This document describes input and output adapters for the Esper Java event stream and complex event processor.
If you are new to Esper, the Esper reference manual should be your first stop.
If you are looking for information on a specific adapter, you are at the right spot.
Input and output adapters to Esper provide the means of accepting events from various sources, and for making available events to destinations.
Esper has a fully-evolved API and natively accepts various input event formats and natively produces various output event objects, as part of core Esper.
It is therefore not necessary to use any of the adapters listed herein. Simply use the public Esper APIs directly in your code.
Most adapters present their own configuration as well as API. Some adapters also provide operators for use in data flows.
The Adapter interface allows client applications to control the state of an input and output adapter. It provides state transition methods that each
input and output adapter implements.
An input or output adapter is always in one of the following states:
Opened - The begin state; The adapter is not generating or accepting events in this state
Started - When the adapter is active, generating and accepting events
Paused - When operation of the adapter is suspended
Destroyed
The state transition table below outlines adapter states and, for each state, the valid state transitions:
Table 1.1. Adapter State Transitions
| Start State | Method | Next State |
|---|---|---|
| Opened | start() | Started |
| Opened | destroy() | Destroyed |
| Started | stop() | Opened |
| Started | pause() | Paused |
| Started | destroy() | Destroyed |
| Paused | resume() | Started |
| Paused | stop() | Opened |
| Paused | destroy() | Destroyed |
The file input and output adapter consists of:
File (including CSV) input and output utilizing data flow operators.
The CSV input adapter API.
This adapter only requires Esper runtime as a dependency and does not require Esper compiler.
In order to use the File source and sink data flow operators, add esperio-csv-version.jar to your classpath and import the operator package.
For example:
Configuration configuration = new Configuration(); configuration.getCommon().addImport(FileSourceForge.class.getPackage().getName() + ".*");
The File input and output adapter provides the following data flow operators:
Table 2.1. File Operators
| Operator | Description |
|---|---|
| FileSink |
Write events to a file. See Section 2.1.2, “FileSink Operator”. |
| FileSource |
Read events from a file. See Section 2.1.3, “FileSource Operator”. |
The FileSink operator receives input stream events, transforms events to comma-separated format and writes to a file.
The FileSink operator must have a single input stream.
The FileSink operator cannot declare any output streams.
Parameters for the FileSink operator are (required parameters are listed first):
Table 2.2. FileSink Parameters
| Name | Description |
|---|---|
| file (required) | An expression returning the file name string. An absolute or relative file name. |
| classpathFile | An expression returning a boolean indicator whether the file name is found in a classpath directory, false by default. |
| append | An expression returning a boolean indicator whether to append or overwrite the file when it exists. false by default causes the existing file, if any, to be overwritten. |
The following example declares a data flow that is triggered by MyMapEventType events from the event bus (type not declared here) and that writes to the file output.csv the CSV-formatted events:
create dataflow FileSinkSampleFlow
EventBusSource -> outstream<MyMapEventType> {}
FileSink(outstream) {
file: 'output.csv',
append: true
}The FileSource operator reads from files, transforms file data and populates a data flow instance with events.
The FileSource operator cannot declare any input streams.
The FileSource operator must have at least one output stream. You can declare additional output streams to hold beginning-of-file and end-of-file indication.
Parameters for the FileSource operator are listed below, with the required parameters listed first:
Table 2.3. FileSource Parameters
| Name | Description |
|---|---|
file (required, or provide adapterInputSource) | An expression returning the file name string |
adapterInputSource (required, or provide file) | An instance of AdapterInputSource if a file name cannot be provided. |
| classpathFile | An expression returning a boolean indicator whether the file is found in a classpath directory, false by default. |
| dateFormat | An expression returning the format to use when parsing dates; the default is SimpleDateFormat of yyyy-MM-dd'T'HH:mm:ss.SSS for Date and Calendar type properties. |
| format | An expression returning csv (the default) for comma-separate value or line for single-line. |
| hasTitleLine | An expression returning a boolean indicator whether a title line exists that the operator should read and parse to obtain event property names. For use with the csv format. |
| hasHeaderLine | An expression returning a boolean indicator whether a header line exists that the operator should skip. For use with the csv format. |
| numLoops | An expression returning a an integer value that instructs the runtime to restart reading the file upon encountering EOF, defaults to zero. For use with the csv format. |
| propertyNames | String array constant that provides a list of property names in the same order they appear in the file. For use with the csv format. |
| propertyNameLine | An expression returning the property name of the output event type that receives the line text of type string. For use with the line format. |
| propertyNameFile | An expression returning the property name of the output event type(s) that receive the file name of type string. For use with the line format. |
The first output stream holds per-line output events. For use with the line format and if declaring two output streams, the second stream holds end-of-file indication. If declaring three output streams, the second stream holds beginning-of-file indication and the third stream holds end-of-file indication.
The line format requires that the output stream's event type is an object-array event type that features a single string-type property that the operator populates with each line of the file.
The file name (or adapterInputSource) may point to a zip file. If the file name ends with the literal zip the operator opens the zip file and uses the first packaged file.
All other parameters including the format parameter for CSV or line-formatting then apply to the zipped file.
This example defines a data flow that consists of two operators that work together to read a file and send the resulting events into the runtime:
create dataflow SensorCSVFlow
FileSource -> sensorstream<TemperatureEventStream> {
file: 'sensor_events.csv',
propertyNames: ['sensor','temp','updtime'],
numLoops: 3
}
EventBusSink(sensorstream){}
The data flow above configures the FileSource operator to read the file sensor_events.csv, populate the sensor, temp and updtime properties of the TemperatureEventStream event type (type definition not shown here) and make the output events available within the data flow under the name sensorstream.
The data flow above configures the EventBusSource operator to send the sensorstream events into the runtime for processing.
This example shows the EPL and code to read and count lines in text files.
Below EPL defines an event type to each hold the file line text as well as to indictate the beginning and end of a file (remove the semicolon if creating EPL individually and not as a module):
// for beginning-of-file events create objectarray schema MyBOF (filename string); // for end of file events create objectarray schema MyEOF (filename string); // for line text events create objectarray schema MyLine (filename string, line string);
The next EPL statements count lines per file outputting the final line count only when the end-of-file is reached.
// Initiate a context partition for each file, terminate upon end-of-file create context FileContext initiated by MyBOF as mybof terminated by MyEOF(filename=mybof.filename); // For each file, count lines context FileContext select context.mybof.filename as filename, count(*) as cnt from MyLine(filename=context.mybof.filename) output snapshot when terminated;
The below EPL defines a data flow that reads text files line-by-line and that send events into the runtime for processing.
create dataflow MyEOFEventFileReader
FileSource -> mylines<MyLine>, mybof<MyBOF>, myeof<MyEOF> {
format: 'line',
propertyNameLine: 'line', // store the text in the event property 'line'
propertyNameFile: 'filename' // store the file name in 'filename'
}
EventBusSink(mylines, mybof, myeof) {} // send events into runtimeThe next sample code instantiates and runs data flows passing a file name:
EPDataFlowInstantiationOptions options = new EPDataFlowInstantiationOptions();
options.addParameterURI("FileSource/file", "myfile.txt");
EPDataFlowInstance instance = runtime.getDataFlowService()
.instantiate("MyEOFEventFileReader",options);
instance.run();
This chapter discusses the CSV input adapter API. CSV is an abbreviation for comma-separated values. CSV files are simple text files in which each line
is a comma-separated list of values. CSV-formatted text can be read from many different input sources via com.espertech.esperio.csv.AdapterInputSource.
Please consult the JavaDoc for additional information on AdapterInputSource and the CSV adapter.
In summary the CSV input adapter API performs the following functions:
Read events from an input source providing CSV-formatted text and send the events to an Esper runtime instance
Read from different types of input sources
Use a timestamp column to schedule events being sent into the runtime
Playback with options such as file looping, events per second and other options
Use the Esper runtime timer thread to read the CSV file
Read multiple CSV files using a timestamp column to simulate events coming from different streams
The following formatting rules and restrictions apply to CSV-formatted text:
Comment lines are prefixed with a single hash or pound # character
Strings are placed in double quotes, e.g. "value"
Escape rules follow common spreadsheet conventions, i.e. double quotes can be escaped via double quote
A column header is required unless a property order is defined explicitly
If a column header is used, properties are assumed to be of type String unless otherwise configured
The value of the timestamp column, if one is given, must be in ascending order
The adapter does not allocate new event types. Any event type names provided must exist and
their bus-event-type modifier must be visible.
The adapter reads events from a CSV input source and sends events to an runtime using the class com.espertech.esperio.csv.CSVInputAdapter.
The below code snippet reads the CSV-formatted text file "simulation.csv" expecting the file in the classpath. The AdapterInputSource class can take other input sources.
AdapterInputSource source = new AdapterInputSource("simulation.csv");
(new CSVInputAdapter(runtime, source, "PriceEvent")).start();
To use the CSVInputAdapter without any options, the event type PriceEvent and its property names and value types must be known to the runtime. The next section elaborates on adapter options.
