In the given Java example, we are finding all the log files from the "c:/temp" directory. Filtering all matching files in the specified directory File directory = new File("/path/directory") įile files = directory.listFiles(logFilefilter) 3. The best way to use the FileFilter is to pass it to listFiles() method in File class where File represents a directory location. FileFilter logFilefilter = new FileFilter() It returns true if and only if pathname should be included in the list. The FileFilter class has only a single method accept() that tests whether or not the specified abstract pathname should be included in a pathname list. Creating FileFilter with Lambda Expression Dataflow shown in the image below is fetching file from one directory using GetFile processor and storing it in another directory using PutFile. Every processor has different functionality, which contributes to the creation of output flowfile. Maven archetype provides us the easiest way to get started with our own NiFi processor.Ģ. Apache NiFi processors are the basic blocks of creating a data flow.
Steps for Creating a Custom Apache NiFi Processor So, let’s dig into creating a custom processor, creating a custom controller service, and lastly creating a custom processor that will use a custom controller service. Controllers are used to provide shared resources, such as a database, ssl context, or a server connection to an external server and much more. Writing your own custom processor provides a way to perform different operations or to transform flowfile content according to specfic needs.Ī NiFi Controller Service provides a shared starting point and functionality across Processors, other ControllerServices, and ReportingTasks within a single JVM. Processors provide an interface through which NiFi provides access to a flowfile, its attributes and its content. Apache NiFi Processors and Controller ServicesĪ NiFi Processor is the basic building block for creating an Apache NiFi dataflow. In addition, NiFi has 48 ready to run Controller Services that are used for a variety of system focused data flow business requirements.Įven with all of those processors and controller services available out of the box, there are many situations where a custom processor or controller service is called for that isn’t covered in the list referenced above.Īt Hashmap, our engineering and consulting teams have developed a wide range of custom Apache NiFi processors and controller services for a variety of clients and business requirements - some generic and some very industry specific. I created a JRuby ExecuteScript processor to use the header row of the CSV file as the JSON schema, and the filename to determine which index/type to use for each Elasticsearch document. What Do You Get Out of the Box?Īpache NiFi comes with a wide assortment of Processors (at this writing 260) providing a easy path to consume, get, convert, listen, publish, put, query data. In this post I’ll share a Nifi workflow that takes in CSV files, converts them to JSON, and stores them in different Elasticsearch indexes based on the file schema. Now we have a processor which will fetch the files from FileSource folder.
Get file path filter to filter csv nifi full#
We'll put the full path of our FileSource folder here : /home/oguz/Documents/Olric/FileSource/. The only thing we'll change here is the 'Input Directory' attribute. In this post I’ll review my experience in developing custom processors and controllers for Apache NiFi and focus on three areas - creating a custom processor, creating a custom controller service, and finally showing how a custom processor and custom controller service can be used together. Double click the GetFile processor to edit its attributes. One of the solutions that I’ve used very effectively is Apache NiFi, which is an open source, visually oriented technology tool for effectively and efficiently processing and distributing data across an organization from system to system.
Get file path filter to filter csv nifi software#
As a software engineer and developer at a Big Data and IoT services company, I’m constantly presented with new challenges and business problems that involve data flows, data integration, data transformations and data enrichment.
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