Distributed Computing with Spark SQL
Learn SQL Basics for Data Science,
This course is all about big data. It’s for students with SQL experience that want to take the next step on their data journey by learning distributed computing using Apache Spark. Students will gain a thorough understanding of this open-source standard for working with large datasets. Students will gain an understanding of the fundamentals of data analysis using SQL on Spark, setting the foundation for how to combine data with advanced analytics at scale and in production environments. The four modules build on one another and by the end of the course you will understand: the Spark architecture, queries within Spark, common ways to optimize Spark SQL, and how to build reliable data pipelines. The first module introduces Spark and the Databricks environment including how Spark distributes computation and Spark SQL. Module 2 covers the core concepts of Spark such as storage vs. compute, caching, partitions, and troubleshooting performance issues via the Spark UI. It also covers new features in Apache Spark 3.x such as Adaptive Query Execution. The third module focuses on Engineering Data Pipelines including connecting to databases, schemas and data types, file formats, and writing reliable data. The final module covers data lakes, data warehouses, and lakehouses. Students build production grade data pipelines by combining Spark with the open-source project Delta Lake. By the end of this course, students will hone their SQL and distributed computing skills to become more adept at advanced analysis and to set the stage for transitioning to more advanced analytics as Data Scientists.
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| Rating | 3.7★ based on 4 ratings |
|---|---|
| Length | 5 weeks |
| Effort | 4 weeks of study, 2-5 hours/week |
| Starts | Jul 3 (46 weeks ago) |
| Cost | $49 |
| From | University of California, Davis via Coursera |
| Instructors | Brooke Wenig, Conor Murphy |
| Download Videos | On all desktop and mobile devices |
| Language | English |
| Subjects | Data Science Programming |
| Tags | Data Science Data Analysis Machine Learning |
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What people are saying
executing pieces of available
Executing pieces of available course without sufficient practice This has been an amazing course.
available course without sufficient
very superficial using databricks
very superficial using databricks.
highly recommended for anyone
Highly recommended for anyone who is new to Spark Extremely informative for those who are seeking to learn the fundamentals for distributed computing using Spark SQL.
fundamentals for distributed computing
content was delivered
What is worth mentioning is how the content was delivered.
courses misses depth
The courses misses depth to be of any use.
video quality needs
video quality needs to be improved.
databricks commercial
It is more a Databricks commercial.
nice hands
Nice hands on.
any use
careful about
Be careful about the last assignment.
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| Rating | 3.7★ based on 4 ratings |
|---|---|
| Length | 5 weeks |
| Effort | 4 weeks of study, 2-5 hours/week |
| Starts | Jul 3 (46 weeks ago) |
| Cost | $49 |
| From | University of California, Davis via Coursera |
| Instructors | Brooke Wenig, Conor Murphy |
| Download Videos | On all desktop and mobile devices |
| Language | English |
| Subjects | Data Science Programming |
| Tags | Data Science Data Analysis Machine Learning |
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