Configure the runtime instance for a Map-based event type
Place a header record in your CSV file that names each column as specified in the event type
The sample application code below shows all the steps to configure, via API, a Map-based event type and play the CSV file without setting any of the available options.
Map<String, Class> eventProperties = new HashMap<String, Class>();
eventProperties.put("symbol", String.class);
eventProperties.put("price", double.class);
eventProperties.put("volume", Integer.class);
Configuration configuration = new Configuration();
configuration.getCommon().addEventType("PriceEvent", eventProperties);
runtime = EPRuntimeProvider.getDefaultRuntime(configuration);
EPStatement stmt = compileDeploy(runtime, "select symbol, price, volume from PriceEvent.win:length(100)"); // see docs for compile and deploy
(new CSVInputAdapter(runtime, new AdapterInputSource(filename), "PriceEvent")).start();The contents of a sample CSV file is shown next.
symbol,price,volume IBM,55.5,1000
The next code snippet outlines using a java.io.Reader as an alternative input source :
String myCSV = "symbol, price, volume" + NEW_LINE + "IBM, 10.2, 10000"; StringReader reader = new StringReader(myCSV); (new CSVInputAdapter(runtime, new AdapterInputSource(reader), "PriceEvent")).start();
In the previous code samples, the PriceEvent properties were defined programmatically with their correct types. It is possible to
skip this step and use only a column header record. In such a case you must define property types in the header otherwise a type of String is assumed.
Consider the following:
symbol,double price, int volume IBM,55.5,1000 symbol,price,volume IBM,55.5,1000
The first CSV file defines explicit types in the column header while the second file does not. With the second file a statement like
select sum(volume) from PriceEvent.win:time(1 min) will be rejected as in the second file volume is defaulted
to type String - unless otherwise programmatically configured.
The previous section used an event type based on java.util.Map. The adapter can also populate the CSV data into JavaBean events directly, as long as your event class provides setter-methods that follow JavaBean conventions. Note that esperio will ignore read-only properties i.e. if you have a read-only property priceByVolume it will not expect a corresponding column in the input file.
To use Java objects as events instead of Map-based event types, simply register the event type name for the Java class and provide the same name to the CSV adapter.
The below code snipped assumes that a PriceEvent class exists that exposes setter-methods for the three properties. The setter-methods are, for example, setSymbol(String s), setPrice(double p) and setVolume(long v).
Configuration configuration = new Configuration();
configuration.getCommon().addEventType("PriceEvent", PriceEvent.class);
runtime = EPRuntimeProvider.getDefaultRuntime(configuration);
EPStatement stmt = compileDeploy(runtime, "select symbol, price, volume from PriceEvent.win:length(100)"); // see docs for compile and deploy
(new CSVInputAdapter(runtime, new AdapterInputSource(filename), "PriceEvent")).start();When using JavaBean POJO Events, the event properties types are known from the underlying event type configuration. The CSV file row header does not need to define column type explicitly.
Wether you use JavaBean POJO or Map-based event types, EsperIO provides support for nested event properties up to one level of nesting.
The row header must then refer to the properties using a propertyName.nestedPropertyName syntax.
There is no support for mapped or indexed properties.
For example consider the following:
public class Point {
int x;
int y;
// with getters & setters
}
public class Figure {
String name;
Point point; // point.x and point.y are nested properties
//with getters & setters
}Or the equivalent representation with nested maps, assuming "Figure" is the declared event type name, the CSV file can contain the following row header:
name, point.x, point.y
Use the CSVInputAdapterSpec class to set playback options. The following options are available:
Loop - Reads the CSV input source in a loop; When the end is reached, the input adapter rewinds to the beginning
Events per second - Controls the number of events per second that the adapter sends to the runtime
Property order - Controls the order of event property values in the CSV input source, for use when the CSV input source does not have a header column
Property types - Defines the property types, overriding property types of the event type.
Runtime thread - Instructs the adapter to use the runtime timer thread to read the CSV input source and send events to the runtime
External timer - Instructs the adapter to use the esper's external timer rather than the internal timer. See "Sending timer events" below
Timestamp column name - Defines the name of the timestamp column in the CSV input source; The timestamp column must carry long-typed timestamp values relative to the current time; Use zero for the current time
The next code snippet shows the use of CSVInputAdapterSpec to set playback options.
CSVInputAdapterSpec spec = new CSVInputAdapterSpec(new AdapterInputSource(myURL), "PriceEvent"); spec.setEventsPerSec(1000); spec.setLooping(true); InputAdapter inputAdapter = new CSVInputAdapter(runtime, spec); inputAdapter.start(); // method blocks unless runtime thread option is set
The adapter can be instructed to use either esper's internal timer, or to drive timing itself by sending external timer events. If the internal timer is used, esperio will send all events in "real time". For example, if an input file contains the following data:
symbol,price,volume,timestamp IBM,55.5,1000,2 GOOG,9.5,1000,3 MSFT,8.5,1000,3 JAVA,7.5,1000,1004
then esperio will sleep for 1001 milliseconds between sending the MSFT and JAVA events to the runtime.
If external timing is enabled then esperio will run through the input file at full speed without pausing. The algorithm used sends a time event after all events for a particular time have been received. For the above example file a time event for 2 will be sent after IBM, for 3 after MSFT and 1004 after JAVA. For many of use cases this gives a performance improvement.
The CSV input adapter can run simulations of events arriving in time-order from different input streams. Use the AdapterCoordinator as a specialized input adapter for coordinating multiple CSV input sources by timestamp.
The sample application code listed below simulates price and trade events arriving in timestamp order. Via the adapter the application reads two CSV-formatted files from a URL that each contain a timestamp column as well as price or trade events. The AdapterCoordinator uses the timestamp column to send events to the runtime in the exact ordering prescribed by the timestamp values.
AdapterInputSource sourceOne = new AdapterInputSource(new URL("FILE://prices.csv"));
CSVInputAdapterSpec inputOne = new CSVInputAdapterSpec(sourceOne, "PriceEvent");
inputOne.setTimestampColumn("timestamp");
AdapterInputSource sourceTwo = new AdapterInputSource(new URL("FILE://trades.csv"));
CSVInputAdapterSpec inputTwo = new CSVInputAdapterSpec(sourceTwo, "TradeEvent");
inputTwo.setTimestampColumn("timestamp");
AdapterCoordinator coordinator = new AdapterCoordinatorImpl(runtime, true);
coordinator.coordinate(new CSVInputAdapter(inputOne));
coordinator.coordinate(new CSVInputAdapter(inputTwo));
coordinator.start();
The AdapterCoordinatorImpl is provided with two parameters: the runtime instance, and a boolean value
that instructs the adapter to use the runtime timer thread if set to true, and the adapter can use the application thread if the flag passed is false.
You may not set an event rate per second when using a timestamp column and time-order.
The CSV adapter can employ the runtime timer thread of an Esper runtime instance to read and send events. This can be controlled via the setUsingRuntimeThread method on CSVInputAdapterSpec. We use that feature in the sample code below to pause and resume a running CSV input adapter.
CSVInputAdapterSpec spec = new CSVInputAdapterSpec(new AdapterInputSource(myURL), "PriceEvent"); spec.setEventsPerSec(100); spec.setUsingRuntimeThread(true); InputAdapter inputAdapter = new CSVInputAdapter(runtime, spec); inputAdapter.start(); // method starts adapter and returns, non-blocking Thread.sleep(5000); // sleep 5 seconds inputAdapter.pause(); Thread.sleep(5000); // sleep 5 seconds inputAdapter.resume(); Thread.sleep(5000); // sleep 5 seconds inputAdapter.stop();
This chapter discusses the input and output adapters for JMS based on the Spring JmsTemplate technology. For more information on Spring, and the latest version of Spring, please visit http://www.springframework.org.
The output adapter requires Esper compiler as well as Esper runtime as a dependency. The input adapter only requires Esper runtime as a dependency.
Here are the steps to use the adapters:
Configure an Esper runtime instance to use a SpringContextLoader for loading input and output adapters, and point it to a Spring JmsTemplate configuration file.
Create a Spring JmsTemplate configuration file for your JMS provider and add all your input and output adapter entries in the same file.
For receiving events from a JMS destination into an runtime (input adapter):
List the destination and un-marshalling class in the Spring configuration.
Create EPL statements using the event type name matching the event objects or the Map-event type names received.
For sending events to a JMS destination (output adapter):
Use the insert-into syntax naming the stream to insert-into using the same name as listed in the Spring configuration file
Configure the Map event type of the stream in the runtime configuration
In summary the Spring JMS input adapter performs the following functions:
Initialize from a given Spring configuration file in classpath or from a filename. The Spring configuration file sets all JMS parameters such as JMS connection factory, destination and listener pools.
