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start [2022/08/09 20:52]
deadline [Class Notes for Getting Started-Kafka]
start [2024/01/29 21:19] (current)
deadline [Linux Hadoop Minimal (LHM) Virtual Machine Sandbox]
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 =====Welcome to the Effective Data Pipelines Series ===== =====Welcome to the Effective Data Pipelines Series =====
-(previously Scalable Analytics with Apache Hadoop and Spark) 
  
-**The five or so essential trainings on the path to +This page provides many of the resources for books, videos and on-line trainings.
-scalable data science pipelines nirvana--or at least a good start**+
  
-====Training Descriptions and Links====+You can find more information on all current [[https://www.safaribooksonline.com/search/?query=eadline| video and book titles and upcoming on-line trainings]] from O'Reilly. 
 +====Training Descriptions====
  
-Click on the training name for availability and further informationNew trainings are always being added. For best results, trainings should be taken in the recommended order (shown below).  Trainings 1 and (2&3) can be taken out of order. Training 4 builds on training 1 and (2&3). Training 5 builds-on and assumes competence with topics in Training 4, (3&2), and 1. Finally, Training 6 requires understanding of tools and topics in trainings 1-5.+Many of the trainings are run on a regular basis. Check the [[https://www.safaribooksonline.com/search/?query=eadline|O'Reilly]] site for upcoming live eventsWhere possible, trainings are demonstrated using the [[start#Linux Hadoop Minimal (LHMVirtual Machine Sandbox|freely available virtual machine]]To facilitate continued exploration using the virtual machine, training notes (text filesavailable below.
  
-**NOTE: If the link does not lead you to the training, it has not yet been scheduledCheck back at a later date**+  * **Apache Hadoop, Spark, and Kafka Foundations** - (POPULAR) A great introduction to the Hadoop Big Data Ecosystem with Spark and Kafka. A non-programming introduction to Hadoop, Spark, HDFS, MapReduce, and Kafka. After completing the workshop attendees will gain a workable understanding of the Hadoop/Spark/Kafka technical value proposition and provide a solid background for following training in the Effective Data Pipelines Series (3 hours-1 day) 
 +  *  **Bash Programming Quick-start for Data Science** - Quickly learn the essentials of using the Linux command line for Data Science at scale. Download/upload filesrun applications, monitor resources, edit files, write scripts, and navigate the Linux command line interface used on almost all modern analytics clustersStudents can download and run examples on the "Linux Hadoop Minimal" virtual machine, see below. (4 hours-1 day) 
 +  * **Hands-on Introduction to Apache Hadoop, Spark, and Kafka Programming** - (POPULAR) A hands-on introduction to using Hadoop, Hive, Sqoop, Spark, Kafka and Zeppelin notebooks. Students can download and run examples on the "Linux Hadoop Minimal" virtual machine, see below. (6 hours-2 days) 
 +  * **Getting Started with Kafka** - (POPULAR) Apache Kafka is designed to manage data flow by decoupling the data source from the destination. Kafka can provide a robust data buffer or broker that can help create and manage data pipelines. In this training, the basic Kafka data broker design and operation is explained and illustrated using both the command line and a GUI.  
 +  * **Kafka Methods and Administration** - Additional Kafka features that go beyond those presented in Getting Started with Kafka will be addressed. These topics include writing to databases and HDFS, producer and consumer options, working with Kafka Connect, and Kafka installation and administration.    
 +  * **Up and Running with Kubernetes** - Kubernetes can be considered a container operating system where application resource and storage needs are matched to an underlying cluster environment (either virtual or real). This course provides both background for users coupled with a practical hands-on introduction to Kubernetes. 
 +  * **Data Engineering at Scale with Apache Hadoop and Spark** - As part of the Effective Data Pipelines series, this training provides background and examples on data "munging" or transforming raw data into form that can be used with analytical modeling libraries. Also referred to as data wrangling, transformation, or ETL these techniques are often performed "at scale" on a real cluster using Hadoop and Spark.(3 hours-1 days) 
 +  * **Scalable Analytics with Apache Hadoop, Spark, and Kafka** - A complete data science investigation requires different tools and strategies. In this training, learn How to apply Hadoop, Spark, and Kafka tools to Predict Airline Delays. All programming will be done using Hadoop, Spark, and Kafka with the Zeppelin web notebook on a four node cluster. The notebook will be made available for download so student can reproduce the examples. (3 hours-1 day)
  
