Publisher |
Packt Publishing Limited |
Publication Year |
2021 |
ISBN-13 |
9781801819077 |
ISBN-10 |
1801819076 |
Binding |
Paperback |
Number of Pages |
230 Pages |
Language |
(English) |
Weight (grms) |
404 |
Databricks is an industry-leading, cloud-based platform for data analytics, data science, and data engineering supporting thousands of organizations across the world in their data journey. It is a fast, easy, and collaborative Apache Spark-based big data analytics platform for data science and data engineering in the cloud.
In Optimizing Databricks Workloads, you will get started with a brief introduction to Azure Databricks and quickly begin to understand the important optimization techniques. The book covers how to select the optimal Spark cluster configuration for running big data processing and workloads in Databricks, some very useful optimization techniques for Spark DataFrames, best practices for optimizing Delta Lake, and techniques to optimize Spark jobs through Spark core. It contains an opportunity to learn about some of the real-world scenarios where optimizing workloads in Databricks has helped organizations increase performance and save costs across various domains.
Anirudh Kala
Anirudh Kala lives in Ludhiana and is a psychiatrist by profession. His experience as a psychiatrist shows in how he sketches out his characters and their personality traits. This is his second book as a fiction writer, the first being The Unsafe Asylum: Stories of Partition and Madness (2018).
His focus is always to educate people about mental health and mental illness, focusing on eradicating stigma, labels, and prejudice.
Besides his professional passions, Anirudh Kala also likes reading Urdu poetry, hiking, and listening to Indian semi-classical music.
Anirudh Kala
Packt Publishing Limited