Attach to a JMS destination and listen to messages using the Spring class org.springframework.jms.core.JmsTemplate
Unmarshal a JMS message and send into the configured runtime instance
The Spring JMS output adapter can:
Initialize from a given Spring configuration file in classpath or from a filename, and attach to a JMS destination
Act as a listener to one or more named streams populated via insert-into syntax by EPL statements
Marshal events generated by a stream into a JMS message, and send to the given destination
The Spring JMS input and output adapters are configured as part of the Esper runtime configuration. EsperIO supplies a SpringContextLoader class that loads a Spring
configuration file which in turn configures the JMS input and output adapters. List the SpringContextLoader class as an adapter loader in the Esper configuration file as the below example shows. The configuration API can alternatively be used to configure one or more adapter loaders.
<esper-configuration xmlns="http://www.espertech.com/schema/esper">
<runtime>
<!-- Sample configuration for an input/output adapter loader -->
<plugin-loader name="MyLoader" class-name="com.espertech.esperio.jms.SpringContextLoader">
<!-- SpringApplicationContext translates into Spring ClassPathXmlApplicationContext
or FileSystemXmlApplicationContext. Only one app-context of a sort can be used.
When both attributes are used classpath and file, classpath prevails -->
<init-arg name="classpath-app-context" value="spring\jms-spring.xml" />
<init-arg name="file-app-context" value="spring\jms-spring.xml" />
</plugin-loader>
</runtime>
</esper-configuration>
The loader loads the Spring configuration file from classpath via the classpath-app-context configuration, or from a file via file-app-context.
The Spring configuration file must list input and output adapters to be initialized by SpringContextLoader upon runtime initialization.
Please refer to your JMS provider documentation, and the Spring framework documentation on help to configure your specific JMS provider via Spring.
The next XML snippet shows a complete sample configuration for an input adapter. The sample includes the JMS configuration for an Apache ActiveMQ JMS provider.
<!-- Spring Application Context -->
<beans default-destroy-method="destroy">
<!-- JMS ActiveMQ Connection Factory -->
<bean id="jmsActiveMQFactory" class="org.apache.activemq.pool.PooledConnectionFactory">
<property name="connectionFactory">
<bean class="org.apache.activemq.ActiveMQConnectionFactory">
<property name="brokerURL" value="tcp://localhost:61616"/>
</bean>
</property>
</bean>
<!-- ActiveMQ destination to use by default -->
<bean id="defaultDestination"
class="org.apache.activemq.command.ActiveMQQueue">
<constructor-arg value="ESPER.QUEUE"/>
</bean>
<!-- Spring JMS Template for ActiveMQ -->
<bean id="jmsActiveMQTemplate" class="org.springframework.jms.core.JmsTemplate">
<property name="connectionFactory">
<ref bean="jmsActiveMQFactory"/>
</property>
<property name="defaultDestination">
<ref bean="defaultDestination"/>
</property>
</bean>
<!-- Provides listener threads -->
<bean id="listenerContainer"
class="org.springframework.jms.listener.SimpleMessageListenerContainer">
<property name="connectionFactory" ref="jmsActiveMQFactory"/>
<property name="destination" ref="defaultDestination"/>
<property name="messageListener" ref="jmsInputAdapter"/>
</bean>
<!-- Default unmarshaller -->
<bean id="jmsMessageUnmarshaller"
class="com.espertech.esperio.jms.JMSDefaultAnyMessageUnmarshaller"/>
<!-- Input adapter -->
<bean id="jmsInputAdapter" class="com.espertech.esperio.jms.SpringJMSTemplateInputAdapter">
<property name="jmsTemplate">
<ref bean="jmsActiveMQTemplate"/>
</property>
<property name="jmsMessageUnmarshaller">
<ref bean="jmsMessageUnmarshaller"/>
</property>
</bean>
</beans>
This input adapter attaches to the JMS destination ESPER.QUEUE at an Apache MQ broker available at port tcp://localhost:61616. It configures an un-marshalling class as discussed next.
EsperIO provides a class for unmarshaling JMS message instances into events for processing by an runtime in the class JMSDefaultAnyMessageUnmarshaller. The class unmarshals as follows:
If the received Message is of type javax.xml.MapMessage, extract the event type name out of the message and send to the runtime via sendEventMap(Map, name)
If the received Message is of type javax.xml.ObjectMessage, extract the Serializable out of the message and send to the runtime via sendEventBean(Object, object.getClass().getSimpleName())
If the received Message is of type javax.xml.TextMessage, extract the text out of the message, parse it as JSON-formatted message according to the named JSON event type that was previously created by create json schema and send to the runtime via sendEventJson(json, eventTypeName) (see below for eventTypeName).
Else the un-marshaller outputs a warning and ignores the message
For map messages, the unmarshaller must be made aware of the event type of events within MapMessage messages. This is achieved by the client application setting a well-defined property on the message: InputAdapter.ESPERIO_MAP_EVENT_TYPE. An example code snippet is:
MapMessage mapMessage = jmsSession.createMapMessage(); mapMessage.setObject(InputAdapter.ESPERIO_MAP_EVENT_TYPE, "MyInputEvent");
For text JSON messages, the unmarshaller must be made aware of the event type of events within TextMessage messages. This is achieved by the client application setting a well-defined property on the message: InputAdapter.ESPERIO_JSON_EVENT_TYPE. An example code snippet is:
MapMessage mapMessage = jmsSession.createMapMessage(); mapMessage.setString(InputAdapter.ESPERIO_JSON_EVENT_TYPE, "MyJsonEvent");
The Spring configuration file lists all input and output adapters in one file. The SpringContextLoader upon runtime initialization starts all input and output adapters.
The next XML snippet shows a complete sample configuration of an output adapter. Please check with your JMS provider for the appropriate Spring class names and settings. Note that the input and output adapter Spring configurations can be in the same file.
<!-- Application Context -->
<beans default-destroy-method="destroy">
<!-- JMS ActiveMQ Connection Factory -->
<bean id="jmsActiveMQFactory" class="org.apache.activemq.pool.PooledConnectionFactory">
<property name="connectionFactory">
<bean class="org.apache.activemq.ActiveMQConnectionFactory">
<property name="brokerURL" value="tcp://localhost:61616"/>
</bean>
</property>
</bean>
<!-- ActiveMQ destination to use by default -->
<bean id="defaultDestination"
class="org.apache.activemq.command.ActiveMQQueue">
<constructor-arg value="ESPER.QUEUE"/>
</bean>
<!-- Spring JMS Template for ActiveMQ -->
<bean id="jmsActiveMQTemplate" class="org.springframework.jms.core.JmsTemplate">
<property name="connectionFactory">
<ref bean="jmsActiveMQFactory"/>
</property>
<property name="defaultDestination">
<ref bean="defaultDestination"/>
</property>
<property name="receiveTimeout">
<value>30000</value>
</property>
</bean>
<!-- Marshaller marshals events into map messages -->
<bean id="jmsMessageMarshaller" class="com.espertech.esperio.jms.JMSDefaultMapMessageMarshaller"/>
<bean id="myCustomMarshaller" class="com.espertech.esperio.jms.JMSDefaultMapMessageMarshaller"/>
<!-- Output adapter puts it all together -->
<bean id="jmsOutputAdapter" class="com.espertech.esperio.jms.SpringJMSTemplateOutputAdapter">
<property name="jmsTemplate">
<ref bean="jmsActiveMQTemplate"/>
</property>
<property name="subscriptionMap">
<map>
<entry>
<key><idref local="subscriptionOne"/></key>
<ref bean="subscriptionOne"/>
</entry>
<entry>
<key><idref local="subscriptionTwo"/></key>
<ref bean="subscriptionTwo"/>
</entry>
</map>
</property>
<property name="jmsMessageMarshaller">
<ref bean="jmsMessageMarshaller"/>
</property>
</bean>
<bean id="subscriptionOne" class="com.espertech.esperio.jms.JMSSubscription">
<property name="eventTypeName" value="MyOutputStream"/>
</bean>
<bean id="subscriptionTwo" class="com.espertech.esperio.jms.JMSSubscription">
<property name="eventTypeName" value="MyOtherOutputStream"/>
<property name="jmsMessageMarshaller">
<ref bean="myCustomMarshaller"/>
</property>
</bean>
</beans>
EsperIO provides a marshal implementation in the class JMSDefaultMapMessageMarshaller. This marshaller constructs a JMS MapMessage from any event received by copying
event properties into the name-value pairs of the message. The configuration file makes it easy to configure a custom marshaller that adheres to the com.espertech.esperio.jms.JMSMessageMarshaller interface.
Note that this marshaller uses javax.jms.MapMessage name-value pairs and not general javax.jms.Message properties.
This means when you'll read the event properties back from the JMS MapMessage, you will have to use the javax.jms.MapMessage.getObject(...) method.
The SpringJMSTemplateOutputAdapter is configured with a list of subscription instances of type JMSSubscription as the sample configuration shows. Each subscription defines
an event type name that must be configured and used in the insert-into syntax of a statement.
