SQL

SQL Server: key-value store table and hash index

Hash indexes are used as entry points for memory-optimized tables; both features were introduced in SQL Server 2014. Let's look at index performance in scenario "key-value store".

Scenario and environment

The table stores a significant volume (about 10 millions rows) of pairs key-value. The key is of integer type and the value is a small random string.

The table store is used :

  • random read of a value from a key
  • random update of a value by a key

We will tests the scenario for the following types of table :

SQL: generate random character string

Collection of methods to generate random string in a single SQL statement

M1: Recursive string concatenation

On SQL Server the method is limited by 100 characters owing to the recursion level limitation. The method has the performance issues when using in loops/joins because the table always have 100 rows generated every time.

Types of joins in SQL (cheatsheet for beginners)

This article is used in my book "Programming with databases".

Better to see once than to hear a hundred times. This small article explains what are the different kinds of joins in SQL.

At the first time you should take into account that SQL is a declarative 4th generation language. So the best way to use it (especially for beginners) is to write the query and let SQL optimizer do its job. That means thinking in set-oriented terms and avoiding sub-queries.

Let's take two example tables: Companies and Contacts.

SQL: generate date/time series

There are many examples of user defined table functions generating the series of dates(times) between two specified values. Usually, in OLAP you can see a table filled by the date/time series, too. Such table avoid to generate the values "on the fly".

However, in some cases you may be unable to use an UDF or a table. Fortunately, "pure SQL" method still works.

Suppose, the start and finish dates are specified as entry parameters. The transact SQL code below generates the series "moth by month".

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