Одну секунду
Что-то сучилось. Попробуйте еще раз.
Scala kafka смотреть последние обновления за сегодня на .
Written form: 🤍 In this video, we'll learn Kafka Streams in Scala, from scratch. We're going to go through all of its most important features on a realistic scenario: - how to set up a Kafka stream in Scala - how to transform data - how to join semi-static data with KTables - how to compose Kafka streams together - how to start a complete Kafka Streams application Follow Rock the JVM on: LinkedIn: 🤍 Twitter: 🤍 Blog: 🤍 - Home: 🤍 -
Apache Kafka is a distributed event streaming platform used to handle large amounts of realtime data. Learn the basics of Kafka in this quickstart tutorial. #programming #datascience #100SecondsOfCode 💬 Chat with Me on Discord 🤍 🔗 Resources - Kafka Homepage 🤍 - Kafka Github 🤍 - RabbitMQ in 100 Seconds 🤍 🔥 Get More Content - Upgrade to PRO Upgrade at 🤍 Use code YT25 for 25% off PRO access 🎨 My Editor Settings - Atom One Dark - vscode-icons - Fira Code Font 🔖 Topics Covered - What is Apache Kafka? - Who created Apache Kafka? - What is Kafka used for? - How do large apps handle streaming data? - Apache Kafka basic examples
Tutorial is related to the learning materials posted on 🤍 Source code: 🤍 In this tutorial we quick overview how to implement a Scala application to consume and produce to Kafka topics. We also review the effect of group ID and different partitioning methods.
Spark Programming and Azure Databricks ILT Master Class by Prashant Kumar Pandey - Fill out the google form for Course inquiry. 🤍 - Data Engineering using is one of the highest-paid jobs of today. It is going to remain in the top IT skills forever. Are you in database development, data warehousing, ETL tools, data analysis, SQL, PL/QL development? I have a well-crafted success path for you. I will help you get prepared for the data engineer and solution architect role depending on your profile and experience. We created a course that takes you deep into core data engineering technology and masters it. If you are a working professional: 1. Aspiring to become a data engineer. 2. Change your career to data engineering. 3. Grow your data engineering career. 4. Get Databricks Spark Certification. 5. Crack the Spark Data Engineering interviews. ScholarNest is offering a one-stop integrated Learning Path. The course is open for registration. The course delivers an example-driven approach and project-based learning. You will be practicing the skills using MCQ, Coding Exercises, and Capstone Projects. The course comes with the following integrated services. 1. Technical support and Doubt Clarification 2. Live Project Discussion 3. Resume Building 4. Interview Preparation 5. Mock Interviews Course Duration: 6 Months Course Prerequisite: Programming and SQL Knowledge Target Audience: Working Professionals Batch start: Registration Started Fill out the below form for more details and course inquiries. 🤍 Learn more at 🤍 Best place to learn Data engineering, Bigdata, Apache Spark, Databricks, Apache Kafka, Confluent Cloud, AWS Cloud Computing, Azure Cloud, Google Cloud - Self-paced, Instructor-led, Certification courses, and practice tests. SPARK COURSES - 🤍 🤍 🤍 🤍 🤍 KAFKA COURSES 🤍 🤍 🤍 AWS CLOUD 🤍 🤍 PYTHON 🤍 We are also available on the Udemy Platform Check out the below link for our Courses on Udemy 🤍 = You can also find us on Oreilly Learning 🤍 🤍 🤍 🤍 🤍 🤍 🤍 🤍 = Follow us on Social Media 🤍 🤍 🤍 🤍 🤍 🤍
A quick introduction to how Apache Kafka works and differs from other messaging systems using an example application. In this video I explain partitioning, consumer offsets, replication and many other concepts found in Kafka. Please support me through my Udemy courses: Pass your coding interview in Java : 🤍 Python: 🤍 Ruby: 🤍 JavaScript: 🤍 Learn Dynamic Programming in, Java: 🤍 Python: 🤍 Ruby: 🤍 Multithreading in, Go Lang: 🤍 Python: 🤍 Java: 🤍 Book on Kafka (Manning publications): 🤍 Blog: 🤍