-| 1 | [[https://www.oreilly.com/search/?query=Apache%20Hadoop%2C%20Spark%2C%20and%20Kafka%20Foundations%3A%20Effective%20Data%20Pipelines&extended_publisher_data=true&field=title|Apache Hadoop, Spark, and Kafka Foundations: Effective Data Pipelines]] A great introduction to the Hadoop Big Data Ecosystem with Spark and Kafka. A non-programming introduction to Hadoop, Spark, HDFS, MapReduce, and Kafka. After completing the workshop attendees will gain a workable understanding of the Hadoop/Spark/Kafka technical value proposition and provide a solid background for following training in the Effective Data Pipelines Series (3 hours-1 day)|{{:wiki:oreilly-foundations-dp.png?400}}| +----
-| 2 |[[https://www.oreilly.com/search/?query=Linux%20Command%20Line%20Quick-Start%20for%20Data%20Engineers&extended_publisher_data=true&highlight=true&&formats=live%20online%20training| Linux Command Line Quick-Start for Data Engineers: Effective Data Pipelines]] - Quickly learn the essentials of using the Linux command line for Data Science at scale. Download/upload files, run applications, monitor resources, edit files, write scripts, and navigate the Linux command line interface used on almost all modern analytics clusters. Students can download and run examples on the "Linux Hadoop Minimal" virtual machine, see below. (3.5 hours-1 day)|{{:wiki:oreilly-cl-quick-web-image.png?400}}| +
-| 3 |[[https://www.safaribooksonline.com/search/?query=Hands-on%20Introduction%20to%20Apache%20Hadoop%20Spark%20and%20Kafka%20Programming&field=title|Hands-on Introduction to Apache Hadoop, Spark, and Kafka Programming]] - A hands-on introduction to using Hadoop, Hive, Sqoop, Spark, Kafka and Zeppelin notebooks. Students can download and run examples on the "Linux Hadoop Minimal" virtual machine, see below. (6 hours-2 days)|{{:wiki:oreilly-hands-on-logo.png?400|}}| +
-| 4 |[[https://www.oreilly.com/search/?query=Data%20Engineering%20at%20Scale%20with%20Apache%20Hadoop%20and%20Spark%3A%20Effective%20Data%20Pipelines&extended_publisher_data=true&field=title|Data Engineering at Scale with Apache Hadoop and Spark]] - As part of the Effective Data Pipelines series, this training provides background and examples on data "munging" or transforming raw data into a form that can be used with analytical modeling libraries. Also referred to as data wrangling, transformation, or ETL these techniques are often performed "at scale" on a real cluster using Hadoop and Spark.(3 hours-1 days)|{{:wiki:oreilly-data-eng-at-scale-dp-logo.png?400|}}| +
-| 5| [[https://www.oreilly.com/search/?query=Scalable%20Analytics%20with%20Apache%20Hadoop%2C%20Spark%2C%20and%20Kafka%3A%20Effective%20Data%20Pipelines&extended_publisher_data=true&field=title|Scalable Analytics with Apache Hadoop, Spark, and Kafka]] - A complete data science investigation requires different tools and strategies. In this training, learn How to apply Hadoop, Spark, and Kafka tools to Predict Airline Delays. All programming will be done using Hadoop, Spark, and Kafka with the Zeppelin web notebook on a four node cluster. The notebook will be made available for download so student can reproduce the examples. (3 hours-1 day)|{{wiki: scalable-DS-course2.png}}|+
  
