#SQLDataBase

[madesimplemssql]

LCK_M_IS Wait Type: A Complete Manual

https://madesimplemssql.com/lck-m-is-wait-type/

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[asadmukhtarr]

MySQL is an open-source relational database management system (RDBMS) that is widely used for storing, managing, and retrieving data efficiently. It is one of the most popular database systems, known for its speed, reliability, and ease of use. MySQL is commonly used in web development, powering applications such as WordPress, Facebook, and many others.

[simple-logic]

Is your SQL database lagging behind? Discover why performance tuning is crucial for maintaining speed and efficiency. This blog explores how optimizing SQL databases can reduce bottlenecks, enhance queries, and improve overall performance. Ensure seamless operations with expert tuning techniques and take your database performance to the next level! 🔧📊

[govindhtech]

Boost the Performance of Amazon Databases with Intel VCPUs

VCPUs

Databases have powered websites, apps, and more for years, but organizations are facing an unprecedented amount of data from various sources. Companies are keeping more data than ever for  AI, business analytics, and applications. To process more data, more databases and faster performance are needed. Companies run these databases in the cloud for flexibility, scalability, and accessibility.

While using a public cloud like Amazon Web Services (AWS) has benefits, choosing instances and configuring them may be difficult. This blog discusses new Amazon Elastic Cloud Compute (EC2) instances with 4th Gen Intel Xeon Scalable  CPUs and how databases run on them. They also provide database configuration tips and methods.

An Overview of AWS

AWS still dominates the public cloud industry with 31% market share in February 2024. AWS’s huge selection of services and products can make choosing the correct database workload configuration difficult, even if your firm already runs workloads and applications there.

With numerous instance families, each with 22 offerings and fully-managed database services, it can be hard to choose the best performance or cost-effective solution. They’ll give a high-level overview of the solutions most likely to meet database workload needs, then we’ll dig into particular database types with performance data and details.

Quick overview of Amazon EC2 instance families. AWS has top-level instance categories depending on workload optimization. General Purpose, Compute, Memory, and HPC Optimized. You’ll likely choose General Purpose, Memory Optimized, or Storage Optimized depending on your database.

The next level of categorization within each wide optimization family is processor vendor (Intel or Graviton) and processor generation (3rd Gen or 4th Gen Intel Xeon). Finally, some categories address unique needs. M7i-flex instances reduce money but don’t guarantee maximum performance, while M5n instances increase network bandwidth caps.

The performance tests below show how processor generation affects database workload performance. Choosing an instance size or vCPUs count is the final step. They provide database benchmark results at various instance sizes to aid your decision. To choose the right size instance, consider our database workload’s average and peak usage.

When choosing a cloud option, remember that while cloud possibilities may seem unlimited, each has certain configuration parameters, many of which are fixed. For instance, your task may require few vCPUs but fast networks. In almost every instance family, smaller instances have lower network bandwidth restrictions.

Instances also limit disc attachments and storage bandwidth. You may unintentionally buy a high-performance storage volume only to discover that your instance uses 20% of it. Smaller instances may only guarantee maximum performance for 30 minutes. When you find an instance that meets your needs, study the footnotes and tiny print to avoid stifling performance or inflating prices.

AWS Databases

Let’s conclude with managed database services like Amazon RDS. These services are popular because they give AWS more environment management. Users must execute OS updates, database installation and updates, database backups, and other operations with Amazon EC2 instances. AWS handles those tasks with RDS, freeing clients to control the application. Their performance tests did not use managed database services, however clients can choose which instance to host their database in. Knowing which instances perform best is still useful.

However, managed database services usually offer a limited number of Amazon EC2 instances. As of this writing, the AWS console drop-down selection to build a PostgreSQL database with RDS does not offer any instances with the latest CPU from any vendor. Read on to learn how instances effect database performance, whether you use infrastructure-as-a-service or RDS.

MySQL/PostgreSQL Performance

Over the past decade, MySQL and PostgreSQL have been among the top five databases. About every firm, regardless of industry, employs several transactional databases to store customer, employee, website backend, and other data. Many usage and performance needs differ, but many databases function best with gobs of RAM and/or high-speed storage.

They used memory-optimized Amazon EC2 R-series instances for PostgreSQL and MySQL performance tests because they have greater memory per vCPUs. Newer instances with stronger  CPUs improve transactional database performance independent of instance size, according to testing.

The HammerDB database benchmark was used by Principled Technologies to test PostgreSQL. Report contains comprehensive test findings. In PostgreSQL tests, memory-optimized R7i instances with 4th Gen Intel Xeon Scalable processors had 1.138 times as many new orders per minute as R6i instances with 3rd Gen processors.

