Citizen Streaming Engineer - A How To
•
1 like•196 views
Citizen Streaming Engineer - A How To https://apachecon.com/acasia2022/sessions/integration-1010.html Democratizing the ability to build streaming data pipelines will help turn everyone who needs streaming data to be able to do it themselves. By utilizing the open source streaming stack known as FLiPNS will let us achieve this. FLiPNS is a stack of Apache Flink, Apache Pulsar, Apache Spark and Apache NiFi. Apache NiFi provides a Web UI for cse’s to build their own data pipelines. These citizen applications can be used to ingest data, route, transform, enrich, join and store it. As part of these applications Pulsar will provide a streaming data hub for ML model access as well as plugging in additional processing components. Speakers: Timothy SPann: StreamNative, Developer Advocate, Tim Spann is a Developer Advocate for StreamNative. He works with StreamNative Cloud, Apache Pulsar, Apache Flink, Flink SQL, Apache NiFi, MiniFi, Apache MXNet, TensorFlow, Apache Spark, Big Data, the IoT, machine learning, and deep learning. Tim has over a decade of experience with the IoT, big data, distributed computing, messaging, streaming technologies, and Java programming. Previously, he was a Principal DataFlow Field Engineer at Cloudera, a Senior Solutions Engineer at Hortonworks, a Senior Solutions Architect at AirisData, a Senior Field Engineer at Pivotal and a Team Leader at HPE. He blogs for DZone, where he is the Big Data Zone leader, and runs a popular meetup in Princeton on Big Data, Cloud, IoT, deep learning, streaming, NiFi, the blockchain, and Spark. Tim is a frequent speaker at conferences such as ApacheCon, DeveloperWeek, Pulsar Summit and many more. He holds a BS and MS in computer science.
Report
Share
Report
Share
Download to read offline
Recommended
ApacheCon2022_Citizen Streaming Engineer - A How To
ApacheCon2022_Citizen Streaming Engineer - A How To
Democratizing the ability to build streaming data pipelines will help turn everyone who needs streaming data to be able to do it themselves. By utilizing the open source streaming stack known as FLiPNS will let us achieve this.
FLiPNS is a stack of Apache Flink, Apache Pulsar, Apache Spark and Apache NiFi. Apache NiFi provides a Web UI for cse’s to build their own data pipelines. These citizen applications can be used to ingest data, route, transform, enrich, join and store it. As part of these applications Pulsar will provide a streaming data hub for ML model access as well as plugging in additional processing components.
Speakers:
Timothy SPann: StreamNative, Developer Advocate, Tim Spann is a Developer Advocate for StreamNative. He works with StreamNative Cloud, Apache Pulsar, Apache Flink, Flink SQL, Apache NiFi, MiniFi, Apache MXNet, TensorFlow, Apache Spark, Big Data, the IoT, machine learning, and deep learning. Tim has over a decade of experience with the IoT, big data, distributed computing, messaging, streaming technologies, and Java programming. Previously, he was a Principal DataFlow Field Engineer at Cloudera, a Senior Solutions Engineer at Hortonworks, a Senior Solutions Architect at AirisData, a Senior Field Engineer at Pivotal and a Team Leader at HPE. He blogs for DZone, where he is the Big Data Zone leader, and runs a popular meetup in Princeton on Big Data, Cloud, IoT, deep learning, streaming, NiFi, the blockchain, and Spark. Tim is a frequent speaker at conferences such as ApacheCon, DeveloperWeek, Pulsar Summit and many more. He holds a BS and MS in computer science.
Designing Event-Driven Applications with Apache NiFi, Apache Flink, Apache Sp...
Designing Event-Driven Applications with Apache NiFi, Apache Flink, Apache Spark
DevNexus 2022 Atlanta
https://devnexus.com/presentations/7150/
This talk is a quick overview of the How, What and WHY of Apache Pulsar, Apache Flink and Apache NiFi. I will show you how to design event-driven applications that scale the cloud native way.
This talk was done live in person at DevNexus across from the booth in room 311
Tim Spann
Tim Spann is a Developer Advocate for StreamNative. He works with StreamNative Cloud, Apache Pulsar, Apache Flink, Flink SQL, Apache NiFi, MiniFi, Apache MXNet, TensorFlow, Apache Spark, big data, the IoT, machine learning, and deep learning. Tim has over a decade of experience with the IoT, big data, distributed computing, streaming technologies, and Java programming. Previously, he was a Principal DataFlow Field Engineer at Cloudera, a Senior Solutions Architect at AirisData, a Senior Field Engineer at Pivotal and a Team Leader at HPE. He blogs for DZone, where he is the Big Data Zone leader, and runs a popular meetup in Princeton on big data, the IoT, deep learning, streaming, NiFi, the blockchain, and Spark. Tim is a frequent speaker at conferences such as IoT Fusion, Strata, ApacheCon, Data Works Summit Berlin, DataWorks Summit Sydney, and Oracle Code NYC. He holds a BS and MS in computer science.
Deep Dive into Building Streaming Applications with Apache Pulsar
Deep Dive into Building Streaming Applications with Apache Pulsar
philly ete
apache pulsar with java, python, flink, nifi, spark
Music city data Hail Hydrate! from stream to lake
Music city data Hail Hydrate! from stream to lake
with apache pulsar, apache flink, apache nifi, datalake, cloud, streaming data, IoT.
The Next Generation of Streaming
The Next Generation of Streaming
https://www.meetup.com/new-york-city-apache-pulsar-meetup/events/291048765/
https://www.meetup.com/risingwave-community/events/291294056/
The Next Generation of Streaming
David Kjerrumgaard, Developer Advocate
Tim Spann
Building a cloud-native streaming application requires a team, from the start of events to the final analytics. I'll walk you through using Apache Pulsar as your central messaging hub to distribute events and real-time messages from and to everywhere it needs to be. All instantly. The next step is to stream into continuous SQL.
Agenda
9:00 -- 9:20 The Next Generation of Streaming by Tim Spann,
Developer Advocate at StreamNative
9:20 -- 9:40 RisingWave: Cloud-Native Streaming SQL over Pulsar by Rayees Pasha, Head of Product at RisingWave Labs
23-feb-2023 12:15pm EST
https://github.com/tspannhw/Flow-SGP30-MLX90640
Apache NiFi, Apache Pulsar, Apache Kafka, MQTT, RabbitMQ, AMQP, Source, Sink, Stream Processing
CODEONTHEBEACH_Streaming Applications with Apache Pulsar
CODEONTHEBEACH_Streaming Applications with Apache Pulsar
https://www.codeonthebeach.com/schedule
Deep Dive into Building Streaming Applications with Apache Pulsar - Timothy Spann
In this session I will get you started with real-time cloud native streaming programming with Java, Golang, Python and Apache NiFi. I will start off with an introduction to Apache Pulsar and setting up your first easy standalone cluster in docker. We will then go into terms and architecture so you have an idea of what is going on with your events. I will then show you how to produce and consume messages to and from Pulsar topics. As well as using some of the command line and REST interfaces to monitor, manage and do CRUD on things like tenants, namespaces and topics.
We will discuss Functions, Sinks, Sources, Pulsar SQL, Flink SQL and Spark SQL interfaces. We also discuss why you may want to add protocols such as MoP (MQTT), AoP (AMQP/RabbitMQ) or KoP (Kafka) to your cluster. We will also look at WebSockets as a producer and consumer. I will demonstrate a simple web page that sends and receives Pulsar messages with basic JavaScript.
After this session you will be able to build simple real-time streaming and messaging applications with your chosen language or tool of your choice.
Cloud lunch and learn real-time streaming in azure
Cloud lunch and learn real-time streaming in azure
Apache pulsar is an open source, cloud-native distributed messaging and streaming platform.
Using Apache NiFi with Apache Pulsar for Fast Data On-Ramp
Using Apache NiFi with Apache Pulsar for Fast Data On-Ramp
https://pulsar-summit.org/event/europe-2023/schedule
https://pulsar-summit.org/event/europe-2023/sessions/europe-2023-using-apache-nifi-with-apache-pulsar-for-fast-data-on-ramp
12:30 PM - 1:00 PM, CEST , May 23
Using Apache Nifi with Apache Pulsar for Fast Data On-Ramp
As the Pulsar communities grows, more and more connectors will be added. To enhance the availability of sources and sinks and to make use of the greater Apache Streaming community, joining forces between Apache NiFi and Apache Pulsar is a perfect fit. Apache NiFi also adds the benefits of ELT, ETL, data crunching, transformation, validation and batch data processing. Once data is ready to be an event, NiFi can launch it into Pulsar at light speed.
Timothy Spann
Principal Developer Advocate for Data in Motion @ Cloudera
Recommended
ApacheCon2022_Citizen Streaming Engineer - A How To
ApacheCon2022_Citizen Streaming Engineer - A How To
Democratizing the ability to build streaming data pipelines will help turn everyone who needs streaming data to be able to do it themselves. By utilizing the open source streaming stack known as FLiPNS will let us achieve this.
FLiPNS is a stack of Apache Flink, Apache Pulsar, Apache Spark and Apache NiFi. Apache NiFi provides a Web UI for cse’s to build their own data pipelines. These citizen applications can be used to ingest data, route, transform, enrich, join and store it. As part of these applications Pulsar will provide a streaming data hub for ML model access as well as plugging in additional processing components.
Speakers:
Timothy SPann: StreamNative, Developer Advocate, Tim Spann is a Developer Advocate for StreamNative. He works with StreamNative Cloud, Apache Pulsar, Apache Flink, Flink SQL, Apache NiFi, MiniFi, Apache MXNet, TensorFlow, Apache Spark, Big Data, the IoT, machine learning, and deep learning. Tim has over a decade of experience with the IoT, big data, distributed computing, messaging, streaming technologies, and Java programming. Previously, he was a Principal DataFlow Field Engineer at Cloudera, a Senior Solutions Engineer at Hortonworks, a Senior Solutions Architect at AirisData, a Senior Field Engineer at Pivotal and a Team Leader at HPE. He blogs for DZone, where he is the Big Data Zone leader, and runs a popular meetup in Princeton on Big Data, Cloud, IoT, deep learning, streaming, NiFi, the blockchain, and Spark. Tim is a frequent speaker at conferences such as ApacheCon, DeveloperWeek, Pulsar Summit and many more. He holds a BS and MS in computer science.
Designing Event-Driven Applications with Apache NiFi, Apache Flink, Apache Sp...
Designing Event-Driven Applications with Apache NiFi, Apache Flink, Apache Spark
DevNexus 2022 Atlanta
https://devnexus.com/presentations/7150/
This talk is a quick overview of the How, What and WHY of Apache Pulsar, Apache Flink and Apache NiFi. I will show you how to design event-driven applications that scale the cloud native way.
This talk was done live in person at DevNexus across from the booth in room 311
Tim Spann
Tim Spann is a Developer Advocate for StreamNative. He works with StreamNative Cloud, Apache Pulsar, Apache Flink, Flink SQL, Apache NiFi, MiniFi, Apache MXNet, TensorFlow, Apache Spark, big data, the IoT, machine learning, and deep learning. Tim has over a decade of experience with the IoT, big data, distributed computing, streaming technologies, and Java programming. Previously, he was a Principal DataFlow Field Engineer at Cloudera, a Senior Solutions Architect at AirisData, a Senior Field Engineer at Pivotal and a Team Leader at HPE. He blogs for DZone, where he is the Big Data Zone leader, and runs a popular meetup in Princeton on big data, the IoT, deep learning, streaming, NiFi, the blockchain, and Spark. Tim is a frequent speaker at conferences such as IoT Fusion, Strata, ApacheCon, Data Works Summit Berlin, DataWorks Summit Sydney, and Oracle Code NYC. He holds a BS and MS in computer science.
Deep Dive into Building Streaming Applications with Apache Pulsar
Deep Dive into Building Streaming Applications with Apache Pulsar
philly ete
apache pulsar with java, python, flink, nifi, spark
Music city data Hail Hydrate! from stream to lake
Music city data Hail Hydrate! from stream to lake
with apache pulsar, apache flink, apache nifi, datalake, cloud, streaming data, IoT.
The Next Generation of Streaming
The Next Generation of Streaming
https://www.meetup.com/new-york-city-apache-pulsar-meetup/events/291048765/
https://www.meetup.com/risingwave-community/events/291294056/
The Next Generation of Streaming
David Kjerrumgaard, Developer Advocate
Tim Spann
Building a cloud-native streaming application requires a team, from the start of events to the final analytics. I'll walk you through using Apache Pulsar as your central messaging hub to distribute events and real-time messages from and to everywhere it needs to be. All instantly. The next step is to stream into continuous SQL.
Agenda
9:00 -- 9:20 The Next Generation of Streaming by Tim Spann,
Developer Advocate at StreamNative
9:20 -- 9:40 RisingWave: Cloud-Native Streaming SQL over Pulsar by Rayees Pasha, Head of Product at RisingWave Labs
23-feb-2023 12:15pm EST
https://github.com/tspannhw/Flow-SGP30-MLX90640
Apache NiFi, Apache Pulsar, Apache Kafka, MQTT, RabbitMQ, AMQP, Source, Sink, Stream Processing
CODEONTHEBEACH_Streaming Applications with Apache Pulsar
CODEONTHEBEACH_Streaming Applications with Apache Pulsar
https://www.codeonthebeach.com/schedule
Deep Dive into Building Streaming Applications with Apache Pulsar - Timothy Spann
In this session I will get you started with real-time cloud native streaming programming with Java, Golang, Python and Apache NiFi. I will start off with an introduction to Apache Pulsar and setting up your first easy standalone cluster in docker. We will then go into terms and architecture so you have an idea of what is going on with your events. I will then show you how to produce and consume messages to and from Pulsar topics. As well as using some of the command line and REST interfaces to monitor, manage and do CRUD on things like tenants, namespaces and topics.