-=== About the Presenter === +==== About the Presenter ==== 
-**Douglas Eadline**, began his career as Analytical Chemist with an interest in computer methods. Starting with the first Linux Beowulf How-to document, Doug has written instructional documents covering many aspects of Linux HPC, Hadoop, and Analytics computing. Currently, Doug serves as editor of the //ClusterMonkey.net// website and was previously editor of //ClusterWorld Magazine//, and senior HPC Editor for //Linux Magazine//. He is also a writer and consultant to the scalable HPC/Analytics industry. His recent video tutorials and books include of the Hadoop Fundamentals LiveLessons (Addison Wesley) video, Hadoop 2 Quick Start Guide (Addison Wesley), High Performance Computing for Dummies (Wiley) and Practical Data Science with Hadoop and Spark (Co-author, Addison Wesley).+**Douglas Eadline**, began his career as Analytical Chemist with an interest in computer methods. Starting with the first Linux Cluster Beowulf How-to document, Doug has written instructional documents covering many aspects of Linux High Performance Computing (HPCand scalable data analytics computing. Currently, Doug serves as editor of the //ClusterMonkey.net// website and was previously editor of //ClusterWorld Magazine//, and senior HPC Editor for //Linux Magazine//. He is also a writer and consultant to the scalable HPC/Analytics industry. His recent video tutorials and books include of the Hadoop Fundamentals LiveLessons (Addison Wesley) video, Hadoop 2 Quick Start Guide (Addison Wesley), High Performance Computing for Dummies (Wiley) and Practical Data Science with Hadoop and Spark (Co-author, Addison Wesley). Doug also designs [[https://www.limulus-computing.com|high performance desk-side clusters]] for both HPC and data analytics
  
-**Update:** I will be teaching ''DS575 Big Data Techniques'' as part of an on-line (remote) [[https://www.juniata.edu/academics/graduate-programs/data-science.php| Masters in Data Science]] from Juniata College. The class will include more in-depth treatment and practical application of the scalable computing topics and examples I cover in these trainings. Consider enrolling in the Data Science program.+In addition to the on-line trainings, Doug also teaches graduate level courses as part of two Masters in Data science programs: 
 +  * **DS575 Big Data Techniques** as part of an on-line [[https://www.juniata.edu/academics/graduate-programs/data-science.php| Masters in Data Science]] from Juniata College.  
 +  * **DSCI 411 Data Management for Big Data** as part of in-person and online [[https://engineering.lehigh.edu/academics/graduate/masters/data-science|Masters in Data Science]] from Lehigh University 
 + 
 +These classes include more in-depth treatment and practical application of the scalable computing tools and examples I cover in the one-day trainings. Consider enrolling in one of these excellent Data Science programs. 
 + 
 +Contact: ''deadline''(you know what goes here)''eadline''(and here)''org''\\  
 +Mast: @thedeadline@mast.hpc.social \\  
 +Twitter: @thedeadline
  
 ---- ----
  
-====Class Notes for Linux Command Line Quick Start==== +====Class Notes for Bash Programming Quick-start==== 
-(Updated 14-Jul-2021 +(Updated 19-Apr-2023) 
-  * [[First Steps for Linux Command Line Training]]   +  * [[First Steps for Bash Programming Training]]   
-  * [[https://www.clustermonkey.net/download/Hands-on_Hadoop_Spark/Linux-CL-Quick-Start-V1.0.tgz|Class Notes]] (tgz format) +  * [[https://www.clustermonkey.net/download/Hands-on_Hadoop_Spark/Bash-Programming-Quick-start-v1.tgz|Class Notes]] (tgz format) 
-  * [[https://www.clustermonkey.net/download/Hands-on_Hadoop_Spark/Linux-CL-Quick-Start-V1.0.zip|Class Notes]] (zip format)+  * [[https://www.clustermonkey.net/download/Hands-on_Hadoop_Spark/Bash-Programming-Quick-start-v1.zip|Class Notes]] (zip format) 
 + 
  
