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NIFI-152: Updated developer guide

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@ -22,64 +22,60 @@ Apache NiFi Team <dev@nifi.incubator.apache.org>
== Introduction
This Developer Guide is written by developers for developers. It is expected that before reading this
guide, you have a basic understanding of Apache NiFi (incubating) and the concepts of dataflow. If not,
please see the link:overview.html[NiFi Overview] and the link:user-guide.html[NiFi User Guide] to familiar
yourself with the concepts of NiFi.
The intent of this Developer Guide is to provide the reader with the information needed to understand how Apache NiFi (incubating)
extensions are developed and help to explain the thought process behind developing the components. It provides an introduction to
and explanation of the API that is used to develop extensions. It does not, however, go into great detail about each
of the methods in the API, as this guide is intended to supplement the JavaDocs of the API rather than replace them.
This guide also assumes that the reader is familiar with Java 7 and Apache Maven.
The intent of this guide is to provide the reader with the information needed to understand how NiFi extensions
are developed and help to explain the thought process behind developing the components.
This guide is written by developers for developers. It is expected that before reading this
guide, you have a basic understanding of NiFi and the concepts of dataflow. If not, please see the link:overview.html[NiFi Overview]
and the link:user-guide.html[NiFi User Guide] to familiarize yourself with the concepts of NiFi.
[[components]]
== NiFi Components
NiFi provides several extension points to provide developers the
ability to add functionality
to the application to meet their needs. The following list provides a
high-level description
of the most common extension points:
ability to add functionality to the application to meet their needs. The following list provides a
high-level description of the most common extension points:
- Processor
- The Processor interface is the mechanism through which NiFi
exposes access to
FlowFiles, their attributes, and their content. The Processor is
the basic building
block used to comprise a NiFi dataflow. This interface is used
to accomplish
* The Processor interface is the mechanism through which NiFi exposes access to
<<flowfile>>s, their attributes, and their content. The Processor is the basic building
block used to comprise a NiFi dataflow. This interface is used to accomplish
all of the following tasks:
- Create FlowFiles
- Read FlowFile content
- Write FlowFile content
- Read FlowFile attributes
- Update FlowFile attributes
- Ingest data
- Egress data
- Route data
- Extract data
- Modify data
** Create FlowFiles
** Read FlowFile content
** Write FlowFile content
** Read FlowFile attributes
** Update FlowFile attributes
** Ingest data
** Egress data
** Route data
** Extract data
** Modify data
- ReportingTask
- The ReportingTask interface is a mechanism that NiFi exposes to allow metrics,
monitoring information, and internal NiFI state to be published to external
sources, such as log files, e-mail, and remote web services.
* The ReportingTask interface is a mechanism that NiFi exposes to allow metrics,
monitoring information, and internal NiFi state to be published to external
endpoints, such as log files, e-mail, and remote web services.
- ControllerService
- A ControllerService provides shared state across Processors, other ControllerServices,
* A ControllerService provides shared state and functionality across Processors, other ControllerServices,
and ReportingTasks within a single JVM. An example use case may include loading a very
large dataset into memory. By performing this work in a ControllerService, the data
can be loaded once and be exposed to all Processors via this service.
can be loaded once and be exposed to all Processors via this service, rather than requiring
many different Processors to load the dataset themselves.
- FlowFilePrioritizer
- The FlowFilePrioritizer interface provides a mechanism by which FlowFiles
* The FlowFilePrioritizer interface provides a mechanism by which <<flowfile>s
in a queue can be prioritized, or sorted, so that the FlowFiles can be processed in an order
that is most effective for a particular use case.
- AuthorityProvider
- An AuthorityProvide is responsible for determining which privileges and roles, if any,
* An AuthorityProvide is responsible for determining which privileges and roles, if any,
a given user should be granted.
@ -103,20 +99,15 @@ Processors must adhere to the following rules:
While `Processor` is an interface that can be implemented directly, it
will be extremely rare to do so, as
the `org.apache.nifi.processor.AbstractProcessor` is the base class
for almost all Processor
implementations. The `AbstractProcessor` class provides a significant
amount of functionality, which makes
the task of developing a Processor much easier and more convenient.