To connect the Spring JMS output adapter and the EPL statements producing events, use the insert-into syntax to direct events for output. Here is a sample statement that sends events into MyOutputStream:
insert into MyOutputStream select assetId, zone from RFIDEvent
The type MyOutputStream must be known to a runtime. The output adapter requires the name to be configured with the runtime instance, e.g.:
<esper-configuration xmlns="http://www.espertech.com/schema/esper">
<common>
<event-type name="MyOutputStream">
<java-util-map>
<map-property name="assetId" class="String"/>
<map-property name="zone" class="int"/>
</java-util-map>
</event-type>
</common>
</esper-configuration>This chapter discusses the input and output adapters for AMQP. AMQP input and output utilizes data flow operators.
This adapter only requires Esper runtime as a dependency and does not require Esper compiler.
In order to use the AMQP data flow operators, add esperio-amqp-version.jar to your classpath and import the operator package or class using the static or runtime configuration.
The following code snippet uses the runtime configuration API to import the AMQP adapter classes:
Configuration configuration = new Configuration(); configuration.getCommon().addImport(AMQPSource.class.getPackage().getName() + ".*");
The AMQP input and output adapter provides the following data flow operators:
Table 4.1. AMQP Operators
| Operator | Description |
|---|---|
| AMQPSink |
Send messages to an AMQP broker. See Section 4.2, “AMQPSink Operator”. |
| AMQPSource |
Receive messages from an AMQP broker. See Section 4.3, “AMQPSource Operator”. |
The AMQPSink operator receives input stream events, transforms events to AMQP messages and sends messages into an AMQP queue.
The AMQPSink operator must have a single input stream.
The AMQPSink operator cannot declare any output streams.
Parameters for the AMQPSink operator are:
Table 4.2. AMQPSink Parameters
| Name | Description |
|---|---|
| host (required) | An expression returning the host name string |
| queueName | An expression returning the queue name string |
| collector (required) | Transformation class or instance for events to AMQP message |
| port | An expression returning the port number integer |
| username | An expression returning the user name string |
| password | An expression returning the password string (also see systemProperties or data flow instantiation options) |
| vhost | An expression returning the vhost string |
| exchange | An expression returning the exchange name string |
| routingKey | An expression returning the routing key string |
| logMessages | An expression returning a boolean indicator whether to log a text for each message (requires debug-level logging) |
| waitMSecNextMsg | An expression returning the number of milliseconds wait between messages, a long-typed value |
| declareDurable | An expression returning a boolean indicator whether durable, false by default |
| declareExclusive | An expression returning a boolean indicator whether exclusive, false by default |
| declareAutoDelete | An expression returning a boolean indicator whether auto-delete, true by default |
| declareAdditionalArgs | Map of additional arguments passed to AMQP of type Map<String, Object> |
Either the queueName or the combination of exchange and routingKey are required parameters.
The collector is required and must be specified to transform events to AMQP messages. The collector instance must implement the interface ObjectToAMQPCollector. The adapter provides a default implementation ObjectToAMQPCollectorSerializable that employs default serialization.
For JSON formatted messages, the adapter provides the ObjectToAMQPCollectorJson JSON collector. The collector emits string-type messages.
You must specify a JSON event type name e.g. create json schema MyJsonEventType(...) and outstream<MyJsonEventType>.
The following example declares a data flow that is triggered by MyMapEventType events from the event bus (type not declared here) that sends serialized messages to an AMQP queue:
create dataflow AMQPOutgoingDataFlow
EventBusSource -> outstream<MyMapEventType> {}
AMQPSink(outstream) {
host: 'localhost',
queueName: 'myqueue',
collector: {class: 'ObjectToAMQPCollectorSerializable'}
}The AMQPSource operator receives AMQP messages from a queue, transforms messages and populates a data flow instance with events.
The AMQPSource operator cannot declare any input streams.
The AMQPSource operator must have a single output stream.
Parameters for the AMQPSource operator are listed below, with the required parameters listed first:
Table 4.3. AMQPSource Parameters
| Name | Description |
|---|---|
| host (required) | An expression returning the host name string |
| queueName (required) | An expression returning the queue name string |
| collector (required) | Transformation class or instance for AMQP message to underlying event transformation |
| port | An expression returning the port number integer |
| username | An expression returning the user name string |
| password | An expression returning the password string (also see systemProperties or data flow instantiation options) |
| vhost | An expression returning the vhost string |
| exchange | An expression returning the exchange name string |
| routingKey | An expression returning the routing key string |
| logMessages | An expression returning a boolean indiator whether to log a text for each message (requires debug-level logging) |
| waitMSecNextMsg | An expression returning the number of milliseconds wait between messages, a long-typed value |
| declareDurable | An expression returning a boolean indicator whether durable, false by default |
| declareExclusive | An expression returning a boolean indicator whether exclusive, false by default |
| declareAutoDelete | An expression returning a boolean indicator whether auto-delete, true by default |
| declareAdditionalArgs | Map of additional arguments passed to AMQP of type Map<String, Object> |
| prefetchCount | An expression returning the prefetch count integer, defaults to 100 |
| consumeAutoAck | An expression returning a boolean indicator whether to auto-ack, true by default |
The collector is required and must be specified to transform AMQP messages to events. The collector instance must implement the interface AMQPToObjectCollector.
The adapter provides a default implementation AMQPToObjectCollectorSerializable that employs default serialization.
For JSON formatted messages, the adapter provides the AMQPToObjectCollectorJson JSON collector. The collector deserializes the AMQP message bytes into a string using the JVM default encoding
and parses the JSON message for processing as an event. You must specify a JSON event type name e.g. create json schema MyJsonEventType(...) and outstream<MyJsonEventType>.
The following example declares a data flow that is receives AMQP messages from a queue, transforms each message and sends each message of type MyMapEventType into the event bus:
create dataflow AMQPIncomingDataFlow
AMQPSource -> outstream<MyMapEventType> {
host: 'localhost',
queueName: 'myqueue',
collector: {class: 'AMQPToObjectCollectorSerializable'},
logMessages: true
}
EventBusSink(outstream){}This chapter discusses the EsperIO Kafka input adapter.
This input adapter is for receiving events and event or runtime time from Kafka topics.
The scope of this input adapter is a local reader and is not meant for coordinated use by multiple servers, which is the scope of Esper Enterprise Edition. Please see Esper Enterprise Edition for information on the horizontal scale-out architecture based on Kafka (the scope of this input adapter is NOT horizontal scale-out).
Please add the esperio-kafka-version.jar jar file to your classpath.
Please also add kafka-clients-version.jar and the Kafka client dependencies to your classpath.
The EsperIO Kafka input adapter supports the new Kafka consumer only and requires Kafka client version 1.0.1 and higher.
The adapter only requires Esper runtime as a dependency.
For use with the Kafka output adapter, and when using the KafkaOutputDefault annotation, please add the KafkaOutputDefault import.
For example:
configuration.getCommon().addImport(KafkaOutputDefault.class);
You may configure and start the EsperIO Kafka input adapter either as part of your Esper configuration file in the plugin loader section or via the adapter API.
The following example shows an Esper configuration file with all properties:
<esper-configuration xmlns="http://www.espertech.com/schema/esper">
<runtime>
<plugin-loader name="KafkaInput" class-name="com.espertech.esperio.kafka.EsperIOKafkaInputAdapterPlugin">
<!--
Kafka Consumer Properties: Passed-Through to Kafka Consumer.
-->
<init-arg name="bootstrap.servers" value="127.0.0.1:9092"/>
<init-arg name="key.deserializer" value="org.apache.kafka.common.serialization.StringDeserializer"/>
<init-arg name="value.deserializer" value="com.mycompany.MyCustomDeserializer"/>
<init-arg name="group.id" value="my_group_id"/>
<!--
EsperIO Kafka Input Properties: Define subscription, topics, processor and timestamp extractor.
-->
<init-arg name="esperio.kafka.input.subscriber" value="com.espertech.esperio.kafka.EsperIOKafkaInputSubscriberByTopicList"/>
<init-arg name="esperio.kafka.topics" value="my_topic"/>
<init-arg name="esperio.kafka.input.processor" value="com.espertech.esperio.kafka.EsperIOKafkaInputProcessorDefault"/>
<init-arg name="esperio.kafka.input.timestampextractor" value="com.espertech.esperio.kafka.EsperIOKafkaInputTimestampExtractorConsumerRecord"/>
</plugin-loader>
</runtime>
</esper-configuration>Alternatively the equivalent API calls to configure the adapter are:
Properties props = new Properties();
// Kafka Consumer Properties
props.put(ConsumerConfig.BOOTSTRAP_SERVERS_CONFIG, "127.0.0.1:9092");
props.put(ConsumerConfig.KEY_DESERIALIZER_CLASS_CONFIG, org.apache.kafka.common.serialization.StringDeserializer.class.getName());
props.put(ConsumerConfig.VALUE_DESERIALIZER_CLASS_CONFIG, com.mycompany.MyCustomDeserializer.class.getName());
props.put(ConsumerConfig.GROUP_ID_CONFIG, "my_group_id");
// EsperIO Kafka Input Adapter Properties
props.put(EsperIOKafkaConfig.INPUT_SUBSCRIBER_CONFIG, EsperIOKafkaInputSubscriberByTopicList.class.getName());
props.put(EsperIOKafkaConfig.TOPICS_CONFIG, "my_topic");
props.put(EsperIOKafkaConfig.INPUT_PROCESSOR_CONFIG, EsperIOKafkaInputProcessorDefault.class.getName());
props.put(EsperIOKafkaConfig.INPUT_TIMESTAMPEXTRACTOR_CONFIG, EsperIOKafkaInputTimestampExtractorConsumerRecord.class.getName());
Configuration config = new Configuration();
config.getRuntime().addPluginLoader("KafkaInput", EsperIOKafkaInputAdapterPlugin.class.getName(), props, null);By adding the plug-in loader to the configuration as above the runtime automatically starts the adapter as part of runtime initialization.