A higher database throughput can signify different things based on your needs. It may involve supporting more users if usage has increased. It could help you handle peak usage without slowing down. It could let you fit more databases on one instance, saving instance expenses over time. Choosing the correct MySQL and PostgreSQL instance is vital to keeping up with expanding user engagement on budget.

MongoDB Speed

MongoDB, a NoSQL database that stores data as documents, has approximately 50,000 customers and is more flexible than table-based relational databases. Users deploy these databases in dispersed clusters for resilience. This distribution allows you to cluster smaller instances instead of using one large instance for a large transactional database.

Their Yahoo!  Cloud Serving Benchmark (YCSB) tests ran on smaller instances from four to sixteen vCPUs to simulate the common use case. C-series compute-optimized instances were chosen to demonstrate performance for database applications that use less memory.

Figure 3: Amazon EC2 C7i instances with 4th Gen Intel Xeon Scalable processors vs. C6i instances with 3rd Gen; normalized MongoDB YCSB throughput.

Performance Redis

Redis, an open-source, in-memory database, can cache and stream data. Redis databases are memory-limited but durable with regular writes to storage. Memory-optimized instances with larger RAM-to-vCPUs ratios would be desirable, however we ran their Redis Memtier benchmark tests on 4 vCPUs General Purpose M-series to simulate smaller Redis applications. These may indicate a minor company or application within a larger corporation.

Their studies indicate how newer instances affect performance, as with other database formats. The 4th Gen Intel Xeon Scalable processor-powered m7i.xlarge instance outperformed the two-generation-older m5.xlarge instance by 1.57 times and the previous-generation m6i.xlarge instance by 1.26 times.

Normalized Redis Memtier throughput on Amazon EC2 M7i instances with 4th Gen Intel Xeon Scalable processors vs. M6i and M5 instances with 3rd and 2nd Gen  CPUs.

Conclusion

There are many factors to consider while hosting database applications on AWS. They have proved that choosing the latest hardware will benefit your workloads for the three databases examined by Intel or a third party. Choose AWS database instances with 4th Gen Intel Xeon Scalable CPUs to save money, support peak times, or allow for growth.

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[techpointfundamentals]

CSV Parameter in SQL Stored Procedure:

How can you return the matching records for passed csv parameter from the stored procedure?

[copperchips]

Connecting Data in Power BI

You can also connect to a range of cloud-based data sources, such as Azure SQL Database, Azure Blob Storage, and Salesforce. 

[genaideepneuron]

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[asdfint]

Championing knowledge, celebrating diversity #ICDS2024 🌍📚 #IntCongress at #Thailand #dbms #sql #database #sqldeveloper #sqldatabase #api #manualtesting #selenium #mariadb #qspiders #kotlin #flutter #qatesting #pyspiders #istqbcertification #cplusplusprogramming...

[bharathtsofttech]

✍Join Now: https://bit.ly/3rp0W84 👉Attend Free Demo On Fullstack Java by Real Time Industrial Experts.

javafullstack #java #corejava #training #softwaredeveloper #javadevelopment #development #bestitjobs #gethired #getplaced #getskilled #congratulations #successful #sqldatabase #javadeveloper #javaprogramming #html #javascriptdeveloper #javafullstackdeveloper #softwareengineer #javascript #itjobs #recruitment #placement #reactjs #devops #automationtesting #developer #selenium #aws

[pypatshala]

Top 30 SQL Most Important SQL Queries for Beginners

1. #SQLQueries 2. #BeginnerSQL 3. #DatabaseQueries 4. #SQLForBeginners 5. #LearnSQL 6. #SQLTutorial 7. #SQLTips 8. #DatabaseProgramming 9. #SQLBasics 10. #SQLBeginnerGuide 11. #DatabaseManagement 12. #SQLTraining 13. #SQLFundamentals 14. #QueryWriting 15. #StructuredQueryLanguage 16. #SQLSyntax 17. #SQLExamples 18. #SQLProgramming 19. #DatabaseDevelopment 20. #SQLDatabases 21. #SQLQueryExamples 22. #SQLQueryTutorials 23. #SQLQueryPractice 24. #SQLDatabaseManagement 25. #DatabaseQueriesForBeginners 26. #SQLQueryExplained 27. #DatabaseManagementForNewbies 28. #SQLDatabaseTutorial 29. #LearnSQLQueries 30. #SQLHelpForBeginners

[vlruso]

Talk to Your SQL Database Using LangChain and Azure OpenAI

Excited to share a comprehensive review of LangChain, an open-source framework for querying SQL databases using natural language, in conjunction with Azure OpenAI's gpt-35-turbo model. This article demonstrates how to convert user input into SQL queries and obtain valuable data insights. It covers setup instructions and prompt engineering techniques for improving the accuracy of AI-generated results. Check out the blog post [here](https://ift.tt/s8PqQCc) to dive deeper into LangChain's capabilities and learn how to harness the power of natural language processing. #LangChain #AzureOpenAI #SQLDatabase #NaturalLanguageProcessing List of Useful Links: AI Scrum Bot - ask about AI scrum and agile Our Telegram @itinai Twitter -  @itinaicom

