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Chapter 18. Integration and Extension

18.1. Overview
18.2. Virtual Data Window
18.2.1. How to Use
18.2.2. Implementing the Factory
18.2.3. Implementing the Virtual Data Window
18.2.4. Implementing the Lookup
18.3. Single-Row Function
18.3.1. Implementing a Single-Row Function
18.3.2. Configuring the Single-Row Function Name
18.3.3. Value Cache
18.3.4. Single-Row Functions in Filter Predicate Expressions
18.3.5. Single-Row Functions Taking Events as Parameters
18.3.6. Receiving a Context Object
18.3.7. Exception Handling
18.4. Derived-value and Data Window View
18.4.1. Implementing a View Factory
18.4.2. Implementing a View
18.4.3. View Contract
18.4.4. Configuring View Namespace and Name
18.4.5. Requirement for Data Window Views
18.4.6. Requirement for Derived-Value Views
18.4.7. Requirement for Grouped Views
18.5. Aggregation Function
18.5.1. Aggregation Single-Function Development
18.5.2. Aggregation Multi-Function Development
18.6. Pattern Guard
18.6.1. Implementing a Guard Factory
18.6.2. Implementing a Guard Class
18.6.3. Configuring Guard Namespace and Name
18.7. Pattern Observer
18.7.1. Implementing an Observer Factory
18.7.2. Implementing an Observer Class
18.7.3. Configuring Observer Namespace and Name
18.8. Event Type And Event Object
18.8.1. How It Works
18.8.2. Steps
18.8.3. URI-based Resolution
18.8.4. Example

This chapter summarizes integration and describes in detail each of the extension APIs that allow integrating external data and/or extend engine functionality.

For information on calling external services via instance method invocation, for instance to integrate with dependency injection frameworks such as Spring or Guice, please see Section 5.17.5, “Class and Event-Type Variables”.

For information on input and output adapters that connect to an event transport and perform event transformation for incoming and outgoing on-the-wire event data, for use with streaming data, please see the EsperIO reference documentation. The data flow instances as described in Chapter 14, EPL Reference: Data Flow are an easy way to plug in operators that perform input and output. Data flows allow providing parameters and managing individual flows independent of engine lifecycle. Also consider using the Plug-in Loader API for creating a new adapter that starts or stops as part of the CEP engine initialization and destroy lifecycle, see Section 15.17, “Plug-in Loader”.

To join data that resides in a relational database and that is accessible via JDBC driver and SQL statement the engine offers a syntax for using SQL within EPL, see Section 5.13, “Accessing Relational Data via SQL”. A relational database input and output adapter for streaming input from and output to a relational database also exists (EsperIO).

To join data that resides in a non-relational store the engine offers a two means: First, the virtual data window, as described below, for transparently integrating the external store as a named window. The second mechanism is a special join syntax based on static method invocation, see Section 5.14, “Accessing Non-Relational Data via Method Invocation”.

Tip

The best way to test that your extension code works correctly is to write unit tests against an EPL statement that utilizes the extension code. Samples can be obtained from Esper regression test code base.

Note

For all extension code and similar to listeners and subscribers, to send events into the engine from extension code the route method should be used (and not sendEvent) to avoid the possibility of stack overflow due to event-callback looping and ensure correct processing of the current and routed event. Note that if outbound-threading is enabled, listeners and subscribers should use sendEvent and not route.

Note

For all extension code it is not safe to administrate the engine within the extension code. For example, it is not safe to implement a data window view that creates a new statement or destroys an existing statement.

Use a virtual data window if you have a (large) external data store that you want to access as a named window. The access is transparent: There is no need to use special syntax or join syntax. All regular queries including subqueries, joins, on-merge, on-select, on-insert, on-delete, on-update and fire-and-forget are supported with virtual data windows.

There is no need to keep any data or events in memory with virtual data windows. The only requirement for virtual data windows is that all data rows returned are EventBean instances.

When implementing a virtual data window it is not necessary to send any events into the engine or to use insert-into. The event content is simply assumed to exist and accessible to the engine via the API implementation you provide.

The distribution ships with a sample virtual data window in the examples folder under the name virtualdw. The code snippets below are extracts from the example.

We use the term store here to mean a source set of data that is managed by the virtual data window. We use the term store row or just row to mean a single data item provided by the store. We use the term lookup to mean a read operation against the store returning zero, one or many rows.

Virtual data windows allow high-performance low-latency lookup by exposing all relevant EPL query access path information. This makes it possible for the virtual data window to choose the desired access method into its store.

The following steps are required to develop and use a virtual data window:

Once you have completed above steps, the virtual data window is ready to use in EPL statements.

From a threading perspective, virtual data window implementation classes must be thread-safe if objects are shared between multiple named windows. If no objects are shared between multiple different named windows, thereby each object is only used for the same named window and other named windows receive a separate instance, it is no necessary that the implementation classes are thread-safe.

Your application must first register the virtual data window factory as part of engine configuration:

Configuration config = new Configuration();
config.addPlugInVirtualDataWindow("sample", "samplevdw", 
    SampleVirtualDataWindowFactory.class.getName());

Your application may then create a named window backed by a virtual data window.

For example, assume that the SampleEvent event type is declared as follows:

create schema SampleEvent as (key1 string, key2 string, value1 int, value2 double)

The next EPL statement creates a named window MySampleWindow that provides SampleEvent events and is backed by a virtual data window provided by SampleVirtualDataWindowFactory as configured above:

create window MySampleWindow.sample:samplevdw() as SampleEvent

You may then access the named window, same as any other named window, for example by subquery, join, on-action, fire-and-forget query or by consuming its insert and remove stream. While this example uses Map-type events, the example code is the same for POJO or other events.

Your application may obtain a reference to the virtual data window from the engine context.

