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Oracle Java CAPS Intelligent Event Processor (IEP) User's Guide Java CAPS Documentation |
Designing Intelligent Event Processor (IEP) Projects
Intelligent Event Processor Overview
Complex Event Processing and Event Stream Processing
IEP Design-Time and Runtime Components
Creating an Intelligent Event Processing Module Project
To Create an Intelligent Event Processing Module Project
To Add an Event Processor to the Project
Adding and Configuring IEP Operators
To Add IEP Operators to an Event Processor
To Configure IEP Operators in an Event Processor
Disabling the Generation of Bindings and Services
To Disable the Generation of Bindings and Services
Creating and Deploying the Composite Application Project
To Create a Composite Application Project
To Add the IEP Module Project to the Composite Application Project
To Define the Binding Components and Connections
To Deploy the Composite Application Project
IEP Operator Inputs and Outputs
Correlation and Filter Operators
To Create a Relation Map Operator
To Create a Stream Projection and Filter Operator
To Create a Tuple Serial Correlation Operator
To Create an External Table Polling Stream Operator
To Create a Replay Stream Operator
To Create a Stream Input Operator
To Create a Table Input Operator
To Create a Batched Stream Output Operator
To Create an Invoke Stream Operator
To Create a Relation Output Operator
To Enable the Save Stream Operator Dynamically at Runtime
To Disable the Save Stream Operator Dynamically at Runtime
To Create a Stream Output Operator
To Create a Table Output Operator
To Create a Delete Stream Operator
To Create an Insert Stream Operator
To Create a Notification Stream Operator
To Create a Relation Stream Operator
To Create an Intersect Operator
To Create a Union All Operator
To Create a Contiguous Order Operator:
To Create a Gap Window Operator:
To Create an Attribute Based Window Operator
To Create a Partitioned Window Operator
To Create a Time Based Window Operator
To Create a Tuple Based Window Operator
WSDL Documents in IEP Module Projects
Data Types in the WSDL Document
Message Objects in the WSDL Document
Bindings and Services in the WSDL Document
Generating Concrete WSDL Documents
Generating Abstract WSDL Documents
Understanding the IEP Database
Configuring the IEP Database to Use Oracle
To Create the IEP User in the Oracle Database
To Install the Oracle Database Driver in the Application Server
To Create the Non-XA Connection Pool
To Create the Non-XA JDBC Resource
To Create the XA Connection Pool
To Create the XA JDBC Resource
To Enable Automatic Recovery of XA Transactions
To Configure the IEP Service Engine to Use the JDBC Resources
To Restart the IEP Service Engine and Create the Database Tables
Configuring the IEP Database to Use MySQL
To Create the IEP User in the MySQL Database
To Install the MySQL Database Driver in the Application Server
To Create the Non-XA Connection Pool
To Create the Non-XA JDBC Resource
To Create the XA Connection Pool
To Create the XA JDBC Resource
To Enable Automatic Recovery of XA Transactions
To Configure the IEP Service Engine to Use the JDBC Resources
To Restart the IEP Service Engine and Create the Database Tables
IEP Service Engine-Specific Database Tables
Event Process-Specific Database Tables
Operator-Specific Database Tables
Configuring Message Reliability in an IEP Module Project
Aggregator operators enable you to aggregate data and to perform additional operations on that data to obtain output.
The following table lists the input and output for each operator.
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The Relation Aggregator operator takes as input the output of a relation, treats that output as if it were a database table, and performs a SQL SELECT on that table. The Relation Aggregator operator issues output in the form of a relation.
Use the Relation Aggregator operator when you want to perform SQL operations on a relation.
The property editor opens with the default name of the Relation Aggregator operator and the output schema name populated. The Property Window displays the schema of the data that is input to the Relation Aggregator operator.
Any attribute that you specify must appear in the group-by clause. Attributes that you select as expression entries must be in the form of an attribute name, a literal, or an aggregate function supported by the database you use. Examples include COUNT, MAX, MIN, and AVG.
To save some typing, you can drag input attribute field names from the Inputs area into the Expression field.
The Time Based Aggregator operator performs statistical analysis within a specified amount of time that you provide as a size, which is period of time over which you can perform a calculation, or the time slot. Increment specifies the frequency of the calculation; that is, how often you calculate the statistical analysis.
Assume that you want to calculate a stock price's 20–day moving average. You can supply a size of 20 in the property editor, and an increment that specifies how often you want to perform that calculation (for example, once a day).
Statistics that you can compute via SQL statements in the property editor of the Time Based Aggregator operator include:
Sum
Average
Minimum
Maximum
COUNT
Use the Time Based Aggregator operator when you want to perform real-time statistical analysis. You can do simple or complex SQL manipulation within the time frame that you specify, by using the Select, From and Where clauses, as indicated in the property editor.
For example, given a stream of transactions of a stock, you can compute the new stream that holds the hourly minimum average and the maximum of the stock price.
The property editor opens.
For example:
WHERE price > 30.00 AND stockDate < '2006-01-01' ;
The Tuple Based Aggregator operator performs statistical analysis for a specified number of records (also called tuples) that you provide as a size, and also for an increment that indicates how often you want the operation performed.
Statistics that you can compute via SQL statements in the property editor of the Tuple Based Aggregator operator include:
Sum
Average
Minimum
Maximum
COUNT
Use the Tuple Based Aggregator operator when you want to perform statistical analysis on a specified number of tuples.
For example, provided a stream of stock transactions, the Tuple Based Aggregator operator computes a new stream that holds the minimum, average, and maximum of the stock price of every 10 transactions, in which the size is 10.
The property editor opens.
For example:
WHERE price > 30.00 AND stockDate < '2006-01-01' ;