We will discuss Functions, Sinks, Sources, Pulsar SQL, Flink SQL and Spark SQL interfaces. We also discuss why you may want to add protocols such as MoP (MQTT), AoP (AMQP/RabbitMQ) or KoP (Kafka) to your cluster. We will also look at WebSockets as a producer and consumer. I will demonstrate a simple web page that sends and receives Pulsar messages with basic JavaScript.
After this session you will be able to build simple real-time streaming and messaging applications with your chosen language or tool of your choice.
Cloud lunch and learn real-time streaming in azure
Cloud lunch and learn real-time streaming in azure
Apache pulsar is an open source, cloud-native distributed messaging and streaming platform.
Using Apache NiFi with Apache Pulsar for Fast Data On-Ramp
Using Apache NiFi with Apache Pulsar for Fast Data On-Ramp
https://pulsar-summit.org/event/europe-2023/schedule
https://pulsar-summit.org/event/europe-2023/sessions/europe-2023-using-apache-nifi-with-apache-pulsar-for-fast-data-on-ramp
12:30 PM - 1:00 PM, CEST , May 23
Using Apache Nifi with Apache Pulsar for Fast Data On-Ramp
As the Pulsar communities grows, more and more connectors will be added. To enhance the availability of sources and sinks and to make use of the greater Apache Streaming community, joining forces between Apache NiFi and Apache Pulsar is a perfect fit. Apache NiFi also adds the benefits of ELT, ETL, data crunching, transformation, validation and batch data processing. Once data is ready to be an event, NiFi can launch it into Pulsar at light speed.
Timothy Spann
Principal Developer Advocate for Data in Motion @ Cloudera
Devfest uk & ireland using apache nifi with apache pulsar for fast data on-r...
Devfest uk & ireland using apache nifi with apache pulsar for fast data on-ramp 2022
As the Pulsar communities grows, more and more connectors will be added. To enhance the availability of sources and sinks and to make use of the greater Apache Streaming community, joining forces between Apache NiFi and Apache Pulsar is a perfect fit. Apache NiFi also adds the benefits of ELT, ETL, data crunching, transformation, validation and batch data processing. Once data is ready to be an event, NiFi can launch it into Pulsar at light speed.
I will walk through how to get started, some use cases and demos and answer questions.
https://www.devfest-uki.com/schedule
https://linktr.ee/tspannhw
OSS EU: Deep Dive into Building Streaming Applications with Apache Pulsar
OSS EU: Deep Dive into Building Streaming Applications with Apache Pulsar
In this session I will get you started with real-time cloud native streaming programming with Java, Golang, Python and Apache NiFi. If there’s a preferred language that the attendees pick, we will focus only on that one. I will start off with an introduction to Apache Pulsar and setting up your first easy standalone cluster in docker. We will then go into terms and architecture so you have an idea of what is going on with your events. I will then show you how to produce and consume messages to and from Pulsar topics. As well as using some of the command line and REST interfaces to monitor, manage and do CRUD on things like tenants, namespaces and topics. We will discuss Functions, Sinks, Sources, Pulsar SQL, Flink SQL and Spark SQL interfaces. We also discuss why you may want to add protocols such as MoP (MQTT), AoP (AMQP/RabbitMQ) or KoP (Kafka) to your cluster. We will also look at WebSockets as a producer and consumer. I will demonstrate a simple web page that sends and receives Pulsar messages with basic JavaScript. After this session you will be able to build simple real-time streaming and messaging applications with your chosen language or tool of your choice.
apache pulsar
DBCC 2021 - FLiP Stack for Cloud Data Lakes
DBCC 2021 - FLiP Stack for Cloud Data Lakes
With Apache Pulsar, Apache NiFi, Apache Flink. The FLiP(N) Stack for Event processing and IoT. With StreamNative Cloud.
DBCC International – Friday 15.10.2021
Powered by Apache Pulsar, StreamNative provides a cloud-native, real-time messaging and streaming platform to support multi-cloud and hybrid cloud strategies.
ApacheCon2022_Deep Dive into Building Streaming Applications with Apache Pulsar
ApacheCon2022_Deep Dive into Building Streaming Applications with Apache Pulsar
In this session I will get you started with real-time cloud native streaming programming with Java, Golang, Python and Apache NiFi. If there’s a preferred language that the attendees pick, we will focus only on that one. I will start off with an introduction to Apache Pulsar and setting up your first easy standalone cluster in docker. We will then go into terms and architecture so you have an idea of what is going on with your events. I will then show you how to produce and consume messages to and from Pulsar topics. As well as using some of the command line and REST interfaces to monitor, manage and do CRUD on things like tenants, namespaces and topics. We will discuss Functions, Sinks, Sources, Pulsar SQL, Flink SQL and Spark SQL interfaces. We also discuss why you may want to add protocols such as MoP (MQTT), AoP (AMQP/RabbitMQ) or KoP (Kafka) to your cluster. We will also look at WebSockets as a producer and consumer. I will demonstrate a simple web page that sends and receives Pulsar messages with basic JavaScript. After this session you will be able to build simple real-time streaming and messaging applications with your chosen language or tool of your choice.
apache pulsar
tim spann developer advocate
streamnative
datainmotion.dev
[AI Dev World 2022] Build ML Enhanced Event Streaming
[AI Dev World 2022] Build ML Enhanced Event Streaming
3:00 PM - 3:25 PM PDT
[#VIRTUAL] OPEN TALK (AI): BUILD ML ENHANCED EVENT STREAMING APPLICATIONS WITH JAVA MICROSERVICES
VIRTUAL ONLY API WORLD & AI DEVWORLD STAGE
VIRTUAL ONLY VIRTUAL APPLIED MACHINE LEARNING
Timothy Spann
Timothy Spann
StreamNative, Developer Advocate
In this talk we will walk through how to build event streaming applications as functions running in with cloud native messaging via Apache Pulsar that run on near infinite scale in any cloud, docker or K8. We will show you have to deploy ML functions to transform real-time data for IoT, Streaming Analytics and many other use cases. After this talk you will be able to build Java microservices with ease and deploy them anywhere utilizing the open source unified streaming and messaging platform, Apache Pulsar. Finally, we will show you have to add dashboards with Web Sockets, no code data sinks, integrate with Apache NiFi data pipelines, SQL Reports with Apache Spark and finally continuous ETL with Apache Flink. I have built many of these applications for many organizations as part of the FLiPN Stack. Let's build next generation applications today regardless if your data is REST APIs, Sensors, Logs, NoSQL Sources, Events or Database tables.
https://aidevworld.com/conference/conference-tracks/applied-machine-learning/
https://github.com/tspannhw/pulsar-transit-function
https://github.com/tspannhw/FLiPStackWeekly/blob/main/README.md
Data science online camp using the flipn stack for edge ai (flink, nifi, pu...
Data science online camp using the flipn stack for edge ai (flink, nifi, pulsar)
Dec 3, 2021
Apache NiFi
Apache Flink
Apache Pulsar
Edge AI
Cloud Native Made Easy
StreamNative
Scenic City Summit (2021): Real-Time Streaming in any and all clouds, hybrid...
Scenic city summit real-time streaming in any and all clouds, hybrid and beyond
24-September-2021. Scenic City Summit. Virtual. Real-Time Streaming in Any and All Clouds, Hybrid and Beyond
Apache Pulsar, Apache NiFi, Apache Flink
StreamNative
Tim Spann
https://sceniccitysummit.com/
Using the FLiPN Stack for Edge AI (Flink, NiFi, Pulsar)
Using the FLiPN Stack for Edge AI (Flink, NiFi, Pulsar)
https://github.com/tspannhw/FLiP-Pi-DeltaLake-Thermal/
Tim Spann
Streamnative
https://github.com/tspannhw/pulsar-pychat-function
https://events.dataidols.com/talks/using-the-flipn-stack-for-edge-ai-flink-nifi-pulsar/
Hosted by Karen Jean-Francois.
Introducing the FLiPN stack which combines Apache Flink, Apache NiFi, Apache Pulsar and other Apache tools to build fast applications for IoT, AI, rapid ingest.
FLiPN provides a quick set of tools to build applications at any scale for any streaming and IoT use cases.
Tools Apache Flink, Apache Pulsar, Apache NiFi, MiNiFi, Apache MXNet, DJL.AI
References https://www.datainmotion.dev/2019/08/rapid-iot-development-with-cloudera.html https://www.datainmotion.dev/2019/09/powering-edge-ai-for-sensor-reading.html https://www.datainmotion.dev/2019/05/dataworks-summit-dc-2019-report.html https://www.datainmotion.dev/2019/03/using-raspberry-pi-3b-with-apache-nifi.html
Data Idols - Summer School - Data Science
Hail hydrate! from stream to lake using open source
(VIRTUAL) Hail Hydrate! From Stream to Lake Using Open Source - Timothy J Spann, StreamNative
https://osselc21.sched.com/event/lAPi?iframe=no
A cloud data lake that is empty is not useful to anyone. How can you quickly, scalably and reliably fill your cloud data lake with diverse sources of data you already have and new ones you never imagined you needed. Utilizing open source tools from Apache, the FLiP stack enables any data engineer, programmer or analyst to build reusable modules with low or no code. FLiP utilizes Apache NiFi, Apache Pulsar, Apache Flink and MiNiFi agents to load CDC, Logs, REST, XML, Images, PDFs, Documents, Text, semistructured data, unstructured data, structured data and a hundred data sources you could never dream of streaming before. I will teach you how to fish in the deep end of the lake and return a data engineering hero. Let's hope everyone is ready to go from 0 to Petabyte hero.
https://osselc21.sched.com/event/lAPi/virtual-hail-hydrate-from-stream-to-lake-using-open-source-timothy-j-spann-streamnative
ApacheCon 2021 - Apache NiFi Deep Dive 300
21-September-2021 - ApacheCon - Tuesday 17:10 UTC Apache NIFi Deep Dive 300
* https://github.com/tspannhw/EverythingApacheNiFi
* https://github.com/tspannhw/FLiP-ApacheCon2021
* https://www.datainmotion.dev/2020/06/no-more-spaghetti-flows.html
* https://github.com/tspannhw/FLiP-IoT
* https://github.com/tspannhw/FLiP-Energy
* https://github.com/tspannhw/FLiP-SOLR
* https://github.com/tspannhw/FLiP-EdgeAI
* https://github.com/tspannhw/FLiP-CloudQueries
* https://github.com/tspannhw/FLiP-Jetson
* https://www.linkedin.com/pulse/2021-schedule-tim-spann/
Tuesday 17:10 UTC
Apache NIFi Deep Dive 300
Timothy Spann
For Data Engineers who have flows already in production, I will dive deep into best practices, advanced use cases, performance optimizations, tips, tricks, edge cases, and interesting examples. This is a master class for those looking to learn quickly things I have picked up after years in the field with Apache NiFi in production.
This will be interactive and I encourage questions and discussions.
You will take away examples and tips in slides, github, and articles.
This talk will cover:
Load Balancing
Parameters and Parameter Contexts
Stateless vs Stateful NiFi
Reporting Tasks
NiFi CLI
NiFi REST Interface
DevOps
Advanced Record Processing
Schemas
RetryFlowFile
Lookup Services
RecordPath
Expression Language
Advanced Error Handling Techniques
Tim Spann is a Developer Advocate @ StreamNative where he works with Apache NiFi, Apache Pulsar, Apache Flink, Apache MXNet, TensorFlow, Apache Spark, big data, the IoT, machine learning, and deep learning. Tim has over a decade of experience with the IoT, big data, distributed computing, streaming technologies, and Java programming. Previously, he was a Principal Field Engineer at Cloudera, a senior solutions architect at AirisData and a senior field engineer at Pivotal. He blogs for DZone, where he is the Big Data Zone leader, and runs a popular meetup in Princeton on big data, the IoT, deep learning, streaming, NiFi, the blockchain, and Spark. Tim is a frequent speaker at conferences such as IoT Fusion, Strata, ApacheCon, Data Works Summit Berlin, DataWorks Summit Sydney, and Oracle Code NYC. He holds a BS and MS in computer science.
Big mountain data and dev conference apache pulsar with mqtt for edge compu...
Big mountain data and dev conference apache pulsar with mqtt for edge computing
Using FLiP with InfluxDB for EdgeAI IoT at Scale 2022
Using FLiP with InfluxDB for EdgeAI IoT at Scale 2022
https://adtmag.com/webcasts/2021/12/influxdata-february-10.aspx?tc=page0
Using FLiP with InfluxDB for EdgeAI IoT at Scale
Date: Thursday, February 10th at 11am PT / 2pm ET
Join this webcast as Timothy from StreamNative takes you on a hands-on deep-dive using Pulsar, Apache NiFi + Edge Flow Manager + MiniFi Agents with Apache MXNet, OpenVino, TensorFlow Lite, and other Deep Learning Libraries on the actual edge devices including Raspberry Pi with Movidius 2, Google Coral TPU and NVidia Jetson Nano.