This code snippet looks up the virtual data window by the named window name:

try {
  return (VirtualDataWindow) epService.getContext().lookup("/virtualdw/MySampleWindow");
}
catch (NamingException e) {
  throw new RuntimeException("Failed to look up virtual data window, is it created yet?");
}

When you application registers a subquery, join or on-action query or executes a fire-and-forget query against a virtual data window the engine interacts with the virtual data window. The interaction is a two-step process.

At time of EPL statement creation (once), the engine analyzes the EPL where-clause, if present. It then compiles a list of hash-index and binary tree (btree, i.e. sorted) index properties. It passes the property names that are queried as well as the operators (i.e. =, >, range etc.) to the virtual data window. The virtual data window returns a lookup strategy object to the engine.

At time of EPL statement execution (repeatedly as triggered) , the engine uses that lookup strategy object to execute a lookup. It passes to the lookup all actual key values (hash, btree including ranges) to make fast and efficient lookup achievable.

To explain in detail, assume that your application creates an EPL statement with a subquery as follows:

select (select * from MySampleWindow where key1 = 'A1') from OtherEvent

At the time of creation of the EPL query above the engine analyzes the EPL query. It determines that the subquery queries a virtual data window. It determines from the where-clause that the lookup uses property key1 and hash-equals semantics. The engine then provides this information as part of VirtualDataWindowLookupContext passed to the getLookup method. Your application may inspect hash and btree properties and may determine the appropriate store access method to use.

The hash and btree property lookup information is for informational purposes, to enable fast and performant queries that returns the smallest number of rows possible. Your implementation classes may use some or none of the information provided and may also instead return some or perhaps even all rows, as is practical to your implementation. The where-clause still remains in effect and gets evaluated on all rows that are returned by the lookup strategy.

Following the above example, the sub-query executes once when a OtherEvent event arrives. At time of execution the engine delivers the string value A1 to the VirtualDataWindowLookup lookup implementation provided by your application. The lookup object queries the store and returns store rows as EventBean instances.

As a second example, consider an EPL join statement as follows:

select * from MySampleWindow, MyTriggerEvent where key1 = trigger1 and key2 = trigger2

The engine analyzes the query and passes to the virtual data window the information that the lookup occurs on properties key1 and key2 under hash-equals semantics. When a MyTriggerEvent arrives, it passes the actual value of the trigger1 and trigger2 properties of the current MyTriggerEvent to the lookup.

As a last example, consider an EPL fire-and-forget statement as follows:

select * from MySampleWindow key1 = 'A2' and value1 between 0 and 1000

The engine analyzes the query and passes to the virtual data window the lookup information. The lookup occurs on property key1 under hash-equals semantics and on property value1 under btree-open-range semantics. When you application executes the fire-and-forget query the engine passes A2 and the range endpoints 0 and 1000 to the lookup.

For more information, please consult the JavaDoc API documentation for class com.espertech.esper.client.hook.VirtualDataWindow, VirtualDataWindowLookupContext or VirtualDataWindowLookupFieldDesc.

For each named window that refers to the virtual data window, the engine instantiates one instance of the factory.

A virtual data window factory class is responsible for the following functions:

The engine instantiates a VirtualDataWindowFactory instance for each named window created via create window. The engine invokes the initialize method once in respect to the named window being created passing a VirtualDataWindowFactoryContext context object.

If not using contexts, the engine calls the create method once after calling the initialize method. If using contexts, the engine calls the create method every time it allocates a context partition. If using contexts and your virtual data window implementation operates thread-safe, you may return the same virtual data window implementation object for each context partition. If using contexts and your implementation object is not thread safe, return a separate thread-safe implementation object for each context partition.

The engine invokes the destroyAllContextPartitions once when the named window is stopped or destroyed. If not using contexts, the engine calls the destroy method of the virtual data window implementation object before calling the destroyAllContextPartitions method on the factory object. If using contexts, the engine calls the destroy method on each instance associates to a context partition at the time when the associated context partition terminates.

The sample code shown here can be found among the examples in the distribution under virtualdw:

public class SampleVirtualDataWindowFactory implements VirtualDataWindowFactory {

    public void initialize(VirtualDataWindowFactoryContext factoryContext) {
		// Can add initialization logic here.
    }

  public VirtualDataWindow create(VirtualDataWindowContext context) {
    // This example allocates a new virtual data window (one per context partitions if using contexts).
    // For sharing the virtual data window instance between context partitions, return the same reference.
    return new SampleVirtualDataWindow(context);
  }
  
  public void destroyAllContextPartitions() {
    // Release shared resources here
  }
}

Your factory class must implement the create method which receives a VirtualDataWindowContext object. This method is called once for each EPL that creates a virtual data window (see example create window above).

The VirtualDataWindowContext provides to your application:

String namedWindowName;	// Name of named window being created.
Object[] parameters;  // Any optional parameters provided as part of create-window.
EventType eventType;  // The event type of events.
EventBeanFactory eventFactory;  // A factory for creating EventBean instances from store rows.
VirtualDataWindowOutStream outputStream;  // For stream output to consuming statements.
AgentInstanceContext agentInstanceContext;  // Other EPL statement information in statement context.

When using contexts you can decide whether your factory returns a new virtual data window for each context partition or returns the same virtual data window instance for all context partitions. Your extension code may refer to the named window name to identify the named window and may refer to the agent instance context that holds the agent instance id which is the id of the context partition.

A virtual data window implementation is responsible for the following functions:

The sample code shown here can be found among the examples in the distribution under virtualdw.

The implementation class must implement the VirtualDataWindow interface like so:

public class SampleVirtualDataWindow implements VirtualDataWindow {

  private final VirtualDataWindowContext context;
  
  public SampleVirtualDataWindow(VirtualDataWindowContext context) {
    this.context = context;
  } ...

When the engine compiles an EPL statement and detects a virtual data window, the engine invokes the getLookup method indicating hash and btree access path information by passing a VirtualDataWindowLookupContext context. The lookup method must return a VirtualDataWindowLookup implementation that the EPL statement uses for all lookups until the EPL statement is stopped or destroyed.