Written form: 🤍 The article also contains the SBT settings, the Kafka Docker container, the shell commands and the entire code in the video. Related videos: ZIO Fibers: 🤍 ZIO layers: 🤍 This video is for Scala engineers of all levels, with some basic experience with ZIO and Kafka (the basic concepts are covered in the article). We discuss how ZIO and Kafka can work together, what the main abstractions are, how we can read data from a Kafka topic, how we can decode our own data types automatically, how we can process data from Kafka as a ZIO Stream, and how we can produce values into a Kafka topic programmatically. Follow Rock the JVM on: LinkedIn: 🤍 Twitter: 🤍 Blog: 🤍 - Home: 🤍 -
As part of this topic we will see how we can develop programs to produce messages to Kafka Topic and consume messages from Kafka Topic using Scala as Programming language. * Revision about Kafka Topic * Understand producer as well as consumer APIs * Create new project with KafkaWorkshop * Define dependencies in build.sbt * Create application.properties for passing zookeeper and kafka broker information * Use producer API to produce messages to Kafka topic * Use consumer API to consume messages from Kafka topic Connect with me or follow me at 🤍 🤍 🤍 🤍 🤍
Hi Friends, In today's video, I have explained a Spark Consumer program for consuming data from Kafka and displaying this to console. I have explained the steps for starting zookeeper, Kafka, creating topic, producing the data and finally consuming the data from topic. Please use the below commands while working on this scenario. 1) Zookeeper must be up and running go to C:\zookeeper\bin and type zkServer 2) Kafka services must be up and running c:\kafka\bin\windows\kafka-server-start.bat c:\kafka\config\server.properties 3) Create Kafka topic c:\kafka\bin\windows\kafka-topics.bat create zookeeper localhost:2181 replication-factor 1 partitions 1 topic TEST_DEV 4) Kafka producer to push the data c:\kafka\bin\windows\kafka-console-producer.bat bootstrap-server localhost:9092 topic TEST_DEV Please subscribe to my channel and provide your feedback in the comments section.
In this tutorial, I gonna show you Kafka consumer scala example and explanation of properties Apache kafka || kafka consumer || kafka properies || scala example || kafka consumer example || kafka in 5 minutes =Software engineer's library= The Definitive Guide: 🤍 Kafka streams in action: 🤍 Kafka in action: 🤍 Mastering Kafka Streams and ksqlDB: 🤍 Apache Kafka Quick Start Guide: 🤍 00:00 Beginning 00:35 SBT configuration 00:55 Consumer Scala example 1:38 bootstrap.servers 1:55 client.id 2:16 consumer group configuration 2:36 group.id 2:50 session.timeout.ms 3:39 heartbeat.interval.ms 4:00 max.poll.interval.ms 04:20 max.poll.records
Written form to keep for later: 🤍 This article is for the Java/Scala programmer who wants to decide which framework to use for the streaming part of a massive application, or simply wants to know the fundamental differences between them, just in case. I'm going to write Scala, but all the frameworks I'm going to describe also have Java APIs. I'm going to discuss the main strengths and weaknesses of Akka Streams, Kafka Streams and Spark Streaming, and I'm going to give you a feel of how you would use them in a very simple word-counting application, which is one of the basic things to start with when one learns any distributed programming tool. Akka Streams: 🤍 Kafka Streams: 🤍 Spark Streaming: 🤍 Contents: 0:00 intro 1:13 Kafka Streams 6:08 Akka Streams 11:31 Spark Streaming Follow Rock the JVM on: LinkedIn: 🤍 Twitter: 🤍 Blog: 🤍 - Home: 🤍 -
Migrating Open Source projects to Scala 3 will be a recurring task in the future. Check out our experience while proofing the migration of Apache Kafka. We’ll share the obstacles faced, like tooling and compatibility checks, as well as where the community can improve to make such migrations smoother
In this video, We will learn how to integrated Kafka with Spark along with a Simple Demo. We will use spark with scala to have a consumer API and display the processed output in Spark console. Hope this video will be useful to start with Spark streaming and Kafka.
