#SQL Query

[tranquilbird]

I put the queer in SQL query

[sqlsplat]

Understanding the Risks of SQL Server NOLOCK

Admittedly, I use NOLOCK all the time in my queries. But in my defense, most of the queries that I write ad-hoc are returning information that I’m not that concerned about. Using the NOLOCK table hint in SQL Server can have significant implications, both positive and negative, depending on the use case. While it is commonly used to improve performance by avoiding locks on a table, it has several…

[teklink]

Understanding SQL Query Execution: A Data Engineer’s Guide

As data engineers, we work with SQL daily, but how many of us truly understand the inner workings of a SQL query? Knowing the order of execution can significantly improve the way you write SQL queries. Let’s dive into the process with a practical example.

For more information, visit Teklink International LLC

[riczkypratama]

Menggali Lebih Dalam: 5 Fakta Menarik tentang SQL Query

SQL (Structured Query Language) merupakan bahasa pemrograman khusus yang digunakan untuk mengelola dan mengakses basis data relasional. SQL Query adalah perintah atau instruksi yang digunakan untuk berinteraksi dengan basis data. Dalam dunia pengembangan perangkat lunak dan administrasi basis data, SQL Query menjadi landasan utama. Mari kita telaah 5 fakta menarik tentang SQL Query yang dapat memberikan wawasan lebih dalam.

1. Basis Data Relasional dan SQL

SQL Query paling sering digunakan dalam konteks basis data relasional. Basis data relasional menggunakan tabel untuk menyimpan data dan memanipulasinya dengan menggunakan relasi antar tabel. SQL memungkinkan pengguna untuk menentukan, mengakses, dan memanipulasi data dalam tabel-tabel ini dengan mudah melalui Query.

2. DML dan DDL: Perbedaan dalam SQL Query

SQL Query dapat dibagi menjadi dua jenis utama: Data Manipulation Language (DML) dan Data Definition Language (DDL). DML digunakan untuk mengelola data dalam basis data, seperti menambahkan, menghapus, atau memperbarui catatan. Di sisi lain, DDL digunakan untuk mendefinisikan struktur basis data, seperti membuat, mengubah, atau menghapus tabel.

3. Klausa WHERE: Penyaringan Data

Klausa WHERE adalah salah satu elemen kunci dalam SQL Query. Digunakan untuk menyaring data berdasarkan kondisi tertentu, klausa WHERE memungkinkan pengguna untuk mengambil data yang memenuhi kriteria tertentu. Misalnya, SELECT * FROM Tabel WHERE Kolom = Nilai akan mengembalikan baris-baris yang memenuhi persyaratan tersebut.

4. JOIN: Menggabungkan Data dari Berbagai Tabel

JOIN merupakan fungsionalitas penting dalam SQL Query yang memungkinkan pengguna untuk menggabungkan data dari dua atau lebih tabel. Dengan JOIN, kita dapat mengambil data yang berkaitan dari tabel-tabel yang berbeda berdasarkan kolom-kolom yang memiliki nilai yang sama. Ini memungkinkan pengguna untuk membuat kueri yang lebih kompleks dan mendapatkan informasi yang lebih terperinci.

5. Transaksi dan Kepatuhan ACID

SQL Query sering digunakan dalam konteks transaksi basis data. Transaksi adalah serangkaian operasi yang membentuk suatu tindakan tunggal, dan SQL mendukung sifat-sifat transaksi yang dikenal sebagai ACID: Atomicity, Consistency, Isolation, dan Durability. Ini menjamin bahwa operasi-operasi tersebut dapat dijalankan secara aman dan konsisten.

Melalui kekuatannya dalam memanipulasi data dalam basis data relasional, SQL Query menjadi elemen kunci dalam pengembangan aplikasi dan administrasi sistem basis data. Dengan memahami konsep dan fungsionalitas dasar SQL Query, para pengembang dan administrator basis data dapat mengoptimalkan kinerja dan efisiensi operasi mereka.