The sample implementation does not use the hash and btree access path information and simply returns a lookup object:

public VirtualDataWindowLookup getLookup(VirtualDataWindowLookupContext desc) {

  // Place any code that interrogates the hash-index and btree-index fields here.

  // Return the lookup strategy.
  return new SampleVirtualDataWindowLookup(context);
}

If your virtual data window returns null instead of a lookup object, the EPL query creation fails and throws an EPStatementException.

The engine calls the update method when data changes because of on-merge, on-delete, on-update or insert-into. For example, if you have an on-merge statement that is triggered and that updates the virtual data window, the newData parameter receives the new (updated) event and the oldData parameters receives the event prior to the update. Your code may use these events to update the store or delete from the store, if needed.

If your application plans to consume data from the virtual data window, for example via select * from MySampleWindow, then the code must implement the update method to forward insert and remove stream events, as shown below, to receive the events in consuming statements. To post insert and remove stream data, use the VirtualDataWindowOutStream provided by the context object as follows.

public void update(EventBean[] newData, EventBean[] oldData) {
  // This sample simply posts into the insert and remove stream what is received.
  context.getOutputStream().update(newData, oldData);
}

Your application should not use VirtualDataWindowOutStream to post new events that originate from the store. The object is intended for use with on-action EPL statements. Use insert-into instead for any new events that originate from the store.

A lookup implementation is responsible for the following functions:

The sample code shown here can be found among the examples in the distribution under virtualdw.

The implementation class must implement the VirtualDataWindowLookup interface:

public class SampleVirtualDataWindowLookup implements VirtualDataWindowLookup {

  private final VirtualDataWindowContext context;
  
  public SampleVirtualDataWindowLookup(VirtualDataWindowContext context) {
    this.context = context;
  } ...

When an EPL query fires, the engine invokes the lookup and provides the actual lookup values. The lookup values are provided in the same exact order as the access path information that the engine provided when obtaining the lookup.

Each store row must be wrapped as an EventBean instance. The context object provides an EventBeanFactory implementation returned by getEventFactory() that can be used to wrap rows.

The sample implementation does not use the lookup values and simply returns a hardcoded sample event:

public Set<EventBean> lookup(Object[] lookupValues) {
  // Add code to interogate lookup values here.

  // Create sample event.
  // This example uses Map events; Other underlying events such as POJO are exactly the same code.
  Map<String, Object> eventData = new HashMap<String, Object>();
  eventData.put("key1", "sample1");
  eventData.put("key2", "sample2");
  eventData.put("value1", 100);
  eventData.put("value2", 1.5d);
  EventBean event = context.getEventFactory().wrap(eventData);
  return Collections.singleton(event);
}

The lookupValues object array represents all actual joined property values or expression results if you where-clause criteria are expressions. The code may use these keys to for efficient store access.

When a key value is a range, the key value is an instance of VirtualDataWindowKeyRange.

Single-row functions return a single value. They are not expected to aggregate rows but instead should be stateless functions. These functions can appear in any expressions and can be passed any number of parameters.

The following steps are required to develop and use a custom single-row function with Esper.

  1. Implement a class providing one or more public static methods accepting the number and type of parameters as required.

  2. Register the single-row function class and method name with the engine by supplying a function name, via the engine configuration file or the configuration API.

You may not override a built-in function with a single-row function provided by you. The single-row function you register must have a different name then any of the built-in functions.

An example single-row function can also be found in the examples under the runtime configuration example.

Views in Esper are used to derive information from an event stream, and to represent data windows onto an event stream. This chapter describes how to plug-in a new, custom view.

The following steps are required to develop and use a custom view with Esper.

  1. Implement a view factory class. View factories are classes that accept and check view parameters and instantiate the appropriate view class.

  2. Implement a view class. A view class commonly represents a data window or derives new information from a stream.

  3. Configure the view factory class supplying a view namespace and name in the engine configuration file.

The example view factory and view class that are used in this chapter can be found in the examples source folder in the OHLC (open-high-low-close) example. The class names are OHLCBarPlugInViewFactory and OHLCBarPlugInView.

Views can make use of the following engine services available via StatementServiceContext:

  • The SchedulingService interface allows views to schedule timer callbacks to a view

  • The EventAdapterService interface allows views to create new event types and event instances of a given type.

  • The StatementStopService interface allows view to register a callback that the engine invokes to indicate that the view's statement has been stopped

Section 18.4.3, “View Contract” outlines the requirements for correct behavior of a your custom view within the engine.

Note that custom views may use engine services and APIs that can be subject to change between major releases. The engine services discussed above and view APIs are considered part of the engine internal public API and are stable. Any changes to such APIs are disclosed through the release change logs and history. Please also consider contributing your custom view to the Esper project team by submitting the view code through the mailing list or via a JIRA issue.

A view factory class is responsible for the following functions:

View factory classes simply subclass com.espertech.esper.view.ViewFactorySupport:

public class OHLCBarPlugInViewFactory extends ViewFactorySupport { ...

Your view factory class must implement the setViewParameters method to accept and parse view parameters. The next code snippet shows an implementation of this method. The code checks the number of parameters and retains the parameters passed to the method:

public class OHLCBarPlugInViewFactory extends ViewFactorySupport {
    private ViewFactoryContext viewFactoryContext;
    private List<ExprNode> viewParameters;
    private ExprNode timestampExpression;
    private ExprNode valueExpression;

    public void setViewParameters(ViewFactoryContext viewFactoryContext, 
            List<ExprNode> viewParameters) throws ViewParameterException {
        this.viewFactoryContext = viewFactoryContext;
        if (viewParameters.size() != 2) {
            throw new ViewParameterException(
                "View requires a two parameters: " +
                "the expression returning timestamps and the expression supplying OHLC data points");
        }
        this.viewParameters = viewParameters;
    }
  ...