For the scope of this document,
we will focus primarily on the `AbstractProcessor` class when dealing
for almost all Processor implementations. The `AbstractProcessor` class provides a significant
amount of functionality, which makes the task of developing a Processor much easier and more convenient.
For the scope of this document, we will focus primarily on the `AbstractProcessor` class when dealing
with the Processor API.
.Concurrency Note
NiFi is a highly concurrent framework. This means that all extensions
must be thread-safe.
If unfamiliar with writing concurrent software in Java, it is highly
recommended that you familiarize
yourself with the principles of Java concurrency.
must be thread-safe. If unfamiliar with writing concurrent software in Java, it is highly
recommended that you familiarize yourself with the principles of Java concurrency.
[[supporting_api]]
@ -138,27 +129,18 @@ immutable. Modifications to a FlowFile are made possible by the ProcessSession.
[[process_session]]
==== ProcessSession
The ProcessSession, often referred to as simply a "session," provides
a mechanism by which FlowFiles
can be created, destroyed, examined, cloned, and transferred to other
Processors. Additionally, a
ProcessSession provides mechanism for creating modified versions of
FlowFiles, by adding or removing
attributes, or by modifying the FlowFile's content. The ProcessSession
also exposes a mechanism for
emitting provenance events that provide for the ability to track the
lineage and history of a FlowFile.
After operations are performed on one or more FlowFiles, a
ProcessSession can be either committed or
rolled back.
a mechanism by which FlowFiles can be created, destroyed, examined, cloned, and transferred to other
Processors. Additionally, a ProcessSession provides mechanism for creating modified versions of
FlowFiles, by adding or removing attributes, or by modifying the FlowFile's content. The ProcessSession
also exposes a mechanism for emitting provenance events that provide for the ability to track the
lineage and history of a FlowFile. After operations are performed on one or more FlowFiles, a
ProcessSession can be either committed or rolled back.
[[process_context]]
==== ProcessContext
The ProcessContext provides a bridge between a Processor and the
framework. It provides information
about how the Processor is currently configured and allows the
Processor to perform
Framework-specific tasks, such as yielding its resources so that the
framework will schedule other
The ProcessContext provides a bridge between a Processor and the framework. It provides information
about how the Processor is currently configured and allows the Processor to perform
Framework-specific tasks, such as yielding its resources so that the framework will schedule other
Processors to run without consuming resources unnecessarily.
@ -1337,30 +1319,248 @@ If the callback succeeds, a CONTENT_MODIFIED Provenance Event is emitted.
== Error Handling
When writing a Processor, there are several different unexpected cases that can occur.
It is important that Processor developers understand the mechanics of how the NiFi framework
behaves if Processors do not handle errors themselves, and it's important to understand
what error handling is expected of Processors. Here, we will discuss how Processors should
handle unexpected errors during the course of their work.
=== Exceptions within the Processor
During the execution of the `onTrigger` method of a Processor, many things can potentially go
awry. Common failure conditions include:
- Incoming data is not in the expected format.
- Network connections to external services fail.
- Reading or writing data to a disk fails.
- There is a bug in the Processor or a dependent library.
Any of these conditions can result in an Exception being thrown from the Processor. From the framework
perspective, there are two types of Exceptions that can escape a Processor: `ProcessException` and
all others.
If a ProcessException is thrown from the Processor, the framework will assume that this is a failure that
is a known outcome. Moreover, it is a condition where attempting to process the data again later may
be successful. As a result, the framework will roll back the session that was being processed and penalize
the FlowFiles that were being processed.
If any other Exception escapes the Processor, though, the framework will assume that it is a failure that
was not taken into account by the developer. In this case, the framework will also roll back the session
and penalize the FlowFiles. However, in this case, we can get into some very problematic cases. For example,
the Processor may be in a bad state and may continually run, depleting system resources, without providing
any useful work. This is fairly common, for instance, when a NullPointerException is thrown continually.
In order to avoid this case, if an Exception other than ProcessException is able to escape the Processor's
`onTrigger` method, the framework will also "Administratively Yield" the Processor. This means that the
Processor will not be triggered to run again for some amount of time. The amount of time is configured
in the `nifi.properties` file but is 10 seconds by default.