Spark Programming and Azure Databricks ILT Master Class by Prashant Kumar Pandey - Fill out the google form for Course inquiry. 🤍 - Data Engineering using is one of the highest-paid jobs of today. It is going to remain in the top IT skills forever. Are you in database development, data warehousing, ETL tools, data analysis, SQL, PL/QL development? I have a well-crafted success path for you. I will help you get prepared for the data engineer and solution architect role depending on your profile and experience. We created a course that takes you deep into core data engineering technology and masters it. If you are a working professional: 1. Aspiring to become a data engineer. 2. Change your career to data engineering. 3. Grow your data engineering career. 4. Get Databricks Spark Certification. 5. Crack the Spark Data Engineering interviews. ScholarNest is offering a one-stop integrated Learning Path. The course is open for registration. The course delivers an example-driven approach and project-based learning. You will be practicing the skills using MCQ, Coding Exercises, and Capstone Projects. The course comes with the following integrated services. 1. Technical support and Doubt Clarification 2. Live Project Discussion 3. Resume Building 4. Interview Preparation 5. Mock Interviews Course Duration: 6 Months Course Prerequisite: Programming and SQL Knowledge Target Audience: Working Professionals Batch start: Registration Started Fill out the below form for more details and course inquiries. 🤍 Learn more at 🤍 Best place to learn Data engineering, Bigdata, Apache Spark, Databricks, Apache Kafka, Confluent Cloud, AWS Cloud Computing, Azure Cloud, Google Cloud - Self-paced, Instructor-led, Certification courses, and practice tests. SPARK COURSES - 🤍 🤍 🤍 🤍 🤍 KAFKA COURSES 🤍 🤍 🤍 AWS CLOUD 🤍 🤍 PYTHON 🤍 We are also available on the Udemy Platform Check out the below link for our Courses on Udemy 🤍 = You can also find us on Oreilly Learning 🤍 🤍 🤍 🤍 🤍 🤍 🤍 🤍 = Follow us on Social Media 🤍 🤍 🤍 🤍 🤍 🤍
🤍 Find Spark & Scala Training in London: 🤍 This is Spark Storm Scala Kafka training video for both beginners and advanced learners that covers Spark Storm Scala Kafka Desktop, Architecture, Dashboard and hands-on training in designing Spark Storm Scala Kafka Reports. Become expert in Spark Storm Scala Kafka analytics, Spark Storm Scala Kafka & R integration, and Spark Storm Scala Kafka advanced concepts for Spark Storm Scala Kafka Certification. Check our Spark Storm Scala Kafka Tutorials and Interview questions to get a Spark Storm Scala Kafka inside view.
This comprehensive Kafka tutorial focuses on with building foundation about all major concepts in Apache Kafka. This part of the course is important to understand how Kafka really works and it will help you with hands-on exercises later in this course. Course Link: 🤍y/apache-kafka/ In the later part of this Kafka tutorial, we will have lots of hands-on exercises covering from basic to advanced topics of Kafka. You will learn how to set up Apache Kafka on your personal computer (Mac/Linux or Windows PC). Then create Kafka topics (where actual data is stored inside Kafka) & perform various operations on your topics. Later you will setup Kafka producers and Kafka consumers to send and receive data. In more advance topics you will learn how to create your own Kafka Producers and Kafka Consumers. Why Apache Kafka Apache Kafka is an open source distributed streaming platform which can handle 100s of billions of events in a day. Originally Kafka was built to replace legacy messaging systems with a reliable, fast and distributed streaming platform. Apache Kafka was built and open sourced by LinkedIn in 2011. Today it has become the most sort after data streaming platform in the world. It is a tough competitor to Apache Spark Streaming engine. Like Hadoop is a distributed storage and distributed processing platform & spark is a distributed in-memory processing engine, Apache Kafka is a distributed data streaming platform. All these 3 systems complement each other. If you know Hadoop and Spark systems then Kafka is the missing link for connecting the dots. You will learn Section 1 – APACHE KAFKA & IT’S FEATURES In this section of the course, we will start with building the knowledge about various key concepts of Apache Kafka. This will be important section, so make sure you watch all videos before moving to the next section of the course. Here are some of the chapters covered in this section: What is Apache Kafka? How Apache Kafka provides High Level of Scalability? Kafka’s