11-20-2024, 12:23 PM
Apache Storm: Stream Processing and Big Data Analytics
![[Image: a5a1885089a2aa4717cd8b069ecb8bb3.jpeg]](https://i124.fastpic.org/big/2024/1120/b3/a5a1885089a2aa4717cd8b069ecb8bb3.jpeg)
Published 11/2024
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 1h 40m | Size: 679 MB
Harness the power of Apache Storm for lightning-fast stream processing and real-time data analytics!
What you'll learn
Understand the architecture and core components of Apache Storm
Configure and install Apache Storm on various platforms
Master stream processing concepts like spouts, bolts, and stream grouping
Develop, deploy, and manage Storm topologies for real-time data analytics
Optimize Storm applications for parallel processing and fault tolerance
Requirements
Basic knowledge of Big Data technologies (e.g., Hadoop). Familiarity with Java programming. Understanding of distributed systems. A computer with at least 4GB RAM.
Description
Apache Storm is a distributed real-time computation system, enabling fast and reliable stream processing. This course, "Mastering Apache Storm: Real-Time Stream Processing and Big Data Analytics," is designed to guide you through the fundamentals of Apache Storm, its architecture, and hands-on implementation for efficient stream processing.Section 1: IntroductionKickstart your journey into real-time stream processing with an overview of Apache Storm.Key Topics Covered:Lecture 1: IntroductionAn overview of stream processing and Apache Storm's capabilities in handling real-time data.By the end of this section, you'll understand the basics of stream processing and the role Apache Storm plays in the Big Data landscape.Section 2: HistoryDive into the background and evolution of Apache Storm, understanding its origins and significance in the Big Data ecosystem.Key Topics Covered:Lecture 2: Description of HadoopIntroduction to Hadoop and its role in Big Data processing.Lecture 3: Storm IntroductionAn introduction to Apache Storm and its use cases for real-time data processing.Lecture 4: Apache Storm HistoryThe evolution of Apache Storm and its impact on real-time analytics.By the end of this section, you'll have a historical perspective on Apache Storm and its relevance to Big Data technologies.Section 3: FeaturesExplore the unique features and architecture of Apache Storm that set it apart as a real-time data processing system.Key Topics Covered:Lecture 5: Features of Apache StormOverview of Storm's features like scalability, fault-tolerance, and distributed processing.Lecture 6: Architecture of Apache StormIntroduction to Storm's architecture, including its core components.Lecture 7: Architecture Explanation in DetailA deep dive into Storm's architecture for efficient data flow management.Lecture 8: TopologyUnderstanding Storm topologies and how they define data flow.Lecture 9: Spouts and BoltsKey components of Storm: Spouts (data sources) and Bolts (data processors).Lecture 10: StreamExplanation of data streams and their role in Storm's processing model.By the end of this section, you'll be proficient in the architecture and key components of Apache Storm.Section 4: InstallationLearn how to set up and configure Apache Storm on your system to start processing real-time data streams.Key Topics Covered:Lecture 11: Installation ProcessStep-by-step guide to installing Apache Storm, including system requirements and configurations.By the end of this section, you'll be able to install and configure Apache Storm on various platforms.Section 5: ConceptsMaster core concepts like stream grouping, task management, and reliability to optimize data processing.Key Topics Covered:Lecture 12: Stream GroupingDifferent types of stream grouping techniques in Storm (Shuffle, Fields, All, etc.).Lecture 13: Stream Grouping ContinueAdvanced stream grouping methods for optimized data flow.Lecture 14: ReliabilityEnsuring message reliability and fault tolerance in Storm topologies.Lecture 15: TasksUnderstanding tasks and their role in Storm's parallel processing.Lecture 16: WorkersHow workers manage processing units in Storm's distributed architecture.By the end of this section, you'll have a strong grasp of core concepts to optimize your Storm topologies.Section 6: Java InstallationGet your development environment ready with Java, Zookeeper, and Eclipse for building Storm applications.Key Topics Covered:Lecture 17: Java Installation and ZookeeperInstalling Java and Zookeeper for Storm's coordination service.Lecture 18: Zookeeper InstallationStep-by-step guide to setting up Zookeeper, a crucial component for Storm.Lecture 19: Eclipse InstallationSetting up the Eclipse IDE for Java-based Storm development.Lecture 20: Command Line ClientUsing the command line client to manage Storm topologies.Lecture 21: Parallelism in Storm TopologyTechniques for optimizing parallelism in Storm to boost performance.By the end of this section, you'll be fully equipped with a development environment for building and running Apache Storm applications.Conclusion:This course provides a comprehensive guide to mastering Apache Storm for real-time data processing. By the end of the course, you will be proficient in using Storm to build robust, scalable, and efficient real-time applications.
