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How to Join Two Tables with Composite Keys in SQL?

Joining tables in SQL with composite keys requires careful consideration to match rows based on multiple columns that uniquely identify records.
Using composite keys like in the Income_o and Outcome_o tables allows for more precise data organization and analysis, essential for understanding income and outcome data together.
To join tables with composite keys, a FULL OUTER JOIN is employed to combine data based on the point and date columns from both tables.
The use of COALESCE helps handle NULL values and ensures a complete result set, merging income and outcome information seamlessly for further analysis.

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Pymnts

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Databricks Boosts AI Agent Business With $1 Billion Neon Purchase

Databricks acquires database startup Neon to boost its AI agent business.
The acquisition aims to enhance database and developer experience for Neon customers.
Reportedly, the acquisition deal is valued at around $1 billion, according to The Wall Street Journal.
Databricks emphasizes the importance of AI agents in modern workflows and the value of Neon in supporting agentic workloads.

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Dev

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How to Use SQL in Go

Learn how to use SQL in Go (Golang) using SQLite including connecting to a database, writing queries, creating tables, CRUD operations, and handling context and timeouts.
To set up the project, initialize with 'go mod init sql-in-go' and install SQLite using 'go get -u github.com/mattn/go-sqlite3'.
Connecting to the database involves using sql.Open function with the driver name and database file path, checking for errors, and closing the connection after use.
Common database operations include creating, inserting, querying, updating, and deleting data with corresponding SQL queries.
Creating OrderRepository and Order structs allows for defining methods to interact with the database like creating tables, inserting data, and retrieving orders.
It is essential to use placeholders instead of concatenating strings to avoid SQL injection while inserting data into the database.
Context and Timeout can be used to set deadlines for query execution to avoid blocking the database connection for too long.
The tutorial provides practical code examples for creating tables, inserting and retrieving data, updating, and deleting records in SQLite database using Go.
By following this tutorial, you can effectively work with SQL databases in Go and efficiently manage data operations.
The code snippets provided demonstrate how to perform various database operations utilizing the SQL capabilities in Go with SQLite.

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Hackernoon

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Why Hybrid API + NL2SQL Wins: The Smart Way to Talk to Your Database

Hybrid approach of combining bulletproof APIs with NL2SQL is the winning strategy for effective database interaction.
AI alone cannot replace strong backend architecture, emphasizing the need for a Hybrid Approach.
Hybrid architecture blueprint consists of Frontend, Backend with traditional APIs, and an AI-assisted NL2SQL layer.
Backend responsibilities include schema serving, safe query execution, connection pooling, and error handling.
AI/NL2SQL responsibilities involve translating user intent into SQL, suggesting queries, and exploring data flexibly.
Smart prompt engineering example demonstrates efficient SQL query generation using NL2SQL.
Combining solid backend with flexible, user-friendly AI layers leads to successful production systems.
Hybrid approach saves from catastrophes by using traditional APIs for data filtering and sending smart prompts to AI.
AI-driven systems should feed knowledge to AI, not raw data, to ensure smart answers over crashes.
DBConvert Streams offers tools for hybrid approach implementation, with NL2SQL coming soon in the next release.

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Dev

253

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The LIMIT offset, count Trap: Why Large Offsets Slow Down MySQL?

Large offsets in MySQL queries using LIMIT can significantly slow down performance, especially in deep pagination scenarios.
The slowdown is due to MySQL processing all offset + count rows before discarding offset rows and returning requested rows.
Factors like indexing, bookmark lookups, and filesorts contribute to the performance issues.
To optimize, keyset pagination using starting values or covering indexes with subqueries are recommended.
Keyset pagination allows direct seeking to the starting point, enhancing efficiency in sequential pagination.
Covering indexes with subqueries reduce bookmark lookups, improving performance for arbitrary page jumps.
Implementing covering indexes ensures all query requirements are met directly from the index, reducing costly lookups.
Tools like Chat2DB provide AI-powered query optimization and EXPLAIN analysis to streamline SQL optimization processes.
Chat2DB enhances productivity by assisting in complex query writing and database management tasks.

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Dev

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Find Consecutive Alphabetical Characters in String — From SQL to SPL #28

Task: Find strings in a database table that contain at least 5 consecutive letters sorted alphabetically.
SQL requires nested subqueries and CONNECT BY to simulate sequences, while SPL provides direct sequence calculation functions.
In SPL, the string is split into a sequence by character, and the longest substring with consecutive letters in ascending order with a length of 5 or more is selected.
SPL's approach is more straightforward and efficient compared to SQL for this task.

