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Databases
Dev
2w
219
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Find the superset from the relationship table:SQL VS SPL#13
- The MySQL database has two tables: bag table and bag item relationship table.
- The query is used to find the superset for each bag using SQL.
- The SQL query involves two layers of loop traversal and requires three layers of nesting combined with JOIN and EXISTS.
- In contrast, SPL can easily implement the superset finding using two-layer loops combined with intuitive set operations.
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Sqldbanow
2w
155
T-SQL script that retrieves the last full backup, differential backup, and log backup along with their backup locations and status for all databases:
- The given T-SQL script retrieves the last full backup, differential backup, and log backup along with their backup locations and status for all databases.
- The script uses the tables msdb.dbo.backupset and msdb.dbo.backupmediafamily to retrieve backup information.
- By joining these tables with the sys.databases table, it collects backup details for each database.
- The script includes information like database name, last backup time for full, differential, and log backups, backup locations, and backup status.
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Dev
2w
103
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sqlc: Type-Safe Querying in Go
- sqlc is a tool that generates type-safe and idiomatic Go interface code based on SQL statements, significantly reducing boilerplate code and potential errors in database interactions.
- To start using sqlc, install it using 'go install github.com/sqlc-dev/sqlc/cmd/sqlc@latest' and ensure you have the necessary database drivers like 'github.com/lib/pq' and 'github.com/go-sql-driver/mysql'.
- Writing SQL statements in separate files, along with a small configuration file (sqlc.yaml) defining queries and schema, enables the generation of corresponding Go code.
- Running 'sqlc generate' creates database operation code, including model structures and operation interfaces based on the SQL definitions.
- The generated code offers methods like CreateUser, DeleteUser, GetUser, and ListUsers, providing type-safe interactions with the database.
- Integrated examples demonstrate the usage of the generated queries for common CRUD operations on a PostgreSQL database.
- By following specific comment syntax in SQL statements, sqlc efficiently generates methods with correct return types, ensuring type safety and robust error handling.
- sqlc also supports advanced features like emit_json_tags, emit_prepared_queries, and emit_interface for flexible code generation configurations.
- Overall, sqlc simplifies Go database coding, improves efficiency, and minimizes errors, making it a recommended tool for PostgreSQL users.
- Leapcell, a serverless platform for Golang hosting, offers features like multi-language support, free project deployment, cost efficiency, streamlined developer experience, effortless scalability, and high performance.
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Dev
2w
207
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SQL Query Logical Order
- Understanding the logical execution order of an SQL query is essential for writing optimized and efficient database queries.
- The logical execution order of an SQL query follows a systematic approach: FROM, JOIN, ON, WHERE, GROUP BY, HAVING, ORDER BY, and LIMIT.
- The query first identifies the data source (FROM), then merges tables (JOIN), defines match conditions (ON), and filters rows (WHERE).
- The data is then grouped (GROUP BY), filtered based on groups (HAVING), sorted (ORDER BY), and the output is restricted (LIMIT).
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Dev
2w
285
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Oracle 23ai — Track Table and Partition Scan Access
- Oracle 23ai introduces a new view named [dba|all|user]_table_access_stats.
- The new view allows users to view the access history of tables and partitions.
- The view shows the number of times each table or partition has been scanned, and the last time a table was accessed.
- The view provides valuable insights into table and partition access patterns and can help optimize performance.
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Dev
2w
272
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ps --forest | for navigating Oracle PID's
- A ps (Process Status) Session involves analyzing active processes running on a Linux system using the ps command.
- Running ps -ef --forest allows administrators to visualize parent-child relationships between processes for tracking user activities and troubleshooting performance issues.
- Oracle DBAs commonly use commands like pf -ef|grep pmon to check database and listener processes.
- ps -ef --forest provides a hierarchical view of running processes, aiding in visualizing process relationships and dependencies for troubleshooting.
- By using ps -ef --forest, one can identify parent processes, track user sessions, and analyze process dependencies on a Linux system.
- Visualizing session hierarchy with ps -ef --forest assists in understanding process initiation, parent-child relationships, and unexpected processes.
- Running ps -ef --forest portrays a tree-like structure of processes, showing how user sessions and services interact and spawn on the system.
- To filter Oracle-related sessions using ps -ef --forest, one can use a grep command to focus on processes related to 'oracle' or 'sqlplus.'
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Dbi-Services
2w
389
What is the most secure way to call an external job from an Oracle (pluggable) database?