The team runs deep learning models on the edge devices, sends images, and captures real-time GPS and sensor data. Their low-coding IoT applications provide easy edge routing, transformation, data acquisition and alerting before they decide what data to stream in real-time to their data space. These edge applications classify images and sensor readings in real-time at the edge and then send Deep Learning results to Flink SQL and Apache NiFi for transformation, parsing, enrichment, querying, filtering and merging data to InfluxDB.
In this session you will learn how to:
Build an end-to-end streaming edge app
Pull messages from Pulsar topics and persists the messages to InfluxDB
Build a data stream for IoT with NiFi and InfluxDB
Use Apache Flink + Apache Pulsar
Timothy Spann, Developer Advocate, StreamNative
Tim Spann is a Developer Advocate at StreamNative where he works with Apache NiFi, MiniFi, Kafka, Apache Flink, Apache MXNet, TensorFlow, Apache Spark, big data, the IoT, machine learning, and deep learning. Tim has over a decade of experience with the IoT, big data, distributed computing, streaming technologies, and Java programming. Previously, he was a senior solutions architect at AirisData and a senior field engineer at Pivotal. He blogs for DZone, where he is the Big Data Zone leader, and runs a popular meetup in Princeton on big data, the IoT, deep learning, streaming, NiFi, the blockchain, and Spark. Tim is a frequent speaker at conferences such as IoT Fusion, Strata, ApacheCon, Data Works Summit Berlin, DataWorks Summit Sydney, and Oracle Code NYC. He holds a BS and MS in computer science.
Using FLiP with influxdb for edgeai iot at scale 2022
https://adtmag.com/webcasts/2021/12/influxdata-february-10.aspx?tc=page0
FLiP Stack (Apache Flink, Apache Pulsar, Apache NiFi, Apache Spark) with Influx DB for Edge AI and IoT workloads at scale
Tim Spann
Developer Advocate
StreamNative
datainmotion.dev
OSSNA Building Modern Data Streaming Apps
OSSNA
Building Modern Data Streaming Apps
https://ossna2023.sched.com/event/1Jt05/virtual-building-modern-data-streaming-apps-with-open-source-timothy-spann-streamnative
Timothy Spann
Cloudera
Principal Developer Advocate
Data in Motion
In my session, I will show you some best practices I have discovered over the last seven years in building data streaming applications, including IoT, CDC, Logs, and more. In my modern approach, we utilize several open-source frameworks to maximize all the best features. We often start with Apache NiFi as the orchestrator of streams flowing into Apache Pulsar. From there, we build streaming ETL with Apache Spark and enhance events with Pulsar Functions for ML and enrichment. We make continuous queries against our topics with Flink SQL. We will stream data into various open-source data stores, including Apache Iceberg, Apache Pinot, and others. We use the best streaming tools for the current applications with the open source stack - FLiPN. https://www.flipn.app/ Updates: This will be in-person with live coding based on feedback from the crowd. This will also include new data stores, new sources, and data relevant to and from the Vancouver area. This will also include updates to the platforms and inclusion of Apache Iceberg, Apache Pinot and some other new tech.
https://github.com/tspannhw/SpeakerProfile Tim Spann is a Principal Developer Advocate for Cloudera. He works with Apache Kafka, Apache Flink, Flink SQL, Apache NiFi, MiniFi, Apache MXNet, TensorFlow, Apache Spark, Big Data, the IoT, machine learning, and deep learning. Tim has over a decade of experience with the IoT, big data, distributed computing, messaging, streaming technologies, and Java programming. Previously, he was a Principal DataFlow Field Engineer at Cloudera, a Senior Solutions Engineer at Hortonworks, a Senior Solutions Architect at AirisData, a Senior Field Engineer at Pivotal and a Team Leader at HPE. He blogs for DZone, where he is the Big Data Zone leader, and runs a popular meetup in Princeton on Big Data, Cloud, IoT, deep learning, streaming, NiFi, the blockchain, and Spark. Tim is a frequent speaker at conferences such as ApacheCon, DeveloperWeek, Pulsar Summit and many more. He holds a BS and MS in computer science.
Timothy J Spann
Cloudera
Principal Developer Advocate
Hightstown, NJ
Websitehttps://datainmotion.dev/
Data minutes #2 Apache Pulsar with MQTT for Edge Computing Lightning - 2022
21-Jan-2022. Friday 9:45 AM — 10 min. DataMinutes. Apache Pulsar with MQTT for Edge Computing. https://datagrillen.com/dataminutes/
Apache Pulsar with MQTT for Edge Computing Lightning - 2022
Tim Spann
Real time cloud native open source streaming of any data to apache solr
Real time cloud native open source streaming of any data to apache solr
Utilizing Apache Pulsar and Apache NiFi we can parse any document in real-time at scale. We receive a lot of documents via cloud storage, email, social channels and internal document stores. We want to make all the content and metadata to Apache Solr for categorization, full text search, optimization and combination with other datastores. We will not only stream documents, but all REST feeds, logs and IoT data. Once data is produced to Pulsar topics it can instantly be ingested to Solr through Pulsar Solr Sink.
Utilizing a number of open source tools, we have created a real-time scalable any document parsing data flow. We use Apache Tika for Document Processing with real-time language detection, natural language processing with Apache OpenNLP, Sentiment Analysis with Stanford CoreNLP, Spacy and TextBlob. We will walk everyone through creating an open source flow of documents utilizing Apache NiFi as our integration engine. We can convert PDF, Excel and Word to HTML and/or text. We can also extract the text to apply sentiment analysis and NLP categorization to generate additional metadata about our documents. We also will extract and parse images that if they contain text we can extract with TensorFlow and Tesseract.
Building an Event Streaming Architecture with Apache Pulsar
What is Apache Pulsar? How does it differ from other event streaming technologies available? StreamNative Developer Advocate Tim Spann will walk you through the features and architecture of this increasingly popular event streaming system, along with best practices for streaming and storing your data.
DevNexus: Apache Pulsar Development 101 with Java
DevNexus: Apache Pulsar Development 101 with Java
06-april-2023 georgia conference center atlanta, ga
https://devnexus.com/presentations/apache-pulsar-development-101-with-java
Abstract
In this session I will get you started with real-time cloud native streaming programming with Java. We will start off with a gentle introduction to Apache Pulsar and setting up your first easy standalone cluster. We will then l show you how to produce and consume message to Pulsar using several different Java libraries including native Java client, websockets, MQTT and even Kafka. After this session you will building real-time streaming and messaging applications with Java. We will also touch on Apache Spark and Apache Flink.
Timothy Spann
Tim Spann is a Developer Advocate @ Cloudera where he works with Apache Pulsar, Apache Flink, Apache NiFi, Apache MXNet, TensorFlow, Apache Spark, big data, the IoT, machine learning, and deep learning. Tim has over a decade of experience with the IoT, big data, distributed computing, streaming technologies, and Java programming. Previously, he was a Principal Field Engineer at Cloudera, a Senior Solutions Architect at AirisData and a senior field engineer at Pivotal. He blogs for DZone, where he is the Big Data Zone leader, and runs a popular meetup in Princeton on big data, the IoT, deep learning, streaming, NiFi, the blockchain, and Spark. Tim is a frequent speaker at conferences such as IoT Fusion, Strata, ApacheCon, Data Works Summit Berlin, DataWorks Summit Sydney, and Oracle Code NYC. He holds a BS and MS in computer science. https://www.datainmotion.dev/p/about-me.html https://dzone.com/users/297029/bunkertor.html https://conferences.oreilly.com/strata/strata-ny-2018/public/schedule/speaker/185963
MLconf 2022 NYC Event-Driven Machine Learning at Scale.pdf
MLconf 2022 NYC Event-Driven Machine Learning at Scale
https://mlconf.com/agenda/mlconf-2022-NYC/
https://mlconf.com/speakers/timothy-spann/
Bio
Tim Spann is a Developer Advocate for StreamNative. He works with StreamNative Cloud, Apache Pulsar, Apache Flink, Flink SQL, Apache NiFi, MiniFi, Apache MXNet, TensorFlow, Apache Spark, Big Data, the IoT, machine learning, and deep learning. Tim has over a decade of experience with the IoT, big data, distributed computing, messaging, streaming technologies, and Java programming. Previously, he was a Principal DataFlow Field Engineer at Cloudera, a Senior Solutions Engineer at Hortonworks, a Senior Solutions Architect at AirisData, a Senior Field Engineer at Pivotal and a Team Leader at HPE. He blogs for DZone, where he is the Big Data Zone leader, and runs a popular meetup in Princeton on Big Data, Cloud, IoT, deep learning, streaming, NiFi, the blockchain, and Spark. Tim is a frequent speaker at conferences such as ApacheCon, DeveloperWeek, Pulsar Summit and many more. He holds a BS and MS in computer science. He is currently working on a book about the FLiP Stack.
Upcoming Abstract Summary
Event-Driven Machine Learning at Scale
Utilizing the FLiP stack we can drive NLP and other machine learning classifications in the cloud, on-premise, hybrid and at the edge utilizing the open source Apache Pulsar project. We often utilize the full FLiPN stack which includes Apache Flink, Apache NiFi and Apache Pulsar.
Apache Pulsar is a unified messaging platform that can host and execute classifications as events arrive asynchronously to topics. We deploy our functionality in lightweight functions that can run as processes, threads or in K8. We often use the serverless FunctionMesh to run these. This allows us to run machine learning classes built in Go, Python and Java. We will show you utilizing Vader Sentiment, Pytorch, TensorFlow, DJL.AI, MXNet and other machine learning options with ease.
Using the flipn stack for edge ai (flink, nifi, pulsar)
Pulsar Summit Asia 2021/2022
Using The FLiPN Stack for EdgeAI (Flink, Pulsar, NiFi)
Tim Spann
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Dat...
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Data and AI
Round table discussion of vector databases, unstructured data, ai, big data, real-time, robots and Milvus.
A lively discussion with NJ Gen AI Meetup Lead, Prasad and Procure.FYI's Co-Found
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Dat...
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Data and AI
Discussion on Vector Databases, Unstructured Data and AI
https://www.meetup.com/unstructured-data-meetup-new-york/
This meetup is for people working in unstructured data. Speakers will come present about related topics such as vector databases, LLMs, and managing data at scale. The intended audience of this group includes roles like machine learning engineers, data scientists, data engineers, software engineers, and PMs.This meetup was formerly Milvus Meetup, and is sponsored by Zilliz maintainers of Milvus.
More Related Content
Similar to Citizen Streaming Engineer - A How To
Devfest uk & ireland using apache nifi with apache pulsar for fast data on-r...
Devfest uk & ireland using apache nifi with apache pulsar for fast data on-ramp 2022
As the Pulsar communities grows, more and more connectors will be added. To enhance the availability of sources and sinks and to make use of the greater Apache Streaming community, joining forces between Apache NiFi and Apache Pulsar is a perfect fit. Apache NiFi also adds the benefits of ELT, ETL, data crunching, transformation, validation and batch data processing. Once data is ready to be an event, NiFi can launch it into Pulsar at light speed.
I will walk through how to get started, some use cases and demos and answer questions.
https://www.devfest-uki.com/schedule
https://linktr.ee/tspannhw
OSS EU: Deep Dive into Building Streaming Applications with Apache Pulsar
OSS EU: Deep Dive into Building Streaming Applications with Apache Pulsar
In this session I will get you started with real-time cloud native streaming programming with Java, Golang, Python and Apache NiFi. If there’s a preferred language that the attendees pick, we will focus only on that one. I will start off with an introduction to Apache Pulsar and setting up your first easy standalone cluster in docker. We will then go into terms and architecture so you have an idea of what is going on with your events. I will then show you how to produce and consume messages to and from Pulsar topics. As well as using some of the command line and REST interfaces to monitor, manage and do CRUD on things like tenants, namespaces and topics. We will discuss Functions, Sinks, Sources, Pulsar SQL, Flink SQL and Spark SQL interfaces. We also discuss why you may want to add protocols such as MoP (MQTT), AoP (AMQP/RabbitMQ) or KoP (Kafka) to your cluster. We will also look at WebSockets as a producer and consumer. I will demonstrate a simple web page that sends and receives Pulsar messages with basic JavaScript. After this session you will be able to build simple real-time streaming and messaging applications with your chosen language or tool of your choice.
apache pulsar
DBCC 2021 - FLiP Stack for Cloud Data Lakes
DBCC 2021 - FLiP Stack for Cloud Data Lakes
With Apache Pulsar, Apache NiFi, Apache Flink. The FLiP(N) Stack for Event processing and IoT. With StreamNative Cloud.
DBCC International – Friday 15.10.2021
Powered by Apache Pulsar, StreamNative provides a cloud-native, real-time messaging and streaming platform to support multi-cloud and hybrid cloud strategies.