In-built Fault Tolerance Apache Kafka is damn Popular Section 2 – WHY APACHE KAFKA? In this part of the course, we will discuss why we really need Apache Kafka and what kind of real world problem does it solve? Here are some of the chapters covered in this section: Why we need Apache Kafka? Decoupling of Systems Section 3 – APACHE KAFKA ARCHITECTURE It’s time to dig deeper into how Apache Kafka really works and we will do this by understanding Kafka’s architecture. Apache Kafka Architecture How Netflix is using Kafka Section 4 – ANATOMY OF APACHE KAFKA In this section of the course, we will look at various components that make Apache Kafka what it is today. This is an important section of this course. It will help you really build the core understanding about each individual component of a Kafka application. What is Kafka Broker Kafka Topic Explained Learn about Kafka Topic Partitions What are Kafka Offsets How Replication Works in Kafka Who is the leader Let’s talk about Zookeeper Kafka Producers Kafka Consumers Putting everything together Section 5 – DESIGNING APACHE KAFKA APPLICATIONS In this section, we will talk about what to consider while designing Apache Kafka applications. Designing Considerations Section 6 – EXPERT LEVEL HANDS-ON Let’s use the knowledge and get our hands dirty by working on some real exercises. Setup Apache Kafka on Local Computer (Mac & Linux users) Setup Apache Kafka on Local Computer (Windows PC users) How to connect to HDP Sandbox terminal (Windows PC users) Let’s fire up a local cluster (Windows PC users) It’s time to create some Kafka Topics What Kafka topics you got? Peak inside a Kafka topic How to delete a Kafka topic Running a Kafka Producer Running a Kafka Consumer What to do when a Kafka Producer or Kafka Consumer goes down in production Section 7 – ADVANCE LEVEL HANDS-ON In this part of the course, you will work on more advanced subjects. How to create your own Kafka Producer (Java Code) How to create your own Kafka Consumer (Java Code) Integrating Kafka with Spark Streaming (Scala Code) Running your Spark Data aggregator Section 8 – BONUS LECTURES Trick #1 – Generate data for your Kafka Console Producer Trick #2 – Simulate a Real Time Streaming Data Source Find us on: Website: 🤍y Pinterest: 🤍 Facebook: 🤍 Twitter: 🤍 LinkedIn: 🤍 Training: 🤍 #kafkatutorial #kafkatutorialforbeginners #kafka
If you're new to Kafka Streams and want to use Scala, hopefully, you'll find this helpful. This video is intended to accompany the entire tutorial available at 🤍
With the recent release of Scala `3`, we’ll see an increasing number of projects adding support for it alongside a couple of older versions like `2.12` and `2.13`. Apache Kafka represents an interesting use case since it’s written in both Java and Scala, with the core module being almost completely written in Scala and currently supporting Scala `2.12` and `2.13`. Adding the support for Scala `3` is a required task if we want to avoid a complete rewrite. We took the challenge and this session explores our migration attempt, starting by stating the main problems unearthed while proofing how complicated the migration would be. The talk will then cover the missing pieces in the ecosystem, like the interoperability between Java and Scala, or differences in bytecode generation, and suggest how the community can help. Why did those problems occur and what does it need to change to have even smoother migrations in the future? Check out our experience and learn how this can be extrapolated to other mixed Java/Scala OSS projects. 🤍 🤍
This talk was recorded at Scala Swarm Conference 2017 in Porto, Portugal. Subscribe to our YouTube channel and follow us on Twitter 🤍 and 🤍 website for more information. Abstract: Apache Kafka is now widely adopted among modern distributed systems. In this presentation we will see how Akka Streams can add even more power to Kafka by exposing it as a reactive stream. We will see some examples of how the Reactive Kafka library can be leveraged to build a well-fitting and elegant match of partitioned, pull-based distributed log and asynchronous, backpressured streaming model. 🤍 🤍 Our other events: Follow us on Twitter 🤍 and on the website for more information 🤍.
Weekly system design newsletter: 🤍 Checkout our bestselling System Design Interview books: Volume 1: 🤍 Volume 2: 🤍 Other things we made: Digital version of System Design Interview books: 🤍 Twitter: 🤍 LinkedIn: 🤍 ABOUT US: Covering topics and trends in large-scale system design, from the authors of the best-selling System Design Interview series.