- Oracle offers various methods to call external jobs from an Oracle (pluggable) database, including DBMS_SCHEDULER jobs.
- DBMS_SCHEDULER supports different types for calling external programs such as STORED_PROCEDURE, EXECUTABLE, and EXTERNAL_SCRIPT.
- Java Stored procedures can be used to spawn a dedicated server process on the database server to call a SHELL script.
- To interact with Java programs, a PL/SQL function is required and permissions must be granted to the Oracle JVM for the desired database schema.
- External C/C++ programs, also known as extproc, were introduced in Oracle 8i and have similarities to Java programs.
- External C/C++ programs require source code compilation and linking to create a shared object file that can be used in PL/SQL functions.
- Configuration settings like EXTPROC_DLLS parameter in Oracle Listener or whitelisting libraries in the Oracle Home can be used for external C/C++ programs.
- DBMS_SCHEDULER also supports job types like EXECUTABLE, EXTERNAL_SCRIPT, STORED_PROCEDURE, and PLSQL_BLOCK.
- Credentials and jobs can be created using DBMS_SCHEDULER for different job types to execute external programs from the database.
- Various methods like Java, C/C++ programs, and DBMS_SCHEDULER jobs were explored to run external jobs securely from an Oracle pluggable database.
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Amazon
2w
303
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Amazon DocumentDB Quick Start: Zero Setup with AWS CloudShell
- Amazon DocumentDB has launched its integration with AWS CloudShell, allowing users to connect to DocumentDB with a single click on the AWS Management Console without any setup required.
- Amazon DocumentDB is a fully managed native JSON document database that simplifies architecture and offers built-in storage and I/O auto scaling, security best practices, continuous backups, and native AWS service integrations.
- AWS CloudShell is a browser-based shell that allows users to securely manage and interact with AWS resources, including Amazon DocumentDB, at no additional charge.
- This integration provides a preconfigured CloudShell environment with the necessary tools and network setup to connect to Amazon DocumentDB effortlessly through the AWS Console.
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Siliconangle
2w
138
Image Credit: Siliconangle
Intel gets a new CEO, and investors start doubting when AI will pay off
- Intel has appointed a new CEO, Lip-Bu Tan, signaling change in the company's leadership amidst challenges in turning around the business.
- Interest in AI is on the rise with the emergence of new AI services, although the practical impact is currently limited.
- Companies are introducing more lightweight language models, expanding the possibilities in AI, despite high compute costs.
- Investors are growing impatient with the perceived slow progress of AI in driving enterprise value, as indicated by the performance of companies like UiPath and Adobe.
- Quantum computing is gaining investor interest, with D-Wave claiming to achieve quantum supremacy, though opinions on this vary.
- Upcoming events like Nvidia GTC are expected to shed light on new technology developments including AI models and quantum computing.
- In the AI and data sector, a range of new models and services have been introduced, highlighting advancements such as AI APIs, robotics models, and AI planning systems.
- Significant financial transactions have taken place in the AI industry, with acquisitions and funding rounds boosting companies like ServiceNow, Qualcomm, and several AI startups.
- In the enterprise realm, Intel's new CEO faces the challenge of steering the company, while various tech companies announce partnerships and new products aimed at enhancing AI performance and infrastructure.
- Earnings reports reveal mixed outcomes, with companies like Oracle and Asana experiencing disappointments, while others such as Rubrik and PagerDuty outperform market expectations.
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8 Likes
Soais
2w
121
Profile Execution in Uipath Studio
- Profile execution in UiPath Studio allows developers to measure execution times, analyze resource utilization, and identify performance bottlenecks in automation projects.
- Key features include precise execution timing, resource monitoring, customizable reports, and real-time insights for workflow optimization.
- To enable profile execution, users need to have UiPath Studio (version 2022.10 or later) and follow steps to activate profiling mode and analyze results.
- An example workflow showcases how profile execution helps identify and eliminate delay bottlenecks, improving overall performance.
- Profile execution aids in bottleneck identification, performance monitoring, and optimization validation for efficient workflow development.
- Real-life scenarios highlight how delays in data processing, interaction with external systems, file operations, UI automation, and redundant activities can be resolved using profile execution insights.
- By leveraging profile execution, developers can address inefficiencies, improve automation efficiency, and build scalable solutions for enterprise environments.
- Incorporating profile execution in the development process ensures workflows are not only functional but also optimized and performance-driven.
