Apache Flink First Half of 2015 Community Update
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Flink has graduated from an Apache incubator project to a top-level project, attracting many new contributors. Recent releases have added features like a Table API, Gelly graph processing, and integrations with SAMOA machine learning and Google Dataflow. The talk outlines Flink's history and recent developments from 2014 to mid-2015, including three students working on Flink over the summer, and announces the first Flink Forward conference in October 2015.
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Apache Flink is an open source stream processing framework developed by the Apache Software Foundation. The core of Apache Flink is a distributed streaming dataflow engine written in Java and Scala. Apache Flink’s dataflow programming model provides event-at-a-time processing on both finite and infinite datasets. At a basic level, Flink programs consist of streams and transformations. Conceptually, a stream is a (potentially never-ending) flow of data records, and a transformation is an operation that takes one or more streams as input, and produces one or more output streams as a result. Programs can be written in Java, Scala, Python, and SQL and are automatically compiled and optimized into dataflow programs that are executed in a cluster or cloud environment.
http://www.learntek.org
Learntek is global online training provider on Big Data Analytics, Hadoop, Machine Learning, Deep Learning, IOT, AI, Cloud Technology, DEVOPS, Digital Marketing and other IT and Management courses. We are dedicated to designing, developing and implementing training programs for students, corporate employees and business professional.
Real time stock processing with apache nifi, apache flink and apache kafka
Real time stock processing with apache nifi, apache flink and apache kafka with Kafka Connect apps, SMM, NiFi Registry, Scheam Registry, Kafka topics, Flink SQL, NiFi
Apache flink
https://www.learntek.org/apache-flink/
https://www.learntek.org/
Learntek is global online training provider on Big Data Analytics, Hadoop, Machine Learning, Deep Learning, IOT, AI, Cloud Technology, DEVOPS, Digital Marketing and other IT and Management courses.
Apache flink
Apache Flink Training
https://www.learntek.org/apache-flink/
https://www.learntek.org/
Learntek is global online training provider on Big Data Analytics, Hadoop, Machine Learning, Deep Learning, IOT, AI, Cloud Technology, DEVOPS, Digital Marketing and other IT and Management courses.
Community Update May 2016 (January - May) | Berlin Apache Flink Meetup
This document provides a community update from Robert Metzger about Apache Flink activities from January to May 2016. Key events include the release of Apache Flink 1.0.0 in March, the announcement of Flink Forward 2016, new connectors being released, and work beginning on Flink 1.1 including documentation improvements and new features. Upcoming talks promoting Flink at various conferences are also listed.
Webinar: Le novità di Alfresco 5.1
Alfresco One è una piattaforma di Enterprise Content Management (ECM) cloud ibrida che permette di gestire e sincronizzare i contenuti tra diversi repository on premise e nel cloud. Grazie all'avanzato supporto per dispositivi mobili e alle tante integrazioni applicative, gli utenti possono accedere ai contenuti e collaborare ovunque si trovino e nelle modalità che preferiscono. L'architettura aperta e moderna di Alfresco One offre eccezionale flessibilità e permette alle aziende di soddisfare esigenze di business specifiche e in evoluzione, in modo molto più semplice e conveniente rispetto ai sistemi ECM proprietari.
Guarda la registrazione: https://www.alfresco.com/it/eventi/webinar/le-novita-di-alfresco-51
Boston Hadoop Meetup: Presto for the Enterprise
1. The document summarizes a presentation given by Kamil Bajda-Pawlikowski and Matt Fuller at the Boston Hadoop User Group Meetup on July 7, 2015 about Presto and Teradata's involvement with it.
2. Presto is an open source distributed SQL query engine that allows fast interactive querying of large datasets. It was originally developed at Facebook and is now supported by Teradata.
3. Teradata acquired the company that founded Presto in 2014 and has been contributing to the open source project, with plans to further its support and expand Presto's capabilities and adoption over multiple phases.
Alfresco 5.0 Technology Review
The recent launch of Alfresco One 5.0 included many key enhancements to the software. Some are provided to increase ease-of-use to end users while others bring new and improved integrations and capabilities to administrators and developers. In addition to several bug fixes, SharePoint Protocol was replaced by Alfresco Office Services and now supports property mapping and better browser support. HTML5 preview includes full text search and the ability to download or permalink from the preview—all without Flash.
The latest improvements to solr 4 will bring a more responsive and faceted search to the software. This includes inline actions for search results as well as the search criteria defaulting to AND rather than OR. Support for clustering/sharding and term highlighting is expected soon as well.
