Creating a distributed 3-node system involves setting up a network where data is distributed across three different nodes (servers). This type of architecture can be useful for load balancing, fault tolerance, and scalability. Below, I outline the steps to set up a basic 3-node distributed system and discuss some key concepts related to data distribution at the distribution level.

1. Choosing the Technology Stack

First, choose the technology stack for your distributed system. Some popular options include:

• Distributed databases: Cassandra, MongoDB, or CockroachDB.
• Distributed file systems: Hadoop HDFS, GlusterFS.
• Distributed computing frameworks: Apache Kafka, Apache Spark.

For this example, let's consider using Apache Cassandra, a distributed NoSQL database designed for high availability and scalability.

2. Setting Up the Nodes

Node Configuration

Starting the Nodes

3. Data Distribution

Replication Strategy

• SimpleStrategy: Suitable for single data center setups.
• NetworkTopologyStrategy: Suitable for multiple data centers, providing better control over the replication.

Example for NetworkTopologyStrategy:

sqlCopier le codeCREATE KEYSPACE mykeyspace WITH REPLICATION = { 'class': 'NetworkTopologyStrategy', 'datacenter1': 2 };

Consistency Levels

Decide on the consistency level for read and write operations:

• ONE: Ensures data is written to at least one node.
• QUORUM: Ensures data is written to the majority of nodes.
• ALL: Ensures data is written to all nodes.

Example write operation with QUORUM consistency:

sqlCopier le codeINSERT INTO mytable (id, data) VALUES (1, 'sample data') USING CONSISTENCY QUORUM;

4. Load Balancing and Fault Tolerance

Cassandra automatically handles data distribution and load balancing using the partitioner specified in cassandra.yaml (default is Murmur3Partitioner). Data is distributed across nodes based on the partition key, ensuring even distribution and fault tolerance.

5. Monitoring and Maintenance

• Monitoring Tools: Use tools like nodetool, DataStax OpsCenter, or Grafana for monitoring the health and performance of your cluster.
• Regular Maintenance: Regularly perform operations like repair, cleanup, and backup to ensure data integrity and availability.

Example Data Distribution

Assume you have a table with a primary key id and you insert three records:

sqlCopier le codeINSERT INTO mytable (id, data) VALUES (1, 'data1'); INSERT INTO mytable (id, data) VALUES (2, 'data2'); INSERT INTO mytable (id, data) VALUES (3, 'data3');

Cassandra will distribute these records across the three nodes based on the partition key (id). Each node will store part of the data, ensuring that no single node holds all the data, providing redundancy and high availability.

Conclusion

Setting up a 3-node distributed system involves configuring each node correctly, ensuring proper data distribution, and maintaining the cluster for optimal performance. By leveraging the replication and consistency features of a distributed database like Cassandra, you can achieve a robust and scalable system.