I have moved this over to the Tech Interview Cheat Sheet Repo and has been expanded and even has code challenges you can run and practice against!
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package **.******.***.***.util; | |
import java.util.Date; | |
import javax.servlet.http.HttpSession; | |
import javax.servlet.http.HttpSessionEvent; | |
import javax.servlet.http.HttpSessionListener; | |
public class MySessionListener implements HttpSessionListener { |
This article introduces Databricks Delta Lake. A revolutionary storage layer that brings reliability and improve performance of data lakes using Apache Spark.
First, we'll go through the dry parts which explain what Apache Spark and data lakes are and it explains the issues faced with data lakes. Then it talks about Delta lake and how it solved these issues with a practical, easy-to-apply tutorial.
If you don't know what Spark is, Apache Spark is a large-scale data processing and unified analytics engine for big data and machine learning. It was originally developed at UC Berkeley in 2009. Apache Spark is 100% open source, hosted at the vendor-independent Apache Software Foundation.