Useful Links
Computer Science
Stream Processing
Streaming Data Processing with Apache Kafka and KSQL
1. Introduction to Stream Processing
2. Fundamentals of Apache Kafka
3. Introduction to ksqlDB
4. Setting Up the Environment
5. ksqlDB Data Definition Language (DDL)
6. Querying and Transforming Data
7. Aggregations and Windowing
8. Joining Streams and Tables
9. Advanced ksqlDB Features
10. Building Real-Time Applications
11. Operations and Production Considerations
Joining Streams and Tables
Join Types in ksqlDB
INNER JOIN
Matching Records Only
LEFT JOIN
Left Side Preservation
RIGHT JOIN
Right Side Preservation
FULL OUTER JOIN
All Records Preservation
Common Join Patterns
Stream-Stream Joins
Use Cases and Limitations
Temporal Constraints
Stream-Table Joins
Enriching Streams with Reference Data
Lookup Patterns
Table-Table Joins
Combining State from Multiple Tables
Foreign Key Joins
Join Windowing Requirements
Time Constraints for Joins
Window Size Configuration
Join Window Types
Partitioning for Joins
Key Alignment Requirements
Repartitioning Streams
Co-partitioning
Performance Implications
Previous
7. Aggregations and Windowing
Go to top
Next
9. Advanced ksqlDB Features