Hello Guys, In this video i have explained, how you can manage Kafka offsets in Spark Streaming code, using scala. This video will explain the kafka offset concepts and how you implement the kafka offsets in spark programs. Command used to start kafka producer - kafka-console-producer.sh broker-list localhost:9092 topic kafkaOS The video in which the initial code base (used in this video) was built from scratch: 🤍 Below are the other relevant videos from my channel: Handle incremental load in HIVE - 🤍 Spark Streaming with kafka and HBase - 🤍 Spark Streaming with kafka - 🤍 Installation of kafka on Cloudera quickstart VM 🤍
Riproduzione del treno EC 357 Franz Kafka da Monaco di Baviera per Praga, nella sua eterogenea composizione mista di carrozze Alex Arriva Landerbahn Express e České Dráhy
Learn how to detect real-time trending topics on the Wikipedia web site using Apache Spark and Kaftka in a Jupyter notebook running in the IBM Data Science Experience (DSX). 🤍
Getting started with Kafka Streams Testing screencast to accompany the tutorial available at 🤍
This video was recorded at Scala Days Berlin 2018 Follow us on Twitter 🤍ScalaDays or visit our website for more information 🤍 Find more information and the abstract here: 🤍
Actors are what makes cloud-based applications built in Akka virtually indestructible. See how actors work in 1 minute.
► TRY THIS YOURSELF: 🤍 Learn about Kafka Streams, a stream-processing Java API. Kafka Streams enables you to access filtering, joining, aggregating, and grouping, so you don't need any new original framework code. ► For a COMPLETE IMMERSIVE HANDS-ON EXPERIENCE, go to 🤍 - - - ABOUT CONFLUENT Confluent, founded by the creators of Apache Kafka, enables organizations to harness the business value of live data. The Confluent Platform manages the barrage of stream data and makes it available throughout an organization. It provides various industries, from retail, logistics, and manufacturing, to financial services and online social networking, a scalable, unified, real-time data pipeline that enables applications ranging from large-volume data integration to big data analysis with Hadoop to real-time stream processing. To learn more, please visit 🤍 #kafka #kafkastreams #streamprocessing #apachekafka #confluent
Hello Guys, In this video i have created a a big data pipeline where we are taking the live inputs from a Kafka producer into a Spark Streaming application, processing the same and storing the output to HBase. This is a simple small project that could help you undrstand the Streaming APIs integration. Below are the other relevant videos from my channel: Spark Streaming with kafka - 🤍 Installation of kafka on Cloudera quickstart VM 🤍 CLI Commands used in the video: Starting the producer /usr/lib/kafka/bin/kafka-console-producer.sh broker-list localhost:9092 topic kafkatutorial Creating the Hbase table - create 'Streaming_wordcount', 'Word_count', 'Occurances'
Spark Programming and Azure Databricks ILT Master Class by Prashant Kumar Pandey - Fill out the google form for Course inquiry. 🤍 - Data Engineering using is one of the highest-paid jobs of today. It is going to remain in the top IT skills forever. Are you in database development, data warehousing, ETL tools, data analysis, SQL, PL/QL development? I have a well-crafted success path for you. I will help you get prepared for the data engineer and solution architect role depending on your profile and experience. We created a course that takes you deep into core data engineering technology and masters it. If you are a working professional: 1. Aspiring to become a data engineer. 2. Change your career to data engineering. 3. Grow your data engineering career. 4. Get Databricks Spark Certification. 5. Crack the Spark Data Engineering interviews. ScholarNest is offering a one-stop integrated Learning Path. The course is open for registration. The course delivers an example-driven approach and project-based learning. You will be practicing the skills using MCQ, Coding Exercises, and Capstone Projects. The course comes with the following integrated services. 1. Technical support and Doubt Clarification 2. Live Project Discussion 3. Resume Building 4. Interview Preparation 5. Mock Interviews Course Duration: 6 Months Course Prerequisite: Programming and SQL Knowledge Target Audience: Working Professionals Batch start: Registration Started Fill out the below form for more details and course inquiries. 🤍 Learn more at 🤍 Best place to learn Data engineering, Bigdata, Apache Spark, Databricks, Apache Kafka, Confluent Cloud, AWS Cloud Computing, Azure Cloud, Google Cloud - Self-paced, Instructor-led, Certification courses, and practice tests. SPARK COURSES - 🤍 🤍 🤍 🤍 🤍 KAFKA COURSES 🤍 🤍 🤍 AWS CLOUD 🤍 🤍 PYTHON 🤍 We are also available on the Udemy Platform Check out the below link for our Courses on Udemy 🤍 = You can also find us on Oreilly Learning 🤍 🤍 🤍 🤍 🤍 🤍 🤍 🤍 = Follow us on Social Media 🤍 🤍 🤍 🤍 🤍 🤍