=== Exceptions within a callback: IOException, RuntimeException
=== Exceptions within the Processor: ProcessException, others.
More often than not, when an Exception occurs in a Processor, it occurs from within a callback (I.e.,
`InputStreamCallback`, `OutputStreamCallback`, or `StreamCallback`). That is, during the processing of a
FlowFile's content. Callbacks are allowed to throw either `RuntimeException` or `IOException`. In the case
of RuntimeException, this Exception will propagate back to the `onTrigger` method. In the case of an
`IOException`, the Exception will be wrapped within a ProcessException and this ProcessException will then
be thrown from the Framework.
For this reason, it is recommended that Processors that use callbacks do so within a `try/catch` block
and catch `ProcessException` as well as any other `RuntimeException` that they expect their callback to
throw. It is *not* recommended that Processors catch the general `Exception` or `Throwable` cases, however.
This is discouraged for two reasons.
First, if an unexpected RuntimeException is thrown, it is likely a bug
and allowing the framework to rollback the session will ensure no data loss and ensures that DataFlow Managers
are able to deal with the data as they see fit by keeping the data queued up in place.
Second, when an IOException is thrown from a callback, there really are two types of IOExceptions: those thrown
from Processor code (for example, the data is not in the expected format or a network connection fails), and
those that are thrown from the Content Repository (where the FlowFile content is stored). If the latter is the case,
the framework will catch this IOException and wrap it into a `FlowFileAccessException`, which extends `RuntimeException`.
This is done explicitly so that the Exception will escape the `onTrigger` method and the framework can handle this
condition appropriately. Catching the general Exception prevents this from happening.
=== Catching ProcessException from callback
=== Penalization vs. Yielding
=== Session Rollback: with and within penalization
When an issue occurs during processing, the framework exposes two methods to allow Processor developers to avoid performing
unnecessary work: "penalization" and "yielding." These two concepts can become confusing for developers new to the NiFi API.
A developer is able to penalize a FlowFile by calling the `penalize(FlowFile)` method of ProcessSession. This causes the
FlowFile itself to be inaccessible to downstream Processors for a period of time. The amount of time that the FlowFile is
inaccessible is determined by the DataFlow Manager by setting the "Penalty Duration" setting in the Processor Configuration
dialog. The default value is 30 seconds. Typically, this is done when a Processor determines that the data cannot be processed
due to environmental reasons that are expected to sort themselves out. A great example of this is the PutSFTP processor, which
will penalize a FlowFile if a file already exists on the SFTP server that has the same filename. In this case, the Processor
penalizes the FlowFile and routes it to failure. A DataFlow Manager can then route failure back to the same PutSFTP Processor.
This way, if a file exists with the same filename, the Processor will not attempt to send the file again for 30 seconds
(or whatever period the DFM has configured the Processor to use). In the meantime, it is able to continue to process other
FlowFiles.
On the other hand, yielding allows a Processor developer to indicate to the framework that it will not be able to perform
any useful function for some period of time. This commonly happens with a Processor that is communicating with a remote
resource. If the Processor cannot connect to the remote resource, or if the remote resource is expected to provide data
but reports that it has none, the Processor should call `yield` on the `ProcessContext` object and then return. By doing
this, the Processor is telling the framework that it should not waste resources triggering this Processor to run, because
there's nothing that it can do - it's better to use those resources to allow other Processors to run.
=== Session Rollback
Thus far, when we have discussed the `ProcessSession`, we have typically referred to it simply as a mechanism for accessing
FlowFiles. However, it provides another very important capability, which is transactionality. All methods that are called
on a ProcessSession happen as a transaction. When we decided to end the transaction, we can do so either by calling
`commit()` or by calling `rollback()`. Typically, this is handled by the `AbstractProcessor` class: if the `onTrigger` method
throws an Exception, the AbstractProcessor will catch the Exception, call `session.rollback()`, and then re-throw the Exception.
Otherwise, the AbstractProcessor will call `commit()` on the ProcessSession.