After the engine supplied view parameters to the factory, the engine will ask the view to attach to its parent view and validate any parameter expressions against the parent view's event type. If the view will be generating events of a different type then the events generated by the parent view, then the view factory can create the new event type in this method:

public void attach(EventType parentEventType, 
		StatementContext statementContext, 
		ViewFactory optionalParentFactory, 
		List<ViewFactory> parentViewFactories) throws ViewParameterException {
		
    ExprNode[] validatedNodes = ViewFactorySupport.validate("OHLC view", 
	      parentEventType, statementContext, viewParameters, false);

    timestampExpression = validatedNodes[0];
    valueExpression = validatedNodes[1];

    if ((timestampExpression.getExprEvaluator().getType() != long.class) && 
        (timestampExpression.getExprEvaluator().getType() != Long.class)) {
        throw new ViewParameterException(
            "View requires long-typed timestamp values in parameter 1");
    }
    if ((valueExpression.getExprEvaluator().getType() != double.class) && 
        (valueExpression.getExprEvaluator().getType() != Double.class)) {
        throw new ViewParameterException(
            "View requires double-typed values for in parameter 2");
    }
}

Finally, the engine asks the view factory to create a view instance, and asks for the type of event generated by the view:

public View makeView(AgentInstanceViewFactoryChainContext agentInstanceViewFactoryContext) {
    return new OHLCBarPlugInView(agentInstanceViewFactoryContext, timestampExpression, valueExpression);
}

public EventType getEventType() {
    return OHLCBarPlugInView.getEventType(viewFactoryContext.getEventAdapterService());
}

The update method must adhere to the following conventions, to prevent memory leaks and to enable correct behavior within the engine:

Your view implementation can register a callback indicating when a statement using the view, or a context partition using the view, is stopped or terminated. Your view code must implement, or provide an implementation, of the com.espertech.esper.util.StopCallback interface. Register the stop callback in order for the engine to invoke the callback:

agentInstanceContext.getTerminationCallbacks().add(this);

Please refer to the sample views for a code sample on how to implement iterator and cloneView methods.

In terms of multiple threads accessing view state, there is no need for your custom view factory or view implementation to perform any synchronization to protect internal state. The iterator of the custom view implementation does also not need to be thread-safe. The engine ensures the custom view executes in the context of a single thread at a time. If your view uses shared external state, such external state must be still considered for synchronization when using multiple threads.

Aggregation functions are stateful functions that aggregate events, event property values or expression results. Examples for built-in aggregation functions are count(*), sum(price * volume), window(*) or maxby(volume).

Esper allows two different ways for your application to provide aggregation functions. We use the name aggregation single-function and aggregation multi-function for the two independent extension APIs for aggregation functions.

The aggregation single-function API is simple to use however it imposes certain restrictions on how expressions that contain aggregation functions share state and are evaluated.

The aggregation multi-function API is more powerful and provides control over how expressions that contain aggregation functions share state and are evaluated.

The next table compares the two aggregation function extension API's:


The following sections discuss developing an aggregation single-function first, followed by the subject of developing an aggregation multi-function.

Note

The aggregation multi-function API is a powerful and lower-level API to extend the engine. Any classes that are not part of the client, plugin or agg.access package are subject to change between minor and major releases of the engine.

This section describes the aggregation single-function extension API for providing aggregation functions.

The following steps are required to develop and use a custom aggregation single-function with Esper.

The optional keyword distinct ensures that only distinct (unique) values are aggregated and duplicate values are ignored by the aggregation function. Custom plug-in aggregation single-functions do not need to implement the logic to handle distinct values. This is because when the engine encounters the distinct keyword, it eliminates any non-distinct values before passing the value for aggregation to the custom aggregation single-function.

Custom aggregation functions can also be passed multiple parameters, as further described in Section 18.5.1.4, “Aggregation Single-Function: Accepting Multiple Parameters”. In the example below the aggregation function accepts a single parameter.

The code for the example aggregation function as shown in this chapter can be found in the runtime configuration example in the package com.espertech.esper.example.runtimeconfig by the name MyConcatAggregationFunction. The sample function simply concatenates string-type values.

An aggregation function factory class is responsible for the following functions:

Aggregation function classes implement the interface com.espertech.esper.client.hook.AggregationFunctionFactory:

public class MyConcatAggregationFunctionFactory implements AggregationFunctionFactory { ...

The engine generally constructs one instance of the aggregation function factory class for each time the function is listed in an EPL statement, however the engine may decide to reduce the number of aggregation class instances if it finds equivalent aggregations.

The aggregation function factory instance receives the aggregation function name via set setFunctionName method.

The sample concatenation function factory provides an empty setFunctionName method:

public void setFunctionName(String functionName) {
  // no action taken
}

An aggregation function factory must provide an implementation of the validate method that is passed a AggregationValidationContext validation context object. Within the validation context you find the result type of each of the parameters expressions to the aggregation function as well as information about constant values and data window use. Please see the JavaDoc API documentation for a comprehensive list of validation context information.

Since the example concatenation function requires string types, it implements a type check:

public void validate(AggregationValidationContext validationContext) {
  if ((validationContext.getParameterTypes().length != 1) ||
    (validationContext.getParameterTypes()[0] != String.class)) {
    throw new IllegalArgumentException("Concat aggregation requires a single parameter of type String");
  }
}

In order for the engine to validate the type returned by the aggregation function against the types expected by enclosing expressions, the getValueType must return the result type of any values produced by the aggregation function:

public Class getValueType() {
  return String.class;
}

Finally the factory implementation must provide a newAggregator method that returns instances of AggregationMethod. The engine invokes this method for each new aggregation state to be allocated.

public AggregationMethod newAggregator() {
  return new MyConcatAggregationFunction();
}

An aggregation function class is responsible for the following functions:

Aggregation function classes implement the interface AggregationMethod:

public class MyConcatAggregationFunction implements AggregationMethod { ...