  
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 ====Class Notes for Up and Running with Kubernetes==== ====Class Notes for Up and Running with Kubernetes====
-(Updated 12-Apr-2022) +(Updated 07-Sep-2022) 
-  * [[https://www.clustermonkey.net/download/Hands-on_Hadoop_Spark/Up_Running_Kubernetes-V1.2.tgz|Class Notes]] (tgz format) +  * [[https://www.clustermonkey.net/download/Hands-on_Hadoop_Spark/Up_Running_Kubernetes-V1.3.tgz|Class Notes]] (tgz format) 
-  * [[https://www.clustermonkey.net/download/Hands-on_Hadoop_Spark/Up_Running_Kubernetes-V1.2.zip|Class Notes]] (zip format)+  * [[https://www.clustermonkey.net/download/Hands-on_Hadoop_Spark/Up_Running_Kubernetes-V1.3.zip|Class Notes]] (zip format)
  
 +/*
 ====Class Notes for Implementing an Edge Computing Apache Kafka Inference Engine==== ====Class Notes for Implementing an Edge Computing Apache Kafka Inference Engine====
 (Updated 14-Apr-2021) (Updated 14-Apr-2021)
   * [[https://www.clustermonkey.net/download/Hands-on_Hadoop_Spark/Edge-Kafka-Keras-V2.0.tgz|Class Notes]] (tgz format)   * [[https://www.clustermonkey.net/download/Hands-on_Hadoop_Spark/Edge-Kafka-Keras-V2.0.tgz|Class Notes]] (tgz format)
   * [[https://www.clustermonkey.net/download/Hands-on_Hadoop_Spark/Edge-Kafka-Keras-V2.0.zip|Class Notes]] (zip format)   * [[https://www.clustermonkey.net/download/Hands-on_Hadoop_Spark/Edge-Kafka-Keras-V2.0.zip|Class Notes]] (zip format)
 +*/
 ====Class Notes for Getting Started with Kafka ==== ====Class Notes for Getting Started with Kafka ====
 (Updated **09-Aug-2022** - fixes typos)  (Updated **09-Aug-2022** - fixes typos) 
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   * [[https://www.clustermonkey.net/download/Hands-on_Hadoop_Spark/Getting-Started-Kafka-V2.1.tgz|Class Notes]] (tgz format)   * [[https://www.clustermonkey.net/download/Hands-on_Hadoop_Spark/Getting-Started-Kafka-V2.1.tgz|Class Notes]] (tgz format)
   * [[https://www.clustermonkey.net/download/Hands-on_Hadoop_Spark/Getting-Started-Kafka-V2.1.zip|Class Notes]] (zip format)   * [[https://www.clustermonkey.net/download/Hands-on_Hadoop_Spark/Getting-Started-Kafka-V2.1.zip|Class Notes]] (zip format)
 +
 +====Class Notes for Kafka Methods and Administration ====
 +(Update **20-Mar-2023** - some code and typo fixes) 
 +  * [[First Steps for Kafka Methods and Administration]]
 +  * [[https://www.clustermonkey.net/download/Hands-on_Hadoop_Spark/Kafka-Methods-and-Administration-V1.2.tgz|Class Notes]] (tgz format)
 +  * [[https://www.clustermonkey.net/download/Hands-on_Hadoop_Spark/Kafka-Methods-and-Administration-V1.2.zip|Class Notes]] (zip format)
 +
 +====Class Notes for Scalable PySpark for Data Science ====
 +(Update **07-Jan-2024**) 
 +  * [[First Steps for Scalable PySpark for Data Science]]
 +  * [[https://www.clustermonkey.net/download/Hands-on_Hadoop_Spark/Scalable-PySpark-v1.tgz|Class Notes]] (tgz format)
 +  * [[https://www.clustermonkey.net/download/Hands-on_Hadoop_Spark/Scalable-PySpark-v1.zip|Class Notes]] (zip format)
 +  * [[https://www.clustermonkey.net/download/Hands-on_Hadoop_Spark/Zeppelin-Notebooks/Scalable_PySpark_with_CSV_Files_and_Hive_Tables.json| PySpark for Data Science Zeppelin Notebook]] (Right Click, Save Link As ...)
  