There are times, however, that developers will want to roll back a session explicitly. This can be accomplished at any time
by calling the `rollback()` or `rollback(boolean)` method. If using the latter, the boolean indicates whether or not those
FlowFiles that have been pulled from queues (via the ProcessSession `get` methods) should be penalized before being added
back to their queues.
When `rollback` is called, any modification that has occurred to the FlowFiles in that session are discarded, to included
both content modification and attribute modification. Additionally, all Provenance Events are rolled back (with the exception
of any SEND event that was emitted by passing a value of `true` for the `force` argument). The FlowFiles that were pulled from
the input queues are then transferred back to the input queues (and optionally penalized) so that they can be processed again.
On the other hand, when the `commit` method is called, the FlowFile's new state is persisted in the FlowFile Repository, and
any Provenance Events that occurred are persisted in the Provenance Repository. The previous content is destroyed (unless
another FlowFile references the same piece of content), and the FlowFiles are transferred to the outbound queues so that the
next Processors can operate on the data.
It is also important to note how this behavior is affected by using the `org.apache.nifi.annotations.behavior.SupportsBatching`
annotation. If a Processor utilizes this annotation, calls to `ProcessSession.commit` may not take affect immediately. Rather,
these commits may be batched together in order to provide higher throughput. However, if at any point, the Processor rolls back
the ProcessSession, all changes since the last call to `commit` will be discarded and all "batched" commits will take affect.
These "batched" commits are not rolled back.
=== Administrative Yielding
== General Design Considerations
=== Cohesion / Reusability : Do one thing and do it well!
When designing a Processor, there are a few important design considering to keep in mind. This section of the Developer Guide
brings to the forefront some of the ideas that a developer should be thinking about when creating a Processor.
=== Consider the User
One of the most important concepts to keep in mind when developing a Processor (or any other component) is the user
experience that you are creating. It's important to remember that as the developer of such a component, you may have
important knowledge about the context that others do not have. Documentation should always be supplied so that those
less familiar with the process are able to use it with ease.
When thinking about the user experience, it is also important to note that consistency is very important. It is best
to stick with the standard <<naming-convensions>>. This is true for Processor names, Property names and value, Relationship
names, and any other aspect that the user will experience.
Simplicity is crucial! Avoid adding properties that you don't expect users to understand or change. As developers, we are
told that hard-coding values is bad. But this sometimes results in developers exposing properties that, when asked for clarification,
tell users to just leave the default value. This leads to confusion and complexity.
=== Cohesion and Reusability
For the sake of making a single, cohesive unit, developers are sometimes tempted to combine several functions into a single Processor.
This is very true for the case when a Processor expects input data to be in format X so that the Processor can convert the data into
format Y and send the newly-formatted data to some external service.
Taking this approach of formatting the data for a particular endpoint and then sending the data to that endpoint within the same Processor
has several drawbacks:
- The Processor becomes very complex, as it has to perform the data translation task as well as the task of
sending the data to the remote service.
- If the Processor is unable to communicate with the remote service, it will route the data to a `failure` Relationship. In this case,
the Processor will be responsible to perform the data translation again. And if it fails again, the translation is done yet again.
- If we have five different Processors that translate the incoming data into this new format before sending the data, we have a great
deal of duplicated code. If the schema changes, for instance, many Processors must be updated.
- This intermediate data is thrown away when the Processor finishes sending to the remote service. The intermediate data format
may well be useful to other Processors.
In order to avoid these issues, and make Processors more reusable, a Processor should always stick to the principal of "do one thing and do
it well." Such a Processor should be broken into two separate Processors: one to convert the data from Format X to Format Y, and another
Processor to send data to the remote resource.
[[naming-convensions]]
=== Naming Conventions
In order to deliver a consistent look and feel to users, it is advisable that Processors keep with standard naming conventions. The following
is a list of standard conventions that are used:
- Processors that pull data from a remote system are named Get<Service> or Get<Protocol>, depending on if they poll data from arbitrary
sources over a known Protocol (such as GetHTTP or GetFTP) or if they pull data from a known service (such as GetKafka)
- Processors that push data to a remote system are named Put<Service> or Put<Protocol>.
- Relationship names are lower-cased and use spaces to delineated words.