The class that provides the aggregation and implements AggregationMethod does not have to be threadsafe.

The constructor initializes the aggregation function:

public class MyConcatAggregationFunction implements AggregationMethod {
  private final static char DELIMITER = ' ';
  private StringBuilder builder;
  private String delimiter;

  public MyConcatAggregationFunction() {
    builder = new StringBuilder();
    delimiter = "";
  }
  ...

In order for the engine to validate the type returned by the aggregation function against the types expected by enclosing expressions, the getValueType must return the result type of any values produced by the aggregation function:

public Class getValueType() {
  return String.class;
}

The enter method adds a datapoint to the current aggregation value. The example enter method shown below adds a delimiter and the string value to a string buffer:

public void enter(Object value) {
  if (value != null) {
    builder.append(delimiter);
    builder.append(value.toString());
    delimiter = String.valueOf(DELIMITER);
  }
}

Conversly, the leave method removes a datapoint from the current aggregation value. The example leave method removes from the string buffer:

public void leave(Object value) {
  if (value != null) {
    builder.delete(0, value.toString().length() + 1);
  }
}

Finally, the engine obtains the current aggregation value by means of the getValue method:

public Object getValue() {
  return builder.toString();
}

For on-demand queries the aggregation function must support resetting its value to empty or start values. Implement the clear function to reset the value as shown below:

public void clear() {
  builder = new StringBuilder();
  delimiter = "";
}

This section introduces the aggregation multi-function API. Please refer to the JavaDoc for more complete class and method-level documentation.

Among the Esper examples we provide an example use of the aggregation multi-function API in the example by name Cycle-Detect. Cycle-Detect takes incoming transaction events that have from-account and to-account fields. The example detects a cycle in the transactions between accounts in order to detect a possible transaction fraud. Please note that the graph and cycle detection logic of the example is not part of Esper: The example utilizes the jgrapht library.

In the Cycle-Detect example, the vertices of a graph are the account numbers. For example the account numbers Acct-1, Acct-2 and Acct-3. In the graph the edges are transaction events that identify a from-account and a to-account. An example edge is {from:Acct-1, to:Acct-2}. An example cycle is therefore in the three transactions {from:Acct-1, to:Acct-2}, {from:Acct-2, to:Acct-3} and {from:Acct-3, to:Acct-1}.

The code for the example aggregation multi-function as shown in this chapter can be found in the Cycle-Detect example in the package com.espertech.esper.example.cycledetect. The example provides two aggregation functions named cycledetected and cycleoutput:

In the Cycle-Detect example, the following statement utilizes the two functions cycledetected and cycleoutput that share the same graph state to detect a cycle among the last 1000 events:

@Name('CycleDetector') select cycleoutput() as cyclevertices
from TransactionEvent.win:length(1000)
having cycledetected(fromAcct, toAcct)

If instead the goal is to run graph cycle detection every 1 second (and not upon arrival of a new event), this sample EPL statement uses a pattern to trigger cycle detection:

@Name('CycleDetector')
select (select cycleoutput(fromAcct, toAcct) from TransactionEvent.win:length(1000)) as cyclevertices
from pattern [every timer:interval(1)]

The following steps are required to develop and use a custom aggregation multi-function with Esper.

An aggregation multi-function factory class is responsible for the following functions:

Aggregation multi-function factory classes implement the interface com.espertech.esper.plugin.PlugInAggregationMultiFunctionFactory:

public class CycleDetectorAggregationFactory implements PlugInAggregationMultiFunctionFactory { ...

The engine constructs a single instance of the aggregation multi-function factory class that is shared for all aggregation function expressions in a statement that have one of the function names provided in the configuration object.

The engine invokes the addAggregationFunction method at the time it parses an EPL statement or compiles a statement object model (SODA API). The method receives a declaration-time context object that provides the function name as well as additional information.

The sample Cycle-Detect factory class provides an empty addAggregationFunction method:

public void addAggregationFunction(PlugInAggregationMultiFunctionDeclarationContext declarationContext) {
  // no action taken
}

The engine invokes the validateGetHandler method at the time of expression validation. It passes a PlugInAggregationMultiFunctionValidationContext validation context object that contains actual parameters expressions. Please see the JavaDoc API documentation for a comprehensive list of validation context information.

The validateGetHandler method must return a handler object the implements the PlugInAggregationMultiFunctionHandler interface. Return a handler object for each aggregation function expression according to the aggregation function name and its parameters that are provided in the validation context.

The example cycledetect function takes two parameters that provide the cycle edge (from-account and to-account):

public PlugInAggregationMultiFunctionHandler validateGetHandler(PlugInAggregationMultiFunctionValidationContext validationContext) {
  if (validationContext.getParameterExpressions().length == 2) {
    fromExpression = validationContext.getParameterExpressions()[0].getExprEvaluator();
    toExpression = validationContext.getParameterExpressions()[1].getExprEvaluator();
  }
  return new CycleDetectorAggregationHandler(this, validationContext);
}

An aggregation multi-function handler class must implement the PlugInAggregationMultiFunctionHandler interface and is responsible for the following functions:

Typically your API returns a handler instance for each aggregation function in an EPL statement expression.

In the Cycle-Detect example, the class CycleDetectorAggregationHandler is the handler for all aggregation functions.

public class CycleDetectorAggregationHandler implements PlugInAggregationMultiFunctionHandler { ...

The getAccessor methods return a reader object according to whether the aggregation function name is cycledetected or cycleoutput:

public AggregationAccessor getAccessor() {
  if (validationContext.getFunctionName().toLowerCase().equals(CycleDetectorConstant.CYCLEOUTPUT_NAME)) {
    return new CycleDetectorAggregationAccessorOutput();
  }
  return new CycleDetectorAggregationAccessorDetect();
}

The getReturnType method provided by the handler instructs the engine about the return type of each aggregation accessor. The class com.espertech.esper.client.util.ExpressionReturnType holds return type information.

