying cluster sizes for optimal performance.

Trilobita is developed by the following group members:

• Guo Yuchen
• Guo Ziniu
• Liang Junyi
• Wang Yanbao
• Xiang Siqi

Trilobita's architecture is structured into three layers: Core, Engine, and Runtime. Each layer builds upon the functionalities of the preceding one, providing a comprehensive and modular design.

Particularly, the relationships between the master, workers, and master replicas are illustrated below.

We implement a rich set of features in Trilobita to empower users with efficiency, reliability, and scalability in distributed graph processing.

• Distributed Graph Processing: WokerServer, MasterServer, TrilobitaEnvironment

• Fault Tolerance for Worker and Master: Heartbeat, Snapshot

• Functionable Instances: Combiner, Aggregator, User Self-defined Functionable

• Server Performance Monitor

• Scalable Cluster and Parallelism

• User-definable APIs: Vertex, Computable, GraphParser, PartitionStrategy

All dependencies required by Trilobita are listed in the maven pom file.

To get started with Trilobita, proceed with these steps.

Clone the Repository:

git clone https://github.com/TsukiSky/Trilobita.git

Install Dependencies:

mvn install

Run Examples:

We implement two examples in the examples module, which can be run by the following sequence.

Note: the examples are run on a local cluster with 3 workers and 1 master.

Example 1: PageRank Algorithm

Navigate to the PageRank example directory: examples\src\main\java\com\trilobita\examples\pagerank

Compile files:

javac *.java

Run Worker Server: (You might need to indicate the Worker Id in the filename)

java WorkerServer.java

Run Master Server:

java MasterServer.java

Example 2: Shortest Path Search Algorithm

Navigate to the Shortest Path Search example directory: examples\src\main\java\com\trilobita\examples\shortestpath

Compile files:

javac *.java

Run Worker Server: (You might need to indicate the Worker Id in the filename)

java WorkerServer.java

Run Master Server:

java MasterServer.java

Our reports can be found on:

• Checkpoint 1 Report
• Checkpoint 2 Report
• Checkpoint 3 report
• Final Report

This project is licensed under the MIT License.