Alternatively, the adapter can be started and stopped programatically as follows:
// start adapter EsperIOKafkaInputAdapter adapter = new EsperIOKafkaInputAdapter(props, "default"); adapter.start(); // destroy the adapter when done adapter.destroy();
All properties are passed to the Kafka consumer. This allows your application to add additional properties that are not listed here and according to Kafka consumer documentation.
Required properties are below. ConsumerConfig is part of the Kafka API in org.apache.kafka.clients.consumer.ConsumerConfig.
Table 5.1. Kafka Consumer Required Properties
| Name | API Name | Description |
|---|---|---|
bootstrap.servers | ConsumerConfig.BOOTSTRAP_SERVERS_CONFIG | Kafka bootstrap server list. |
key.deserializer | ConsumerConfig.KEY_DESERIALIZER_CLASS_CONFIG | Fully-qualified class name of Kafka message key de-serializer. |
value.deserializer | ConsumerConfig.VALUE_DESERIALIZER_CLASS_CONFIG | Fully-qualified class name of Kafka message value de-serializer. |
group.id | ConsumerConfig.GROUP_ID_CONFIG | Application consumer group id. |
The input adapter operation depends on the subscriber and processor.
The subscriber is responsible for calling Kafka consumer subscribe methods, i.e. calls Kafka API consumer.subscribe(...).
The processor is responsible for processing Kafka API ConsumerRecords messages, i.e. implements process(ConsumerRecords records).
Properties that define the subscriber and consumer are below.
EsperIOKafka is part of the EsperIO Kafka API in com.espertech.esperio.kafka.EsperIOKafkaConfig.
Table 5.2. Kafka Input Adapter Properties
| Name | API Name | Description |
|---|---|---|
esperio.kafka.input.subscriber | EsperIOKafkaConfig.INPUT_SUBSCRIBER_CONFIG |
Required property. Fully-qualified class name of subscriber that subscribes to topics and partitions.
The class must implement the interface
You may use |
esperio.kafka.topics | EsperIOKafkaConfig.TOPICS_CONFIG |
Optional property and only required if the subscriber is Specifies a comma-separated list of topic names to subscribe to. |
esperio.kafka.input.processor | EsperIOKafkaConfig.INPUT_PROCESSOR_CONFIG |
Required property. Fully-qualified class name of the Kafka consumer records processor that sends events into the runtime and may advance runtime time.
The class must implement the interface
You may use |
esperio.kafka.input.timestampextractor | EsperIOKafkaConfig.INPUT_TIMESTAMPEXTRACTOR_CONFIG |
Optional property. Fully-qualified class name of the Kafka message timestamp extractor that extracts a long-typed timestamp from a consumer record, for use as time.
The class must implement the interface
You may use |
esperio.kafka.input.eventtypename | EsperIOKafkaConfig.INPUT_EVENTTYPENAME |
Optional property.
Event type name of the JSON event type; For use with JSON and |
The subcriber is responsible for calling consumer.subscribe(...).
The adapter provides a default implementation by name EsperIOKafkaInputSubscriberByTopicList.
Your application may provide its own subscriber by implementing the simple EsperIOKafkaInputSubscriber interface.
This default implementation takes the value of esperio.kafka.topics and subscribes to each topic.
For reference, we provide the code of the default subscriber below (repository or source jar for full code):
public class EsperIOKafkaInputSubscriberByTopicList implements EsperIOKafkaInputSubscriber {
public void subscribe(EsperIOKafkaInputSubscriberContext context) {
String topicsCSV = EsperIOKafkaInputAdapter.getRequiredProperty(context.getProperties(), EsperIOKafkaConfig.TOPICS_CONFIG);
String[] topicNames = topicsCSV.split(",");
List<String> topics = new ArrayList<>();
for (String topicName : topicNames) {
if (topicName.trim().length() > 0) {
topics.add(topicName.trim());
}
}
context.getConsumer().subscribe(topics);
}
}
The processor is responsible for processing Kafka API ConsumerRecords.
The adapter provides a default implementation by name EsperIOKafkaInputProcessorDefault.
Your application may provide its own processor by implementing the simple EsperIOKafkaInputProcessor interface.
This default processor can be configured with an optional timestamp extractor that obtains a timestamp for each consumer record. If no timestamp extractor is configured, the default processor does not advance time.
For reference, we provide the (slightly simplified) code of the default processor below (repository or source jar for full code):
public class EsperIOKafkaInputProcessorDefault implements EsperIOKafkaInputProcessor {
private EPRuntime runtime;
private EsperIOKafkaInputTimestampExtractor timestampExtractor;
public void init(EsperIOKafkaInputProcessorContext context) {
this.runtime = context.getRuntime();
String timestampExtractorClassName = context.getProperties().getProperty(EsperIOKafkaConfig.INPUT_TIMESTAMPEXTRACTOR_CONFIG);
if (timestampExtractorClassName != null) {
timestampExtractor = (EsperIOKafkaInputTimestampExtractor) JavaClassHelper.instantiate(EsperIOKafkaInputTimestampExtractor.class, timestampExtractorClassName);
}
}
public void process(ConsumerRecords<Object, Object> records) {
for (ConsumerRecord record : records) {
if (timestampExtractor != null) {
long timestamp = timestampExtractor.extract(record);
// advances runtime time
runtime.getEPRuntime().advanceTimeSpan(timestamp);
}
if (record.value() != null) {
Object event = record.value();
runtime.getEPRuntime().sendEventBean(event, event.getClass().getSimpleName());
}
}
}
public void close() {}
}The default processor takes the message value and sends it as an event into the runtime. It assumes the event type name is the simple class name. The default processor takes the extracted time, if a timestamp extractor is provided, and sends a time span event to the runtime to advance runtime time.
For use with JSON, EsperIO provides the EsperIOKafkaInputProcessorJson processor. Please define the esperio.kafka.input.eventtypename property
that provides the JSON event type name.
You must provide your own processor if any additional event transformation is required or if using epRuntime.sendEvent(Map/ObjectArray/Node)
or if the default behavior does not fit for other reasons.
You may configure and start the EsperIO Kafka output adapter either as part of your Esper configuration file in the plugin loader section or via the adapter API.
The following example shows an Esper configuration file with all properties:
<esper-configuration xmlns="http://www.espertech.com/schema/esper">
<runtime>
<plugin-loader name="KafkaOutput" class-name="com.espertech.esperio.kafka.EsperIOKafkaOutputAdapterPlugin">
<!--
Kafka Producer Properties: Passed-Through to Kafka Consumer.
-->
<init-arg name="bootstrap.servers" value="127.0.0.1:9092"/>
<init-arg name="key.serializer" value="org.apache.kafka.common.serialization.StringSerializer"/>
<init-arg name="value.serializer" value="com.mycompany.MyCustomSerializer"/>
<!--
EsperIO Kafka Output Properties: Define a flow controller.
-->
<init-arg name="esperio.kafka.output.flowcontroller" value="com.espertech.esperio.kafka.EsperIOKafkaOutputFlowControllerByAnnotatedStmt"/>
<init-arg name="esperio.kafka.topics" value="my_topic"/>
</plugin-loader>
</runtime>
</esper-configuration>Alternatively the equivalent API calls to configure the adapter are:
Properties props = new Properties();
// Kafka Producer Properties
props.put(ProducerConfig.BOOTSTRAP_SERVERS_CONFIG, "127.0.0.1:9092");
props.put(ProducerConfig.KEY_SERIALIZER_CLASS_CONFIG, org.apache.kafka.common.serialization.StringSerializer.class.getName());
props.put(ProducerConfig.VALUE_SERIALIZER_CLASS_CONFIG, org.apache.kafka.common.serialization.StringSerializer.class.getName());
// EsperIO Kafka Output Adapter Properties
props.put(EsperIOKafkaConfig.OUTPUT_FLOWCONTROLLER_CONFIG, EsperIOKafkaOutputFlowControllerByAnnotatedStmt.class.getName());
props.put(EsperIOKafkaConfig.TOPICS_CONFIG, "my_topic");
Configuration config = new Configuration();
config.getRuntime().addPluginLoader("KafkaOutput", EsperIOKafkaOutputAdapterPlugin.class.getName(), props, null);By adding the plug-in loader to the configuration as above the runtime automatically starts the adapter as part of runtime initialization.