In addition to these advancements, the following list touches on some enhancements. In depth information can be found at https://www.alfresco.com/5ready
CMIS 1.1 Item Type
Site Manager and Analytics
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Advanced inline HTML editor (TinyMCE4)
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Flink in action
Artsem Semianenko (Adform) - "Flink in action или как приручить белочку"
Slides for presentation: https://www.youtube.com/watch?v=YSI5_RFlcPE
Source: https://github.com/art4ul/flink-demo
Stinger.Next by Alan Gates of Hortonworks
The document discusses Hortonworks' Stinger initiative to deliver interactive SQL query capabilities in Hadoop. Stinger aims to improve Hive query performance by 100x to enable interactive query times through optimizations like SQL types, analytic functions, and the ORC file format (Phase 1). Future phases will integrate Hive with Apache Tez and introduce a new low-latency execution engine called LLAP to enable sub-second queries (Phase 2-3). The document provides details on various Stinger phases, optimizations, and capabilities to support a wider range of SQL semantics and use cases.
Maximilian Michels - Flink and Beam
http://flink-forward.org/kb_sessions/flink-and-beam-current-state-roadmap/
It is no secret that the Dataflow model, which evolved from Google’s MapReduce, Flume, and MillWheel, has been a major influence to Apache Flink’s streaming API. The essentials of this model are captured in Apache Beam. Beam provides the Dataflow API with the option to deploy to various backends (e.g. Flink, Spark). In this talk we will examine the current state of the Flink Runner. Beam’s Runners manage the translation of the Beam API into the backend API. The Beam project itself has made an effort to summarize the capabilities of each Runner to provide an overview of the supported API concepts. From all open sources backends, Flink is currently the Runner which supports the most features. We will look at the supported Beam features and their counterpart in Flink. Further, we will look at potential improvements and upcoming features of the Flink Runner.
Alfresco Day Vienna 2015 - Technical Track - REST API of the Future
Alfresco Day Vienna 2015 - Technical Track - REST API of the Future - Gavin Cornwell, Engineering Manager,
Alfresco
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Real time stock processing with apache nifi, apache flink and apache kafka
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More from Robert Metzger
How to Contribute to Apache Flink (and Flink at the Apache Software Foundation)
This document discusses how to contribute to the Apache Flink project. It provides an overview of the Apache Software Foundation and Flink's role within it. It describes the various roles within Apache projects like Flink, including committers, PMC members, and contributors. It outlines ways to contribute such as through user support, documentation, code contributions, and reviews. The document emphasizes that there are many paths to contribute and all contributions are welcome.
dA Platform Overview
dA Platform is a production-ready platform for stream processing with Apache Flink®. The Platform includes open source Apache Flink, a stateful stream processing and event-driven application framework, and dA Application Manager, a central deployment and management component. dA Platform schedules clusters on Kubernetes, deploys stateful Flink applications, and controls these applications and their state.
Apache Flink @ Tel Aviv / Herzliya Meetup
Slides of my Apache Flink talk "Big Things" meetup at Proofpoint and "Apache Flink" meetup at Clicktale in January 2018
Apache Flink Community Updates November 2016 @ Berlin Meetup
This document provides a summary of the Flink community update presented at the Berlin Flink Meetup on November 29, 2016. The agenda included a Flink community update discussing developments since May 2016, including the upcoming 1.2 release and work on the 1.3 release. Updates were provided on the Flink developer community growth on GitHub, a new Flink book, and data Artisans' Flink platform launch. Flink adoption by other vendors like Lightbend and on Amazon EMR was highlighted. Details from Flink Forward 2016 like the number of attendees and sessions were shared. The presentation concluded with metrics showing the growing global Flink meetup community and GitHub activity to quantify the expanding Flink community.
A Data Streaming Architecture with Apache Flink (berlin Buzzwords 2016)
This document discusses Apache Flink, an open source stream processing framework. It describes how Flink enables streaming Extract, Transform, Load (ETL) workflows with low latency and high throughput. The document outlines how streaming ETL can continuously move and transform data as it arrives, rather than in periodic batch jobs. It concludes with an announcement for an upcoming Flink hackathon and questions.
GOTO Night Amsterdam - Stream processing with Apache Flink
This document discusses Apache Flink, an open source stream processing framework. It provides an overview of Flink and how it enables low-latency stream processing compared to traditional batch processing systems. Key aspects covered include windowing, state handling, fault tolerance, and performance benchmarks showing Flink can achieve high throughput. The document demonstrates how Flink addresses challenges like out-of-order events, state management, and exactly-once processing through features like event-time processing, managed state, and distributed snapshots.
QCon London - Stream Processing with Apache Flink
Robert Metzger presented on Apache Flink, an open source stream processing framework. He discussed how streaming data enables real-time analysis with low latency compared to traditional batch processing. Flink provides unique building blocks like windows, state handling, and fault tolerance to process streaming data reliably at high throughput. Benchmark results showed Flink achieving throughputs over 15 million messages/second, outperforming Storm by 35x.
