Tag: query

Feed: Planet MySQL; Author: Oracle MySQL Group; MySQL Query Optimization is usually simple engineering. But seeking information about how to tune queries is treated on many web reference sites like some Harry Potter-ish spell casting. There are simple tips you need to be aware of to get the best of your queries ... Read More

Feed: Planet MySQL; Author: Oracle MySQL Group; Performance issues are often stubborn things to cure. Suddenly a query or operation seems slow, or slower-ish. Sadly, the database is often pointed at as the culprit by developers who are either positive their code cannot be at fault or those who see databases as a mysterious box that does odd things ... Read More

Feed: Planet MySQL; Author: Daniel Nichter; Chapter 1 Jan 16, 2022 Editors and technical reviewers suggested that I cover how to configure MySQL query metrics in chapter 1 of Efficient MySQL Performance, but I deferred because it was out of scope for the book, which focuses on engineers using MySQL, not DBAs. As such, there’s only a note in chapter 1 that says: “Ask your DBA or read the MySQL manual.” But I’ll cover the topic here because that’s what this blog post series is for: behind the book. This blog post is the second of eleven: one for the ... Read More

Feed: Recent Announcements. Amazon Kendra is an intelligent search service powered by machine learning. Today, we are excited to announce Kendra’s support for query language, allowing customers to use more advanced search terminology and techniques when needed, to retrieve more precise answers. With Amazon Kendra’s query language, customers can now query Amazon Kendra using advanced query syntax and operators. For example, you can use familiar operators such as OR, AND, NOT, (e.g. “history” AND “movies” NOT “fiction” to find documents about historical movies, but exclude documents about historical fiction movies), specify field-level matches (e.g. “author: John Doe”), and perform range ... Read More

Feed: Planet PostgreSQL. Jupiter's moon Io. Credit: ALMA (ESO/NAOJ/NRAO), I. de Pater et al.; NRAO/AUI NSF, S. Dagnello; NASA/JPL/Space Science InstituteSQL query optimization is challenging for those who have just started working with PostgreSQL. There are many objective reasons for this, such as:the difficulty of the field of system performance in general,lack of good "playground" environments where people can experience how databases work at a larger scale,lack of certain capabilities in Postgres observability tools that are still developing (though, at a good pace),insufficiency of good educational materials.All these barriers are reasonable. They limit the number of engineers possessing well-developed Postgres ... Read More

Feed: AWS Big Data Blog. Amazon Redshift materialized views enable you to significantly improve performance of complex queries that are frequently run as part of your extract, load, and transform (ELT), business intelligence (BI), or dashboarding applications. Materialized views precompute and store the result sets of the SQL query in the view definition. Materialized views speed up data access, because the query doesn’t need to rerun the computation each time the query runs, which also reduces the resource consumption. Amazon Redshift has the ability to automatically rewrite your SQL queries that don’t explicitly reference existing materialized views to use an ... Read More

Feed: Planet PostgreSQL. Published: Mon 03 January 2022 tags: postgresql If this were YouTube, the thumbnail would look something like this But seriously. Is there any way to monitor long running Postgres queries? Kinda! Using sequences. The Setup We create two tables. One small and one big. DROP TABLE IF EXISTS small; CREATE TABLE small ( some_val int ); INSERT INTO small SELECT gs FROM generate_series(1, 100) AS gs; DROP TABLE IF EXISTS big; CREATE TABLE big ( other_val int ); INSERT INTO big SELECT gs % 100 + 1 FROM generate_series(1, 50000000) AS gs; CREATE INDEX ON big (other_val); ... Read More

Feed: Planet NoSQL. Author: Keshav Murthy.  Use N1QL when you're in a JSON pickle. - ConfuciusFor the JSON data model, the general advice is to think of collections as tables, JSON documents as denormalized rows, and field names as columns — roughly. All this holds true in databases like Couchbase and MongoDB when recommendations are strictly followed. There are many reasons why users don't simply follow this key-value pair model all the time. Here are the main reasons:You want to convert a map/hashmap data structure where the keys are dynamic.Timeseries data when the field names are usually encoded timestamps.Dictionary based encoding.Existing document ... Read More

Feed: AWS Big Data Blog. Many AWS customers rely on a multi-account strategy to scale their organization and better manage their data lake across different projects or lines of business. The AWS Glue Data Catalog contains references to data used as sources and targets of your extract, transform, and load (ETL) jobs in AWS Glue. Using a centralized Data Catalog offers organizations a unified metadata repository and minimizes the administrative overhead related to sharing data across different accounts, thereby expanding access to the data lake. Amazon Athena is one of the popular choices to run analytical queries in data lakes ... Read More

Feed: Planet PostgreSQL. 1. Introduction Few weeks ago, I was tasked to have a detailed look inside PostgreSQL’s extended query protocol and study its internal mechanisms for a project that depends on this particular feature. In this blog, I will explain how extended protocol works in my own words and how it differs from simple query. 2. Simple Query A client is able to initiate 2 type of queries against a PostgreSQL server, simple query or extended query. Simple query, as the name suggests, is very simple and straightforward to understand. When we launch the psql client tool to connect ... Read More