ApacheCon2022_Deep Dive into Building Streaming Applications with Apache Pulsar
ApacheCon2022_Deep Dive into Building Streaming Applications with Apache Pulsar
In this session I will get you started with real-time cloud native streaming programming with Java, Golang, Python and Apache NiFi. If there’s a preferred language that the attendees pick, we will focus only on that one. I will start off with an introduction to Apache Pulsar and setting up your first easy standalone cluster in docker. We will then go into terms and architecture so you have an idea of what is going on with your events. I will then show you how to produce and consume messages to and from Pulsar topics. As well as using some of the command line and REST interfaces to monitor, manage and do CRUD on things like tenants, namespaces and topics. We will discuss Functions, Sinks, Sources, Pulsar SQL, Flink SQL and Spark SQL interfaces. We also discuss why you may want to add protocols such as MoP (MQTT), AoP (AMQP/RabbitMQ) or KoP (Kafka) to your cluster. We will also look at WebSockets as a producer and consumer. I will demonstrate a simple web page that sends and receives Pulsar messages with basic JavaScript. After this session you will be able to build simple real-time streaming and messaging applications with your chosen language or tool of your choice.
apache pulsar
tim spann developer advocate
streamnative
datainmotion.dev
[AI Dev World 2022] Build ML Enhanced Event Streaming
[AI Dev World 2022] Build ML Enhanced Event Streaming
3:00 PM - 3:25 PM PDT
[#VIRTUAL] OPEN TALK (AI): BUILD ML ENHANCED EVENT STREAMING APPLICATIONS WITH JAVA MICROSERVICES
VIRTUAL ONLY API WORLD & AI DEVWORLD STAGE
VIRTUAL ONLY VIRTUAL APPLIED MACHINE LEARNING
Timothy Spann
Timothy Spann
StreamNative, Developer Advocate
In this talk we will walk through how to build event streaming applications as functions running in with cloud native messaging via Apache Pulsar that run on near infinite scale in any cloud, docker or K8. We will show you have to deploy ML functions to transform real-time data for IoT, Streaming Analytics and many other use cases. After this talk you will be able to build Java microservices with ease and deploy them anywhere utilizing the open source unified streaming and messaging platform, Apache Pulsar. Finally, we will show you have to add dashboards with Web Sockets, no code data sinks, integrate with Apache NiFi data pipelines, SQL Reports with Apache Spark and finally continuous ETL with Apache Flink. I have built many of these applications for many organizations as part of the FLiPN Stack. Let's build next generation applications today regardless if your data is REST APIs, Sensors, Logs, NoSQL Sources, Events or Database tables.
https://aidevworld.com/conference/conference-tracks/applied-machine-learning/
https://github.com/tspannhw/pulsar-transit-function
https://github.com/tspannhw/FLiPStackWeekly/blob/main/README.md
Data science online camp using the flipn stack for edge ai (flink, nifi, pu...
Data science online camp using the flipn stack for edge ai (flink, nifi, pulsar)
Dec 3, 2021
Apache NiFi
Apache Flink
Apache Pulsar
Edge AI
Cloud Native Made Easy
StreamNative
Scenic City Summit (2021): Real-Time Streaming in any and all clouds, hybrid...
Scenic city summit real-time streaming in any and all clouds, hybrid and beyond
24-September-2021. Scenic City Summit. Virtual. Real-Time Streaming in Any and All Clouds, Hybrid and Beyond
Apache Pulsar, Apache NiFi, Apache Flink
StreamNative
Tim Spann
https://sceniccitysummit.com/
Using the FLiPN Stack for Edge AI (Flink, NiFi, Pulsar)
Using the FLiPN Stack for Edge AI (Flink, NiFi, Pulsar)
https://github.com/tspannhw/FLiP-Pi-DeltaLake-Thermal/
Tim Spann
Streamnative
https://github.com/tspannhw/pulsar-pychat-function
https://events.dataidols.com/talks/using-the-flipn-stack-for-edge-ai-flink-nifi-pulsar/
Hosted by Karen Jean-Francois.
Introducing the FLiPN stack which combines Apache Flink, Apache NiFi, Apache Pulsar and other Apache tools to build fast applications for IoT, AI, rapid ingest.
FLiPN provides a quick set of tools to build applications at any scale for any streaming and IoT use cases.
Tools Apache Flink, Apache Pulsar, Apache NiFi, MiNiFi, Apache MXNet, DJL.AI
References https://www.datainmotion.dev/2019/08/rapid-iot-development-with-cloudera.html https://www.datainmotion.dev/2019/09/powering-edge-ai-for-sensor-reading.html https://www.datainmotion.dev/2019/05/dataworks-summit-dc-2019-report.html https://www.datainmotion.dev/2019/03/using-raspberry-pi-3b-with-apache-nifi.html
Data Idols - Summer School - Data Science
Hail hydrate! from stream to lake using open source
(VIRTUAL) Hail Hydrate! From Stream to Lake Using Open Source - Timothy J Spann, StreamNative
https://osselc21.sched.com/event/lAPi?iframe=no
A cloud data lake that is empty is not useful to anyone. How can you quickly, scalably and reliably fill your cloud data lake with diverse sources of data you already have and new ones you never imagined you needed. Utilizing open source tools from Apache, the FLiP stack enables any data engineer, programmer or analyst to build reusable modules with low or no code. FLiP utilizes Apache NiFi, Apache Pulsar, Apache Flink and MiNiFi agents to load CDC, Logs, REST, XML, Images, PDFs, Documents, Text, semistructured data, unstructured data, structured data and a hundred data sources you could never dream of streaming before. I will teach you how to fish in the deep end of the lake and return a data engineering hero. Let's hope everyone is ready to go from 0 to Petabyte hero.
https://osselc21.sched.com/event/lAPi/virtual-hail-hydrate-from-stream-to-lake-using-open-source-timothy-j-spann-streamnative
ApacheCon 2021 - Apache NiFi Deep Dive 300
21-September-2021 - ApacheCon - Tuesday 17:10 UTC Apache NIFi Deep Dive 300
* https://github.com/tspannhw/EverythingApacheNiFi
* https://github.com/tspannhw/FLiP-ApacheCon2021
* https://www.datainmotion.dev/2020/06/no-more-spaghetti-flows.html
* https://github.com/tspannhw/FLiP-IoT
* https://github.com/tspannhw/FLiP-Energy
* https://github.com/tspannhw/FLiP-SOLR
* https://github.com/tspannhw/FLiP-EdgeAI
* https://github.com/tspannhw/FLiP-CloudQueries
* https://github.com/tspannhw/FLiP-Jetson
* https://www.linkedin.com/pulse/2021-schedule-tim-spann/
Tuesday 17:10 UTC
Apache NIFi Deep Dive 300
Timothy Spann
For Data Engineers who have flows already in production, I will dive deep into best practices, advanced use cases, performance optimizations, tips, tricks, edge cases, and interesting examples. This is a master class for those looking to learn quickly things I have picked up after years in the field with Apache NiFi in production.
This will be interactive and I encourage questions and discussions.
You will take away examples and tips in slides, github, and articles.
This talk will cover:
Load Balancing
Parameters and Parameter Contexts
Stateless vs Stateful NiFi
Reporting Tasks
NiFi CLI
NiFi REST Interface
DevOps
Advanced Record Processing
Schemas
RetryFlowFile
Lookup Services
RecordPath
Expression Language
Advanced Error Handling Techniques
Tim Spann is a Developer Advocate @ StreamNative where he works with Apache NiFi, Apache Pulsar, Apache Flink, Apache MXNet, TensorFlow, Apache Spark, big data, the IoT, machine learning, and deep learning. Tim has over a decade of experience with the IoT, big data, distributed computing, streaming technologies, and Java programming. Previously, he was a Principal Field Engineer at Cloudera, a senior solutions architect at AirisData and a senior field engineer at Pivotal. He blogs for DZone, where he is the Big Data Zone leader, and runs a popular meetup in Princeton on big data, the IoT, deep learning, streaming, NiFi, the blockchain, and Spark. Tim is a frequent speaker at conferences such as IoT Fusion, Strata, ApacheCon, Data Works Summit Berlin, DataWorks Summit Sydney, and Oracle Code NYC. He holds a BS and MS in computer science.
Big mountain data and dev conference apache pulsar with mqtt for edge compu...
Big mountain data and dev conference apache pulsar with mqtt for edge computing
Using FLiP with InfluxDB for EdgeAI IoT at Scale 2022
Using FLiP with InfluxDB for EdgeAI IoT at Scale 2022
https://adtmag.com/webcasts/2021/12/influxdata-february-10.aspx?tc=page0
Using FLiP with InfluxDB for EdgeAI IoT at Scale
Date: Thursday, February 10th at 11am PT / 2pm ET
Join this webcast as Timothy from StreamNative takes you on a hands-on deep-dive using Pulsar, Apache NiFi + Edge Flow Manager + MiniFi Agents with Apache MXNet, OpenVino, TensorFlow Lite, and other Deep Learning Libraries on the actual edge devices including Raspberry Pi with Movidius 2, Google Coral TPU and NVidia Jetson Nano.
The team runs deep learning models on the edge devices, sends images, and captures real-time GPS and sensor data. Their low-coding IoT applications provide easy edge routing, transformation, data acquisition and alerting before they decide what data to stream in real-time to their data space. These edge applications classify images and sensor readings in real-time at the edge and then send Deep Learning results to Flink SQL and Apache NiFi for transformation, parsing, enrichment, querying, filtering and merging data to InfluxDB.
In this session you will learn how to:
Build an end-to-end streaming edge app
Pull messages from Pulsar topics and persists the messages to InfluxDB
Build a data stream for IoT with NiFi and InfluxDB
Use Apache Flink + Apache Pulsar
Timothy Spann, Developer Advocate, StreamNative
Tim Spann is a Developer Advocate at StreamNative where he works with Apache NiFi, MiniFi, Kafka, Apache Flink, Apache MXNet, TensorFlow, Apache Spark, big data, the IoT, machine learning, and deep learning. Tim has over a decade of experience with the IoT, big data, distributed computing, streaming technologies, and Java programming. Previously, he was a senior solutions architect at AirisData and a senior field engineer at Pivotal. He blogs for DZone, where he is the Big Data Zone leader, and runs a popular meetup in Princeton on big data, the IoT, deep learning, streaming, NiFi, the blockchain, and Spark. Tim is a frequent speaker at conferences such as IoT Fusion, Strata, ApacheCon, Data Works Summit Berlin, DataWorks Summit Sydney, and Oracle Code NYC. He holds a BS and MS in computer science.
Using FLiP with influxdb for edgeai iot at scale 2022
https://adtmag.com/webcasts/2021/12/influxdata-february-10.aspx?tc=page0
FLiP Stack (Apache Flink, Apache Pulsar, Apache NiFi, Apache Spark) with Influx DB for Edge AI and IoT workloads at scale
Tim Spann
Developer Advocate
StreamNative
datainmotion.dev
OSSNA Building Modern Data Streaming Apps
OSSNA
Building Modern Data Streaming Apps
https://ossna2023.sched.com/event/1Jt05/virtual-building-modern-data-streaming-apps-with-open-source-timothy-spann-streamnative
Timothy Spann
Cloudera
Principal Developer Advocate
Data in Motion
In my session, I will show you some best practices I have discovered over the last seven years in building data streaming applications, including IoT, CDC, Logs, and more. In my modern approach, we utilize several open-source frameworks to maximize all the best features. We often start with Apache NiFi as the orchestrator of streams flowing into Apache Pulsar. From there, we build streaming ETL with Apache Spark and enhance events with Pulsar Functions for ML and enrichment. We make continuous queries against our topics with Flink SQL. We will stream data into various open-source data stores, including Apache Iceberg, Apache Pinot, and others. We use the best streaming tools for the current applications with the open source stack - FLiPN. https://www.flipn.app/ Updates: This will be in-person with live coding based on feedback from the crowd. This will also include new data stores, new sources, and data relevant to and from the Vancouver area. This will also include updates to the platforms and inclusion of Apache Iceberg, Apache Pinot and some other new tech.
https://github.com/tspannhw/SpeakerProfile Tim Spann is a Principal Developer Advocate for Cloudera. He works with Apache Kafka, Apache Flink, Flink SQL, Apache NiFi, MiniFi, Apache MXNet, TensorFlow, Apache Spark, Big Data, the IoT, machine learning, and deep learning. Tim has over a decade of experience with the IoT, big data, distributed computing, messaging, streaming technologies, and Java programming. Previously, he was a Principal DataFlow Field Engineer at Cloudera, a Senior Solutions Engineer at Hortonworks, a Senior Solutions Architect at AirisData, a Senior Field Engineer at Pivotal and a Team Leader at HPE. He blogs for DZone, where he is the Big Data Zone leader, and runs a popular meetup in Princeton on Big Data, Cloud, IoT, deep learning, streaming, NiFi, the blockchain, and Spark. Tim is a frequent speaker at conferences such as ApacheCon, DeveloperWeek, Pulsar Summit and many more. He holds a BS and MS in computer science.
Timothy J Spann
Cloudera
Principal Developer Advocate
Hightstown, NJ
Websitehttps://datainmotion.dev/
Data minutes #2 Apache Pulsar with MQTT for Edge Computing Lightning - 2022
21-Jan-2022. Friday 9:45 AM — 10 min. DataMinutes. Apache Pulsar with MQTT for Edge Computing. https://datagrillen.com/dataminutes/
Apache Pulsar with MQTT for Edge Computing Lightning - 2022
Tim Spann
Real time cloud native open source streaming of any data to apache solr
Real time cloud native open source streaming of any data to apache solr
Utilizing Apache Pulsar and Apache NiFi we can parse any document in real-time at scale. We receive a lot of documents via cloud storage, email, social channels and internal document stores. We want to make all the content and metadata to Apache Solr for categorization, full text search, optimization and combination with other datastores. We will not only stream documents, but all REST feeds, logs and IoT data. Once data is produced to Pulsar topics it can instantly be ingested to Solr through Pulsar Solr Sink.