January 2016 Flink Community Update & Roadmap 2016
This presentation from the 13th Flink Meetup in Berlin contains the regular community update for January and a walkthrough of the most important upcoming features in 2016
Apache Flink Meetup Munich (November 2015): Flink Overview, Architecture, Int...
This presentation held in at Inovex GmbH in Munich in November 2015 was about a general introduction of the streaming space, an overview of Flink and use cases of production users as presented at Flink Forward.
Chicago Flink Meetup: Flink's streaming architecture
This document summarizes the architecture of Apache Flink's streaming runtime. Flink is a stream processor that embraces the streaming nature of data with low latency, high throughput, and exactly-once guarantees. It achieves this through pipelining to keep data moving efficiently and distributed snapshots for fault tolerance. Flink also supports batch processing as a special case of streaming by running bounded streams as a single global window.
Architecture of Flink's Streaming Runtime @ ApacheCon EU 2015
This is a presentation I gave at ApacheCon 2015 in Budapest.
It explains Apache Flink, its streaming runtime, APIs and unique features.
Click-Through Example for Flink’s KafkaConsumer Checkpointing
See how Apache Flink's Kafka Consumer is integrating with the checkpointing mechanisms of Flink for exactly once guarantees
Apache Flink Deep-Dive @ Hadoop Summit 2015 in San Jose, CA
Flink is a unified stream and batch processing framework that natively supports streaming topologies, long-running batch jobs, machine learning algorithms, and graph processing through a pipelined dataflow execution engine. It provides high-level APIs, automatic optimization, efficient memory management, and fault tolerance to execute all of these workloads without needing to treat the system as a black box. Flink achieves native support through its ability to execute everything as data streams, support iterative and stateful computation through caching and managed state, and optimize jobs through cost-based planning and local execution strategies like sort merge join.
Apache Flink Hands On
This document provides an overview of how to run, debug, and tune Apache Flink applications. It discusses:
- Writing and testing Flink jobs locally and submitting them to a cluster for execution
- Debugging techniques like logs, accumulators, and remote debugging
- Tuning jobs by configuring parallelism, memory settings, and I/O directories
- Common issues like OutOfMemoryErrors and how to resolve them
Unified batch and stream processing with Flink @ Big Data Beers Berlin May 2015
Robert Metzger presented on the 1 year growth of the Apache Flink community and an overview of Flink's capabilities. Flink can natively support streaming, batch, machine learning, and graph processing workloads by executing everything as data streams, allowing some iterative and stateful operations, and operating on managed memory. Key aspects of Flink streaming include its pipelined processing, expressive APIs, efficient fault tolerance, and flexible windows and state. Batch pipelines in Flink are also executed as streaming programs with some blocking operations. Flink additionally supports SQL-like queries, machine learning algorithms through iterative data flows, and graph analysis through stateful delta iterations.
Flink Community Update February 2015
Flink is an open source stream processing framework. The February 2015 Flink community update announced a bugfix release, a new committer, Flink's participation in Google Summer of Code, and new features in development including a graph API, expression API, and access to secured YARN clusters and HDFS. The update also provided links to blog posts about Flink and a call for testing of a new Python API pull request.
Compute "Closeness" in Graphs using Apache Giraph.
The document describes validating different implementations for measuring closeness in graphs using the Apache Giraph framework. Statistical tests show the HyperLogLogSketch implementation exhibits the highest correlation with the baseline "bitfield" implementation on two datasets and outperforms other approaches in approximating closeness values while using less memory. Next steps involve benchmarking the implementations on larger datasets stored out-of-core in Giraph to see if the HyperLogLogSketch performance and accuracy results hold for bigger graphs.
Stratosphere System Overview Big Data Beers Berlin. 20.11.2013
Stratosphere is the next generation big data processing engine.
These slides introduce the most important features of Stratosphere by comparing it with Apache Hadoop.
For more information, visit stratosphere.eu
Based on university research, it is now a completely open-source, community driven development with focus on stability and usability.
Stratosphere Intro (Java and Scala Interface)
A quick walk overview of Stratosphere, including our Scala programming interface.
See also bigdataclass.org for two self-paced Stratosphere Big Data exercises.
More information about Stratosphere: stratosphere.eu
More from Robert Metzger (19)
How to Contribute to Apache Flink (and Flink at the Apache Software Foundation)
How to Contribute to Apache Flink (and Flink at the Apache Software Foundation)
Apache Flink Community Updates November 2016 @ Berlin Meetup
Apache Flink Community Updates November 2016 @ Berlin Meetup
A Data Streaming Architecture with Apache Flink (berlin Buzzwords 2016)
A Data Streaming Architecture with Apache Flink (berlin Buzzwords 2016)
GOTO Night Amsterdam - Stream processing with Apache Flink
GOTO Night Amsterdam - Stream processing with Apache Flink
January 2016 Flink Community Update & Roadmap 2016
January 2016 Flink Community Update & Roadmap 2016
Apache Flink Meetup Munich (November 2015): Flink Overview, Architecture, Int...
