Introduction In this article, we are going to see how Index Selectivity works in relational database systems and why the database Optimizer might choose to avoid using an index if the number of matching records is large. Index selectivity is inversely proportional to the number of index entries matched by a given value. So, a unique index has the highest selectivity because only a single entry can be matched by any given value. On the other hand, if column values are skewed, then a column value matching a large number of table... Read More

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Learn how Multi-Valued Indexing in MySQL 8.0 can enhance query performance by efficiently indexing and querying JSON arrays. Discover the benefits, implementation steps, and considerations for optimizing your MySQL database.

1. Multi-Valued Indexing in MySQL 8.0
2. Understanding Multi-Valued Indexes and their benefits
3. Creating Multi-Valued Indexes in MySQL …

Introduction In this article, I’m going to explain how we can index JSON columns when using MySQL. While other relational database systems provide GIN (Generalized Inverted Index) indexes, MySQL allows you to index a virtual column that mirrors the JSON path expression you are interested in indexing. Database table Let’s assume we have the following database book table: The properties column type is json, so we can store JSON objects as book properties. Querying MySQL JSON columns without an index If we try to filter one record by its associated title attribute... Read More

The post How to index JSON columns using MySQL appeared first on Vlad Mihalcea.

A Guest Post from Jordan Raine, Clio

Jordan Raine is a staff software developer at Clio, the leading provider of legal practice management, client relationship management, and client intake software. Clio is dedicated to helping lawyers meet client needs and run efficient, profitable practices. Jordan wrote this post to help mySQL developers save time/effort and ultimately improve their customers' experience. 

Unlike most code a developer writes, writing SQL only requires us to describe what data we want and not how to get it. When given a query like SELECT id, author_id FROM posts WHERE author_id = 123 ORDER BY id, you needn’t concern yourself with what indexes are used (if any), what type of sort is used, or any other number of implementation details. Instead, the query optimizer handles this for you. This keeps SQL concise and …

In my recent post about the Left-Prefix Index Rule, I explained how queries can use all or part of a compound (multi-column) index. Knowing what makes an index fully usable by a query is important, but it's also important to know how to figure out how much of an index a query is able to use. In this article I'll show you how to do this by reading the query's explain plan. This article covers MySQL, Postgres, and MongoDB.

As a quick review, a query can use an index if it has filtering values that constrain a contiguous leading portion of the index, up to and including the first inequality condition in index-column order. Now let's see where the database server exposes how much of the index is used.

MySQL

In MySQL's …

A covering index is a fantastic query performance optimization. An index covers a query when the index has all the data needed to execute the query, so the server can retrieve the query’s data without reading any rows or documents. Covered queries are usually SELECT queries, but in addition to reads, indexes can cover portions of what a write query needs to do its work.

In this article I’ll explain what a covering index is in a bit more detail; the technical implementation and caveats in MySQL, PostgreSQL, and MongoDB; and how to check that a query is using a covering index.

What’s a Covering Index?

A covering index, or index-covered query, doesn’t refer just to an index. Instead, it’s the combination of a query and an index: the index covers the query. An index that covers one query might not cover another query, so “covering” doesn’t solely describe the index, …

MySQL 5.7 comes with built-in JSON support, comprising two major features:

• A native JSON data type
• A set of built-in functions to manipulate values of the JSON type

Despite being added rather recently (in MySQL 5.7.8 to be precise - one point release number before the 5.7.9 GA version), I feel the JSON support so far looks rather useful. Improvements are certainly possible, but compared to for example XML support (added in 5.1 and 5.5), the JSON feature set added to 5.7.8 is reasonably complete, coherent and standards-compliant.

(We can of course also phrase …

This Log Buffer edition transcends beyond ordinary and loop in few of the very good blog posts from Oracle, SQL Server and MySQL.

Oracle:

• Variable selection also known as feature or attribute selection is an important technique for data mining and predictive analytics.
• The Oracle Utilities SDK V4.3.0.0.2 has been released and is available from My Oracle Support for download.
• This article provides a high level list of the new features that exist in HFM 11.1.2.4 and details the changes/differences between HFM 11.1.2.4 and previous releases.
• In recent …

We’ve heard lots in recent years about Big Data and the alternative models of data management and processing, like Hadoop and NoSQL. But truth be told, relational databases are still the workhorses of most of today’s small and medium sized businesses. Relational DBs date back over 40 years and SQL skills are fairly common, and they’re known to be highly secure.

MySQL is the world’s second most popular relational database management system (RDMS) and is the most popular open-source version of the database. It’s easily accessible and is often known to be part of the LAMP web development stack, standing for the ‘M’ in the acronym of popular tools, along with Linux, Apache, and PHP/Perl/Python. The fact that MySQL is free, easy to setup and scales fast are some of the main reasons why it’s the best match for many SMBs.

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What is JSON
JSON is an text based, human readable format for transmitting data between systems, for serializing objects and for storing document store data for documents that have different attributes/schema for each document. Popular document store databases use JSON (and the related BSON) for storing and transmitting data.

Problems with JSON in MySQL
It is difficult to inter-operate between MySQL and MongoDB (or other document databases) because JSON has traditionally been very difficult to work with. Up until recently, JSON is just a TEXT document. I said up until recently, so what has changed? The biggest thing is that there are new JSON UDF by Sveta Smirnova, which are part of the MySQL 5.7 Labs releases. Currently the JSON UDF are up to version 0.0.4. While these new UDF are a welcome edition to the MySQL database, they don't solve the really tough …