Alternatively, the adapter can be started and stopped programatically as follows:
// start adapter EsperIOKafkaOutputAdapter adapter = new EsperIOKafkaOutputAdapter(props, "default"); adapter.start(); // destroy the adapter when done adapter.destroy();
All properties are passed to the Kafka producer. This allows your application to add additional properties that are not listed here and according to Kafka producer documentation.
Required properties are below. ProducerConfig is part of the Kafka API in org.apache.kafka.clients.producer.ProducerConfig.
Table 5.3. Kafka Producer Required Properties
| Name | API Name | Description |
|---|---|---|
bootstrap.servers | ProducerConfig.BOOTSTRAP_SERVERS_CONFIG | Kafka bootstrap server list. |
key.serializer | ProducerConfig.KEY_SERIALIZER_CLASS_CONFIG | Fully-qualified class name of Kafka message key serializer. |
value.serializer | ProducerConfig.VALUE_SERIALIZER_CLASS_CONFIG | Fully-qualified class name of Kafka message value serializer. |
The output adapter operation depends on the flow controller, which is reponsible for attaching listeners to statements that send messages to Kafka topics.
Properties that define the flow controller are below.
EsperIOKafka is part of the EsperIO Kafka API in com.espertech.esperio.kafka.EsperIOKafkaConfig.
Table 5.4. Kafka Output Adapter Properties
| Name | API Name | Description |
|---|---|---|
esperio.kafka.output.flowcontroller | EsperIOKafkaConfig.OUTPUT_FLOWCONTROLLER_CONFIG |
Required property. Fully-qualified class name of flow controller that produces messages.
The class must implement the interface
You may use |
esperio.kafka.topics | EsperIOKafkaConfig.TOPICS_CONFIG |
Specifies a comma-separated list of topic names to produce to, for use with the above flow controller and not required otherwise. |
The flow controller is responsible for allocating a KafkaProducer and associating statement listeners to the producer, for listeners to send messages to Kafka topics.
The adapter provides a default implementation by name EsperIOKafkaOutputFlowControllerByAnnotatedStmt.
Your application may provide its own subscriber by implementing the simple EsperIOKafkaOutputFlowControllerContext interface.
The flow controller takes the value of esperio.kafka.topics and produces a message to each topic for each statement listener output event.
The flow controller attaches a listener to all statements that have the @KafkaOutputDefault annotation.
Please ensure that the annotation is part of your imports. The adapter considers all newly-created statements that have the annotation.
Thus please create the EPL as follows:
@KafkaOutputDefault select * from ......
The flow controller produces JSON output. It uses the runtime JSON renderer that can be obtained from runtime.getRenderEventService().getJSONRenderer(statement.getEventType());.
The statement listeners that the flow controller attaches do not provide a key or partition id to the producer.
The listeners simply invoke new ProducerRecord(topic, json) for output event and each topic.
The value serializer must be the string serializer.
For reference, please find the source code of the flow controller in the repository.
This chapter discusses the EsperIO HTTP adapter.
The output adapter requires Esper compiler as well as Esper runtime as a dependency. The input adapter only requires Esper runtime as a dependency.
The EsperIO HTTP input and output adapter can be used to send events into an Esper runtime instance as well as perform HTTP requests triggered by output events generated by an Esper runtime instance.
To send events into an Esper runtime instance for processing you declare an HTTP service, which causes the adapter to expose an HTTP protocol server on the configured port to handle incoming requests. Your configuration then attaches Get handlers that receive Get requests that post events into the runtime with data from each request.
Output events generated by an Esper runtime instance can trigger an HTTP Get operation to a URI of your choice. For this purpose define a triggering event stream and the desired target URI and parameters.
You may configure the EsperIO HTTP adapter either as part of your Esper configuration file in the plugin loader section or via the adapter API. Add the esperio-http-version.jar file to your classpath.
For input adapter operation, add the httpcore-version.jar to your classpath. If using Java NIO add the httpcore-nio-version.jar to your classpath in addition.
For output adapter operation, add the httpclient-version.jar to your classpath.
A sample adapter configuration file is provided in esperio-http-sample-config.xml in the etc folder of the distribution. A configuration file must be valid according to schema esperio-http-configuration-8-0.xsd.
You may place the configuration XML directly into your Esper configuration file as the example below shows:
<esper-configuration xmlns="http://www.espertech.com/schema/esper">
<runtime>
<plugin-loader name="EsperIOHTTPAdapter"
class-name="com.espertech.esperio.http.EsperIOHTTPAdapterPlugin">
<init-arg name="esperio.http.configuration.file"
value="file:/path/esperio-http-sample-config.xml" />
</plugin-loader>
</runtime>
</esper-configuration>Alternatively you can provide a URL in the Esper configuration file to point to your adapter configuration file:
<esper-configuration xmlns="http://www.espertech.com/schema/esper">
<runtime>
<plugin-loader name="EsperIOHTTPAdapter"
class-name="com.espertech.esperio.http.EsperIOHTTPAdapterPlugin">
<init-arg name="esperio.http.configuration.file"
value="file:/path/esperio-http-sample-config.xml" />
</plugin-loader>
</runtime>
</esper-configuration>If using Spring or if your application requires API access, the following code snippet configures and starts the adapter via API.
The class for configuring an EsperIO HTTP adapter is com.espertech.esperio.http.config.ConfigurationHTTPAdapter. The adapter class itself is
EsperIOHTTPAdapter.
The code snippet below is a sample that configures using driver manager and starts the adapter via API:
ConfigurationHTTPAdapter adapterConfig = new ConfigurationHTTPAdapter();
// add additional configuration
Request request = new Request();
request.setStream("TriggerEvent");
request.setUri("http://localhost:8077/root");
adapterConfig.getRequests().add(request);
// start adapter
EsperIOHTTPAdapter httpAdapter = new EsperIOHTTPAdapter(adapterConfig, "runtimeURI");
httpAdapter.start();
// destroy the adapter when done
httpAdapter.destroy();A service is required for the adapter to receive events via a HTTP client connection.
The synopsis is as follows:
<esperio-http-configuration> <service name="[name]" port="[port]" [nio="true|false"]/> <!-- add additional configuration here --> </esperio-http-configuration>
The name attribute value is required and provides the name of the HTTP service for use in logging and for get-handlers as described below.
The nio attribute is optional and can be used to enable Java NIO (disabled by default).
If configuring via the adapter API or Spring, use the com.espertech.esperio.http.config.Service class.
An example XML to configure a service and single get-handler is:
<esperio-http-configuration> <service name="myservice" port="8079" nio="false"/> <get service="myservice" pattern="*"/> </esperio-http-configuration>
One or more handlers for HTTP Get operations can be installed for a service and are used to receive events.
Define a get element in the adapter configuration file (or use the GetRequest class) for every handler to register for a service.
The synopsis is as follows:
<get service="[service]" pattern="[pattern]"/>
The service attribute value is required and provides the name of the HTTP service to register the Get operation handler for.
A value for the pattern attribute is required and may be either * for all URIs, *[uri] for all URIs ending with the given URI or [uri]* for all URI starting with the given URI.
A sample Get-handler configuration follows:
<get service="myservice" pattern="*"/>
When posting events to the runtime, the Get request URI must contain a stream parameter that carries the name of the stream (event type) to insert into. Each event property to be populated in the input event must be part of the Get request parameter values.
For example, the URI http://localhost:8079/sendevent?stream=MyFirewallEvent&name=Joe&changed=true entered into a browser sends an input event of type MyFirewallEvent setting the name property of the event to "Joe" and the changed property of the event to true.
Note that if your target type is a Java object event, your event class must provide setter-methods according to JavaBean conventions. The event class should also provide a default constructor taking no parameters. If your event class does not have a default constructor, your application may configure a factory method via ConfigurationEventTypeLegacy.
This facility instructs the adapter to perform an HTTP Get request when a triggering event occurs, passing event properties as URI parameters.
Define a request element in the adapter configuration file (or use the Request class) for every HTTP Get to execute.
The synopsis is as follows:
<request stream="[stream]" uri="[uri_with_placeholders]"/>
A value for the stream attribute is required and provides the name of the stream that triggers the HTTP Get. The adapter expects a stream by this name to exist at adapter start time.
The uri_with_placeholders attribute value is required. You may place event property placeholders inside the URI to format the URI as needed. Placeholders are of the format ${property_name}.