[willalraand]

Hear me out

A The Beholding ritual but it’s just some guy given some enormous spooky database and they have to come up with as many useful sql views for it

(Doing my databases homework for hours and listening to TMA at the same time does interesting things to my mind and it full on feels like some ritual)

[peachybeesplease]

praying to the patron saint of fake it til you make it at a job you're only halfway qualified for (moist von lipwig)

[smaller-comfort]

thinking about something @ocelly said a while back about writing and editing using different parts of the brain/serving different parts of the creative process- and fundamentally that mindset has been invaluable to me.

unfortunately, my brain has been coasting in editing/refining/polishing mode for a while now and I really need it to shift gears into creative/generative/productive mode. don't get me wrong, I genuinely love the editing process! I'd forgotten how much fun it can be to tease out the right words/meaning from something. I really would have been a very happy copyeditor in another universe.

But there's a whole laundry list of shit that I need done, not polished, and the problem with engaging Editing Brain is that it's hard to convince it that I can live without absolute perfection for a while. You can't polish an empty document, asshole! Get the words on the page first and then worry about the details later.

[neuxue]

I need AO3 search to allow window functions

[technicontrastron]

goddamnit can my coworkers do nothing without chatgpt anymore.

[newcodesociety]

[sqlsplat]

Query to get SQL Server Agent job schedules

Learn how to retrieve SQL Server Agent job schedule details with a powerful query. Perfect for auditing, troubleshooting, or documenting your SQL environment. Check it out and simplify your DBA tasks!

Retrieving SQL Agent Job Schedule Details in SQL Server If you’re working with SQL Server Agent jobs, it’s often useful to have a quick way to retrieve schedule details for all jobs in your system. Whether you’re auditing schedules, troubleshooting overlapping jobs, or simply documenting your environment, having this query on hand can save you a lot of time. Below is a SQL query that returns…

[forever-stuck-on-java-8]

so it turns out they weren't kidding when they said breaking a monolith into microservices is hard.

[tpointtech1]

Essential SQL Queries to Boost Your Data Skills

[govindhtech]

Bigtable SQL Introduces Native Support for Real-Time Queries

Upgrades to Bigtable SQL offer scalable, fast data processing for contemporary analytics. Simplify procedures and accelerate business decision-making.

Businesses have battled for decades to use data for real-time operations. Bigtable, Google Cloud's revolutionary NoSQL database, powers global, low-latency apps. It was built to solve real-time application issues and is now a crucial part of Google's infrastructure, along with YouTube and Ads.

Continuous materialised views, an enhancement of Bigtable's SQL capabilities, were announced at Google Cloud Next this week. Maintaining Bigtable's flexible schema in real-time applications requires well-known SQL syntax and specialised skills. Fully managed, real-time application backends are possible with Bigtable SQL and continuous materialised views.

Bigtable has gotten simpler and more powerful, whether you're creating streaming apps, real-time aggregations, or global AI research on a data stream.

The Bigtable SQL interface is now generally available.

SQL capabilities, now generally available in Bigtable, has transformed the developer experience. With SQL support, Bigtable helps development teams work faster.

Bigtable SQL enhances accessibility and application development by speeding data analysis and debugging. This allows KNN similarity search for improved product search and distributed counting for real-time dashboards and metric retrieval. Bigtable SQL's promise to expand developers' access to Bigtable's capabilities excites many clients, from AI startups to financial institutions.

Imagine AI developing and understanding your whole codebase. AI development platform Augment Code gives context for each feature. Scalability and robustness allow Bigtable to handle large code repositories. This user-friendliness allowed it to design security mechanisms that protect clients' valuable intellectual property. Bigtable SQL will help onboard new developers as the company grows. These engineers can immediately use Bigtable's SQL interface to access structured, semi-structured, and unstructured data.

Equifax uses Bigtable to store financial journals efficiently in its data fabric. The data pipeline team found Bigtable's SQL interface handy for direct access to corporate data assets and easier for SQL-savvy teams to use. Since more team members can use Bigtable, it expects higher productivity and integration.

Bigtable SQL also facilitates the transition between distributed key-value systems and SQL-based query languages like HBase with Apache Phoenix and Cassandra.

