CROSS APPLY and OUTER APPLY Examples
Last blog introduced the APPLY operator and covered how it differs from regular JOINs. In today's follow-up, we'll compare the performance of APPLY to that of an INNER JOIN as well as learn how to use APPLY with table valued functions.
Navicat 15 was released with much fanfare back in November of 2019. It came packed with many new features and improvements, most notably in data transfers, the SQL Builder, and modeling. It also added Data Visualization, Dark Mode and native Linux support. Almost two years later to the day, its time to announce the upcoming release of Navicat 16! It's currently downloadable in Beta mode, with the official release to be announced shortly. While we're waiting for that, this blog will outline some of the most note-worthy features and improvements.
Part 1: APPLY vs JOIN
As you are probably aware, JOIN operations in SQL Server are used to join two or more tables. However, in SQL Server, JOIN operations cannot be used to join a table with the output of a table valued function. In case you have not heard of table valued functions, these are functions that return data in the form of tables. In order to allow the joining of two table expressions SQL Server 2005 introduced the APPLY operator. In this blog, we'll learn how the APPLY operator differs from regular JOINs.
Recently, the subject of database indexes has come up a couple of times, specifically, in the The Downside of Database Indexing and The Impact of Database Indexes On Write Operations articles. Both pieces alluded to the fact that relational databases support a number of index types. Today's blog will provide an overview of the most common ones.
Over time, system requirements change. These may necessitate the creation of new databases, tables, and columns as well as the altering of existing table structures. Changing a column's data type may be a trivial operation or a difficult one, depending on the source and target data types, as well as the data contained within the column. This blog will address some of the common challenges in changing a column's data type, along with strategies which you can employ to facilitate the process.
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