Spark Programming and Azure Databricks ILT Master Class by Prashant Kumar Pandey - Fill out the google form for Course inquiry. 🤍 - Data Engineering using is one of the highest-paid jobs of today. It is going to remain in the top IT skills forever. Are you in database development, data warehousing, ETL tools, data analysis, SQL, PL/QL development? I have a well-crafted success path for you. I will help you get prepared for the data engineer and solution architect role depending on your profile and experience. We created a course that takes you deep into core data engineering technology and masters it. If you are a working professional: 1. Aspiring to become a data engineer. 2. Change your career to data engineering. 3. Grow your data engineering career. 4. Get Databricks Spark Certification. 5. Crack the Spark Data Engineering interviews. ScholarNest is offering a one-stop integrated Learning Path. The course is open for registration. The course delivers an example-driven approach and project-based learning. You will be practicing the skills using MCQ, Coding Exercises, and Capstone Projects. The course comes with the following integrated services. 1. Technical support and Doubt Clarification 2. Live Project Discussion 3. Resume Building 4. Interview Preparation 5. Mock Interviews Course Duration: 6 Months Course Prerequisite: Programming and SQL Knowledge Target Audience: Working Professionals Batch start: Registration Started Fill out the below form for more details and course inquiries. 🤍 Learn more at 🤍 Best place to learn Data engineering, Bigdata, Apache Spark, Databricks, Apache Kafka, Confluent Cloud, AWS Cloud Computing, Azure Cloud, Google Cloud - Self-paced, Instructor-led, Certification courses, and practice tests. SPARK COURSES - 🤍 🤍 🤍 🤍 🤍 KAFKA COURSES 🤍 🤍 🤍 AWS CLOUD 🤍 🤍 PYTHON 🤍 We are also available on the Udemy Platform Check out the below link for our Courses on Udemy 🤍 = You can also find us on Oreilly Learning 🤍 🤍 🤍 🤍 🤍 🤍 🤍 🤍 = Follow us on Social Media 🤍 🤍 🤍 🤍 🤍 🤍
Request you to follow my blogs here: 🤍 Apache Spark Use Cases | Hands-On - 🤍 Code, data used in the video can be found here: 🤍 Please subscribe to my YouTube channel to more technology videos: 🤍
Apache Kafka is a distributed stream processing software developed by LinkedIn and written in Scala and Java. Chapters 0:00 Intro 2:32 Kafka Broker 5:39 Kafka Producer 7:11 Kafka Consumer 8:34 Kafka Partitions 12:50 Queue vs Pub-Sub 16:47 Consumer Group 23:06 ZooKeeper 29:45 Coding Example 1:02:48 Kafka Pros-Cons 1:17:00 Summary Download slides here 🤍 (Members get all slides for all my video courses for free) In this video I want to focus on the basics of Kafka, talk about how it works give finally spin up a Kafka cluster and write a producer and a consumer. Kafka Components _ producer _consumer _topic _partition How Kafka works Example ( Ride sharing ) Spin Kafka cluster Write a producer Write a consumer Kafka Applications Pros and Cons Source Code 🤍 Docker commands spin up kafka //if you ever mess up or you want to start fresh just stop and remove the containers and rerun the command docker stop zookeeper kafka docker rm zookeeper kafka docker run name zookeeper -p 2181:2181 -d zookeeper docker run -p 9092:9092 name kafka -e KAFKA_ZOOKEEPER_CONNECT=husseinmac:2181 -e KAFKA_ADVERTISED_LISTENERS=PLAINTEXT://husseinmac:9092 -e KAFKA_OFFSETS_TOPIC_REPLICATION_FACTOR=1 -d confluentinc/cp-kafka Get my fundamentals of database engineering course link redirects to udemy with coupon applied (🤍) Resources KIP 500 (Remove Zookeeper) 🤍 Become a Member on YouTube 🤍 🧑🏫 Courses I Teach 🤍 🏭 Backend Engineering Videos in Order 🤍 💾 Database Engineering Videos 🤍 🎙️Listen to the Backend Engineering Podcast 🤍 Gears and tools used on the Channel (affiliates) 🖼️ Slides and Thumbnail Design Canva 🤍 🎙️ Mic Gear Shure SM7B Cardioid Dynamic Microphone 🤍 Cloudlifter 🤍 XLR cables 🤍 Focusrite Audio Interface 🤍 📷 Camera Gear Canon M50 Mark II 🤍 Micro HDMI to HDMI 🤍 Video capture card 🤍 AC Wall for constant power 🤍 Stay Awesome, Hussein