Pega develops real-time decisioning apps with minimal query latency to provide clients with real-time data to help their business. As it seeks database alternatives, Bigtable's new SQL interface seems promising.

Bigtable is also previewing structured row keys, GROUP BYs, aggregations, and a UNPACK transform for timestamped data in its SQL language this week.

Continuously materialising views in preview

Bigtable SQL works with Bigtable's new continuous materialised views (preview) to eliminate data staleness and maintenance complexity. This allows real-time data aggregation and analysis in social networking, advertising, e-commerce, video streaming, and industrial monitoring.

Bigtable views update gradually without impacting user queries and are fully controllable. Bigtable materialised views accept a full SQL language with functions and aggregations.

Bigtable's Materialised Views have enabled low-latency use cases for Google Cloud's Customer Data Platform customers. It eliminates ETL complexity and delay in time series use cases by setting SQL-based aggregations/transformations upon intake. Google Cloud uses data transformations during import to give AI applications well prepared data with reduced latency.

Ecosystem integration

Real-time analytics often require low-latency data from several sources. Bigtable's SQL interface and ecosystem compatibility are expanding, making end-to-end solutions using SQL and basic connections easier.

Open-source Apache Large Table Washbasin Kafka

Companies utilise Google Cloud Managed Service for Apache Kafka to build pipelines for Bigtable and other analytics platforms. The Bigtable team released a new Apache Kafka Bigtable Sink to help clients build high-performance data pipelines. This sends Kafka data to Bigtable in milliseconds.

Open-source Apache Flink Connector for Bigtable

Apache Flink allows real-time data modification via stream processing. The new Apache Flink to Bigtable Connector lets you design a pipeline that modifies streaming data and publishes it to Bigtable using the more granular Datastream APIs and the high-level Apache Flink Table API.

BigQuery Continuous Queries are commonly available

BigQuery continuous queries run SQL statements continuously and export output data to Bigtable. This widely available capability can let you create a real-time analytics database using Bigtable and BigQuery.

Python developers may create fully-managed jobs that synchronise offline BigQuery datasets with online Bigtable datasets using BigQuery's Python frameworks' bigrames streaming API.

Cassandra-compatible Bigtable CQL Client Bigtable is previewed.

Apache Cassandra uses CQL. Bigtable CQL Client enables developers utilise CQL on enterprise-grade, high-performance Bigtable without code modifications as they migrate programs. Bigtable supports Cassandra's data migration tools, which reduce downtime and operational costs, and ecosystem utilities like the CQL shell.

Use migrating tools and Bigtable CQL Client here.

Using SQL power via NoSQL. This blog addressed a key feature that lets developers use SQL with Bigtable. Bigtable Studio lets you use SQL from any Bigtable cluster and create materialised views on Flink and Kafka data streams.

[joneswebgoods]

Learn SQL Easy

If you're interested in learning SQL (Structured Query Language), the standard database access language, try learning from a place called SQL Easy. They provide a great self-learning environment where you can learn this language or troubleshoot how to code something.

I'm still learning SQL, even after using it for a few years. I came here looking for a code to pull records within a 7-day span and used this page here: https://www.sql-easy.com/learn/how-to-get-last-7-days-record-in-postgresql/

[sizzlingcreatorcycle]

Learn SQL Easily with Takeoff Upskill and Build Your Data Skills

SQL (Structured Query Language) is one of the most important skills for anyone working with data. At Takeoff Upskill, we offer a comprehensive SQL course that makes learning this valuable skill easy and accessible. Whether you are a beginner or someone looking to enhance your database knowledge, this course is designed to meet your needs.

Our SQL course starts with the basics, such as understanding databases, tables, and data types. You will learn how to create, read, update, and delete data using SQL commands. The course also covers advanced topics like joining multiple tables, writing complex queries, and optimizing database performance. These skills are essential for roles like data analyst, software developer, and database administrator.

The training at Takeoff Upskill is practical and hands-on. We provide real-world examples and exercises that help you understand how SQL is used in businesses. By the end of the course, you will be confident in writing queries, managing data, and solving database challenges. Our experienced trainers guide you every step of the way, ensuring you gain a strong foundation.