A sample request configuration follows:
<request stream="TriggerFirewallStream" uri="http://myremotehost:80/root/event"/>
Assuming the HttpTriggerStream has event properties name and ipaddress then a sample Get request URI is as follows:
http://myremotehost:80/root/event?stream=TriggerFirewallStream&name=Joe&ipaddress=120.1.0.0
You may parameterize the URI via placeholders by placing ${property_name} and the special placeholder ${stream} into the URI string.
The next example configuration defines URI parameters via placeholder:
<request stream="TriggerFirewallStream" uri="http://myremotehost:80/root/${stream}?violation&name=${name};violationip=${ipaddress}"/>The URI generated by the adapter:
http://myremotehost:80/root/TriggerFirewallStream?violation&name=Joe&violationip=120.1.0.0
This chapter discusses the EsperIO Socket adapter.
The EsperIO Socket input adapter can be used to send events into an Esper runtime via socket client, either as Java objects or as CSV name-value pair strings.
The adapter only requires Esper runtime as a dependency.
You may configure the EsperIO Socket adapter either as part of your Esper configuration file in the plugin loader section or via the adapter API. Add the esperio-socket-version.jar file to your classpath. There are no other dependent jar files required.
A sample adapter configuration file is provided in esperio-socket-sample-config.xml in the etc folder of the distribution. A configuration file must be valid according to schema esperio-socket-configuration-8-0.xsd.
You may place the configuration XML directly into your Esper configuration file as the example below shows:
<esper-configuration xmlns="http://www.espertech.com/schema/esper">
<runtime>
<plugin-loader name="EsperIOSocketAdapter"
class-name="com.espertech.esperio.socket.EsperIOSocketAdapterPlugin">
<config-xml>
<esperio-socket-configuration>
<socket name="mysocketOne" port="7101" data="object"/>
<socket name="mysocketTwo" port="7102" data="csv" hostname="myhost" backlog="20" unescape="true"/>
</esperio-socket-configuration>
</config-xml>
</plugin-loader>
</runtime>
</esper-configuration>Alternatively you can provide a URL in the Esper configuration file to point to your adapter configuration file:
<esper-configuration xmlns="http://www.espertech.com/schema/esper">
<runtime>
<plugin-loader name="EsperIOSocketAdapter"
class-name="com.espertech.esperio.socket.EsperIOSocketAdapterPlugin">
<init-arg name="esperio.socket.configuration.file"
value="file:/path/esperio-socket-sample-config.xml" />
</plugin-loader>
</runtime>
</esper-configuration>If using Spring or if your application requires API access, the following code snippet configures and starts the adapter via API.
The class for configuring an EsperIO Socket adapter is com.espertech.esperio.socket.config.ConfigurationSocketAdapter. The adapter class itself is
EsperIOSocketAdapter.
The code snippet below is a sample that configures using driver manager and starts the adapter via API:
ConfigurationSocketAdapter adapterConfig = new ConfigurationSocketAdapter();
SocketConfig socket = new SocketConfig();
socket.setDataType(DataType.CSV);
socket.setPort(port);
adapterConfig.getSockets().put("SocketService", socket);
// start adapter
EsperIOSocketAdapter socketAdapter = new EsperIOSocketAdapter(adapterConfig, "runtimeURI");
socketAdapter.start();
// destroy the adapter when done
socketAdapter.destroy();Add a socket configuration for each unique port that you want to expose a socket receive service for use by socket client connections.
The synopsis is as follows:
<esperio-socket-configuration>
<socket name="[name]" port="[port]" data="[csv|object|property_ordered_csv]"
[hostname="hostname"] [backlog="backlog"] [unescape="true|false"]/>
</esperio-socket-configuration>The required name attribute provides the name of the socket service for use in logging.
The required port attribute provides the port that the socket service accepts client connections.
The required data attribute specifies whether the data arriving through the socket is formatted as a Java binary object stream or as CSV string values.
The optional hostname attribute can provide the host name passed to the server socket (ServerSocket).
The optional backlog attribute can provide the backlog number of connections passed to the server socket. This number defaults to 2 when a host name is passed but no backlog is provided.
The optional unescape attribute is false by default. When false the adapter does not unescape (Java escape rules) values. When true the adapter performs an unescape on all values.
If configuring via the adapter API or Spring, use the com.espertech.esperio.socket.config.SocketConfig class.
When sending events as Java objects, configure the data attribute value to object and use ObjectOutputStream to write events to the client socket. When sending a java.util.Map event,
your Map must contain a String value for the key stream which must denote a configured Map event type.
This example XML configures a socket accepting client connections that provide Java objects:
<esperio-socket-configuration> <socket name="objectStreamSocket" port="8079" data="object"/> </esperio-socket-configuration>
When object data type is configured, clients connections are expected to send java.io.Serializable or java.io.Externalizable objects using ObjectOutputStream.
Below is a block of sample code that for use in clients to the adapter. It assumes the MyEvent class implements either of the above interfaces:
// connect first
Socket requestSocket = new Socket("localhost", port);
ObjectOutputStream out = new ObjectOutputStream(requestSocket.getOutputStream());
// send a few events, here we send only one
out.writeObject(new MyEvent("Hello World"));
out.flush();
// Consider resetting the output stream from time-to-time, after sending a number of objects.
// This is because the stream may cache strings etc. . The reset is:
// out.reset();
// close when done
out.close();
requestSocket.close();When sending events as CSV strings, the format of the string should be:
stream=[type],[name]=[value] [,...] (newline)
The CSV string must end with a newline character: Each event is one line. Each CSV element must be in the [name]=[value] format. Your CSV must contain a value for stream which must denote a configured event type.
The adapter parses each string value and populates an instance of the target type.
This next example XML configures a socket accepting client connections that provide events as CSV-formatted strings with name-value pairs :
<esperio-socket-configuration> <socket name="csvStreamSocket" port="8079" data="csv"/> </esperio-socket-configuration>
A piece of client code that sends an event of type MyEvent may look as follows:
// connect first
String newline = System.getProperty("line.separator");
Socket requestSocket = new Socket("localhost", port);
BufferedWriter wr = new BufferedWriter(
new OutputStreamWriter(socket.getOutputStream()));
// send a few events
wr.write("stream=MyEvent,price=20.d,upcCode=A0001");
wr.write(newline);
wr.flush();
// close when done
wr.close();
requestSocket.close();
Note that if your target type is a Java object event, your event class must provide setter-methods according to JavaBean conventions. The event class should also provide a default constructor taking no parameters. If your event class does not have a default constructor, your application may configure a factory method via ConfigurationEventTypeLegacy.
Similar to the string CSV data format as discussed earlier, this data format allows specifying a property order as well as the event type name.
The format of the string that represents an event is the CSV format (no name= or stream= texts are required):
value [, value [,...]] (newline)
This next example XML configures a socket accepting client connections that provide events as CSV-formatted strings with name-value pairs :
<esperio-socket-configuration> <socket name="csvStreamSocket" port="8079" data="property_ordered_csv" stream="MyEvent" propertyOrder="price,upcCode"/> </esperio-socket-configuration>
Set the data attribute to property_ordered_csv. The stream attribute is a required configuration and must contain the event type name.
The propertyOrder attribute is also required and must contain the property names of properties of the event type, in the same order that the value for the property arrives on each line.
As part of the sample client code shown above, the following line sends an event with values 20.0 and A0001.
wr.write("20.0,A0001");
wr.write(newline);
The JSON-formatted message can be processed by following below format. Please make sure to use create json schema to declare the respective JSON event type.
The format of the string that represents an event in JSON format is:
stream=eventtypename,json=jsontext (newline)
The eventtypename is the JSON event type name. The jsontext is the JSON-formatted string without newline characters. The message must end with newline.
This XML snippet configures a socket accepting client connections that provide events as JSON-formatted strings:
<esperio-socket-configuration> <socket name="jsonStreamSocket" port="8079" data="json" stream="MyEvent"/> </esperio-socket-configuration>
A sample message is:
stream=MyEvent,json={"price":20,"upcCode":"A0001"}
Each message must end with a newline character. The above example assumes a JSON event type such as @public @buseventtype create json schema MyEvent(price double, upcCode string).
This chapter discusses the EsperIO adapter for relational databases.
This adapter requires Esper compiler as well as Esper runtime as a dependency.
The EsperIO relational database adapter can write events to a database table.
If your application only reads from tables, the Esper jar file and Esper configuration suffices and there is no additional EsperIO DB adapter configuration or jar file required. Please see below tips for reading or polling tables.
The EsperIO DB adapter supports two means to write to a database table:
Execute a SQL DML (Data Manipulation, i.e. Update, Insert, Delete or stored procedure call) statement as a response to a triggering event.
Execute an Update-Insert: The adapter attempts an Update of a row by key and if unsuccessful (update returns zero rows updated) the adapter performs an Insert.
The adapter also provides infrastructure for queuing database write requests for execution by a thread pool.
You may configure the EsperIO DB adapter either as part of your Esper configuration file in the plugin loader section or via the adapter API. Add the esperio-db-version.jar file to your classpath as well as the JDBC driver. There are not other dependent jar files required by the adapter.