► TRY THIS YOURSELF: 🤍 In this video you learn about Apache Kafka consumers and consumer rebalancing. Youl also learn how to use the consumer API and the KafkaConsumer class to connect to the cluster to subscribe to one or more topics. - - - ► For a COMPLETE IMMERSIVE HANDS-ON EXPERIENCE, go to 🤍 ABOUT CONFLUENT Confluent, founded by the creators of Apache Kafka®, enables organizations to harness the business value of live data. The Confluent Platform manages the barrage of stream data and makes it available throughout an organization. It provides various industries, from retail, logistics, and manufacturing, to financial services and online social networking, a scalable, unified, real-time data pipeline that enables applications ranging from large-volume data integration to big data analysis with Hadoop to real-time stream processing. To learn more, please visit 🤍 #kafka #kafkastreams #streamprocessing #apachekafka #confluent
Kubernetes as a Streaming Data Platform with Kafka, Spark, and Scala Abstract: Kubernetes has become the de-facto platform for running containerized workloads on a cluster. Its native abstractions let us deploy and manage individual distributed applications and services. In contrast, streaming applications require the coordinated deployment of different components such as topics, storage, and application runtimes that need to work in unison. In this talk, we are going to discuss how to use Kubernetes Operators to manage this complexity. In particular, we will see: ➡How to use the Kafka Operator to manage topics ➡How to use the Spark Operator to deploy and manage Spark Structured Streaming applications ➡How a custom operator can harness Kubernetes resources and other operators to implement the operational requirements of our applications. We will share our experience building an operator for streaming data pipelines using Scala and show how this all works in real life.
Kafka is the bedrock of Wix's distributed microservices system. For the last 5 years we have learned a lot about how to successfully scale our event-driven architecture to roughly 1400 microservices, mostly written in Scala. We've managed to achieve higher decoupling and independence for our various services and dev teams that have very different use-cases while maintaining a single uniform infrastructure in place. Our Kafka infrastructure is called Greyhound and was recently completely re-written using ZIO. In this talk you will learn about 10 key decisions and steps you can take in order to safely scale-up your Kafka-based system. These include: How to increase dev velocity of event driven style code. How to optimize working with Kafka in polyglot setting How to support growing amount of traffic and developers. How to tackle multiple DCs environment.
Intellipaat Apache Spark Scala Course:- 🤍 This Kafka Spark Streaming video is an end to end tutorial on kafka and spark where you will learn what is apache kafka, why to learn kafka, kafka architecture, setting up kafka cluster, what is spark, spark components and in the end kafka spark streaming examples in detail. We have covered below topics in this apache kafka with spark streaming tutorial: 00:36 - why Kafka was needed? 02:25 - what is Kafka 03:03 - Kafka components 04:32 - Kafka architecture 09:42 - singer broker configuration setup demo 13:02 - what is Spark 13:32 - Spark Features 14:15 - Spark Industry usage 14:39 - RDDs in Spark 15:35 - Spark components 17:25 - learn Spark streaming 18:20 - Spark streaming features 19:20 - integrating Spark and Kafka Interested to learn Apache Spark still more? Please check similar Spark blogs here:- 🤍 Watch complete Spark tutorials here:- 🤍 Are you looking for something more? Enroll in our Big Data Hadoop, Apache Spark, Kafka course & certification and become a certified Professional (🤍 It is a 60 hrs instructor led training provided by Intellipaat which is completely aligned with industry standards and certification bodies. If you’ve enjoyed this kafka spark streaming integration tutorial, Like us and Subscribe to our channel for more similar informative tutorials. Got any questions about integrating spark and kafka? Ask us in the comment section below. Intellipaat Edge 1. 