Introduction

In this blog post, we will explore how to use Cascading Replication with Psycopg2 in Python. Cascading Replication is a feature in PostgreSQL that allows for the replication of data from one database to another in a hierarchical manner.

What is Cascading Replication?

Cascading Replication is a technique used to replicate data from a primary database server to multiple secondary servers. The primary server continuously streams the changes made to the data to the secondary servers, which in turn replicate the changes to their own replicas. This creates a cascading effect, where changes are propagated in a hierarchical manner.

Setting up Psycopg2

Before we can start using Cascading Replication, we need to set up Psycopg2, a popular PostgreSQL adapter for Python.

import psycopg2

# Establish a connection to the primary database
conn_primary = psycopg2.connect(
    host="primary_host",
    port=5432,
    dbname="primary_db",
    user="primary_user",
    password="primary_password"
)

# Establish a connection to the secondary database
conn_secondary = psycopg2.connect(
    host="secondary_host",
    port=5432,
    dbname="secondary_db",
    user="secondary_user",
    password="secondary_password"
)

Make sure to replace the placeholder values with the actual connection details for your primary and secondary databases.

Enabling Cascading Replication

To enable Cascading Replication, we need to configure the PostgreSQL server.

1. Open the postgresql.conf file on the primary server:

   sudo nano /etc/postgresql/{version}/main/postgresql.conf
   

2. Uncomment the following line to enable streaming replication:

   #wal_level = replica # Uncomment this line
   

3. Save and close the file, then restart the PostgreSQL service:

   sudo service postgresql restart
   

Creating a Replication Slot

A replication slot is a logical replication mechanism that provides a stable point in the replication stream. We need to create a replication slot on the primary server and connect to it from the secondary server.

# Create a replication slot on the primary server
cursor_primary = conn_primary.cursor()
cursor_primary.execute("SELECT * FROM pg_create_physical_replication_slot('replication_slot_name')")
conn_primary.commit()

# Connect to the replication slot on the secondary server
cursor_secondary = conn_secondary.cursor()
cursor_secondary.execute("CREATE_REPLICATION_SLOT replication_slot_name LOGICAL pgoutput")
conn_secondary.commit()

Replace 'replication_slot_name' with a name of your choice for the replication slot.

Starting Replication

With the replication slot in place, we can start replicating the data from the primary server to the secondary server.

# Start the replication process
cursor_secondary.execute("START_REPLICATION SLOT replication_slot_name")
conn_secondary.commit()

# Continuously stream and process the changes
while True:
    message = conn_secondary.poll()
    if message:
        process_message(message)

In the above code snippet, we use a loop to continuously process the changes being streamed from the primary server to the secondary server. The process_message() function should be implemented to handle the replication messages according to your application’s logic.

Conclusion

By utilizing Cascading Replication with Psycopg2 in Python, we can easily replicate data from a primary database to one or more secondary databases. This hierarchical replication strategy ensures that changes to the data are propagated efficiently, providing a robust and scalable solution.

Remember to follow the PostgreSQL documentation to configure the servers correctly and tailor the implementation according to your specific use case. Happy cascading replication!