- Property names capitalize significant words, as would be done with the title of a book.
=== Processor Behavior Annotations
When creating a Processor, the developer is able to provide hints to the framework about how to utilize the Processor most
effectively. This is done by applying annotations to the Processor's class. The annotations that can be applied to a
Processor exist in three sub-packages of `org.apache.nifi.annotations`. Those in the `documentation` sub-package are used
to provide documentation to the user. Those in the `lifecycle` sub-package instruct the framework which methods should
be called on the Processor in order to respond to the appropriate life-cycle events. Those in the `behavior` package
help the framework understand how to interact with the Processor in terms of scheduling and general behavior.
The following annotations from the `org.apache.nifi.annotations.behavior` package can be used to modify how the framework
will handle your Processor:
- `EventDriven`: Instructs the framework that the Processor can be scheduled using the Event-Driven scheduling
strategy. This strategy is still experimental at this point, but can result in reduced resource utilization
on dataflows that do not handle extremely high data rates.
- `SideEffectFree`: Indicates that the Processor does not have any side effects external to NiFi. As a result, the
framework is free to invoke the Processor many times with the same input without causing any unexpected
results to occur. This implies idempotent behavior. This can be used by the framework to improve efficiency by
performing actions such as transferring a ProcessSession from one Processor to another, such that if
a problem occurs many Processors' actions can be rolled back and performed again.
- `SupportsBatching`: This annotation indicates that it is okay for the framework to batch together multiple
ProcessSession commits into a single commit. If this annotation is present, the user will be able to choose
whether they prefer high throughput or lower latency in the Processor's Scheduling tab. This annotation should
be applied to most Processors, but it comes with a caveat: if the Processor calls `ProcessSession.commit`,
there is no guarantee that the data has been safely stored in NiFi's Content, FlowFile, and Provenance Repositories.
As a result, it is not appropriate for those Processors that receive data from an external source, commit the session,
and then delete the remote data or confirm a transaction with a remote resource.
- `TriggerSerially`: When this annotation is present, the framework will not allow the user to schedule more than one
concurrent thread to execute the `onTrigger` method at a time. Instead, the number of thread ("Concurrent Tasks")
will always be set to `1`. This does *not*, however, mean that the Processor does not have to be thread-safe,
as the thread that is executing `onTrigger` may change between invocations.
- `TriggerWhenAnyDestinationAvailable`: By default, NiFi will not schedule a Processor to run if any of its outbound
queues is full. This allows back-pressure to be applied all the way a chain of Processors. However, some Processors
may need to run even if one of the outbound queues is full. This annotations indicates that the Processor should run
if any Relationship is "available." A Relationship is said to be "available" if none of the connections that use
that Relationship is full. For example, the DistributeLoad Processor makes use of this annotation. If the "round robin"
scheduling strategy is used, the Processor will not run if any outbound queue is full. However, if the "next available"
scheduling strategy is used, the Processor will run if any Relationship at all is available and will route FlowFiles
only to those relationships that are available.
- `TriggerWhenEmpty`: The default behavior is to trigger a Processor to run only if its input queue has at least one
FlowFile or if the Processor has no input queues (which is typical of a "source" Processor). Applying this annotation
will cause the framework to ignore the size of the input queues and trigger the Processor regardless of whether or
not there is any data on an input queue. This is useful, for example, if the Processor needs to be triggered to run
periodically to time out a network connection.
=== Data Buffering
An important point to keep in mind is that NiFi provides a generic data processing capability. Data can be in any format. Processors
are generally scheduled with several threads. A common mistake that developers new to NiFi make is to buffer all the contents of a
FlowFile in memory. While there are cases when this is required, it should be avoided if at all possible, unless it is well-known
what format the data is in. For example, a Processor responsible for executing XPath against an XML document will need to load the
entire contents of the data into memory. This is generally acceptable, as XML is not expected to be extremely large. However, a Processor
that searches for a specific byte sequence may be used to search files that are hundreds of gigabytes or more. Attempting to load this
into memory can cause a lot of problems - especially if multiple threads are processing different FlowFiles simultaneously.