Apache Flink Meetup Munich (November 2015): Flink Overview, Architecture, Int...
Chicago Flink Meetup: Flink's streaming architecture
Chicago Flink Meetup: Flink's streaming architecture
Architecture of Flink's Streaming Runtime @ ApacheCon EU 2015
Architecture of Flink's Streaming Runtime @ ApacheCon EU 2015
Click-Through Example for Flink’s KafkaConsumer Checkpointing
Click-Through Example for Flink’s KafkaConsumer Checkpointing
Apache Flink Deep-Dive @ Hadoop Summit 2015 in San Jose, CA
Apache Flink Deep-Dive @ Hadoop Summit 2015 in San Jose, CA
Unified batch and stream processing with Flink @ Big Data Beers Berlin May 2015
Unified batch and stream processing with Flink @ Big Data Beers Berlin May 2015
Compute "Closeness" in Graphs using Apache Giraph.
Compute "Closeness" in Graphs using Apache Giraph.
Stratosphere System Overview Big Data Beers Berlin. 20.11.2013
Stratosphere System Overview Big Data Beers Berlin. 20.11.2013
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Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-and-domino-license-cost-reduction-in-the-world-of-dlau/
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HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAU
Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-und-domino-lizenzkostenreduzierung-in-der-welt-von-dlau/
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Apache Flink First Half of 2015 Community Update
- 1. Bay Area Apache Flink Meetup #1 Community Update June 2015 Robert Metzger Committer and PMC Member rmetzger@apache.org @rmetzger_
- 2. Flink’s Recent History April 2014 April 2015Dec 2014 Top Level Project Graduation 0.70.60.5 0.90.9-m1 This talk
- 3. December 2014 Graduation as Top Level Project 2flink.apache.org Official Press release: https://blogs.apache.org/foundation/entry/the_apa che_software_foundation_announces69 • Officially acknowledged as a healthy, vibrant and growing open-source community, following the Apache Way. • Attracted many new contributors and committers during incubation • More than 75+ contributors
- 4. January 2015 Release 0.8.0 • Lots of stability improvements • Scala Streaming API • Improved streaming windowing semantics • Kryo as the new fallback serializer • Extended FileSystem support (Hadoop compat) flink.apache.org 3
- 5. February 2015 • Table API added • Gelly – Graph API added • flink-hcatalog added • Apache Flink + Apache SAMOA (incubating) integration Machine Learning on streams flink.apache.org 4
- 6. March 2015 • Flink runner for Google DataFlow API available • First code of Flink ML added flink.apache.org 5
- 7. New Wiki pages with system internals • Data Exchange between tasks • Type Extraction and Serialization • Memory Management in (Batch API) • Akka and Actors flink.apache.org 6
- 8. April 2015 • Flink 0.9-milestone1 has been released • Storm compatibility layer pull request • Interactive Scala Shell added • Experimental Python API added flink.apache.org 7
- 9. flink.apache.org 8 Apache Flink got 3 Google Summer of Code students accepted: • Distributed Pattern Matching for Apache Flink • Exact and Approximate Statistics for Data Streams and Windows in Flink • Apache Flink: Asynchronous Iterations and Updates
- 10. May 2015 • Gelly Scala API started (Community contrib) • Stockholm and Bay Area Meetup groups started flink.apache.org 9 Meetup in BudapestMeetup in Stockholm
- 12. June 2015 • Zeppelin + Flink Integration merged • Static Code Analysis added • VOTE for Flink 0.9.0 started Biggest release so far • Chicago Meetup group started flink.apache.org 11
- 13. Flink + Zeppelin integration flink.apache.org 12
- 14. Flink 0.9.0 Highlights • APIs on top: – Flink Machine Learning Library – Gelly Graph Processing API – Table API (SQL-style operations) • Internals – Enhanced YARN (single jobs, container restart) – Flink On Apache Tez – Akka for process communication – secure HDFS / YARN support • Streaming Fault-Tolerance • Reworked intermediate results representation flink.apache.org 13
- 15. Ways to get in touch with the Community • Mailing lists – news@flink.apache.org (announcements only, low traffic) – user@flink.apache.org (user support, medium traffic) – dev@flink.apache.org (internal discussions, high traffic) • Twitter (@ApacheFlink) • flink.apache.org/blog • Local Meetup groups: http://apache- flink.meetup.com/ flink.apache.org 14
- 17. Flink Forward registration & call for abstracts is open now flink.apache.org 16 • 12/13 October 2015 • Kulturbrauerei Berlin • With Flink Workshops / Trainings!