Utilizing a number of open source tools, we have created a real-time scalable any document parsing data flow. We use Apache Tika for Document Processing with real-time language detection, natural language processing with Apache OpenNLP, Sentiment Analysis with Stanford CoreNLP, Spacy and TextBlob. We will walk everyone through creating an open source flow of documents utilizing Apache NiFi as our integration engine. We can convert PDF, Excel and Word to HTML and/or text. We can also extract the text to apply sentiment analysis and NLP categorization to generate additional metadata about our documents. We also will extract and parse images that if they contain text we can extract with TensorFlow and Tesseract.
Building an Event Streaming Architecture with Apache Pulsar
What is Apache Pulsar? How does it differ from other event streaming technologies available? StreamNative Developer Advocate Tim Spann will walk you through the features and architecture of this increasingly popular event streaming system, along with best practices for streaming and storing your data.
DevNexus: Apache Pulsar Development 101 with Java
DevNexus: Apache Pulsar Development 101 with Java
06-april-2023 georgia conference center atlanta, ga
https://devnexus.com/presentations/apache-pulsar-development-101-with-java
Abstract
In this session I will get you started with real-time cloud native streaming programming with Java. We will start off with a gentle introduction to Apache Pulsar and setting up your first easy standalone cluster. We will then l show you how to produce and consume message to Pulsar using several different Java libraries including native Java client, websockets, MQTT and even Kafka. After this session you will building real-time streaming and messaging applications with Java. We will also touch on Apache Spark and Apache Flink.
Timothy Spann
Tim Spann is a Developer Advocate @ Cloudera where he works with Apache Pulsar, Apache Flink, Apache NiFi, Apache MXNet, TensorFlow, Apache Spark, big data, the IoT, machine learning, and deep learning. Tim has over a decade of experience with the IoT, big data, distributed computing, streaming technologies, and Java programming. Previously, he was a Principal Field Engineer at Cloudera, a Senior Solutions Architect at AirisData and a senior field engineer at Pivotal. He blogs for DZone, where he is the Big Data Zone leader, and runs a popular meetup in Princeton on big data, the IoT, deep learning, streaming, NiFi, the blockchain, and Spark. Tim is a frequent speaker at conferences such as IoT Fusion, Strata, ApacheCon, Data Works Summit Berlin, DataWorks Summit Sydney, and Oracle Code NYC. He holds a BS and MS in computer science. https://www.datainmotion.dev/p/about-me.html https://dzone.com/users/297029/bunkertor.html https://conferences.oreilly.com/strata/strata-ny-2018/public/schedule/speaker/185963
MLconf 2022 NYC Event-Driven Machine Learning at Scale.pdf
MLconf 2022 NYC Event-Driven Machine Learning at Scale
https://mlconf.com/agenda/mlconf-2022-NYC/
https://mlconf.com/speakers/timothy-spann/
Bio
Tim Spann is a Developer Advocate for StreamNative. He works with StreamNative Cloud, Apache Pulsar, Apache Flink, Flink SQL, Apache NiFi, MiniFi, Apache MXNet, TensorFlow, Apache Spark, Big Data, the IoT, machine learning, and deep learning. Tim has over a decade of experience with the IoT, big data, distributed computing, messaging, streaming technologies, and Java programming. Previously, he was a Principal DataFlow Field Engineer at Cloudera, a Senior Solutions Engineer at Hortonworks, a Senior Solutions Architect at AirisData, a Senior Field Engineer at Pivotal and a Team Leader at HPE. He blogs for DZone, where he is the Big Data Zone leader, and runs a popular meetup in Princeton on Big Data, Cloud, IoT, deep learning, streaming, NiFi, the blockchain, and Spark. Tim is a frequent speaker at conferences such as ApacheCon, DeveloperWeek, Pulsar Summit and many more. He holds a BS and MS in computer science. He is currently working on a book about the FLiP Stack.
Upcoming Abstract Summary
Event-Driven Machine Learning at Scale
Utilizing the FLiP stack we can drive NLP and other machine learning classifications in the cloud, on-premise, hybrid and at the edge utilizing the open source Apache Pulsar project. We often utilize the full FLiPN stack which includes Apache Flink, Apache NiFi and Apache Pulsar.
Apache Pulsar is a unified messaging platform that can host and execute classifications as events arrive asynchronously to topics. We deploy our functionality in lightweight functions that can run as processes, threads or in K8. We often use the serverless FunctionMesh to run these. This allows us to run machine learning classes built in Go, Python and Java. We will show you utilizing Vader Sentiment, Pytorch, TensorFlow, DJL.AI, MXNet and other machine learning options with ease.
Using the flipn stack for edge ai (flink, nifi, pulsar)
Pulsar Summit Asia 2021/2022
Using The FLiPN Stack for EdgeAI (Flink, Pulsar, NiFi)
Tim Spann
Similar to Citizen Streaming Engineer - A How To (20)
Devfest uk & ireland using apache nifi with apache pulsar for fast data on-r...
Devfest uk & ireland using apache nifi with apache pulsar for fast data on-r...
OSS EU: Deep Dive into Building Streaming Applications with Apache Pulsar
OSS EU: Deep Dive into Building Streaming Applications with Apache Pulsar
ApacheCon2022_Deep Dive into Building Streaming Applications with Apache Pulsar
ApacheCon2022_Deep Dive into Building Streaming Applications with Apache Pulsar
[AI Dev World 2022] Build ML Enhanced Event Streaming
[AI Dev World 2022] Build ML Enhanced Event Streaming
Data science online camp using the flipn stack for edge ai (flink, nifi, pu...
Data science online camp using the flipn stack for edge ai (flink, nifi, pu...
Scenic City Summit (2021): Real-Time Streaming in any and all clouds, hybrid...
Scenic City Summit (2021): Real-Time Streaming in any and all clouds, hybrid...
Using the FLiPN Stack for Edge AI (Flink, NiFi, Pulsar)
Using the FLiPN Stack for Edge AI (Flink, NiFi, Pulsar)
Hail hydrate! from stream to lake using open source
Hail hydrate! from stream to lake using open source
Big mountain data and dev conference apache pulsar with mqtt for edge compu...
Big mountain data and dev conference apache pulsar with mqtt for edge compu...
Using FLiP with InfluxDB for EdgeAI IoT at Scale 2022
Using FLiP with InfluxDB for EdgeAI IoT at Scale 2022
Using FLiP with influxdb for edgeai iot at scale 2022
Using FLiP with influxdb for edgeai iot at scale 2022
Data minutes #2 Apache Pulsar with MQTT for Edge Computing Lightning - 2022
Data minutes #2 Apache Pulsar with MQTT for Edge Computing Lightning - 2022
Real time cloud native open source streaming of any data to apache solr
Real time cloud native open source streaming of any data to apache solr
Building an Event Streaming Architecture with Apache Pulsar
Building an Event Streaming Architecture with Apache Pulsar
MLconf 2022 NYC Event-Driven Machine Learning at Scale.pdf
MLconf 2022 NYC Event-Driven Machine Learning at Scale.pdf
Using the flipn stack for edge ai (flink, nifi, pulsar)
Using the flipn stack for edge ai (flink, nifi, pulsar)
More from Timothy Spann
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Dat...
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Data and AI
Round table discussion of vector databases, unstructured data, ai, big data, real-time, robots and Milvus.
A lively discussion with NJ Gen AI Meetup Lead, Prasad and Procure.FYI's Co-Found
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Dat...
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Data and AI
Discussion on Vector Databases, Unstructured Data and AI
https://www.meetup.com/unstructured-data-meetup-new-york/
This meetup is for people working in unstructured data. Speakers will come present about related topics such as vector databases, LLMs, and managing data at scale. The intended audience of this group includes roles like machine learning engineers, data scientists, data engineers, software engineers, and PMs.This meetup was formerly Milvus Meetup, and is sponsored by Zilliz maintainers of Milvus.
DATA SUMMIT 24 Building Real-Time Pipelines With FLaNK
Building Real-Time Pipelines With FLaNK
Timothy Spann, Principal Developer Advocate, Streaming - Cloudera Future of Data meetup, startup grind, AI Camp
The combination of Apache Flink, Apache NiFi, and Apache Kafka for building real-time data processing pipelines is extremely powerful, as demonstrated by this case study using the FLaNK-MTA project. The project leverages these technologies to process and analyze real-time data from the New York City Metropolitan Transportation Authority (MTA). FLaNK-MTA demonstrates how to efficiently collect, transform, and analyze high-volume data streams, enabling timely insights and decision-making.
Apache NiFi
Apache Kafka
Apache Flink
Apache Iceberg
LLM
Generative AI
Slack
Postgresql
Generative AI on Enterprise Cloud with NiFi and Milvus
Gen AI on Enterprise Cloud
Apache NiFi
Milvus
Apache Kafka
Apache Flink
Cloudera Machine Learning
Cloudera DataFlow
https://medium.com/@tspann/building-a-milvus-connector-for-nifi-34372cb3c7fa
https://www.meetup.com/futureofdata-princeton/events/300737266/
https://lu.ma/q7pcfyjn?source=post_page-----34372cb3c7fa--------------------------------&tk=TTyakY
If you're interested in working with Generative AI on the cloud, this virtual workshop is for you.
Tim Spann from Cloudera and Yujian Tang from Zilliz will cover how you can implement your own GenAI workflows on the cloud at enterprise scale.
9:00 - 9:05: Intro
9:05 - 9:15: What is Milvus
9:15 - 9:25: Cloudera Development Platform
9:25 - 10:00: Demo
Location
https://www.youtube.com/watch?v=IfWIzKsoHnA
https://github.com/tspannhw/SpeakerProfile
https://www.linkedin.com/in/yujiantang/
April 2024 - NLIT Cloudera Real-Time LLM Streaming 2024
https://www.fbcinc.com/e/nlit/agenda.aspx
Cloudera booth
data in motion
tim spann
seattle
April 2024
Real-Time AI Streaming - AI Max Princeton
AI Max Conference Princeton
https://www.startupgrind.com/events/details/startup-grind-princeton-presents-startup-grind-hosts-ai-max-summit/
Conf42-LLM_Adding Generative AI to Real-Time Streaming Pipelines
Conf42-LLM_Adding Generative AI to Real-Time Streaming Pipelines
https://www.youtube.com/watch?v=Yeua8NlzQ3Y
https://www.conf42.com/Large_Language_Models_LLMs_2024_Tim_Spann_generative_ai_streaming
Adding Generative AI to Real-Time Streaming Pipelines
Abstract
Let’s build streaming pipelines that convert streaming events into prompts, call LLMs, and process the results.
Summary
Tim Spann: My talk is adding generative AI to real time streaming pipelines. I'm going to discuss a couple of different open source technologies. We'll touch on Kafka, Nifi, Flink, Python, Iceberg. All the slides, all the code and GitHub are out there.
Llm, if you didn't know, is rapidly evolving. There's a lot of different ways to interact with models. That enrichment, transformation, processing really needs tools. The amount of models and projects and software that are available is massive.
Nifi supports hundreds of different inputs and can convert them on the fly. Great way to distribute your data quickly to whoever needs it without duplication, without tight coupling. Fun to find new things to integrate into.
So what we can do is, well, I want to get a meetup chat going. I have a processor here that just listens for events as they come from slack. And then I'm going to clean it up, add a couple fields and push that out to slack. Every model is a little bit of different tweaking.
Nifi acts as a whole website. And as you see here, it can be get, post, put, whatever you want. We send that response back to flink and it shows up here. Thank you for attending this talk. I'm going to be speaking at some other events very shortly.
Transcript
This transcript was autogenerated. To make changes, submit a PR.
Hi, Tim Spann here. My talk is adding generative AI to real time streaming pipelines, and we're here for the large language model conference at Comp 42, which is always a nice one, great place to be. I'm going to discuss a couple of different open source technologies that work together to enable you to build real time pipelines using large language models. So we'll touch on Kafka, Nifi, Flink, Python, Iceberg, and I'll show you a little bit of each one in the demos. I've been working with data machine learning, streaming IoT, some other things for a number of years, and you could contact me at any of these places, whether Twitter or whatever it's called, some different blogs, or in person at my meetups and at different conferences around the world. I do a weekly newsletter, cover streaming ML, a lot of LLM, open source, Python, Java, all kinds of fun stuff, as I mentioned, do a bunch of different meetups. They are not just in the east coast of the US, they are available virtually live, and I also put them on YouTube, and if you need them somewhere else, let me know. We publish all the slides, all the code and GitHub. Everything you need is out there. Let's get into the talk. Llm, if you didn't know, is rapidly evolving. While you're typing down the things that you use, it
2024 XTREMEJ_ Building Real-time Pipelines with FLaNK_ A Case Study with Tra...
2024 XTREMEJ_ Building Real-time Pipelines with FLaNK_ A Case Study with Transit Data
https://xtremej.dev/2023/schedule/
Building Real-time Pipelines with FLaNK: A Case Study with Transit Data
Overview of the problem, the application (code walkthru and running), overview of FLaNK, introduction to NiFi, introduction to Kafka, and introduction to Flink.
28March2024-Codeless-Generative-AI-Pipelines
28March2024-Codeless-Generative-AI-Pipelines
https://www.meetup.com/futureofdata-princeton/events/299440871/
https://www.meetup.com/real-time-analytics-meetup-ny/events/299290822/
******Note*****
The event is seat-limited, therefore please complete your registration here. Only people completing the form will be able to attend.