Instead of buffering this data into memory, it is advisable to instead evaluate the data as it is streamed from the Content Repository
(i.e., scan the content from the `InputStream` that is provided to your callback by `ProcessSession.read`). Of course, in this case,
we don't want to read from the Content Repository for each byte, so we would use a BufferedInputStream or somehow buffer some small
amount of data, as appropriate.
@ -1618,26 +1818,104 @@ Processor is valid or not, according to our expectations.
=== Enqueue FlowFiles
Before triggering a Processor to run, it is usually necessary to enqueue FlowFiles for the Processor to process.
This can be achieved by using the `enqueue` methods of the `TestRunner` class. The `enqueue` method has several
different overrides, and allows data to be added in the form of a `byte[]`, `InputStream`, or `Path`. Each of these
methods also supports a variation that allows a `Map<String, String>` to be added to support FlowFile attributes.
Additionally, there is an `enqueue` method that takes a var-args of FlowFile objects. This can be useful, for example,
to obtain the output of a Processor and then feed this to the input of the Processor.
=== Run the Processor
After configuring the Controller Services and enqueuing the necessary FlowFiles, the Processor can be triggered
to run by calling the `run` method of `TestRunner`. If this method is called without any arguments, it will
invoke any method in the Processor with an `@OnScheduled` annotation, call the Processor's `onTrigger` method once,
and then run the `@OnUnscheduled` and finally `@OnStopped` methods.
If it is desirable to run several iterations of the `onTrigger` method before the other `@OnUnscheduled` and
`@OnStopped` life-cycle events are triggered, the `run(int)` method can be used to specify now many iterations
of `onTrigger` should be called.
There are times when we want to trigger the Processor to run but not trigger the `@OnUnscheduled` and `@OnStopped`
life-cycle events. This is useful, for instance, to inspect the Processor's state before these events occur. This
can be achieved using the `run(int, boolean)` and passing `false` as the second argument. After doing this, though,
calling the `@OnScheduled` life-cycle methods could cause an issue. As a result, we can now run `onTrigger` again
without causing these events to occur by using the `run(int,boolean,boolean)` version of the `run` method and
passing `false` as the third argument.
If it is useful to test behavior that occurs with multiple threads, this can also be achieved by calling the
`setThreadCount` method of `TestRunner`. The default is 1 thread. If using multiple threads, it is important
to remember that the `run` call of `TestRunner` specifies how many times the Processor should be triggered, not
the number of times that the Processor should be triggered per thread. So, if the thread count is set to 2 but
`run(1)` is called, only a single thread will be used.
=== Validate Output Counts
=== Validate Output
After a Processor has finished running, a unit test will generally want to validate that the FlowFiles went where
they were expected to go. This can be achieved using the `TestRunners` `assertAllFlowFilesTransferred` and
`assertTransferCount` methods. The former method takes as arguments a Relationship and an integer to dictate how many
FlowFiles should have been transferred to that Relationship. The method will fail the unit test unless this number of
FlowFiles were transferred to the given Relationship *or* if any FlowFile was transferred to any other Relationship.
The `assertTransferCount` method validates only that the FlowFile count was the expected number for the given Relationship.
After validating the counts, we can then obtain the actual output FlowFiles via the `getFlowFilesForRelationship` method.
This method returns a `List<MockFlowFile>`. It's important to note that the type of the List is `MockFlowFile`, rather
than the `FlowFile` interface. This is done because `MockFlowFile` comes with many methods for validating the contents.
For example, `MockFlowFile` has methods for asserting that FlowFile Attributes exist (`assertAttributeExists`), asserting
that other attributes are not present (`assertAttributeNotExists`), or that Attributes have the correct value
(`assertAttributeEquals`, `assertAttributeNotEquals`). Similar methods exist for verifying the contents of the FlowFile.
The contents of a FlowFile can be compared to a `byte[]`, and `InputStream`, a file, or a String. If the data is expected
to be textual, the String version is preferred, as it provides a more intuitive error message if the output is not
as expected.