In the Cycle-Detect example the cycledetected function returns a single boolean value. The cycleoutput returns a collection of vertices:

public ExpressionReturnType getReturnType() {
  if (validationContext.getFunctionName().toLowerCase().equals(CycleDetectorConstant.CYCLEOUTPUT_NAME)) {
    return ExpressionReturnType.collectionOfSingleValue(factory.getFromExpression().getType());
  }
  return ExpressionReturnType.singleValue(Boolean.class) ;
}

The engine invokes the getAggregationStateUniqueKey method to determine whether multiple aggregation function expressions in the same statement can share the same aggregation state or should receive different aggregation state instances.

The getAggregationStateUniqueKey method must return an instance of AggregationStateKey. The engine uses equals-semantics (the hashCode and equals methods) to determine whether multiple aggregation function share the state object. If the key object returned for each aggregation function by the handler is an equal key object then the engine shares aggregation state between such aggregation functions for the same statement and context partition.

In the Cycle-Detect example the state is shared, which it achieves by simply returning the same key instance:

private static final AggregationStateKey CYCLE_KEY = new AggregationStateKey() {};

public AggregationStateKey getAggregationStateUniqueKey() {
  return CYCLE_KEY;   // Share the same aggregation state instance
}

The engine invokes the getStateFactory method to obtain an instance of PlugInAggregationMultiFunctionStateFactory. The state factory is responsible to instantiating separate aggregation state instances. If you statement does not have a group by clause, the engine obtains a single aggregation state from the state factory. If your statement has a group by clause, the engine obtains an aggregation state instance for each group when it encounters a new group.

In the Cycle-Detect example the method passes the expression evaluators providing the from-account and to-account expressions to the state factory:

public PlugInAggregationMultiFunctionStateFactory getStateFactory() {
  return new CycleDetectorAggregationStateFactory(factory.getFromExpression(), factory.getToExpression());
}

Pattern guards are pattern objects that control the lifecycle of the guarded sub-expression, and can filter the events fired by the subexpression.

The following steps are required to develop and use a custom guard object with Esper.

  1. Implement a guard factory class, responsible for creating guard object instances.

  2. Implement a guard class.

  3. Register the guard factory class with the engine by supplying a namespace and name, via the engine configuration file or the configuration API.

The code for the example guard object as shown in this chapter can be found in the test source folder in the package com.espertech.esper.regression.client by the name MyCountToPatternGuardFactory. The sample guard discussed here counts the number of events occurring up to a maximum number of events, and end the sub-expression when that maximum is reached.

A guard factory class is responsible for the following functions:

Guard factory classes subclass com.espertech.esper.pattern.guard.GuardFactorySupport:

public class MyCountToPatternGuardFactory extends GuardFactorySupport { ...

The engine constructs one instance of the guard factory class for each time the guard is listed in a statement.

The guard factory class implements the setGuardParameters method that is passed the parameters to the guard as supplied by the statement. It verifies the guard parameters, similar to the code snippet shown next. Our example counter guard takes a single numeric parameter:

public void setGuardParameters(List<ExprNode> guardParameters, 
			MatchedEventConvertor convertor) throws GuardParameterException {
    String message = "Count-to guard takes a single integer-value expression as parameter";
    if (guardParameters.size() != 1) {
        throw new GuardParameterException(message);
    }

    if (guardParameters.get(0).getExprEvaluator().getType() != Integer.class) {
        throw new GuardParameterException(message);
    }

    this.numCountToExpr = guardParameters.get(0);
    this.convertor = convertor;
}

The makeGuard method is called by the engine to create a new guard instance. The example makeGuard method shown below passes the maximum count of events to the guard instance. It also passes a Quitable implementation to the guard instance. The guard uses Quitable to indicate that the sub-expression contained within must stop (quit) listening for events.

public Guard makeGuard(PatternAgentInstanceContext context,
      MatchedEventMap beginState, 
      Quitable quitable, 
      Object stateNodeId, 
      Object guardState) {
      
    Object parameter = PatternExpressionUtil.evaluate("Count-to guard", 
        beginState, numCountToExpr, convertor);
    if (parameter == null) {
        throw new EPException("Count-to guard parameter evaluated to a null value");
    }

    Integer numCountTo = (Integer) parameter;
    return new MyCountToPatternGuard(numCountTo, quitable);
}

Pattern observers are pattern objects that are executed as part of a pattern expression and can observe events or test conditions. Examples for built-in observers are timer:at and timer:interval. Some suggested uses of observer objects are:

  • Implement custom scheduling logic using the engine's own scheduling and timer services

  • Test conditions related to prior events matching an expression

The following steps are required to develop and use a custom observer object within pattern statements:

  1. Implement an observer factory class, responsible for creating observer object instances.

  2. Implement an observer class.

  3. Register an observer factory class with the engine by supplying a namespace and name, via the engine configuration file or the configuration API.

The code for the example observer object as shown in this chapter can be found in the test source folder in package com.espertech.esper.regression.client by the name MyFileExistsObserver. The sample observer discussed here very simply checks if a file exists, using the filename supplied by the pattern statement, and via the java.io.File class.

An observer factory class is responsible for the following functions:

Observer factory classes subclass com.espertech.esper.pattern.observer.ObserverFactorySupport:

public class MyFileExistsObserverFactory extends ObserverFactorySupport { ...

The engine constructs one instance of the observer factory class for each time the observer is listed in a statement.