 === Old Notes ==== === Old Notes ====
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 Used for //Hands-on//, //Command Line//, and //Scalable Data Science// trainings above. Note: This VM can also be used for the //Hadoop and Spark Fundamentals: LiveLessons// video mentioned below. Used for //Hands-on//, //Command Line//, and //Scalable Data Science// trainings above. Note: This VM can also be used for the //Hadoop and Spark Fundamentals: LiveLessons// video mentioned below.
  
-===VERSION 2-beta8: (Current)===  +===VERSION 2-8.1: (Current)=== 
-=== IMPORTANT: VirtualBox will not work on the new Apple M1 based systems ====+
  
-(Updated Aug-08-2022) 
-CentOS Linux 7.6, Anaconda 3:Python 3.7.4, R 3.6.0, Hadoop 3.3.0, Hive 3.1.2, Apache Spark 2.4.5, Derby 10.14.2.0, Zeppelin 0.8.2, Sqoop 1.4.7, Kafka 2.5.0, HBase 2.4.10, NiFi 1.15.3, KafkaEsque. **Used in all current trainings.** 
  
-  * [[Linux Hadoop Minimal Installation Instructions VERSION 2]] (Read First)  +(Updated Jan-25-2024
-  * [[https://www.clustermonkey.net/download/Hands-on_Hadoop_Spark/Linux-Hadoop-Minimal-V2.0-beta8.MD5.txt|Linux Hadoop Minimal V2.0-beta8 MD5]] +CentOS Linux 7.6, Anaconda 3:Python 3.7.4, R 3.6.0, Hadoop 3.3.0, Hive 3.1.2, Apache Spark 2.4.5, Derby 10.14.2.0, Zeppelin 0.8.2, Sqoop 1.4.7, Kafka 2.5.0, HBase 2.4.10NiFi 1.17.0KafkaEsque. **Used in all current trainings.**
-  * Linux Hadoop Minimal Virtual Machine V2.0-beta7 OVA file [[https://www.clustermonkey.net/download/Hands-on_Hadoop_Spark/Linux-Hadoop-Minimal-V2.0-beta8.ova|US]] [[http://134.209.239.225/download/Linux-Hadoop-Minimal-V2.0-beta8.ova|Europe]] (11.0G) **NOTE:** Chrome may prevent //http// downloadsright click the linkchoose "Save Link As" then click "Keep" next to the blue discard box at the bottom of the browser. +
-  [[https://www.clustermonkey.net/download/Hands-on_Hadoop_Spark/Hadoop-Minimal-Install-Notes-V2-beta7.tgz|Hadoop Minimal Build Notes (tgz format)]] +
-  [[https://www.clustermonkey.net/download/Hands-on_Hadoop_Spark/old|Old Versions]]+
  