[madesimplemssql]

Replication provides a facility to create a mechanism to copy data/database objects from one SQL instance to another while ensuring consistency. Let's Explore Deeply:

https://madesimplemssql.com/top-50-replication-interview-questions/

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[dat-a-queenblog]

Update🌸

All gearing up myself for dbms final lab exam.Need to practise all sql queries from scratch.Also feeling so fresh today after a very long time....💕

[thelightinglamp]

SQL is everywhere, from small-scale Industries to large-scale Industries. Companies like Google, Instagram, Quora, and other tech company use SQL to query data. Is SQL is still in demand? Indeed advertised more than 30,000 job vacancies by 2021. 57% of Data Analyst jobs demand SQL as a primary skill. According to Stack over flow’s 2020 developer survey, SQL is the most popular language among PHP, Java, JavaScript, Python, C, and C++. Practicing is the best way to learn SQL. Here, The Lighting Lamp gives you practical sessions with live projects and a Superior Learning Experience. Because we know learning SQL is valuable and essential to start a career in data.

[govindhtech]

Pinecone’s Vectors, Empowered by Spanner’s PostgreSQL

Pinecone’s vectors database that is is powered by Spanner’s well-known PostgreSQL Pinecone provides a fully managed, scalable, and user-friendly vector search engine with one of the top vector databases. Her vector database powers several apps and is used by a diverse clientele that includes Fortune 500 firms and startups. They moved Pinecone’s fundamental database engine to Spanner recently; here is her experience.

Why would Spanner do this?

With tens of thousands of active users at any one moment, her free-tier offering depends on a highly scalable, multitenant design that lowers storage costs without compromising user experience. Pointers and manifests holding a uniform view of the index make up each index’s data plane metadata. Since the metadata is accessed via the crucial read route,he had to store it in a highly accessible database that offered low-latency point reads. More precisely, thought that Spanners read replicas and its millisecond read latencies in the single digits could guarantee that would consistently have low latency in the crucial route for search queries.

Additionally, a transactionally-sense SQL database that could grow in any dimension was what were searching for. In addition to present multi-tenant workloads, They required this to enable unannounced future services in the rapidly advancing AI sector. Along with having very high durability and effective read/write speed, it also required to be free from the operational overhead of failover, scalability, and sharding management. Any database They selected had to be able to manage the three orders of magnitude scaling that anticipated being necessary for Pinecone’s free tier over the next year, all the while being reasonably priced.

Spanner fulfills every one of these requirements. In addition to offering great availability and endurance, it is also highly scalable and reasonably priced. Moreover, Spanner’s PostgreSQL interface is portable and comfortable. Spanner’s recently achieved significant price-performance improvements, which sweetened the pot for us. They now provide no-change pricing, up to 50% more throughput, 2.5 times more storage per node, and reduced latency.

In order to sum up, Google Cloud has proved to be a fantastic collaborator. They are constantly traveling up with fresh concepts and displays to make it simple for business to establish and operate her company. he can’t wait to see where his collaboration goes in the future.

Methodology of migration

Prior to using Spanner, already had a free tier offering, so he had to carefully manage the migration to make sure he gave users the best experience possible while gaining confidence in using Spanner at a larger scale in production.

They created feature flagging to direct a small percentage of signups to the new tier after creating, testing, and benchmarking the new free-tier architecture using Spanner PostgreSQL. Then, in order to guarantee a favorable user experience and predicted cost-of-goods-sold (COGS), They devoted weeks to scrutinizing key performance indicators (KPIs).

As a result of gradual increase in traffic, the new Spanner-based multitenant architecture is now automatically used by all newly registered free tier customers.

Her expenditures to maintain the free tier have decreased by ten times, and now have close to 40,000 customers using this architecture in production. The general user experience has also improved.

In conclusion

An excellent illustration of how to create and manage creative and crucial workloads using Spanner is the Pinecone-Spanner use case.

They are able to greatly expand the free trials that will provide to clients on Google Cloud because of Spanner’s scalability, dependability, and performance. Her platform would be much enhanced by Spanner’s capacity to manage substantial amounts of data and transactions.

Read more on Govindhtech.com

[lvl-ds]

Новый день новый шаг начал проходить SQL (SELECT FROM WHILE), поздравляю вы овладели SQL ... , почти.

Не оборачивайся оно сзади! Математика для DS, оно тебя сожрëт!