The observer factory class implements the setObserverParameters method that is passed the parameters to the observer as supplied by the statement. It verifies the observer parameters, similar to the code snippet shown next. Our example file-exists observer takes a single string parameter:

public void setObserverParameters(List<ExprNode> expressionParameters, 
			MatchedEventConvertor convertor) throws ObserverParameterException {
    String message = "File exists observer takes a single string filename parameter";
    if (expressionParameters.size() != 1) {
	    throw new ObserverParameterException(message);
    }
    if (!(expressionParameters.get(0).getExprEvaluator().getType() == String.class)) {
	    throw new ObserverParameterException(message);
    }

    this.filenameExpression = expressionParameters.get(0);
    this.convertor = convertor;
}

The pattern engine calls the makeObserver method to create a new observer instance. The example makeObserver method shown below passes parameters to the observer instance:

public EventObserver makeObserver(PatternAgentInstanceContext context,
			MatchedEventMap beginState, 
			ObserverEventEvaluator observerEventEvaluator, 
			Object stateNodeId, 
			Object observerState) {
    Object filename = PatternExpressionUtil.evaluate("File-exists observer ", beginState, filenameExpression, convertor);
    if (filename == null) {
	    throw new EPException("Filename evaluated to null");
    }

    return new MyFileExistsObserver(beginState, observerEventEvaluator, filename.toString());
}

The ObserverEventEvaluator parameter allows an observer to indicate events, and to indicate change of truth value to permanently false. Use this interface to indicate when your observer has received or witnessed an event, or changed it's truth value to true or permanently false.

The MatchedEventMap parameter provides a Map of all matching events for the expression prior to the observer's start. For example, consider a pattern as below:

a=MyEvent -> myplugin:my_observer(...)

The above pattern tagged the MyEvent instance with the tag "a". The pattern engine starts an instance of my_observer when it receives the first MyEvent. The observer can query the MatchedEventMap using "a" as a key and obtain the tagged event.

Creating a plug-in event representation can be useful under any of these conditions:

  • Your application has existing Java classes that carry event metadata and event property values and your application does not want to (or cannot) extract or transform such event metadata and event data into one of the built-in event representations (POJO Java objects, Map or XML DOM).

  • Your application wants to provide a faster or short-cut access path to event data, for example to access XML event data through a Streaming API for XML (StAX).

  • Your application must perform a network lookup or other dynamic resolution of event type and events.

Note that the classes to plug-in custom event representations are held stable between minor releases, but can be subject to change between major releases.

Currently, EsperIO provides the following additional event representations:

  • Apache Axiom provides access to XML event data on top of the fast Streaming API for XML (StAX).

The source code is available for these and they are therefore excellent examples for how to implement a plug-in event representation. Please see the EsperIO documentation for usage details.

Your application provides a plug-in event representation as an implementation of the com.espertech.esper.plugin.PlugInEventRepresentation interface. It registers the implementation class in the Configuration and at the same time provides a unique URI. This URI is called the root event representation URI. An example value for a root URI is type://xml/apacheaxiom/OMNode.

One can register multiple plug-in event representations. Each representation has a root URI. The root URI serves to divide the overall space of different event representations and plays a role in resolving event types and event objects.

There are two situations in an Esper engine instance asks an event representation for an event type:

The implementation of the PlugInEventRepresentation interface must provide implementations for two key interfaces: com.espertech.esper.client.EventType and EventBean. It must also implement several other related interfaces as described below.

The EventType methods provide event metadata including property names and property types. They also provide instances of EventPropertyGetter for retrieving event property values. Each instance of EventType represents a distinct type of event.

The EventBean implementation is the event itself and encapsulates the underlying event object.

Assume you have registered event representations using the following URIs:

When providing an array of child URIs for resolution, the engine compares each child URI to each of the event representation root URIs, in the order provided. Any event representation root URIs that spans the child URI space becomes a candidate event representation. If multiple root URIs match, the order is defined by the more specific root URI first, to the least specific root URI last.

During event type resolution and event sender resolution you provide a child URI. Assuming the child URI provided is type://myFormat/myProject/myName/myEvent?param1=abc&param2=true. In this example both root URIs #1 (the more specific) and #1 (the less specific) match, while root URI #3 is not a match. Thus at the time of type resolution the engine invokes the acceptType method on event presentation for URI #1 first (the more specific), before asking #2 (the less specific) to resolve the type.

The EventSender returned by the getEventSender(URI[]) method follows the same scheme. The event sender instance asks each matching event representation for each URI to resolve the event object in the order of most specific to least specific root URI, and the first event representation to return an instance of EventBean ends the resolution process for event objects.

The type:// part of the URI is an optional convention for the scheme part of an URI that your application may follow. URIs can also be simple names and can include parameters, as the Java software JavaDoc documents for class java.net.URI.

This section implements a minimal sample plug-in event representation. For the sake of keeping the example easy to understand, the event representation is rather straightforward: an event is a java.util.Properties object that consists of key-values pairs of type string.

The code shown next does not document method footprints. Please consult the JavaDoc API documentation for method details.

First, the sample shows how to implement the EventType interface. The event type provides information about property names and types, as well as supertypes of the event type.

Our EventType takes a set of valid property names:

public class MyPlugInPropertiesEventType implements EventType {
  private final Set<String> properties;

  public MyPlugInPropertiesEventType(Set<String> properties) {
    this.properties = properties;
  }

  public Class getPropertyType(String property) {
    if (!isProperty(property)) {
      return null;
    }
    return String.class;
  }

  public Class getUnderlyingType() {
    return Properties.class;
  }
  
  //... further methods below
}

An EventType is responsible for providing implementations of EventPropertyGetter to query actual events. The getter simply queries the Properties object underlying each event:

  public EventPropertyGetter getGetter(String property) {
    final String propertyName = property;
    
    return new EventPropertyGetter() {
      public Object get(EventBean eventBean) throws PropertyAccessException {
        MyPlugInPropertiesEventBean propBean = (MyPlugInPropertiesEventBean) eventBean;
        return propBean.getProperties().getProperty(propertyName);
      }
      
      public boolean isExistsProperty(EventBean eventBean) {
        MyPlugInPropertiesEventBean propBean = (MyPlugInPropertiesEventBean) eventBean;
        return propBean.getProperties().getProperty(propertyName) != null;
      }
      
      public Object getFragment(EventBean eventBean) {
	    return null;	// The property is not a fragment
      }
    };
  }