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Siliconangle

187

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Nvidia, AMD and Amazon to cash in on Saudi Arabia’s AI hub ambitions

Nvidia and AMD are set to supply chips to Saudi Arabia for data centers under a deal brokered by President Trump.
Humain, backed by Saudi Arabia’s Public Investment Fund, will operate the data centers to become an AI hub for the Middle East.
Nvidia will provide its powerful chips to Humain, while AMD plans to offer its own chips and software for the data centers.
The Trump administration lifted export restrictions on semiconductor shipments to Saudi Arabia, enabling these deals.
Humain aims to build AI infrastructure and develop Arabic-language models for generative AI applications.
Nvidia and AMD stocks surged after the announcements, as they seek to expand their AI accelerator customer base.
Humain plans to build AI factories with a capacity of up to 500 megawatts per facility and acquire Nvidia processors.
Saudi Arabia's move towards technology hub transformation attracts investments from U.S. tech giants like AWS, Google, and Oracle.
AWS also plans to invest in a new 'AI Zone' in Saudi Arabia alongside the potential deal with the UAE for Nvidia chips.
The UAE may acquire over a million Nvidia chips, with a portion going to G42 AI firm and the rest to U.S. data center projects.

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Amazon

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Scaling Amazon RDS for MySQL performance for Careem’s digital platform on AWS

Careem faced performance challenges with their 270 TB Amazon RDS for MySQL due to increased storage utilization, slow queries, and high replica lag.
To tackle this, they implemented a phased data purging strategy, reducing the storage footprint from 270 TB to 78 TB while enhancing performance.
The purging process consisted of structured steps like data identification, read replica creation, ON DELETE CASCADE activation, and testing before promoting the read replica to production.
Data purge was executed in iterations to effectively manage historical data, with 24 TB being successfully removed through this process.
Challenges arose during Phase 4 due to performance issues like increased read and write latency, necessitating adjustments in IOPS and undo log management.
The article details Careem's strategic data purging and database transformation phases, showcasing AWS DMS Serverless migration to optimize storage, performance, and costs.
Careem achieved results like reduced DB footprint, improved read latency, minimal downtime, and operational efficiency through this optimization journey.
The post emphasizes lessons learned, challenges faced, and future plans, highlighting the importance of strategic data management and leveraging cloud technologies.
Careem plans to transition to a service-based DB architecture with table partitioning for enhanced scalability, performance, and cost efficiency.
This optimization journey was successfully executed through a phased data purging approach and AWS services, emphasizing the significance of strategic data management.
The authors include Kanhaiya Lal, Khurram Naseem, Imane ZEROUAL, and Haziq Masud, each contributing expertise in AWS, engineering, and database management.

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Dev

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Do I Need to Use CASE in SQL WHERE Clause Too?

Developers often wonder if they need to use the CASE statement in SQL WHERE clause for effective filtering of records.
The CASE statement helps in creating conditional logic in SELECT clause while WHERE clause limits rows based on conditions.
In most cases, both CASE and WHERE clauses are needed to filter and categorize results effectively.
However, you can use subqueries or CTEs to filter based on CASE logic without explicitly replicating conditions in WHERE clause.

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Analyticsindiamag

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NVIDIA to Deploy 18,000 Chips for AI Data Centres in Saudi Arabia

HUMAIN, a subsidiary of Saudi Arabia's Public Investment Fund, partners with NVIDIA to deploy 18,000 GB300 Grace Blackwell chips for AI factories in the Kingdom.
NVIDIA and HUMAIN to build hyperscale AI data centres using hundreds of thousands of NVIDIA GPUs, supporting training of sovereign AI models and digital transformation.
The partnership includes workforce training programs for Saudi developers in AI, robotics, and digital twin technologies, aligned with Vision 2030 goals.
NVIDIA is part of several technology companies investing in Saudi Arabia, with Oracle committing $14 billion and AMD partnering with HUMAIN for AI infrastructure development.

