Description

Introduction

kdb+ is a high-performance time-series database widely used in capital markets, telecom, energy, and real-time analytics systems. One of its most powerful capabilities is Inter-Process Communication (IPC), which enables processes to communicate efficiently across local and remote systems.

This training provides a comprehensive and hands-on understanding of IPC in kdb+, covering synchronous and asynchronous messaging, client-server architecture, handle management, authentication, serialization, performance tuning, and secure communication. Participants will learn how to build distributed kdb+ systems where processes interact seamlessly for data ingestion, querying, streaming, and real-time analytics.

By the end of this course, learners will be able to design, implement, and troubleshoot IPC-based distributed architectures in kdb+ environments.

Prerequisites

1. Basic knowledge of q programming language
2. Familiarity with kdb+ database concepts (tables, in-memory vs on-disk storage)
3. Understanding of client-server architecture fundamentals
4. Basic knowledge of networking concepts (IP, ports, sockets)
5. Experience working in Linux/Unix environments

Table of Contents

Module 1: Overview of IPC in kdb+

1. What is IPC?
2. Role of IPC in distributed kdb+ systems
3. IPC architecture in kdb+
4. Process types (tickerplant, RDB, HDB, gateways)
5. Use cases in real-time data systems

Module 2: kdb+ Process Architecture

1. Starting kdb+ with a listening port
2. Understanding handles
3. Connection lifecycle
4. Process discovery and communication flow
5. Local vs remote IPC

Module 3: Synchronous Communication

1. Blocking calls using handle (h"query")
2. Request-response patterns
3. Error handling in synchronous calls
4. Performance considerations
5. Practical lab: Building a synchronous client-server model

Module 4: Asynchronous Communication

1. Non-blocking messaging
2. Fire-and-forget patterns
3. Message queuing and event-driven processing
4. Callback handling
5. Practical lab: Streaming data using async IPC

Module 5: Serialization & Data Transfer

1. How kdb+ serializes objects
2. Data types and IPC transmission
3. Compression techniques
4. Large message handling
5. Optimizing network usage

Module 6: Authentication & Security

1. User authentication in kdb+
2. Access control
3. Securing IPC ports
4. SSL/TLS setup
5. Best practices for secure distributed systems

Module 7: Error Handling & Debugging

1. Common IPC errors
2. Timeout handling
3. Monitoring active connections
4. Logging strategies
5. Troubleshooting connectivity issues

Module 8: Performance Optimization

1. Latency analysis
2. Connection pooling
3. Asynchronous load balancing
4. Scaling distributed kdb+ architectures
5. Benchmarking IPC performance

Module 9: Distributed System Patterns

1. Tickerplant architecture with IPC
2. Gateway query routing
3. Real-time streaming pipelines
4. Fault tolerance strategies
5. High-availability design patterns

Module 10: Hands-on Capstone Project

1. Designing a distributed market data system
2. Implementing IPC-based ingestion
3. Real-time querying via gateway
4. Performance tuning and testing
5. Final review and best practices