
What is Apache Spark – explained using mind maps
This blog post introduces the basic of Apache Spark concepts, with an overview of Resilient Distributed Datasets (RDD), DataFrames and more.
This blog post introduces the basic of Apache Spark concepts, with an overview of Resilient Distributed Datasets (RDD), DataFrames and more.
A comprehensive post on Materialized views in Redshift focused on its best features such as auto rewriting, limitations and best practices
Coalesce means to combine! Redshift Coalesce is a conditional expression which returns the first non-null value from multiple input values. The beauty of coalesce is,
This post on Redshift date functions is intended to simplify the core list of date functions. The 15 date functions with examples are the most
Amazon Redshift is more than just an optimized relational database, able to handle structured, unstructured and semi-structured data
SQL How to Add a column explained using DROP, ALTER, CTAS and CREATE methods. 4 examples to sql add column in a database agnostic way
Athena SQL is the query language used in Amazon Athena to interact with data in S3. Mastering Athena SQL is not a monumental task if
The less is more approach to Redshift data types. Focus on these 14 character, numeric, datetime and boolean data types in Redshift.
Learn how to use CloudFormation parameters in your template. Master the basics of CloudFormation parameter types & properties from examples.
This post elaborates on Apache Spark transformation and action operations by providing a step by step walk through of Spark examples in Scala. Before you
Aah…. duplicates! They are everywhere! Look around you – multiple charger cables, headphones, pictures in your smartphone! But we are not here to talk about
In this blog post, let us look at some Redshift Create Table Examples, 10 to be exact ! However, before we get started, what exactly
In this post we will address Spark SQL Date Functions, its syntax and what it does. There are 28 Spark SQL Date functions, meant to
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