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Based on the DEBS 2015 Tutorial "Tutorial 1: Patterns for Realtime Streaming Analytics" by Srinath Perera, Sriskandarajah Suhothayan we will show how Odysseus can be used for the following streaming analytics pattern.

Pattern 1: Preprocessing

Filtering some events

Reshaping a stream by removing, renaming, or adding new attributes to events in the stream

Splitting and combining attributes in a stream

Transforming attributes

Pattern 2: Alerts and Thresholds

This pattern detects a condition and generates alerts based on a condition. (e.g., Alarm on high temperature). These alerts can be based on a simple value or more complex conditions such as rate of increase etc.

Pattern 3: Simple Counting and Counting with Windows

Pattern 4: Joining Event Streams

Pattern 5: Data Correlation,Missing Events, and Erroneous Data

Pattern 6: Interacting with Databases

Pattern 7: Detecting Temporal Event Sequence Patterns

Pattern 8: Tracking

Pattern 9: Detecting Trends

Pattern 10: Running the Same Query in Batch and Realtime Pipelines

Pattern 11: Detecting and Switching to Detailed Analysis

Pattern 12: Using a Model

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In the following we will show different processing scenarios. All scenarios are build with Procedural Query Language (PQL) and for many cases we use the Nexmark scenario (Getting Started with Nexmark). You should also have installed the nexmark source (Simple Query Processing).

All queries defined in Odysseus are data pipelines, i.e. data is received from one operator, processed and send to the next operator. By this, complex processing pipelines can be built.