-----------------------
We're excited to invite you to join us in-person, for a Real-Time Analytics exploration!
Join us for an evening of insights, networking as we delve into the OSS technologies shaping the field!
Agenda:
05:30-06:00: Pizza and friends
06:00- 06:40: Codeless GenAI Pipelines with Flink, Kafka, NiFi
06:40- 07:20 Real-Time Analytics in the Corporate World: How Apache Pinot® Powers Industry Leaders
07:20-07:30 QNA
Codeless GenAI Pipelines with Flink, Kafka, NiFi | Tim Spann, Cloudera
Explore the power of real-time streaming with GenAI using Apache NiFi. Learn how NiFi simplifies data engineering workflows, allowing you to focus on creativity over technical complexities. I'll guide you through practical examples, showcasing NiFi's automation impact from ingestion to delivery. Whether you're a seasoned data engineer or new to GenAI, this talk offers valuable insights into optimizing workflows. Join us to unlock the potential of real-time streaming and witness how NiFi makes data engineering a breeze for GenAI applications!
Real-Time Analytics in the Corporate World: How Apache Pinot® Powers Industry Leaders | Viktor Gamov, StarTree
Explore how industry leaders like LinkedIn, Uber Eats, and Stripe are mastering real-time data with Viktor as your guide. Discover how Apache Pinot transforms data into actionable insights instantly. Viktor will showcase Pinot's features, including the Star-Tree Index, and explain why it's a game-changer in data strategy. This session is for everyone, from data geeks to business gurus, eager to uncover the future of tech. Join us and be wowed by the power of real-time analytics with Apache Pinot!
-------
Tim Spann is a Principal Developer Advocate in Data In Motion for Cloudera.
He works with Apache NiFi, Apache Kafka, Apache Pulsar, Apache Flink, Flink SQL, Apache Pinot, Trino, Apache Iceberg, DeltaLake, Apache Spark, Big Data, IoT, Cloud, AI/DL, machine learning, and deep learning. Tim has over ten years of experience with the IoT, big data, distributed computing, messaging, streaming technologies, and Java programming. Previously, he was a Developer Advocate at StreamNative, Principal DataFlow Field Engineer at Cloudera, a Senior Solutions Engineer at Hortonworks, a Senior Solutions Architect at AirisData, a Senior Field Engineer at Pivotal and a Team Leader at HPE. He blogs for DZone, where he is the Big Data Zone leader, and runs a popular meetup in Princeton & NYC on Big Data, Cloud, IoT, deep learning, streaming, NiFi, the blockchain, and Spark. Tim is a frequent speaker at conferences such as ApacheCon, DeveloperWeek, Pulsar Summit and many more.
TCFPro24 Building Real-Time Generative AI Pipelines
https://princetonacm.acm.org/tcfpro/
18th Annual IEEE IT Professional Conference (ITPC)
Armstrong Hall at The College of New Jersey
Friday, March 15th, 2024 | 10:00 AM to 5:00 PM
IT Professional Conference at Trenton Computer Festival
IEEE Information Technology Professional Conference on Friday, March 15th, 2024
TCFPro24 Building Real-Time Generative AI Pipelines
Building Real-Time Generative AI Pipelines
In this talk, Tim will delve into the exciting realm of building real-time generative AI pipelines with streaming capabilities. The discussion will revolve around the integration of cutting-edge technologies to create dynamic and responsive systems that harness the power of generative algorithms.
From leveraging streaming data sources to implementing advanced machine learning models, the presentation will explore the key components necessary for constructing a robust real-time generative AI pipeline. Practical insights, use cases, and best practices will be shared, offering a comprehensive guide for developers and data scientists aspiring to design and implement dynamic AI systems in a streaming environment.
Tim will show a live demo showing we can use Apache NiFi to provide a live chat between a person in Slack and several LLM models all orchestrated with Apache NiFi, Apache Kafka and Python. We will use RAG against Chroma and Pinecone vector data stores, Hugging Face and WatsonX.AI LLM, and add additional context with NiFi lookups of stocks, weather and other data streams in real-time.
Timothy Spann
Tim Spann is a Principal Developer Advocate in Data In Motion for Cloudera. He works with Apache NiFi, Apache Pulsar, Apache Kafka, Apache Flink, Flink SQL, Apache Pinot, Trino, Apache Iceberg, DeltaLake, Apache Spark, Big Data, IoT, Cloud, AI/DL, machine learning, and deep learning. Tim has over ten years of experience with the IoT, big data, distributed computing, messaging, streaming technologies, and Java programming.
Previously, he was a Developer Advocate at StreamNative, Principal DataFlow Field Engineer at Cloudera, a Senior Solutions Engineer at Hortonworks, a Senior Solutions Architect at AirisData, a Senior Field Engineer at Pivotal and a Team Leader at HPE. He blogs for DZone, where he is the Big Data Zone leader, and runs a popular meetup in Princeton & NYC on Big Data, Cloud, IoT, deep learning, streaming, NiFi, the blockchain, and Spark.
Tim is a frequent speaker at conferences such as ApacheCon, DeveloperWeek, Pulsar Summit and many more. He holds a BS and MS in computer science.
2024 Build Generative AI for Non-Profits
2024_BuildGenerativeAIforNon-Profits
https://www.meetup.com/futureofdata-princeton/events/299515503/
https://www.meetup.com/applied-generative-artificial-intelligence-applications/events/299486639/
LLM
2024 February 28 - NYC - Meetup Unlocking Financial Data with Real-Time Pipel...
2024 February 28 - NYC - Meetup Unlocking Financial Data with Real-Time Pipelines
https://www.meetup.com/futureofdata-newyork/events/298660453/
Unlocking Financial Data with Real-Time Pipelines
(Flink Analytics on Stocks with SQL )
By Timothy Spann
Financial institutions thrive on accurate and timely data to drive critical decision-making processes, risk assessments, and regulatory compliance. However, managing and processing vast amounts of financial data in real-time can be a daunting task. To overcome this challenge, modern data engineering solutions have emerged, combining powerful technologies like Apache Flink, Apache NiFi, Apache Kafka, and Iceberg to create efficient and reliable real-time data pipelines. In this talk, we will explore how this technology stack can unlock the full potential of financial data, enabling organizations to make data-driven decisions swiftly and with confidence.
Introduction: Financial institutions operate in a fast-paced environment where real-time access to accurate and reliable data is crucial. Traditional batch processing falls short when it comes to handling rapidly changing financial markets and responding to customer demands promptly. In this talk, we will delve into the power of real-time data pipelines, utilizing the strengths of Apache Flink, Apache NiFi, Apache Kafka, and Iceberg, to unlock the potential of financial data. I will be utilizing NiFi 2.0 with Python and Vector Databases.
Timothy Spann
Principal Developer Advocate, Cloudera
Tim Spann is a Principal Developer Advocate in Data In Motion for Cloudera. He works with Apache NiFi, Apache Kafka, Apache Pulsar, Apache Flink, Flink SQL, Apache Pinot, Trino, Apache Iceberg, DeltaLake, Apache Spark, Big Data, IoT, Cloud, AI/DL, machine learning, and deep learning. Tim has over ten years of experience with the IoT, big data, distributed computing, messaging, streaming technologies, and Java programming. Previously, he was a Developer Advocate at StreamNative, Principal DataFlow Field Engineer at Cloudera, a Senior Solutions Engineer at Hortonworks, a Senior Solutions Architect at AirisData, a Senior Field Engineer at Pivotal and a Team Leader at HPE. He blogs for DZone, where he is the Big Data Zone leader, and runs a popular meetup in Princeton & NYC on Big Data, Cloud, IoT, deep learning, streaming, NiFi, the blockchain, and Spark. Tim is a frequent speaker at conferences such as ApacheCon, DeveloperWeek, Pulsar Summit and many more. He holds a BS and MS in computer science.
https://twitter.com/PaaSDev
https://www.linkedin.com/in/timothyspann/
https://medium.com/@tspann
https://github.com/tspannhw/FLiPStackWeekly/
Conf42-Python-Building Apache NiFi 2.0 Python Processors
Conf42-Python-Building Apache NiFi 2.0 Python Processors
https://www.conf42.com/Python_2024_Tim_Spann_apache_nifi_2_processors
Building Apache NiFi 2.0 Python Processors
Abstract
Let’s enhance real-time streaming pipelines with smart Python code. Adding code for vector databases and LLM.
Summary
Tim Spann: I'm going to be talking today, be building Apache 9520 Python processors. One of the main purposes of supporting Python in the streaming tool Apache Nifi is to interface with new machine learning and AI and Gen AI. He says Python is a real game changer for Cloudera.
You're just going to add some metadata around it. It's a great way to pass a file along without changing it too substantially. We really need you to have Python 310 and again JDK 21 on your machine. You got to be smart about how you use these models.
There are a ton of python processors available. You can use them in multiple ways. We're still in the early world of Python processors, so now's the time to start putting yours out there. Love to see a lot of people write their own.
When we are parsing documents here, again, this is the Python one I'm picking PDF. Lots of different things you could do. If you're interested on writing your own python code for Apache Nifi, definitely reach out and thank.
Conf42Python -Using Apache NiFi, Apache Kafka, RisingWave, and Apache Iceberg...
Conf42Python -Using Apache NiFi, Apache Kafka, RisingWave, and Apache Iceberg with Stock Data and LLM
Abstract
In this talk, we’ll discuss how to use Apache NiFi, Apache Kafka, RisingWave, and Apache Iceberg to process and analyze stock data. We demonstrated the ingestion, processing, and analysis of stock data. Additionally, we illustrated how to use an LLM to generate predictions from the analyzed data.
Karin Wolok
Developer Relations, Dev Marketing, and Community Programming @ Project Elevate
Karin Wolok's LinkedIn account Karin Wolok's twitter account
Tim Spann
Principal Developer Advocate @ Cloudera
Tim Spann's LinkedIn account Tim Spann's twitter account
https://www.conf42.com/Python_2024_Karin_Wolok_Tim_Spann_nifi__kafka_risingwave_iceberg_llm
2024 Feb AI Meetup NYC GenAI_LLMs_ML_Data Codeless Generative AI Pipelines
2024 Feb AI Meetup NYC GenAI_LLMs_ML_Data Codeless Generative AI Pipelines
https://www.aicamp.ai/event/eventdetails/W2024022214
apache nifi
llm
generative ai
gen ai
ml
dl
machine learning
apache kafka
apache flink
postgresql
python
AI Meetup (NYC): GenAI, LLMs, ML and Data
Feb 22, 05:30 PM EST
Welcome to the monthly in-person AI meetup in New York City, in collaboration with Microsoft. Join us for deep dive tech talks on AI, GenAI, LLMs and machine learning, food/drink, networking with speakers and fellow developers
Agenda:
* 5:30pm~6:00pm: Checkin, Food/drink and networking
* 6:00pm~6:10pm: Welcome/community update
* 6:10pm~8:30pm: Tech talks
* 8:30pm: Q&A, Open discussion
Tech Talk: Searching and Reasoning Over Multimedia Data with Vector Databases and LMMs
Speaker: Zain Hasan (Weaviate LinkedIn)
Abstract: In this talk, Zain Hasan will discuss how we can use open-source multimodal embedding models in conjunction with large generative multimodal models that can that can see, hear, read, and feel data(!), to perform cross-modal search(searching audio with images, videos with text etc.) and multimodal retrieval augmented generation (MM-RAG) at the billion-object scale with the help of open source vector databases. I will also demonstrate, with live code demos, how being able to perform this cross-modal retrieval in real-time can enables users to use LLMs that can reason over their enterprise multimodal data. This talk will revolve around how we can scale the usage of multimodal embedding and generative models in production.
Tech Talk: Codeless Generative AI Pipelines
Speaker: Timothy Spann (Cloudera LinkedIn)
Abstract: Join us for an insightful talk on leveraging the power of real-time streaming tools, specifically Apache NiFi, to revolutionize GenAI data engineering. In this session, we’ll explore how the integration of Apache NiFi can automate the entire process of prompt building, making it a seamless and efficient task.
Speakers/Topics:
Stay tuned as we are updating speakers and schedules. If you have a keen interest in speaking to our community, we invite you to submit topics for consideration: Submit Topics
Sponsors:
We are actively seeking sponsors to support our community. Whether it is by offering venue spaces, providing food/drink, or cash sponsorship. Sponsors will have the chance to speak at the meetups, receive prominent recognition, and gain exposure to our extensive membership base of 20,000+ local or 300K+ developers worldwide.
Venue:
Microsoft NYC - Times Square, 11 Times Square, New York, NY 10036
Room Name: Central Park West 6501
Community on Slack/Discord
- Event chat: chat and connect with speakers and attendees
- Sharing blogs, events, job openings, projects collaborations
Join Slack (search and join the #newyork channel) | Join Discord
DBA Fundamentals Group: Continuous SQL with Kafka and Flink
DBA Fundamentals Group: Continuous SQL with Kafka and Flink
20-Feb-2024
In this talk, I will walk through how someone can set up and run continuous SQL queries against Kafka topics utilizing Apache Flink. We will walk through creating Kafka topics, schemas, and publishing data.
We will then cover consuming Kafka data, joining Kafka topics, and inserting new events into Kafka topics as they arrive. This basic overview will show hands-on techniques, tips, and examples of how to do this.
