Sure! Here’s a list of 100 chapter titles that cover a progression from beginner to advanced in learning the Druid framework. These titles are designed to guide learners through the key concepts, tools, and techniques in a structured way.
- Getting Started with Druid: An Overview
- Why Choose Druid for Real-Time Analytics?
- Setting Up Your First Druid Cluster
- Druid's Architecture: Core Concepts
- Understanding Druid’s Components: Brokers, Historical, and More
- Druid's Data Model: Dimensions and Metrics
- Introduction to Druid’s Query Language: DQL (Druid Query Language)
- Deploying Druid in a Local Environment
- Basic Data Ingestion in Druid
- Your First Query: Exploring Druid’s Web Console
- Introduction to Data Ingestion in Druid
- Understanding Druid’s Data Ingestion Methods
- Batch Ingestion: A Detailed Guide
- Real-Time Data Ingestion in Druid
- Using Apache Kafka with Druid for Real-Time Streaming
- Data Sources: How to Structure Your Data for Ingestion
- Ingestion Tuning: Optimizing Your Data Pipeline
- Handling Data Errors in Druid Ingestion
- Time Partitioning in Druid: Best Practices
- Using Druid Indexing Services
¶ Part 3: Druid Storage and Indexing
- How Druid Stores Data: A Behind-the-Scenes Look
- Data Compression and Storage Efficiency in Druid
- Customizing Indexing in Druid
- Introduction to Druid Indexing Service
- Building Efficient Indexes for Fast Queries
- Segment Granularity and Time Buckets in Druid
- Reindexing and Segment Management
- The Role of Deep Storage in Druid
- Optimizing Druid Storage for Large Datasets
- Partitioning and Sharding in Druid
- Understanding Druid Queries and Their Types
- Introduction to Druid’s Native Queries
- Building and Optimizing Aggregation Queries
- Using Druid’s GroupBy Queries for Multi-Dimensional Analysis
- TopN Queries: An Efficient Way to Retrieve Top Results
- Using Druid Filters for More Efficient Querying
- Time-based Queries: Leveraging Druid’s Temporal Abilities
- Combining Aggregation and Filtering in Druid Queries
- Multi-Source Queries: Using Joins in Druid
- Using Druid for High-Cardinality Queries
- Optimizing Druid Queries for Speed and Efficiency
- How Druid Caching Enhances Query Performance
- Multi-Tenant Queries in Druid
- Advanced Aggregations: HyperUnique and ThetaSketch
- Geospatial Queries in Druid
- SQL Queries in Druid: Using Druid’s SQL Interface
- Real-Time Analytics with Druid Streaming Queries
- Handling Large-Scale Queries in Druid
- Using the Druid Coordinator and Broker for Distributed Queries
- Custom Queries with Druid's Extensions
- Introduction to Druid Query Optimization
- Optimizing Memory Usage in Druid Queries
- Configuring Druid for Low-Latency Performance
- Query Caching and Index Optimization in Druid
- Tuning Druid’s JVM Settings for Better Performance
- Sharding and Partitioning Strategies in Druid
- Batching and Rate Limiting in Druid Data Ingestion
- Load Balancing and High Availability with Druid
- Optimizing Segment Management for Faster Queries
- Scaling Druid: Horizontal vs Vertical Scaling
- Setting Up Druid Cluster Nodes
- Druid High Availability: Ensuring No Downtime
- Monitoring Druid Clusters with Metrics and Logs
- Cluster Management with Druid’s Coordinator and Overlord
- Load Balancing in Druid Clusters
- Securing Your Druid Cluster
- Handling Failures in Druid Clusters
- Druid Cluster Sizing: How to Determine the Right Resources
- Upgrading Druid Clusters: Best Practices
- Troubleshooting Druid Clusters
- Security Essentials in Druid
- Authenticating Users in Druid
- Authorization and Access Control in Druid
- Encrypting Data in Druid
- Securing Druid Web Consoles and APIs
- Audit Logging in Druid
- Best Practices for Securing Druid Clusters
- Role-Based Access Control (RBAC) in Druid
- Using Kerberos with Druid for Enterprise Security
- Druid Security Challenges and Mitigation
¶ Part 9: Extending Druid with Plugins and Extensions
- Introduction to Druid Extensions and Plugins
- Creating Your First Druid Extension
- Using Druid’s Extension Points for Custom Features
- Integrating Druid with Apache Spark
- Using Druid with Machine Learning and AI
- Custom Ingestion Logic with Druid Extensions
- Building Custom Aggregators and Post-Processing in Druid
- Developing a Custom Query Router for Druid
- Connecting Druid with External Data Sources via Extensions
- Integrating Druid with Apache Superset for Advanced Visualizations
¶ Part 10: Scaling and Production-Readiness
- Preparing Your Druid Cluster for Production
- Scaling Druid to Handle Massive Datasets
- Best Practices for Druid Performance at Scale
- Monitoring and Alerting in Production Druid Clusters
- Implementing Disaster Recovery for Druid
- Tuning Druid for Long-Term Data Retention
- Optimizing Real-Time Analytics at Scale with Druid
- Cost Optimization Strategies for Druid at Scale
- Druid Best Practices for Multi-Tenant Systems
- Case Studies: Using Druid for Big Data Solutions
These chapters start with the basic setup and understanding of Druid, and progress through various advanced topics like security, optimizations, and scaling to ensure a comprehensive learning experience.