=== Validate Output Results
=== Mocking External Resources
One of the biggest problems when testing a NiFi processor that connects to a remote resource is that we don't want to
actually connect to some remote resource from a unit test. We can stand up a simple server ourselves in the unit test
and configure the Processor to communicate with it, but then we have to understand and implement the server-specific
specification and may not be able to properly send back error messages, etc. that we would like for testing.
Generally, the approach taken here is to have a method in the Processor that is responsible for obtaining a connection
or a client to a remote resource. We generally mark this method as protected. In the unit test, instead of creating
the `TestRunner` by calling `TestRunners.newTestRunner(Class)` and providing the Processor class, we instead create
a subclass of the Processor in our unit test and use this:
=== Mocking Connections
[source,java]
----
@Test
public void testConnectionFailure() {
final TestRunner runner = TestRunners.newTestRunner(new MyProcessor() {
protected Client getClient() {
// Return a mocked out client here.
return new Client() {
public void connect() throws IOException {
throw new IOException();
}
// ...
// other client methods
// ...
};
}
});
// rest of unit test.
}
----
This allows us to implement a Client that mocks out all of the network communications and returns the different
error results that we want to test, as well as ensure that our logic is correct for handling successful calls
to the client.
=== Additional Testing Capabilities
In addition to the above-mentioned capabilities provided by the
testing framework, the TestRunner provides several
convenience methods for verifying the behavior of a Processor. Methods
@ -1678,10 +1956,28 @@ their NiFi components as NAR packages.
To achieve this, a developer creates a new Maven Artifact, which we
refer to as the NAR artifact. The packaging is
set to `nar`. The `dependencies` section of the POM is then created so
that the NAR has a dependency on all NiFi
Components that are to be included within the NAR.
that the NAR has a dependency on all NiFi Components that are to be included within the NAR.
TODO: DISCUSS HOW TO INCLUDE THE NAR MAVEN PLUGIN.
In order to use a packaging of `nar`, we must use the `nifi-nar-maven-plugin` module.
This is included by adding the following snippet to the NAR's pom.xml:
[source,xml]
----
<build>
<plugins>
<plugin>
<groupId>org.apache.nifi</groupId>
<artifactId>nifi-nar-maven-plugin</artifactId>
<version>1.0.0-incubating</version>
<extensions>true</extensions>
</plugin>
</plugins>
</build>
----
In the Apache NiFi codebase, this exists in the NiFi root POM from which all other NiFi artifacts
(with the exception of the nifi-nar-maven-plugin itself) inherit, so that we do not need to include
this in any of our other POM files.
The NAR is able to have one dependency that is of type `nar`. If more
than one dependency is specified that is of type
@ -1789,16 +2085,41 @@ API artifacts into the same NAR is often acceptable.
== Consider the User Experience
The user...
== How to contribute to Apache NiFi
Git, Maven, ASF processes, NiFi processes, ...
We are always excited to have contributions from the community - especially from new contributors!
We are interested in accepting contributions of code, as well as documentation and even artwork that
can be applied as icons or styling to the application.
=== Technologies
The back end of Apache NiFi is written in Java. The web tier makes use of JAX-RS and JavaScript is extensively
used to provide a user interface. We depend on several third-party JavaScript libraries, including D3 and JQuery,
among others. We make use of Apache Maven for our builds and Git for our version control system.
=== Where to Start?
link:http://issues.apache.org/jira/browse/NIFI[NiFi's Jira page] can be used to find tickets that are tagged as "beginner",
or you can dig into any of the tickets for creating Processors. Processors should be self-contained and not rely on other
outside components (except for Controller Services), so they make for excellent starting points for new NiFi developers to
get started. This exposes the developer to the NiFi API and is the most extensible part of the dataflow system.
=== Supplying a contribution
Contributions can be provided either by creating a patch:
`git format-patch`
and attaching that patch to a ticket, or by generating a Pull Request.
=== Contact Us
The developer mailing list (dev@nifi.incubator.apache.org) is monitored pretty closely, and we tend to respond pretty
quickly. If you have a question, don't hesitate to shoot us an e-mail - we're here to help! Unfortunately, though, e-mails
can get lost in the shuffle, so if you do send an e-mail and don't get a response within a day or two, it's our fault - don't
worry about bothering us. Just ping the mailing list again.