Who this course is for
Big Data Engineers looking to dive into real-time data processing
Data Analysts aiming to harness streaming data for analytics
Software Developers interested in building real-time applications with Apache Storm
IT Professionals and Enthusiasts keen to learn stream processing frameworks
Homepage:
Screenshots
![[Image: 77be452592ae4505019c3167ab9276c4.jpeg]](https://i124.fastpic.org/big/2024/1120/c4/77be452592ae4505019c3167ab9276c4.jpeg)
Say "Thank You"
rapidgator.net:
k2s.cc:
Published 11/2024
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 1h 40m | Size: 679 MB
Harness the power of Apache Storm for lightning-fast stream processing and real-time data analytics!
What you'll learn
Understand the architecture and core components of Apache Storm
Configure and install Apache Storm on various platforms
Master stream processing concepts like spouts, bolts, and stream grouping
Develop, deploy, and manage Storm topologies for real-time data analytics
Optimize Storm applications for parallel processing and fault tolerance
Requirements
Basic knowledge of Big Data technologies (e.g., Hadoop). Familiarity with Java programming. Understanding of distributed systems. A computer with at least 4GB RAM.
Description
Apache Storm is a distributed real-time computation system, enabling fast and reliable stream processing. This course, "Mastering Apache Storm: Real-Time Stream Processing and Big Data Analytics," is designed to guide you through the fundamentals of Apache Storm, its architecture, and hands-on implementation for efficient stream processing.Section 1: IntroductionKickstart your journey into real-time stream processing with an overview of Apache Storm.Key Topics Covered:Lecture 1: IntroductionAn overview of stream processing and Apache Storm's capabilities in handling real-time data.By the end of this section, you'll understand the basics of stream processing and the role Apache Storm plays in the Big Data landscape.Section 2: HistoryDive into the background and evolution of Apache Storm, understanding its origins and significance in the Big Data ecosystem.Key Topics Covered:Lecture 2: Description of HadoopIntroduction to Hadoop and its role in Big Data processing.Lecture 3: Storm IntroductionAn introduction to Apache Storm and its use cases for real-time data processing.Lecture 4: Apache Storm HistoryThe evolution of Apache Storm and its impact on real-time analytics.By the end of this section, you'll have a historical perspective on Apache Storm and its relevance to Big Data technologies.Section 3: FeaturesExplore the unique features and architecture of Apache Storm that set it apart as a real-time data processing system.Key Topics Covered:Lecture 5: Features of Apache StormOverview of Storm's features like scalability, fault-tolerance, and distributed processing.Lecture 6: Architecture of Apache StormIntroduction to Storm's architecture, including its core components.Lecture 7: Architecture Explanation in DetailA deep dive into Storm's architecture for efficient data flow management.Lecture 8: TopologyUnderstanding Storm topologies and how they define data flow.Lecture 9: Spouts and BoltsKey components of Storm: Spouts (data sources) and Bolts (data processors).Lecture 10: StreamExplanation of data streams and their role in Storm's processing model.By the end of this section, you'll be proficient in the architecture and key components of Apache Storm.Section 4: InstallationLearn how to set up and configure Apache Storm on your system to start processing real-time data streams.Key Topics Covered:Lecture 11: Installation ProcessStep-by-step guide to installing Apache Storm, including system requirements and configurations.By the end of this section, you'll be able to install and configure Apache Storm on various platforms.Section 5: ConceptsMaster core concepts like stream grouping, task management, and reliability to optimize data processing.Key Topics Covered:Lecture 12: Stream GroupingDifferent types of stream grouping techniques in Storm (Shuffle, Fields, All, etc.).Lecture 13: Stream Grouping ContinueAdvanced stream grouping methods for optimized data flow.Lecture 14: ReliabilityEnsuring message reliability and fault tolerance in Storm topologies.Lecture 15: TasksUnderstanding tasks and their role in Storm's parallel processing.Lecture 16: WorkersHow workers manage processing units in Storm's distributed architecture.By the end of this section, you'll have a strong grasp of core concepts to optimize your Storm topologies.Section 6: Java InstallationGet your development environment ready with Java, Zookeeper, and Eclipse for building Storm applications.Key Topics Covered:Lecture 17: Java Installation and ZookeeperInstalling Java and Zookeeper for Storm's coordination service.Lecture 18: Zookeeper InstallationStep-by-step guide to setting up Zookeeper, a crucial component for Storm.Lecture 19: Eclipse InstallationSetting up the Eclipse IDE for Java-based Storm development.Lecture 20: Command Line ClientUsing the command line client to manage Storm topologies.Lecture 21: Parallelism in Storm TopologyTechniques for optimizing parallelism in Storm to boost performance.By the end of this section, you'll be fully equipped with a development environment for building and running Apache Storm applications.Conclusion:This course provides a comprehensive guide to mastering Apache Storm for real-time data processing. By the end of the course, you will be proficient in using Storm to build robust, scalable, and efficient real-time applications.
Who this course is for
Big Data Engineers looking to dive into real-time data processing
Data Analysts aiming to harness streaming data for analytics
Software Developers interested in building real-time applications with Apache Storm
IT Professionals and Enthusiasts keen to learn stream processing frameworks
Homepage:
Screenshots
Say "Thank You"
rapidgator.net:
k2s.cc:
