Spring Framework
Q. What is Spring Framework? A. The Spring Framework is lightweight, non-intrusive framework, providing the tools and facilities to write standalone,testable components for use in many common applications and scenarios.Spring...
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Top RatedDelta Table in Azure Databricks
Delta Table in Azure Databricks Delta Tables in Azure Databricks leverage the Delta Lake technology to provide ACID transactions, time travel, and other advanced features for data reliability and performance. These tables can be...
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LatestJava LTS Versions Compared (Java 8 to Java 25): Features, Support Timeline & Upgrade Guide
Java LTS Versions Comparison Java’s Long-Term Support (LTS) releases define the foundation of modern enterprise software. From Java SE 8 (2014) to Java SE 25 (2025), the platform has evolved significantly — improving...
Java LTS Versions Compared (Java 8 to Java 25): Features, Support Timeline & Upgrade Guide
Java LTS Versions Comparison Java’s Long-Term Support (LTS) releases define the foundation of modern enterprise software. From Java SE 8 (2014) to Java SE 25 (2025), the platform has evolved significantly — improving...
Read MoreEmail Notifications in ADF
In Azure Data Factory (ADF), you can set up email notifications to alert users when certain events occur, such as the success or failure of a pipeline or trigger execution. Here’s how you can implement it: 1. Using Logic Apps...
Read MoreTriggers in ADF
In Azure Data Factory (ADF), triggers are used to schedule and automate pipeline execution. They allow pipelines to run on specific schedules, in response to events, or when manually invoked. Triggers help orchestrate and manage...
Read Moreload data from on-premise to Databricks
To transfer data from an on-premise system to Databricks, you need to establish secure connectivity between your on-premise infrastructure and the Databricks environment. After setting up the connection, you can use Databricks...
Read MorePartitioning vs Bucketing in Hive and Spark
In big data ecosystems like Hive and Apache Spark, partitioning and bucketing are powerful techniques used to organize data for better performance during query execution. While both aim to optimize data access, they work...
Read MoreData Science and Technologies used
Here’s a table detailing key components of Data Science and the technologies commonly used: Data Science Component Description Technologies Used Data Collection Gathering raw data from various sources. SQL, MongoDB, APIs, Web...
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