-[[OLD VERSION 0.42]] (Deprecated)+[[Linux Hadoop Minimal Installation Instructions VERSION 2]] (Read First)  
 + 
 +==For VirtualBox X86 PC, Mac, Linux Machines== 
 +  * [[https://www.clustermonkey.net/download/Hands-on_Hadoop_Spark/Linux-Hadoop-Minimal-V2.0-8.1.ova.MD5.txt|Linux Hadoop Minimal V2.0-8.1MD5]] 
 +  * Linux Hadoop Minimal Virtual Machine V2.0-8.1 OVA file [[http://161.35.229.207/download/Linux-Hadoop-Minimal-V2.0-8.1.ova|US]] [[http://134.209.239.225/download/Linux-Hadoop-Minimal-V2.0-8.1.ova|Europe]] (13.0G) **NOTE:** Chrome may prevent //http// downloads, right click the link, choose "Save Link As" then click "Keep" next to the blue discard box at the bottom of the browser. 
 +  * [[https://www.clustermonkey.net/download/Hands-on_Hadoop_Spark/Hadoop-Minimal-Install-Notes-V2.0-8.1.tgz|Hadoop Minimal Build Notes x86 Virtual Box]] (tgz format) 
 + 
 +==For UTM Apple Mac M Machines== 
 +  * [[https://www.clustermonkey.net/download/Hands-on_Hadoop_Spark/Linux-Hadoop-Minimal-V2.0-M8.1.utm.zip.MD5.txt|Linux Hadoop Minimal V2.0-M8.1.zip MD5]] 
 +  * Linux Hadoop Minimal Virtual Machine V2.0-8.1 UTM file [[http://161.35.229.207/download/Linux-Hadoop-Minimal-V2.0-M8.1.utm.zip|US]] [[http://134.209.239.225/download/Linux-Hadoop-Minimal-V2.0-M8.1.utm.zip|Europe]] (8.0G) **NOTE:** Chrome may prevent //http// downloads, right click the link, choose "Save Link As" then click "Keep" next to the blue discard box at the bottom of the browser. 
 +  * [[https://www.clustermonkey.net/download/Hands-on_Hadoop_Spark/Hadoop-Minimal-Install-Notes-V2.0-M8.1.tgz|Hadoop Minimal Build Notes Mac UTM]] (tgz format)
  
  
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 ====Other Resources for all Classes==== ====Other Resources for all Classes====
   * Book: [[https://www.clustermonkey.net/Hadoop2-Quick-Start-Guide/| Hadoop® 2 Quick-Start Guide: Learn the Essentials of Big Data Computing in the Apache Hadoop® 2 Ecosystem]]   * Book: [[https://www.clustermonkey.net/Hadoop2-Quick-Start-Guide/| Hadoop® 2 Quick-Start Guide: Learn the Essentials of Big Data Computing in the Apache Hadoop® 2 Ecosystem]]
-  * **NEW** Video Tutorial: [[https://www.oreilly.com/videos/data-engineering-foundations/9780137440580|Hadoop Data Engineering Foundations Part 1: LiveLessons: Using Spark, Hive, and Hadoop® Tools]]   +  * Book: [[https://www.clustermonkey.net/Practical-Data-Science-with-Hadoop-and-Spark|Practical Data Science with Hadoop® and Spark: Designing and Building Effective Analytics at Scale]]   
-  * Video Tutorial: [[https://www.safaribooksonline.com/library/view/hadoop-and-spark/9780134770871|Hadoop® and Spark Fundamentals: LiveLessons]] +   Video Tutorial: [[https://www.oreilly.com/videos/data-engineering-foundations/9780137440580|Data Engineering Foundations Part 1: LiveLessons: Using Spark, Hive, and Hadoop® Tools]]   
-  * Book: [[https://www.clustermonkey.net/Practical-Data-Science-with-Hadoop-and-Spark|Practical Data Science with Hadoop® and Spark: Designing and Building Effective Analytics at Scale]]+  *  Video Tutorial (**NEW**): [[https://www.informit.com/store/data-engineering-foundations-part-2-building-data-pipelines-9780138086992|Data Engineering Foundations Part 2: Building Data Pipelines with Kafka and Nifi ]]
  
 ---- ----
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 ====Contact==== ====Contact====
  
-For further questions or help with the Linux Hadoop Minimal Virtual Machine please email: ''deadline''(you know what goes here)''limulus-computing''(and here)''com'' +For further questions or help with the Linux Hadoop Minimal Virtual Machine please email: ''deadline''(you know what goes here)''eadline''(and here)''org''
-/*[[http://scr.im/4502|d...@b...g.com]] */+
  
----+----
  
-**Unless otherwise noted, all training content, notes, and examples (c) Copyright Basement Supercomputing 2019, 2020 All rights reserved.**+**Unless otherwise noted, all training content, notes, and examples (c) Douglas Eadline 2019-2024 All rights reserved.**
  
  
start.1660078370.txt.gz · Last modified: 2022/08/09 20:52 by deadline