Python Celery for Distributed Tasks and Parallel Programming [2020, ENG]
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Files
| 1. Start Here | |||
| 1. Introduction.mp4 | 4.96 MB | ||
| 2. Course Lap Setup | |||
| 1. Install Oracle client on ubuntu and install cx_Oracle library.mp4 | 37.53 MB | ||
| 1.1 OraClient_ubunto.pdf | 31.27 KB | ||
| 2. Install Spark and pandas 1.mp4 | 26.67 MB | ||
| 2.1 InstallSpark.pdf | 33.76 KB | ||
| 3. Install Spark and pandas 2.mp4 | 20.68 MB | ||
| 4. Install celery pipeline framework.mp4 | 37.04 MB | ||
| 4.1 InstallCelery.pdf | 244.56 KB | ||
| 3. Working with Pandas Data Frames | |||
| 1. Introduction to data frames.mp4 | 34.01 MB | ||
| 1.1 Pandas+Lec1.zip | 5.83 KB | ||
| 2. Working with index.mp4 | 24.03 MB | ||
| 3. Selecting from data frames.mp4 | 18.77 MB | ||
| 4. Grouping and sorting data in data frames.mp4 | 15.22 MB | ||
| 4.1 Pandas group by and sort.zip | 1.33 KB | ||
| 5. Merging data frames and use apply function.mp4 | 32.34 MB | ||
| 5.1 Pandas Merge and using apply function.zip | 3.52 KB | ||
| 4. Working with Spark Data Frames | |||
| 1. Loading data from Oracle to Spark Data frame.mp4 | 24.18 MB | ||
| 1.1 SparkOracle.py | 743 B | ||
| 2. Loading data from Oracle to Spark Data frame 2.mp4 | 13.66 MB | ||
| 3. Spark Data frames basics.mp4 | 34.85 MB | ||
| 3.1 Spark.zip | 3.49 KB | ||
| 4. Working with user defined functions.mp4 | 37.92 MB | ||
| 4.1 TestUDF.py | 1.5 KB | ||
| 5. Group by and sorting.mp4 | 42.13 MB | ||
| 5.1 SparkGroupby.zip | 4.09 KB | ||
| 6. Pandas and Spark Quiz.mp4 | 1.03 MB | ||
| 6.1 Quiz.pptx | 132.09 KB | ||
| 6.2 QuizCSV.csv | 4.43 KB | ||
| 7. Quiz Answer.mp4 | 145.76 KB | ||
| 7.1 bankdata.py | 2.17 KB | ||
| 5. Working with Celery Pipeline Framework | |||
| 1. When Using Queues.mp4 | 14.03 MB | ||
| 2. Using Oracle Queue to call Send SMS Web Service.mp4 | 17.58 MB | ||
| 2.1 Oracle_Queues.SQL | 3.83 KB | ||
| 3. Using celery to call Send SMS Function.mp4 | 25.37 MB | ||
| 3.1 Celery_SMS.zip | 1.07 KB | ||
| 4. Another Celery Example, Calculate Bank Interest.mp4 | 47.14 MB | ||
| 4.1 Bank_Interest.zip | 4.5 KB | ||
| 5. Adding more Queues and Workers.mp4 | 41.2 MB | ||
| 5.1 Adding more workers.zip | 4.17 KB | ||
| 6. Bouns Section | |||
| 1. Using Kafka JDBC Connector with Oracle DB (Doc Only).mp4 | 1.03 MB | ||
| 1.1 Oracle_Consumer.py | 1.21 KB | ||
| 1.2 Script.txt | 1.66 KB | ||
| 1.3 Kafka_With_Oracle.pdf | 235.71 KB |
Description
Обучающие видео » Компьютерные видеоуроки и обучающие интерактивные DVD » Программирование (видеоуроки)
Python Celery for Distributed Tasks and Parallel Programming
Год выпуска: 2020
Автор: Tarek Abulnaga
Продолжительность: ~3h
Тип раздаваемого материала: Видеоурок
Язык: Английский
Описание: Learn how to Analyze data using Pandas and Spark and how to create background tasks using Celery framework and RabbitMQ
What you'll learn
Pandas and spark for data analysis
Using Queus for parallel programing
Python celery as pipeline framework
Using Kafka JDBC Connector with Oracle DB
Requirements
Basic knowledge of python and SQL
Description
The aim of this course is learning programming techniques to process and analyze data
Data Analysis
Will learn how to load from different data sources (database/files) into data frames, Will learn both pandas data frame and spark date frame
Will learn how to analyze the data (select, filtering, grouping and sorting) These operations will be done without hit the database which Make our analysis extremely faster
Parallel Programming
Insert the functions that need to be called as tasks in queues to be executed in the background while the main program still
This will enhance the performance, as the functions will be executed in parallel not in sequence as traditional programming executing.
Who this course is for:
Python and Oracle developers and students
Файлы примеров: присутствуют
Формат видео: MP4
Видео: AVC, 1280x720, 16:9, 30fps, ~200kbps
Аудио: AAC, 48kHz, 192kbps, stereo
[spoiler="Скриншоты"]
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