Esper - Java Event Stream Processor

Esper Reference Documentation

1.1.0


Table of Contents

Preface
1. Technology Overview
1.1. Introduction to CEP and event stream analysis
1.2. CEP and relational databases
1.3. The Esper engine for CEP
2. Configuration
2.1. Programmatic configuration
2.2. Configuration via XML file
2.3. XML Configuration file
2.4. Configuration items
2.4.1. Event type alias to Java class mapping
2.4.2. Class and package imports
2.4.3. Events represented by java.util.Map
2.4.4. Events represented by org.w3c.dom.Node
2.4.4.1. Schema Resource
2.4.4.2. XPath Property
3. API Reference
3.1. API Overview
3.2. Engine Instances
3.3. The Administrative Interface
3.4. The Runtime Interface
3.5. Time-Keeping Events
3.6. Events Received from the Engine
4. Event Representations
4.1. Event Underlying Java Objects
4.2. Event Properties
4.3. Plain Java Object Events
4.3.1. Java Object Event Properties
4.4. java.util.Map Events
4.5. org.w3c.dom.Node XML Events
5. Event Pattern Reference
5.1. Event Pattern Overview
5.2. How to use Patterns
5.2.1. Pattern Syntax
5.2.2. Subscribing to Pattern Events
5.2.3. Pulling Data from Patterns
5.3. Filter Expressions
5.4. Pattern Operators
5.4.1. Every
5.4.2. And
5.4.3. Or
5.4.4. Not
5.4.5. Followed-by
5.5. Guards
5.5.1. timer:within
5.6. Pattern Observers
5.6.1. timer:interval
5.6.2. timer:at
6. EQL Reference
6.1. EQL Introduction
6.2. EQL Syntax
6.3. Choosing Event Properties And Events: the Select Clause
6.3.1. Choosing all event properties: select *
6.3.2. Choosing specific event properties
6.3.3. Expressions
6.3.4. Renaming event properties
6.4. Specifying Event Streams : the From Clause
6.4.1. Filter-based event streams
6.4.1.1. Specifying an event type
6.4.1.2. Specifying event filter criteria
6.4.2. Pattern-based event streams
6.4.3. Specifying views
6.5. Specifying Search Conditions: the Where Clause
6.6. Aggregates and grouping: the Group-by Clause and the Having Clause
6.6.1. Using aggregate functions
6.6.2. Organizing statement results into groups: the Group-by clause
6.6.3. Selecting groups of events: the Having clause
6.6.4. How the stream filter, Where, Group By and Having clauses interact
6.7. Stabilizing and Limiting Output: the Output Clause
6.7.1. Output Clause Options
6.7.2. Group By, Having and Output clause interaction
6.8. Sorting Output: the Order By Clause
6.9. Merging Streams and Continuous Insertion: the Insert Into Clause
6.10. Single-row Function Reference
6.10.1. The Min and Max Functions
6.10.2. The Coalesce Function
6.10.3. The Case Control Flow Function
6.11. Operator Reference
6.11.1. Arithmatic Operators
6.11.2. Logical And Comparsion Operators
6.11.3. Concatenation Operators
6.11.4. Binary Operators
6.12. Build-in views
6.12.1. Window views
6.12.1.1. Length window
6.12.1.2. Time window
6.12.1.3. Externally-timed window
6.12.1.4. Time window buffer
6.12.2. Standard view set
6.12.2.1. Unique
6.12.2.2. Group By
6.12.2.3. Size
6.12.2.4. Last
6.12.3. Statistics views
6.12.3.1. Univariate statistics
6.12.3.2. Regression
6.12.3.3. Correlation
6.12.3.4. Weighted average
6.12.3.5. Multi-dimensional statistics
6.12.4. Extension View Set
6.12.4.1. Sorted Window View
6.13. Joining Event Streams
6.14. Outer Joins
6.15. User-Defined Functions
7. Adapters
7.1. Adapter
8. Indicators
8.1. Intro
8.2. JMX Indicator
9. Architecture
9.1. Overview
9.2. Building and Testing
10. Examples, Tutorials, Case Studies
10.1. Examples Overview
10.2. Market Data Feed Monitor
10.2.1. Input Events
10.2.2. Computing Rates Per Feed
10.2.3. Detecting a Fall-off
10.2.4. Event generator
10.3. Transaction 3-Event Challenge
10.3.1. The Events
10.3.2. Combined event
10.3.3. Real time summary data
10.3.4. Find problems
10.3.5. Event generator
10.4. AutoID RFID Reader
10.5. StockTicker
10.6. MatchMaker
10.7. QualityOfService
10.8. LinearRoad
10.9. StockTick RSI
11. References
11.1. Reference List