This document provides an overview of Apache NiFi 1.0 and discusses some of its key enhancements and features. NiFi is a tool for managing the flow of data in and between systems and applications. The document outlines NiFi's history and goals. It describes enhancements in NiFi 1.0 including a modernized user interface, increased number of processors, deeper ecosystem integration, multitenant authorization, revisions support, and zero master clustering. The document also discusses using NiFi on edge systems and common issues as well as future plans.
This document provides an overview of Apache NiFi 1.0 and discusses some of its key enhancements and features. NiFi is a tool for managing the flow of data in and between systems and applications. The document outlines NiFi's history and goals. It describes enhancements in NiFi 1.0 including a modernized user interface, increased number of processors, deeper ecosystem integration, multitenant authorization, revisions support, and zero master clustering. The document also discusses using NiFi on edge systems and common issues as well as future plans.
Hortonworks Data in Motion Webinar Series Part 7 Apache Kafka Nifi Better Tog...Hortonworks
Apache NiFi, Storm and Kafka augment each other in modern enterprise architectures. NiFi provides a coding free solution to get many different formats and protocols in and out of Kafka and compliments Kafka with full audit trails and interactive command and control. Storm compliments NiFi with the capability to handle complex event processing.
Join us to learn how Apache NiFi, Storm and Kafka can augment each other for creating a new dataplane connecting multiple systems within your enterprise with ease, speed and increased productivity.
https://www.brighttalk.com/webcast/9573/224063
MiNiFi is a recently started sub-project of Apache NiFi that is a complementary data collection approach which supplements the core tenets of NiFi in dataflow management, focusing on the collection of data at the source of its creation. Simply, MiNiFi agents take the guiding principles of NiFi and pushes them to the edge in a purpose built design and deploy manner. This talk will focus on MiNiFi's features, go over recent developments and prospective plans, and give a live demo of MiNiFi.
The config.yml is available here: https://gist.github.com/JPercivall/f337b8abdc9019cab5ff06cb7f6ff09a
The document provides an introduction to Spark and related Apache projects. It discusses the Spark ecosystem including Spark Core, Spark SQL, Spark Streaming and MLlib. It explains key Spark concepts like RDDs, DataFrames and the Spark SQL optimizer Catalyst. It also introduces the Hortonworks Data Platform which includes components like YARN, HDFS and Zeppelin which can be used with Spark.
HDF Powered by Apache NiFi IntroductionMilind Pandit
The document discusses Apache NiFi and its role in managing enterprise data flows, providing an overview of NiFi's key features and capabilities for reliable data transfer, preparation, and routing. It also demonstrates how NiFi is used in common use cases and provides examples of building simple data flows in NiFi to ingest, filter, and deliver data.
The document provides an overview of Apache Hadoop and how it addresses challenges with traditional data architectures. It discusses how Hadoop uses HDFS for distributed storage and YARN as a data operating system to allow for distributed computing. It also summarizes different data access methods in Hadoop including MapReduce for batch processing and how the Hadoop ecosystem continues to evolve and include technologies like Spark, Hive and HBase.
This document provides an overview of Apache NiFi, a dataflow management software. It begins with an introduction to dataflow and challenges in moving data effectively. It then discusses key features of Apache NiFi like guaranteed delivery, data buffering, and data provenance. The document outlines NiFi's architecture including repositories and extension points. It also advertises an upcoming Birds of a Feather session on streaming, dataflow and cybersecurity. Finally, it encourages learning more about NiFi and getting involved in the community.
Building large scale applications in yarn with apache twillHenry Saputra
This document summarizes a presentation about Apache Twill, which provides abstractions for building large-scale applications on Apache Hadoop YARN. It discusses why Twill was created to simplify developing on YARN, Twill's architecture and components, key features like real-time logging and elastic scaling, real-world uses at CDAP, and the Twill roadmap.
Harnessing the power of YARN with Apache TwillTerence Yim
This document discusses Apache Twill, which aims to simplify developing distributed applications on YARN. Twill provides a Java thread-like programming model for YARN applications, avoiding the complexity of directly using YARN APIs. Key features of Twill include real-time logging, resource reporting, state recovery, elastic scaling, command messaging between tasks, service discovery, and support for executing bundled JAR applications on YARN. Twill handles communication with YARN and the Application Master while providing an easy-to-use API for application developers.
Summarizes new capabilities added to Apache NiFi 1.2.0 (soon to be released).
Disclaimer:
- The contents in this slide deck are derived from Apache NiFi JIRA issues which is labeled with next release target 1.2.0 and source code available at Github (already merged into master branch), however it does NOT mean these are guaranteed to be released and still are subjects to change.
- The motivation of this presentation is share what have been introduced into the project since the latest Apache NiFi 1.1.2 release.
- The contents are created from information available under Apache NiFi project, however, the way summarize it is solely done with my personal thoughts and not a consensus built among Apache NiFi community.
This slide was used at a Lightning Talk of CouchConf Tokyo 2012 to introduce CouchDB JP, Japanese CouchDB community. In this slide, there is an easy-to-grasp history of CouchDB and Couchbase. I hope this slide will help you to clarify the relationship of these products.
The document summarizes the speaker's experience at ApacheCon NA 2011. It discusses several keynotes and sessions attended, including talks on building secure software, the success of Hadoop, Watson's use of Apache technologies, and new features in Lucene 4.0 like improved performance through UTF8 encoding and faster querying through new query types and indexing approaches. The document also mentions several projects that build user interfaces and experiences on top of Solr, like Prism, Blacklight, TwigKit, and Ajax Solr.