Conceptualizing the Processing Model for the GCP Dataflow Service
Год выпуска: 2020
Производитель: Pluralsight
Сайт производителя:
https://www.Pluralsight.com
Автор: Janani Ravi
Продолжительность: 3h 1m
Тип раздаваемого материала: Видеоклипы
Язык: Английский
Субтитры: Английские
Описание: Dataflow represents a fundamentally different approach to Big Data processing than computing engines such as Spark. Dataflow is serverless and fully-managed, and supports running pipelines designed using Apache Beam APIs.
Поток данных представляет собой принципиально иной подход к обработке больших данных, чем вычислительные механизмы типа Spark. Поток данных является бессерверным, полностью управляемым и поддерживает работающие конвейеры, разработанные с использованием API-интерфейсов Apache Beam.
Содержание
Course Overview 2m 5s
Course Overview 2m 5s
Getting Started with Cloud Dataflow 53m 55s
Prerequisites and Course Outline 2m 40s
Overview of Apache Beam 3m 52s
Introducing Cloud Dataflow 4m 50s
Executing Pipelines on Dataflow 6m 15s
Demo: Enabling APIs 2m 32s
Demo: Setting up a Service Account 4m 56s
Demo: Sample Word Count Application 7m 3s
Demo: Executing the Word Count Application on the Beam Runner 2m 8s
Demo: Creating Cloud Storage Buckets 3m 9s
Demo: Implementing a Beam Pipeline to Run on Dataflow 3m 43s
Demo: Running a Beam Pipeline on Cloud Dataflow 4m 20s
Demo: Custom Pipeline Options 3m 59s
Dataflow Pricing 4m 22s
Monitoring Jobs in Cloud Dataflow 42m 37s
Monitoring Jobs 4m 26s
Demo: Implementing a Pipeline with a Side Input 7m 7s
Demo: Running the Code and Exploring the Job Graph 5m 19s
Demo: Exploring Job Metrics 2m 59s
Demo: Autoscaling 3m 40s
Demo: Enabling the Streaming Engine 2m 12s
Demo: Using the Command-line Interface to Monitor Jobs 4m 28s
Demo: Logging Messages in Dataflow 3m 57s
Demo: Tracking Dataflow Metrics with the Metrics Explorer 3m 57s
Demo: Configuring Alerts 4m 27s
Optimizing Cloud Dataflow Pipelines 56m 36s
Structuring User Code 3m 20s
Demo: Writing Pipeline Results to Pub/Sub 6m 34s
Demo: Viewing Pipeline Results in Pub/Sub 2m 11s
Demo: Writing Pipeline Results to BigQuery 4m 50s
Demo: Viewing Pipeline Results in BigQuery 2m 22s
Demo: Performing Join Operations 6m 58s
Demo: Errors and Retries in Dataflow 5m 58s
Fusion and Combine Optimizations 5m 39s
Autoscaling and Dynamic Work Rebalancing 3m 29s
Demo: Reading Streaming Data from Pub/Sub 8m 15s
Demo: Writing Streaming Data to BigQuery 6m 55s
Running Cloud Dataflow Pipelines Using Templates 25m 58s
Introducing Templates in Dataflow 3m 58s
Demo: Built-in Templates in Dataflow 5m 8s
Demo: Running Built-in Templates 3m 46s
Demo: Creating Custom Dataflow Templates 4m 35s
Demo: Executing Custom Templates in Dataflow 7m 16s
Summary and Further Study 1m 12s
Файлы примеров: присутствуют
Формат видео: MP4
Видео: MPEG4 Video (H264) 1280x720 30fps 158kbps
Аудио: AAC 48000Hz stereo 96kbps
Доп. информация:
Level Advanced
Duration 3h 1m
Released 9 Nov 2020