A sample adapter configuration file is provided in esperio-db-sample-config.xml in the etc folder of the distribution. A configuration file must be valid according to schema esperio-db-configuration-8-0.xsd.
You may place the configuration XML directly into your Esper configuration file as the example below shows:
<esper-configuration xmlns="http://www.espertech.com/schema/esper">
<runtime>
<plugin-loader name="EsperIODBAdapter"
class-name="com.espertech.esperio.db.EsperIODBAdapterPlugin">
<config-xml>
<esperio-db-configuration>
<!-- .....as outlined below or contents of esperio-db-sample-config.xml here... -->
</esperio-db-configuration>
</config-xml>
</plugin-loader>
</runtime>
</esper-configuration>Alternatively you can provide a URL in the Esper configuration file to point to your adapter configuration file:
<esper-configuration xmlns="http://www.espertech.com/schema/esper">
<runtime>
<plugin-loader name="EsperIODBAdapter"
class-name="com.espertech.esperio.db.EsperIODBAdapterPlugin">
<init-arg name="esperio.db.configuration.file"
value="file:/path/esperio-db-sample-config.xml" />
</plugin-loader>
</runtime>
</esper-configuration>If using Spring or if your application requires API access, the following code snippet configures and starts the adapter via API.
The class for configuring an EsperIO DB adapter is com.espertech.esperio.db.config.ConfigurationDBAdapter. The adapter class itself is
EsperIODBAdapter.
The code snippet below is a sample that configures using driver manager and starts the adapter via API:
ConfigurationDBAdapter adapterConfig = new ConfigurationDBAdapter();
ConfigurationCommonDBRef configDB = new ConfigurationCommonDBRef();
configDB.setDriverManagerConnection("DRIVER", "URL", new Properties());
adapterConfig.getJdbcConnections().put("db1", configDB);
// add additional configuration such as DML and Upsert
// start adapter
EsperIODBAdapter dbAdapter = new EsperIODBAdapter(adapterConfig, "runtimeURI");
dbAdapter.start();The configuration for the source of JDBC connections follows the Esper configuration. Please consult the Esper documentation or sample adapter configuration file for details.
Your configuration should set auto-commit to true thereby each change to database tables is automatically committed.
The adapter obtains a new connection for each operation and closes the connection after each operation. For optimum performance consider configuring a connection pool.
A sample JDBC connection configuration is shown in below XML. The API class is ConfigurationCommonDBRef. You may also configure a DataSource or DataSource factory as outlined in the Esper docs.
<esperio-db-configuration>
<jdbc-connection name="db1">
<drivermanager-connection class-name="com.mysql.jdbc.Driver" url="jdbc:mysql://localhost/test"
user="root" password="password">
<connection-settings auto-commit="true" catalog="TEST"/>
</jdbc-connection>
<!-- Add DML and Upsert configurations here, as below. -->
</esperio-db-configuration>This facility allows running a SQL DML (Data Manipulation) query, i.e. an Update, Insert, Delete query or a stored procedure when an event in a triggering stream occurs.
Define a dml element in the adapter configuration file (or use the DMLQuery class) for every query to execute.
The synopsis is as follows:
<dml connection="[connection]" stream="[stream]"
[name="name"] [executor-name="executor"] [retry="count"] [retry-interval-sec="sec"]>
<sql>[sql]</sql>
<bindings>
<parameter pos="[position]" property="[property_name]"/>
[...parameters]
</bindings>
</dml>The connection attribute value is required and provides the name of the configured JDBC connection.
A value for the stream attribute is required and provides the name of the stream that triggers the DML. The adapter expects a stream by this name to exist at adapter start time.
The name attribute is optional and is only used for logging errors.
The executor-name attribute is optional. If specified, it must be the name of an executor configuration. If specified, the adapter will use the executor service (queue and thread pool) for performing all DML work. If not specified, the adapter performs the DML work in the same thread.
The retry attribute is optional. If specified, the adapter will retry a given number of times in case an error is encountered. If retry-interval-sec is specified, the adapter waits the given number of seconds between retries.
The sql element is required and provides the SQL DML or stored procedure call to execute, with parameters as question mark (?).
The bindings element is required and provides the bindings for expression parameters.
The parameter element should occur as often as there are parameters in the SQL query. The position attribute starts at 1 and counts up for each parameter. The property parameter provide the name of the event property of the stream to use as the parameter value.
A sample DML configuration follows:
<dml connection="db1" stream="InsertToDBStream"
name="MyInsertQuery" executor-name="queue1" retry="count">
<sql>insert into MyEventStore(key1, value1, value2) values (?, ?, ?)</sql>
<bindings>
<parameter pos="1" property="eventProperty1"/>
<parameter pos="2" property="eventProperty2"/>
<parameter pos="3" property="eventProperty3"/>
</bindings>
</dml>This facility allows running an SQL Update that is followed by an Insert if the Update did not update any rows.
Define an upsert element in the adapter configuration file (or use the UpsertQuery class) for every update-insert to execute.
The synopsis is as follows:
<upsert connection="[connection]" stream="[stream]" table-name="[table]"
[name="name"] [executor-name="executor"] [retry="count"] [retry-interval-sec="sec"]>
<keys>
<column property="[property_name]" column="[column_name]" type="[sql_type]"/>
[...column]
</keys>
<values>
<column property="[property_name]" column="[column_name]" type="[sql_type]"/>
[...column]
</values>
</upsert>The connection attribute value is required and provides the name of the configured JDBC connection.
A value for the stream attribute is required and provides the name of the stream that triggers the Update-Insert. The adapter expects a stream by this name to exist at adapter start time.
The table attribute value is required and provides the database table name.
The name attribute is optional and is only used for logging errors.
The executor-name attribute is optional. If specified, it must be the name of an executor configuration. If specified, the adapter will use the executor service (queue and thread pool) for performing all work. If not specified, the adapter performs the work in the same thread.
The retry attribute is optional. If specified, the adapter will retry a given number of times in case an error is encountered. If retry-interval-sec is specified, the adapter waits the given number of seconds between retries.
The keys element is required and provides the key columns of the table and the values element provides the list of value columns of the table.
The column element should occur as many as there are key and value columns in the table. The property attribute provides the name of the event property, the column attribute provides the database table column name and the type is any of the java.sql.Types names (case ignored).
A sample Update-Insert configuration follows:
<upsert connection="db1" stream="UpdateInsertDBTableTrigger" name="UpdateInsertSample"
table-name="MyKeyedTable" executor-name="queue1" retry="3">
<keys>
<column property="eventProperty1" column="keyColumn1" type="varchar"/>
<column property="eventProperty2" column="keyColumn2" type="varchar"/>
</keys>
<values>
<column property="eventProperty3" column="valueColumn1" type="varchar"/>
<column property="eventProperty4" column="valueColumn2" type="integer"/>
</values>
</upsert>Executors are named thread pools and queues that may be assigned to perform DML or update-insert work.
Define a executor element in the adapter configuration file (or use the Executor class) for every thread pool and queue to declare.
Upon adapter start, for each executor the adapter starts the given number of threads and an unbound queue.
The synopsis is as follows:
<executors> <executor name="[name]" threads="[count]"/> </executors>
The name attribute value is required and provides the name of the executor, while the count attribute specifies the number of threads for the thread pool.
An example executor configuration::
<executors> <executor name="threadPool1" threads="2"/> </executors>
An application can obtain a handle to all thread pools and queues via the Esper runtime context:
ExecutorServices execs = (ExecutorServices)
runtime.getContext().lookup("EsperIODBAdapter/ExecutorServices");Herein we provide sample statements and documentation pointers to use Esper EPL for reading from database tables. If only reading and not writing to a database, no configuration or EsperIO jar is file required.
Please consult the Esper SQL access documentation for more information.
To execute an SQL query repeatedly, Esper provides the opportunity to join a pattern to an SQL statement. The pattern may provide a single interval or crontab schedule or may also contain multiple schedules or combinations thereof via the pattern or operator.
The sample query below simply executes every 10 seconds retrieving all rows from table MyTable:
select * from pattern[every timer:interval(10)], sql:db1 ['select * from MyTable']
To perform an incremental query, consider utilizing a variable to parameterize your SQL statement so that only new rows are returned.
The next EPL statements create a variable and pass the variable value to the query to poll for new rows only. It assumes the timestamp column in the MyTable table holds long-type millisecond values:
// Create a variable to hold the last poll timestamp
create variable long VarLastTimestamp = 0
// Poll every 15 seconds between 8am and 4pm based on variable value
insert into PollStream
select * from pattern[every timer:crontab(*, 8-16, *, *, *, */15)],
sql:db1 ['select * from MyTable where timestamp > ${VarLastTimestamp}']
// Assign last value to variable
on PollStream set VarLastTimestamp = timestampA sample statement to read a table at startup time is below:
select * from pattern[timer:interval(0)], sql:db1 ['select * from MyTable']