Tim Spann
Tim Spann is the Principal Developer Advocate for Data in Motion @ Cloudera where he works with Apache Kafka, Apache Flink, Apache NiFi, Apache Iceberg, TensorFlow, Apache Spark, big data, the IoT, machine learning, and deep learning. Tim has over a decade of experience with the IoT, big data, distributed computing, streaming technologies, and Java programming. Previously, he was a Developer Advocate at StreamNative, Principal Field Engineer at Cloudera, a Senior Solutions Architect at AirisData and a senior field engineer at Pivotal. He blogs for DZone, where he is the Big Data Zone leader, and runs a popular meetup in Princeton on big data, the IoT, deep learning, streaming, NiFi, the blockchain, and Spark. Tim is a frequent speaker at conferences such as IoT Fusion, Strata, ApacheCon, Data Works Summit Berlin, DataWorks Summit Sydney, and Oracle Code NYC. He holds a BS and MS in computer science.
NY Open Source Data Meetup Feb 8 2024 Building Real-time Pipelines with FLaNK...
NY Open Source Data Meetup Feb 8 2024 Building Real-time Pipelines with FLaNK_ A Case Study with Transit Data
OSACon 2023_ Unlocking Financial Data with Real-Time Pipelines
OSACon 2023_ Unlocking Financial Data with Real-Time Pipelines
Unlocking Financial Data with Real-Time Pipelines
Financial institutions thrive on accurate and timely data to drive critical decision-making processes, risk assessments, and regulatory compliance. However, managing and processing vast amounts of financial data in real-time can be a daunting task. To overcome this challenge, modern data engineering solutions have emerged, combining powerful technologies like Apache Flink, Apache NiFi, Apache Kafka, and Iceberg to create efficient and reliable real-time data pipelines. In this talk, we will explore how this technology stack can unlock the full potential of financial data, enabling organizations to make data-driven decisions swiftly and with confidence.
Introduction: Financial institutions operate in a fast-paced environment where real-time access to accurate and reliable data is crucial. Traditional batch processing falls short when it comes to handling rapidly changing financial markets and responding to customer demands promptly. In this talk, we will delve into the power of real-time data pipelines, utilizing the strengths of Apache Flink, Apache NiFi, Apache Kafka, and Iceberg, to unlock the potential of financial data.
Key Points to be Covered:
Introduction to Real-Time Data Pipelines: a. The limitations of traditional batch processing in the financial domain. b. Understanding the need for real-time data processing.
Apache Flink: Powering Real-Time Stream Processing: a. Overview of Apache Flink and its role in real-time stream processing. b. Use cases for Apache Flink in the financial industry. c. How Flink enables fast, scalable, and fault-tolerant processing of streaming financial data.
Apache Kafka: Building Resilient Event Streaming Platforms: a. Introduction to Apache Kafka and its role as a distributed streaming platform. b. Kafka's capabilities in handling high-throughput, fault-tolerant, and real-time data streaming. c. Integration of Kafka with financial data sources and consumers.
Apache NiFi: Data Ingestion and Flow Management: a. Overview of Apache NiFi and its role in data ingestion and flow management. b. Data integration and transformation capabilities of NiFi for financial data. c. Utilizing NiFi to collect and process financial data from diverse sources.
Iceberg: Efficient Data Lake Management: a. Understanding Iceberg and its role in managing large-scale data lakes. b. Iceberg's schema evolution and table-level metadata capabilities. c. How Iceberg simplifies data lake management in financial institutions.
Real-World Use Cases: a. Real-time fraud detection using Flink, Kafka, and NiFi. b. Portfolio risk analysis with Iceberg and Flink. c. Streamlined regulatory reporting leveraging all four technologies.
Best Practices and Considerations: a. Architectural considerations when building real-time financial data pipelines. b. Ensuring data integrity, security, and compliance in real-time pipelines. c. Scalability an
Building Real-Time Travel Alerts
Building Real-time Travel Alerts
In this session, we will walk through how to build a complete streaming application to send alerts based on travel advisories from public data. We will also join in other data sources of relevance and push out alerts.
We will show you how to build this streaming application with Apache NiFi, Apache Kafka, and Apache Flink and show you when/why/how, and what to build to maximize performance, productivity, and ease of development.
Let's get streaming.
Apache Flink
Apache Kafka
Apache NiFi
FLaNK Stack
Tim Spann
Big Data Conference Europe 2023
JConWorld_ Continuous SQL with Kafka and Flink
JConWorld: Continuous SQL with Kafka and Flink
In this talk, I will walk through how someone can setup and run continous SQL queries against Kafka topics utilizing Apache Flink. We will walk through creating Kafka topics, schemas and publishing data.
We will then cover consuming Kafka data, joining Kafka topics and inserting new events into Kafka topics as they arrive. This basic over view will show hands-on techniques, tips and examples of how to do this.
Tim Spann is the Principal Developer Advocate for Data in Motion @ Cloudera where he works with Apache Kafka, Apache Flink, Apache NiFi, Apache Iceberg, TensorFlow, Apache Spark, big data, the IoT, machine learning, and deep learning. Tim has over a decade of experience with the IoT, big data, distributed computing, streaming technologies, and Java programming. Previously, he was a Developer Advocate at StreamNative, Principal Field Engineer at Cloudera, a Senior Solutions Architect at AirisData and a senior field engineer at Pivotal. He blogs for DZone, where he is the Big Data Zone leader, and runs a popular meetup in Princeton on big data, the IoT, deep learning, streaming, NiFi, the blockchain, and Spark. Tim is a frequent speaker at conferences such as IoT Fusion, Strata, ApacheCon, Data Works Summit Berlin, DataWorks Summit Sydney, and Oracle Code NYC. He holds a BS and MS in computer science. https://www.datainmotion.dev/p/about-me.html https://dzone.com/users/297029/bunkertor.html
https://www.youtube.com/channel/UCDIDMDfje6jAvNE8DGkJ3_w?view_as=subscriber
More from Timothy Spann (20)
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Dat...
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Dat...
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Dat...
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Dat...
DATA SUMMIT 24 Building Real-Time Pipelines With FLaNK
DATA SUMMIT 24 Building Real-Time Pipelines With FLaNK
Generative AI on Enterprise Cloud with NiFi and Milvus
Generative AI on Enterprise Cloud with NiFi and Milvus
April 2024 - NLIT Cloudera Real-Time LLM Streaming 2024
April 2024 - NLIT Cloudera Real-Time LLM Streaming 2024
Conf42-LLM_Adding Generative AI to Real-Time Streaming Pipelines
Conf42-LLM_Adding Generative AI to Real-Time Streaming Pipelines
2024 XTREMEJ_ Building Real-time Pipelines with FLaNK_ A Case Study with Tra...
2024 XTREMEJ_ Building Real-time Pipelines with FLaNK_ A Case Study with Tra...
TCFPro24 Building Real-Time Generative AI Pipelines
TCFPro24 Building Real-Time Generative AI Pipelines
2024 February 28 - NYC - Meetup Unlocking Financial Data with Real-Time Pipel...
2024 February 28 - NYC - Meetup Unlocking Financial Data with Real-Time Pipel...
Conf42-Python-Building Apache NiFi 2.0 Python Processors
Conf42-Python-Building Apache NiFi 2.0 Python Processors
Conf42Python -Using Apache NiFi, Apache Kafka, RisingWave, and Apache Iceberg...
Conf42Python -Using Apache NiFi, Apache Kafka, RisingWave, and Apache Iceberg...
2024 Feb AI Meetup NYC GenAI_LLMs_ML_Data Codeless Generative AI Pipelines
2024 Feb AI Meetup NYC GenAI_LLMs_ML_Data Codeless Generative AI Pipelines
DBA Fundamentals Group: Continuous SQL with Kafka and Flink
DBA Fundamentals Group: Continuous SQL with Kafka and Flink
NY Open Source Data Meetup Feb 8 2024 Building Real-time Pipelines with FLaNK...
NY Open Source Data Meetup Feb 8 2024 Building Real-time Pipelines with FLaNK...
OSACon 2023_ Unlocking Financial Data with Real-Time Pipelines
OSACon 2023_ Unlocking Financial Data with Real-Time Pipelines
Recently uploaded
Vitthal Shirke Java Microservices Resume.pdf
Software Engineering, Software Consulting, Tech Lead, Spring Boot, Spring Cloud, Spring Core, Spring JDBC, Spring Transaction, Spring MVC, OpenShift Cloud Platform, Kafka, REST, SOAP, LLD & HLD.
OpenMetadata Community Meeting - 5th June 2024
The OpenMetadata Community Meeting was held on June 5th, 2024. In this meeting, we discussed about the data quality capabilities that are integrated with the Incident Manager, providing a complete solution to handle your data observability needs. Watch the end-to-end demo of the data quality features.
* How to run your own data quality framework
* What is the performance impact of running data quality frameworks
* How to run the test cases in your own ETL pipelines
* How the Incident Manager is integrated
* Get notified with alerts when test cases fail
Watch the meeting recording here - https://www.youtube.com/watch?v=UbNOje0kf6E
BoxLang: Review our Visionary Licenses of 2024
Unleash Unlimited Potential with One-Time Purchase
BoxLang is more than just a language; it's a community. By choosing a Visionary License, you're not just investing in your success, you're actively contributing to the ongoing development and support of BoxLang.
Enterprise Resource Planning System in Telangana
Enterprise Resource Planning System includes various modules that reduce any business's workload. Additionally, it organizes the workflows, which drives towards enhancing productivity. Here are a detailed explanation of the ERP modules. Going through the points will help you understand how the software is changing the work dynamics.
To know more details here: https://blogs.nyggs.com/nyggs/enterprise-resource-planning-erp-system-modules/
Graspan: A Big Data System for Big Code Analysis
We built a disk-based parallel graph system, Graspan, that uses a novel edge-pair centric computation model to compute dynamic transitive closures on very large program graphs.
We implement context-sensitive pointer/alias and dataflow analyses on Graspan. An evaluation of these analyses on large codebases such as Linux shows that their Graspan implementations scale to millions of lines of code and are much simpler than their original implementations.
These analyses were used to augment the existing checkers; these augmented checkers found 132 new NULL pointer bugs and 1308 unnecessary NULL tests in Linux 4.4.0-rc5, PostgreSQL 8.3.9, and Apache httpd 2.2.18.
- Accepted in ASPLOS ‘17, Xi’an, China.
- Featured in the tutorial, Systemized Program Analyses: A Big Data Perspective on Static Analysis Scalability, ASPLOS ‘17.
- Invited for presentation at SoCal PLS ‘16.
- Invited for poster presentation at PLDI SRC ‘16.
Innovating Inference - Remote Triggering of Large Language Models on HPC Clus...
Large Language Models (LLMs) are currently the center of attention in the tech world, particularly for their potential to advance research. In this presentation, we'll explore a straightforward and effective method for quickly initiating inference runs on supercomputers using the vLLM tool with Globus Compute, specifically on the Polaris system at ALCF. We'll begin by briefly discussing the popularity and applications of LLMs in various fields. Following this, we will introduce the vLLM tool, and explain how it integrates with Globus Compute to efficiently manage LLM operations on Polaris. Attendees will learn the practical aspects of setting up and remotely triggering LLMs from local machines, focusing on ease of use and efficiency. This talk is ideal for researchers and practitioners looking to leverage the power of LLMs in their work, offering a clear guide to harnessing supercomputing resources for quick and effective LLM inference.
openEuler Case Study - The Journey to Supply Chain Security
openEuler Case Study - The Journey to Supply Chain Security
Nidhi Software Price. Fact , Costs, Tips
Understanding Nidhi Software Pricing: A Quick Guide 🌟
Choosing the right software is vital for Nidhi companies to streamline operations. Our latest presentation covers Nidhi software pricing, key factors, costs, and negotiation tips.
📊 What You’ll Learn:
Key factors influencing Nidhi software price
Understanding the true cost beyond the initial price
Tips for negotiating the best deal
Affordable and customizable pricing options with Vector Nidhi Software
🔗 Learn more at: www.vectornidhisoftware.com/software-for-nidhi-company/
#NidhiSoftwarePrice #NidhiSoftware #VectorNidhi
AI Genie Review: World’s First Open AI WordPress Website Creator
AI Genie Review: World’s First Open AI WordPress Website Creator
👉👉 Click Here To Get More Info 👇👇
https://sumonreview.com/ai-genie-review
AI Genie Review: Key Features
✅Creates Limitless Real-Time Unique Content, auto-publishing Posts, Pages & Images directly from Chat GPT & Open AI on WordPress in any Niche
✅First & Only Google Bard Approved Software That Publishes 100% Original, SEO Friendly Content using Open AI
✅Publish Automated Posts and Pages using AI Genie directly on Your website
✅50 DFY Websites Included Without Adding Any Images, Content Or Doing Anything Yourself
✅Integrated Chat GPT Bot gives Instant Answers on Your Website to Visitors
✅Just Enter the title, and your Content for Pages and Posts will be ready on your website
✅Automatically insert visually appealing images into posts based on keywords and titles.
✅Choose the temperature of the content and control its randomness.
✅Control the length of the content to be generated.