24*7 Life time Access & Support 2. Flexible Class Schedule 3. Job Assistance 4. Mentors with +14 yrs 5. Industry Oriented Course ware 6. Life time free Course Upgrade Why should you learn Spark? Apache Spark is an open source computing framework up to 100 times faster than Mapreduce and Spark is alternative form of data processing unique in batch processing and streaming. Learning Spark will help you master all the skills needed to increase application performance and enable high-speed processing using Spark RDDs as well as help in customization of Spark using Scala. Who should watch this Apache Spark tutorial? If you want to learn Spark to become fully proficient to work with large amounts of unstructured data with increased speed to handle the real-time analytics then this Intellipaat integrating spark and kafka tutorial is for you. This Intellipaat spark tutorial is your first step to learn Spark and kafka. We are covering the most important spark examples in this Spark tutorial. Since this Spark training video can be taken by anybody, so if you are Software Engineers looking to upgrade Big Data skills, Data Engineers and ETL Developers, Data Scientists and Analytics Professionals or graduates looking to make a career in Big Data then you must watch this spark streaming example tutorial to take your skills to the next level. Why Spark is important? Today there is a widespread deployment of Big Data. With each passing day the requirements of enterprises increases and therefore there is a need for a faster and more efficient form of processing data. Most of the data is in unstructured format and it is coming in thick and fast as streaming data. The Intellipaat Spark beginners tutorial is easy to understand, has real world Spark examples and thus makes you understand why Spark is so important and why you should go for a Spark career. Why should you opt for a Spark career? Apache Spark is seeing widespread demand with enterprises finding it increasingly difficult to hire the right professionals to take on increasingly challenging roles in real world scenarios. It is a fact that today the Apache Spark community is one of the fastest Big Data communities with over 750 contributors from over 200 companies worldwide. The entire Intellipaat Spark course is in line with the industry needs. Hence this Intellipaat tutorial is your stepping stone to a successful career! #KafkaSparkStreaming #ApacheKafkaWithSparkStreaming #SparkKafkaIntegration For more information: Please write us to sales🤍intellipaat.com or call us at: +91-7847955955 Website: 🤍 Facebook: 🤍 LinkedIn: 🤍 Twitter: 🤍
In this tutorial we will be creating a simple Kafka Producer in Java. We will post simple message on a Kafka topic. Install Kafka Using Docker : 🤍
Learn how to overcome tech debts and legacy architecture for reliable backend system scalability. Upgrading monolith to microservices is not the only way. Join our talk and discover how Kafka and event-driven architecture can be leveraged to achieve scalable systems reliably. Gain practical tips and strategies to stay ahead in the constantly evolving tech landscape. During this session Dineshkumar will cover: - Bottlenecks and scalability issues in monolithic and microservices architecture - What is an event-driven system and how it allows for teams and features to be independently scaled - Leveraging Kafka with best practices to handle high scale Dineshkumar's presentation slides: 🤍 - Interested in more great talks? Check the upcoming ones here: 🤍 - Join PlatformCon 2023: 🤍 - Join our Platform Engineering Slack community: 🤍
In this Kafka Integration with Spark Streaming tutorial, the following concepts will be covered: ✓ Kafka Integration with Spark ✓ KafkaUtils API ✓ Kafka Wordcount Example Skillspeed is a live e-learning company focusing on high-technology courses. We provide training experiences in APACHE SPARK & SCALA featuring 24/7 Lifetime Support, 100% Placement Assistance & Real-time Projects in Cloud Based Labs. Email: sales🤍skillspeed.com Website: 🤍skillspeed.com Facebook: 🤍 LinkedIn: 🤍
Pour me soutenir, vous pouvez me faire un don (même juste 2€) Tipeee : 🤍 Utip : 🤍 - Dans cette vidéo, je vous explique ce qu'est Apache Kafka : 00:00 Blague nulle 00:36 Les échanges de données 00:56 A quoi ça sert Kafka? 02:00 Architecture Kafka 03:30 Cas d'utilisation de Kafka 04:20 A bientôt! Restons connectés : Facebook : 🤍 Twitter : 🤍Cookieconnecte Instagram : 🤍Cookieconnecte - N'hésitez pas à poser vos questions, donner des idées de vidéos ou à donner votre avis dans les commentaires.
.svg){kind=small}
