Bookmarks Delta Lake with Apache Spark using Scala

Delta Lake with Apache Spark using Scala
Delta Lake with Apache Spark using Scala
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Delta Lake with Apache Spark using Scala | Size: 678 MB

What you'll learn
You will be able to learn Delta Lake with Apache Spark in few hours
Basics to Advance Level of Knowledge about Delta Lake
Hands on practice with Delta Lake
You will Learn Delta Lake with Apache Spark using Scala on DataBricks Platform
Learn how to leverage the power of Delta Lake with a Spark Environment!
Learn about the DataBricks Platform!
Apache Spark and Scala and SQL basic knowledge is necessary for this course
You will Learn Delta Lake with Apache Spark using Scala on DataBricks Platform
Learn the latest Big Data Technology - Spark! And learn to use it with one of the most popular programming languages, Scala!
One of the most valuable technology skills is the ability to analyze huge data sets, and this course is specifically designed to bring you up to speed on one of the best technologies for this task, Apache Spark! The top technology companies like Google, Facebook, Netflix, Airbnb, Amazon, NASA, and more are all using Spark to solve their big data problems!
Spark can perform up to 100x faster than Hadoop MapReduce, which has caused an explosion in demand for this skill! Because the Spark 3.0 DataFrame framework is so new, you now have the ability to quickly become one of the most knowledgeable people in the job market!
Delta Lake is an open-source storage layer that brings reliability to data lakes. Delta Lake provides ACID transactions, scalable metadata handling, and unifies streaming and batch data processing. Delta Lake runs on top of your existing data lake and is fully compatible with Apache Spark APIs.
Apache Spark is a fast and general-purpose cluster computing system. It provides high-level APIs in Java, Scala, Python and R, and an optimized engine that supports general execution graphs. It also supports a rich set of higher-level tools including Spark SQL for SQL and structured data processing, MLlib for machine learning, GraphX for graph processing, and Spark Streaming.
Topics Included in the Courses
Introduction to Delta Lake
Introduction to Data Lake
Key Features of Delta Lake
Introduction to Spark
Free Account creation in Databricks
Provisioning a Spark Cluster
Basics about notebooks
Create a table
Write a table
Read a table
Schema validation
Update table schema
Table Metadata
Delete from a table
Update a Table
Concurrency Control
Optimistic concurrency control
Migrate Workloads to Delta Lake
Optimize Performance with File Management
Auto Optimize
Optimize Performance with Caching
Delta and Apache Spark caching
Cache a subset of the data
Isolation Levels
Best Practices
Frequently Asked Question in Interview
About Databricks:
Databricks lets you start writing Spark code instantly so you can focus on your data problems.
Who this course is for:
Beginner Apache Spark Developer, Bigdata Engineers or Developers, Software Developer, Machine Learning Engineer, Data Scientist, Data Analyst, Analyst

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