✅Never Worry About Paying Huge Money Monthly To Top Content Creation Platforms
✅100% Easy-to-Use, Newbie-Friendly Technology
✅30-Days Money-Back Guarantee
See My Other Reviews Article:
(1) TubeTrivia AI Review: https://sumonreview.com/tubetrivia-ai-review
(2) SocioWave Review: https://sumonreview.com/sociowave-review
(3) AI Partner & Profit Review: https://sumonreview.com/ai-partner-profit-review
(4) AI Ebook Suite Review: https://sumonreview.com/ai-ebook-suite-review
#AIGenieApp #AIGenieBonus #AIGenieBonuses #AIGenieDemo #AIGenieDownload #AIGenieLegit #AIGenieLiveDemo #AIGenieOTO #AIGeniePreview #AIGenieReview #AIGenieReviewandBonus #AIGenieScamorLegit #AIGenieSoftware #AIGenieUpgrades #AIGenieUpsells #HowDoesAlGenie #HowtoBuyAIGenie #HowtoMakeMoneywithAIGenie #MakeMoneyOnline #MakeMoneywithAIGenie
Utilocate provides Smarter, Better, Faster, Safer Locate Ticket Management
Utilocate offers a comprehensive solution for locate ticket management by automating and streamlining the entire process. By integrating with Geospatial Information Systems (GIS), it provides accurate mapping and visualization of utility locations, enhancing decision-making and reducing the risk of errors. The system's advanced data analytics tools help identify trends, predict potential issues, and optimize resource allocation, making the locate ticket management process smarter and more efficient. Additionally, automated ticket management ensures consistency and reduces human error, while real-time notifications keep all relevant personnel informed and ready to respond promptly.
The system's ability to streamline workflows and automate ticket routing significantly reduces the time taken to process each ticket, making the process faster and more efficient. Mobile access allows field technicians to update ticket information on the go, ensuring that the latest information is always available and accelerating the locate process. Overall, Utilocate not only enhances the efficiency and accuracy of locate ticket management but also improves safety by minimizing the risk of utility damage through precise and timely locates.
Globus Compute wth IRI Workflows - GlobusWorld 2024
As part of the DOE Integrated Research Infrastructure (IRI) program, NERSC at Lawrence Berkeley National Lab and ALCF at Argonne National Lab are working closely with General Atomics on accelerating the computing requirements of the DIII-D experiment. As part of the work the team is investigating ways to speedup the time to solution for many different parts of the DIII-D workflow including how they run jobs on HPC systems. One of these routes is looking at Globus Compute as a way to replace the current method for managing tasks and we describe a brief proof of concept showing how Globus Compute could help to schedule jobs and be a tool to connect compute at different facilities.
E-commerce Application Development Company.pdf
Your business can reach new heights with our assistance as we design solutions that are specifically appropriate for your goals and vision. Our eCommerce application solutions can digitally coordinate all retail operations processes to meet the demands of the marketplace while maintaining business continuity.
Empowering Growth with Best Software Development Company in Noida - Deuglo
Do you want Software for your Business? Visit Deuglo
Deuglo has top Software Developers in India. They are experts in software development and help design and create custom Software solutions.
Deuglo follows seven steps methods for delivering their services to their customers. They called it the Software development life cycle process (SDLC).
Requirement — Collecting the Requirements is the first Phase in the SSLC process.
Feasibility Study — after completing the requirement process they move to the design phase.
Design — in this phase, they start designing the software.
Coding — when designing is completed, the developers start coding for the software.
Testing — in this phase when the coding of the software is done the testing team will start testing.
Installation — after completion of testing, the application opens to the live server and launches!
Maintenance — after completing the software development, customers start using the software.
APIs for Browser Automation (MoT Meetup 2024)
APIs for Browser Automation:
Selenium, Cypress, Puppeteer, and Playwright. Ministry of Testing Athens. Meetup on the Beach. 30 May 2024.
First Steps with Globus Compute Multi-User Endpoints
In this presentation we will share our experiences around getting started with the Globus Compute multi-user endpoint. Working with the Pharmacology group at the University of Auckland, we have previously written an application using Globus Compute that can offload computationally expensive steps in the researcher's workflows, which they wish to manage from their familiar Windows environments, onto the NeSI (New Zealand eScience Infrastructure) cluster. Some of the challenges we have encountered were that each researcher had to set up and manage their own single-user globus compute endpoint and that the workloads had varying resource requirements (CPUs, memory and wall time) between different runs. We hope that the multi-user endpoint will help to address these challenges and share an update on our progress here.
May Marketo Masterclass, London MUG May 22 2024.pdf
Can't make Adobe Summit in Vegas? No sweat because the EMEA Marketo Engage Champions are coming to London to share their Summit sessions, insights and more!
This is a MUG with a twist you don't want to miss.
Providing Globus Services to Users of JASMIN for Environmental Data Analysis
JASMIN is the UK’s high-performance data analysis platform for environmental science, operated by STFC on behalf of the UK Natural Environment Research Council (NERC). In addition to its role in hosting the CEDA Archive (NERC’s long-term repository for climate, atmospheric science & Earth observation data in the UK), JASMIN provides a collaborative platform to a community of around 2,000 scientists in the UK and beyond, providing nearly 400 environmental science projects with working space, compute resources and tools to facilitate their work. High-performance data transfer into and out of JASMIN has always been a key feature, with many scientists bringing model outputs from supercomputers elsewhere in the UK, to analyse against observational or other model data in the CEDA Archive. A growing number of JASMIN users are now realising the benefits of using the Globus service to provide reliable and efficient data movement and other tasks in this and other contexts. Further use cases involve long-distance (intercontinental) transfers to and from JASMIN, and collecting results from a mobile atmospheric radar system, pushing data to JASMIN via a lightweight Globus deployment. We provide details of how Globus fits into our current infrastructure, our experience of the recent migration to GCSv5.4, and of our interest in developing use of the wider ecosystem of Globus services for the benefit of our user community.
Need for Speed: Removing speed bumps from your Symfony projects ⚡️
No one wants their application to drag like a car stuck in the slow lane! Yet it’s all too common to encounter bumpy, pothole-filled solutions that slow the speed of any application. Symfony apps are not an exception.
In this talk, I will take you for a spin around the performance racetrack. We’ll explore common pitfalls - those hidden potholes on your application that can cause unexpected slowdowns. Learn how to spot these performance bumps early, and more importantly, how to navigate around them to keep your application running at top speed.
We will focus in particular on tuning your engine at the application level, making the right adjustments to ensure that your system responds like a well-oiled, high-performance race car.
A Sighting of filterA in Typelevel Rite of Passage
Slide deck home: https://fpilluminated.com/deck/220
Recently uploaded (20)
Innovating Inference - Remote Triggering of Large Language Models on HPC Clus...
Innovating Inference - Remote Triggering of Large Language Models on HPC Clus...
openEuler Case Study - The Journey to Supply Chain Security
openEuler Case Study - The Journey to Supply Chain Security
AI Genie Review: World’s First Open AI WordPress Website Creator
AI Genie Review: World’s First Open AI WordPress Website Creator
Utilocate provides Smarter, Better, Faster, Safer Locate Ticket Management
Utilocate provides Smarter, Better, Faster, Safer Locate Ticket Management
Globus Compute wth IRI Workflows - GlobusWorld 2024
Globus Compute wth IRI Workflows - GlobusWorld 2024
Empowering Growth with Best Software Development Company in Noida - Deuglo
Empowering Growth with Best Software Development Company in Noida - Deuglo
First Steps with Globus Compute Multi-User Endpoints
First Steps with Globus Compute Multi-User Endpoints
May Marketo Masterclass, London MUG May 22 2024.pdf
May Marketo Masterclass, London MUG May 22 2024.pdf
Providing Globus Services to Users of JASMIN for Environmental Data Analysis
Providing Globus Services to Users of JASMIN for Environmental Data Analysis
Need for Speed: Removing speed bumps from your Symfony projects ⚡️
Need for Speed: Removing speed bumps from your Symfony projects ⚡️
A Sighting of filterA in Typelevel Rite of Passage
A Sighting of filterA in Typelevel Rite of Passage
Citizen Streaming Engineer - A How To
- 1. Citizen Streaming Engineer - A How To 2022.07.29 Tim Spann | Developer Advocate
- 2. Tim Spann Developer Advocate ● FLiP(N) Stack = Flink, Pulsar and NiFi Stack ● Streaming Systems/ Data Architect ● Experience: ○ 15+ years of experience with batch and streaming technologies including Pulsar, Flink, Spark, NiFi, Spring, Java, Big Data, Cloud, MXNet, Hadoop, Datalakes, IoT and more.
- 3. Demo
- 5. Apache Pulsar is a Cloud-Native Messaging and Event-Streaming Platform.
- 6. Why Apache Pulsar? Unified Messaging Platform Guaranteed Message Delivery Resiliency Infinite Scalability
- 7. Unified Messaging Model Streaming Consumer Consumer Consumer Subscription Shared Failover Consumer Consumer Subscription In case of failure in Consumer B-0 Consumer Consumer Subscription Exclusive X Consumer Consumer Key-Shared Subscription Pulsar Topic/Partition Messaging
- 8. Ecosystem
- 9. • Ingest Data • Route, Transform, Enrich • Join Data • ML Model Access • Store Easy to Build Streaming Data Pipelines
- 10. Why Apache NiFi? • Guaranteed delivery • Data buffering - Backpressure - Pressure release • Prioritized queuing • Flow specific QoS - Latency vs. throughput - Loss tolerance • Data provenance • Supports push and pull models • Hundreds of processors • Visual command and control • Over a 300 components • Flow templates • Pluggable/multi-role security • Designed for extension • Clustering • Version Control
- 11. Use Apache NiFi For Ingest https://streamnative.io/apache-nifi-connector/ • Ingest Data • Cleanse
- 12. Apache NiFi <-> Apache Pulsar
- 13. Use Apache Pulsar For Ingest
- 14. Use Pulsar to Route/Transform/Enrich • Libraries • Functions • Connectors • AMQP, Kafka, MQTT • Tiered Storage
- 15. • Utilizing JSON Data with a JSON Schema • Consistency, Contracts, Clean Data • This enables easy SQL: • Pulsar SQL (Presto SQL) • Flink SQL • Spark Structured Streaming Use Schemas
- 16. • Use Java, Python or Go • Simple way to add functionality • Route / Filter / Transform • Call Machine Learning Models Use Pulsar Functions
- 17. Deploying AI With an Event-Driven Platform https://dzone.com/trendreports/enterprise-ai-1
- 18. ML Models via Python / Java FN • Visual Question and Answer • Natural Language Processing • Sentiment Analysis • Text Classification • Named Entity Recognition • Content-based Recommendations • Predictive Maintenance • Fault Detection • Fraud Detection • Time-Series Predictions • Naive Bayes
- 20. Use Apache Flink to Join / Aggregate Continuous SQL
- 21. Use Apache Spark To Store val dfPulsar = spark.readStream.format("pulsar") .option("service.url", "pulsar://pulsar1:6650") .option("admin.url", "http://pulsar1:8080") .option("topic", "persistent://public/default/airquality").load() val pQuery = dfPulsar.selectExpr("*") .writeStream.format("parquet") .option("truncate", false).start() https://pulsar.apache.org/docs/en/adaptors-spark/
- 22. Use Pulsar to Stream to Lakehouses
- 23. (Queuing + Streaming) Simple Data Pipeline
- 24. Streaming FLiP-ML Apps StreamNative Hub StreamNative Cloud Unified Batch and Stream COMPUTING Batch (Batch + Stream) Unified Batch and Stream STORAGE Offload (Queuing + Streaming) Tiered Storage Pulsar --- KoP --- MoP --- Websocket Pulsar Sink Streaming Edge Gateway Protocols CDC Apps
- 25. Continuous Air Quality Aggregate Monitoring
- 26. ● Buffer ● Batch ● Route ● Filter ● Aggregate ● Enrich ● Replicate ● Dedupe ● Decouple ● Distribute
- 27. Apache Pulsar Apache Flink Apache NiFi Apache Spark https://streamnative.io/blog/engineering/2022-04-14-what-the-flip-is-the-flip-stack/
- 28. https://streamnative.io/blog/engineering/2021-11-17-building-edge-applications-with-apache-pulsar/
- 29. FLiP Stack Weekly This week in Apache Flink, Apache Pulsar, Apache NiFi, Apache Spark, Java and Open Source friends. https://bit.ly/32dAJft
- 30. Let’s Keep in Touch! Tim Spann Developer Advocate PaaSDev https://www.linkedin.com/in/timothyspann https://github.com/tspannhw
- 31. Apache Pulsar Training • Instructor-led courses • Pulsar Fundamentals • Pulsar Developers • Pulsar Operations • On-demand learning with labs • 300+ engineers, admins and architects trained! StreamNative Academy Now Available On-Demand Pulsar Training Academy.StreamNative.io
- 32. Python For Pulsar on Pi ● https://github.com/tspannhw/FLiP-Pi-BreakoutGarden ● https://github.com/tspannhw/FLiP-Pi-Thermal ● https://github.com/tspannhw/FLiP-Pi-Weather ● https://github.com/tspannhw/FLiP-RP400 ● https://github.com/tspannhw/FLiP-Py-Pi-GasThermal ● https://github.com/tspannhw/FLiP-PY-FakeDataPulsar ● https://github.com/tspannhw/FLiP-Py-Pi-EnviroPlus ● https://github.com/tspannhw/PythonPulsarExamples ● https://github.com/tspannhw/pulsar-pychat-function ● https://github.com/tspannhw/FLiP-PulsarDevPython101
- 33. Thanks