Our sample EventType does not have supertypes. Supertypes represent an extends-relationship between event types, and subtypes are expected to exhibit the same event property names and types as each of their supertypes combined:

  public EventType[] getSuperTypes() {
    return null;	// no supertype for this example
  }

  public Iterator<EventType> getDeepSuperTypes() {
    return null;
  }
  
  public String getName() {
    return name;
  }

  public EventPropertyDescriptor[] getPropertyDescriptors() {
    Collection<EventPropertyDescriptor> descriptorColl = descriptors.values();
    return descriptorColl.toArray(new EventPropertyDescriptor[descriptors.size()]);
  }

  public EventPropertyDescriptor getPropertyDescriptor(String propertyName) {
    return descriptors.get(propertyName);
  }

  public FragmentEventType getFragmentType(String property) {
    return null;  // sample does not provide any fragments
  }

The example event type as above does not provide fragments, which are properties of the event that can themselves be represented as an event, to keep the example simple.

A PlugInEventRepresentation serves to create EventType and EventBean instances through its related interfaces.

The sample event representation creates MyPlugInPropertiesEventType and MyPlugInPropertiesEventBean instances. The PlugInEventTypeHandler returns the EventType instance and an EventSender instance.

Our sample event representation accepts all requests for event types by returning boolean true on the acceptType method. When asked for the PlugInEventTypeHandler, it constructs a new EventType. The list of property names for the new type is passed as an initialization value provided through the configuration API or XML, as a comma-separated list of property names:

public class MyPlugInEventRepresentation implements PlugInEventRepresentation {

  private List<MyPlugInPropertiesEventType> types;

  public void init(PlugInEventRepresentationContext context) {
    types = new ArrayList<MyPlugInPropertiesEventType>();
  }

  public boolean acceptsType(PlugInEventTypeHandlerContext context) {
    return true;
  }

  public PlugInEventTypeHandler getTypeHandler(PlugInEventTypeHandlerContext eventTypeContext) {
    String proplist = (String) eventTypeContext.getTypeInitializer();
    String[] propertyList = proplist.split(",");

    Set<String> typeProps = new HashSet<String>(Arrays.asList(propertyList));

    MyPlugInPropertiesEventType eventType = new MyPlugInPropertiesEventType(typeProps);
    types.add(eventType);

    return new MyPlugInPropertiesEventTypeHandler(eventType);
  }
  // ... more methods below
}

The PlugInEventTypeHandler simply returns the EventType as well as an implementation of EventSender for processing same-type events:

public class MyPlugInPropertiesEventTypeHandler implements PlugInEventTypeHandler {
  private final MyPlugInPropertiesEventType eventType;

  public MyPlugInPropertiesEventTypeHandler(MyPlugInPropertiesEventType eventType) {
    this.eventType = eventType;
  }

  public EventSender getSender(EPRuntimeEventSender runtimeEventSender) {
    return new MyPlugInPropertiesEventSender(eventType, runtimeEventSender);
  }

  public EventType getType() {
    return eventType;
  }
}

The EventSender returned by PlugInEventTypeHandler is expected process events of the same type or any subtype:

public class MyPlugInPropertiesEventSender implements EventSender {
  private final MyPlugInPropertiesEventType type;
  private final EPRuntimeEventSender runtimeSender;

  public MyPlugInPropertiesEventSender(MyPlugInPropertiesEventType type, 
        EPRuntimeEventSender runtimeSender) {
    this.type = type;
    this.runtimeSender = runtimeSender;
  }

  public void sendEvent(Object event) {
    if (!(event instanceof Properties)) {
       throw new EPException("Sender expects a properties event");
    }
    EventBean eventBean = new MyPlugInPropertiesEventBean(type, (Properties) event);
    runtimeSender.processWrappedEvent(eventBean);
  }
}

The plug-in event representation may optionally provide an implementation of PlugInEventBeanFactory. A PlugInEventBeanFactory may inspect event objects and assign an event type dynamically based on resolution URIs and event properties.

Our sample event representation accepts all URIs and returns a MyPlugInPropertiesBeanFactory:

public class MyPlugInEventRepresentation implements PlugInEventRepresentation {

  // ... methods as seen earlier
  public boolean acceptsEventBeanResolution(
        PlugInEventBeanReflectorContext eventBeanContext) {
    return true;
  }

  public PlugInEventBeanFactory getEventBeanFactory(
        PlugInEventBeanReflectorContext eventBeanContext) {
    return new MyPlugInPropertiesBeanFactory(types);
   }
}

Last, the sample MyPlugInPropertiesBeanFactory implements the PlugInEventBeanFactory interface. It inspects incoming events and determines an event type based on whether all properties for that event type are present:

public class MyPlugInPropertiesBeanFactory implements PlugInEventBeanFactory {
  private final List<MyPlugInPropertiesEventType> knownTypes;

  public MyPlugInPropertiesBeanFactory(List<MyPlugInPropertiesEventType> types) {
    knownTypes = types;
  }

  public EventBean create(Object event, URI resolutionURI) {
    Properties properties = (Properties) event;

    // use the known types to determine the type of the object
    for (MyPlugInPropertiesEventType type : knownTypes) {
      // if there is one property the event does not contain, then its not the right type
      boolean hasAllProperties = true;
      for (String prop : type.getPropertyNames()) {
        if (!properties.containsKey(prop)) {
          hasAllProperties = false;
          break;
        }
      }

      if (hasAllProperties) {
        return new MyPlugInPropertiesEventBean(type, properties);
      }
    }
    return null; // none match, unknown event
  }
}