Apache Spark on Databricks | Path [2021, ENG] torrent

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Apache Spark on Databricks | Path

Год выпуска: 2021
Производитель: Pluralsight
Сайт производителя://app.pluralsight.com/paths/skills/apache-spark-on-databricks
Автор: Janani Ravi
Продолжительность: ~14h
Тип раздаваемого материала: Видеоурок
Язык: Английский
Описание: In Apache Spark on Databricks you will learn the in's and out's of Apache Spark via Databricks. You will learn how to handle batch data, processing streaming data, windowing and joining operations, predictive analytics using MLlib, executing graph algorithms and optimizing Apache Spark.

Prerequisites: Intermediate programming experience in Python or Scala. Beginner experience with the DataFrame API.

Related Topics: [Pluralsight / Justin Pihony] Apache Spark Fundamentals [2020, ENG]
[Pluralsight / Janani Ravi] Getting Started with Spark ● Getting Started with Stream Processing with Spark Streaming [2018, ENG]
[Pluralsight / Janani Ravi] Applying MapReduce to Common Data Problems [2016, ENG]
[Pluralsight / Janani Ravi] Getting Started with HBase: The Hadoop Database [2016, ENG]
[Pluralsight / Andrew Brust / Xavier Morera] Big Data: The Big Picture ● Executive Briefing [2021, ENG]
[Pluralsight] Scala Language Fundamentals | Path [2021, ENG]
[Pluralsight] Core Python | Path [2022, ENG]
[Pluralsight] Machine Learning Literacy | Path [2021, ENG]
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Beginner
You will learn Spark transformations, actions, visualizations, and functions leveraging the Databricks API. You will also learn how to transform and aggregate batch data using Spark with built-in and user defined functions, and perform windowing and join operations on batch data. Getting Started with Apache Spark on Databricks (Janani Ravi, 2021)
Handling Batch Data with Apache Spark on Databricks (Janani Ravi, 2021)

Intermediate
You will learn how to use Spark abstractions for streaming data and perform transformations on streaming data using the Spark streaming APIs on Databricks as well as how to leverage windowing, watermarking and join operations on streaming data in Spark for your specific use-cases. Processing Streaming Data with Apache Spark on Databricks (Janani Ravi, 2021)
Windowing and Join Operations on Streaming Data with Apache Spark on Databricks (Janani Ravi, 2021)

Advanced
You will understand and implement important techniques for predictive analytics such as regression and classification using Apache Spark MLlib APIs on Databricks as well as learn how to implement graph algorithms such as Triangle Count and PageRank and visualize them using the GraphFrames API on Spark Databricks. You will also learn how to optimize the performance of Spark clusters by identifying and mitigating various performance issues such as data ingestion problems and leveraging the new features offered by Spark 3. Predictive Analytics Using Apache Spark MLlib on Databricks (Janani Ravi, 2021)
Executing Graph Algorithms with GraphFrames on Databricks (Janani Ravi, 2021)
Optimizing Apache Spark on Databricks (Janani Ravi, 2021) Bonus
This course will teach you about the different components that make up Azure DataBricks. This is done by going through the different capabilities and how they help improve your data estate. Data Literacy: Essentials of Azure Databricks (Dayo Bamikole, 2021)
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Файлы примеров: присутствуют
Субтитры: присутствуют
Формат видео: MP4
Видео: H.264/AVC, 1280x720, 16:9, 29fps, 157 kb/s
Аудио: AAC, 48.0 kHz, 96.0 kbit/s, 2 channels
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