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Amazon

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Amazon CloudWatch Database Insights applied in real scenarios

AWS introduced Amazon CloudWatch Database Insights in December 2024, tailored for Amazon Aurora and Amazon RDS across multiple databases.
CloudWatch Database Insights aims to enhance database observability for DevOps engineers and database administrators, facilitating troubleshooting.
The tool provides two modes of operation- Standard Mode and Advanced Mode, with Advanced Mode offering additional features.
Enabling CloudWatch Database Insights involves activating the Advanced Mode, which incurs a cost.
Accessing CloudWatch Database Insights through the Amazon CloudWatch console allows for efficient troubleshooting.
Demo #1 showcases resolving a query performance issue by identifying the need for an index and optimizing the query execution plan.
Demo #2 illustrates addressing storage capacity limits during database migration using CloudWatch Database Insights.
Demo #3 exemplifies mitigating database restarts due to out-of-memory issues using instance size changes and failover.
By leveraging CloudWatch Database Insights, users can effectively troubleshoot database issues and optimize performance.
Authors include Nirupam Datta, Ryan Moore, and Cade Kettner, experts in AWS database services providing technical assistance and guidance.

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Cloudblog

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Cool stuff customers built, May edition: Visual scouts, racing agents, agile ads & more

AI and cloud technology are transforming industries globally, as highlighted by customers utilizing Google Cloud for innovative projects.
Notable projects include Lowe's Visual Scout product recommendation engine, Formula E's AI-powered Driver Agent for race insights, and Wealth.com's conversational tool Ester AI for financial planning.
Additionally, Yassir consolidated its data infrastructure with Google Cloud, SIGNAL IDUNA enhanced customer service with an AI knowledge assistant, and Nuro improved AI-driven insights with AlloyDB.
Mars Wrigley utilized BigQuery and Cortex Framework for agile media experiments, showcasing the impact of data-driven marketing strategies.
These projects demonstrate how technology like AI, cloud computing, and data analytics are reshaping businesses and customer experiences across various industries.
From enhancing ecommerce experiences to democratizing access to race insights, these initiatives showcase the diverse applications of cutting-edge technology.
By leveraging Google Cloud services, companies are optimizing operations, improving customer satisfaction, and driving innovation in their respective sectors.
These real-world examples underscore the importance of technology partnerships and the potential for AI to augment human expertise and decision-making in complex domains.
As more industry leaders and startups embrace Google Cloud technologies, the impact on business processes, customer interactions, and data-driven insights is set to expand further.
The showcased projects not only highlight the capabilities of Google Cloud but also emphasize the significance of data utilization and AI integration for driving business growth and operational efficiencies.
Collaborations between companies and Google Cloud are enabling transformative projects that enhance user experiences, optimize processes, and propel technological advancements in various sectors.

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Cloudblog

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Democratizing database observability with AI-assisted troubleshooting

Organizations are adopting DevOps practices, requiring application developers to manage databases without specialized expertise, leading to delays in development.
Google Cloud introduced AI-assisted troubleshooting for Cloud SQL and AlloyDB, enabling developers to efficiently manage and troubleshoot databases.
AI-assisted troubleshooting predicts and resolves potential database performance issues, provides actionable recommendations, and simplifies query optimization.
This new feature leverages generative AI and machine learning to enhance database operations, address hotspots, and optimize performance, promoting independence and efficiency among developers.

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Dev

183

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How to Retrieve Hierarchical Flex Values in Oracle EBS?

Hierarchical queries in Oracle EBS help in understanding parent-child relationships within flex values for effective reporting.
Using tables like FND_FLEX_VALUE_NORM_HIERARCHY and FND_FLEX_VALUE_CHILDREN_V aids in constructing queries for hierarchical data retrieval.
Example query using FND_FLEX_VALUE_NORM_HIERARCHY showcases retrieving flex values with their hierarchy, displaying depth and paths.
Alternatively, the query utilizing FND_FLEX_VALUE_CHILDREN_V simplifies hierarchy retrieval, but may not list top parents.

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Dev

433

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Getting Started with Simple Data Integrator (SDI): Direct Connection Setup

Simple Data Integrator (SDI) is a no-code ETL tool for connecting and transferring data between databases and systems.
This article provides a guide on setting up a Direct Connection in SDI, using Oracle as an example.
Steps include opening Connection Settings, filling in Connection Details like Oracle details, and testing the connection.
SDI supports connections to various databases like SQL Server, MySQL, PostgreSQL, DB2, and ODBC-compliant databases with similar setup procedures.

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