Streaming Data Processing with Apache Kafka and KSQL

7.

Aggregations and Windowing

7.1.

Statefulness in ksqlDB

7.1.1.

Materialized Views

7.1.1.1.

Definition and Use Cases

7.1.1.2.

View Maintenance

7.1.2.

7.1.2.1.

Local State Management

7.1.2.2.

Fault Tolerance for State

7.1.2.3.

State Store Types

7.2.

Aggregating Data

7.2.1.

The GROUP BY Clause

7.2.1.1.

Syntax and Usage

7.2.1.2.

7.2.1.3.

Multiple Column Grouping

7.2.2.

Aggregate Functions

7.2.2.1.

7.2.2.2.

7.2.2.3.

7.2.2.4.

7.2.2.5.

7.2.2.6.

7.2.2.7.

7.2.2.8.

7.2.3.

The HAVING Clause

7.2.3.1.

Filtering Aggregated Results

7.2.3.2.

Post-Aggregation Conditions

7.3.

Windowing Concepts

7.3.1.

Purpose of Windowing

7.3.1.1.

Handling Unbounded Data

7.3.1.2.

Time-Based Aggregation

7.3.1.3.

Memory Management

7.3.2.

Types of Windows

7.3.2.1.

Tumbling Windows

7.3.2.1.1.

Fixed-Size Non-Overlapping

7.3.2.1.2.

7.3.2.2.

Hopping Windows

7.3.2.2.1.

Fixed-Size Overlapping

7.3.2.2.2.

Advance and Size Parameters

7.3.2.3.

Session Windows

7.3.2.3.1.

Dynamic Inactivity-Based

7.3.2.3.2.

Session Gap Configuration

7.3.3.

Grace Period for Late-Arriving Data

7.3.3.1.

Handling Out-of-Order Events

7.3.3.2.

Grace Period Configuration

7.3.4.

Window Retention

7.3.4.1.

7.3.4.2.

Retention Policies

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6. Querying and Transforming Data

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8. Joining Streams and Tables