- Profile execution is a valuable tool for RPA developers looking to enhance the performance of their automation projects and deliver robust solutions.
- Optimizing workflows using profile execution results in more efficient and scalable automation solutions for various real-world challenges.
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Medium
2w
112
Image Credit: Medium
SQL Query Optimization: Tips & Tricks for MySQL, PostgreSQL & More
- Common causes of slow queries include poorly written SQL statements, inefficient indexing, lack of database normalization, and insufficient server resources.
- Analyzing query execution plans can help identify bottlenecks for effective optimization.
- Optimization techniques include choosing the right indexes, optimizing table structures, and writing efficient SQL code.
- MySQL and PostgreSQL have different indexing and query optimization features. Understanding these differences is important for effective optimization.
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Siliconangle
2w
117
Image Credit: Siliconangle
Business intelligence startup Omni closes $69M funding round
- Business intelligence startup Omni has closed a $69 million funding round led by ICONIQ Growth.
- Omni's sales grew eightfold in the past year and the company generates nearly $10 million in annualized revenue.
- Omni provides a business intelligence platform that allows companies to turn their data into graphs and dashboards to monitor ad campaign performance.
- The funding will be used for product development, embedding graphs in other applications, and expanding the company's workforce.
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Dev
2w
160
Image Credit: Dev
Game-Changing Guide to SQL for SEO Optimization
- SQL is like a recipe book for culinary fans, providing structured information for SEOs to extract valuable data insights for improving website rankings.
- It automates essential SEO processes, saves time and resources, and allows professionals to work with large datasets and perform in-depth analysis.
- Learning SQL for SEO is essential for strategic planning, efficient data analysis, and delivering more value to clients or employers.
- Popular databases to start with SQL include BigQuery, MySQL, Microsoft SQL Server, PostgreSQL, and SQLite.
- SQL skills benefit keyword analysis, technical SEO audits, merging data sources like GA and GSC, site migrations, A/B testing, link building analysis, and more.
- SQL empowers SEO specialists to handle vast data flows, conduct comprehensive website audits, optimize site content, investigate backlinks, and run thorough A/B tests.
- It helps in addressing technical SEO issues, applying bulk changes to the website, and enhancing overall user experience and site SEO performance.
- SQL for SEO is a game-changer that streamlines sophisticated site optimization workflows, improves decision-making in A/B testing, and simplifies link analysis.
- By mastering SQL, SEO experts can achieve more profound data analysis, identify patterns and trends, optimize SEO strategies, and enhance search rankings.
- In conclusion, SQL skills are crucial for SEO optimization, aiding in data processing, performance analysis, and driving better user experience to boost search rankings.
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Dbi-Services
2w
252
Image Credit: Dbi-Services
pgvector, a guide for DBA – Part3 AI agent and workflows
- The next phase of AI evolution involves implementing AI workflows through agentic frameworks for large to medium-sized organizations to address issues and limitations faced by AI users.
- An agentic framework enables organizations to provide operational data through Retrieve Augmented Generative (RAG) Search, which, combined with business logic and an iterative refinement process, enhances internal productivity significantly.
- Creating AI agents involves using frameworks like LangChain or OpenAI APIs, tailored to an organization's unique requirements and workflow.
- The article delves into the workflow of creating pgvector embeddings for documents and utilizing them in the RAG Search process.
- Steps include document ingestion and chunking, storing in pgvector, user query/embedding, vector similarity search, constructing LLM input, and LLM response generation for precise answers.
- For building AI agents, prompt engineering to control external information sources can provide more specific and relevant responses from local databases.
- The code example in the article demonstrates how to generate answers based on user queries and context, leveraging embeddings and PostgreSQL searches.
- Implementing data privacy solutions, such as filtering data sent to APIs, anonymization, and tight access control to vector databases, is crucial to prevent leaks of sensitive business data.
- Future articles in the series will cover recommended actions for complying with data privacy best practices, exploring topics like RAG with Differential Privacy.
- Overall, the article highlights the advancements in AI workflows and the potential for AI agents to boost productivity and address organizational needs effectively.
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Siliconangle
2w
117
Image Credit: Siliconangle
Arista Networks expands AI performance with new capabilities
- Arista Networks Inc. has introduced new capabilities for its EOS Smart AI Suite to enhance AI cluster performance and efficiency.
- The company's Arista Cluster Load Balancing (CLB) optimizes AI workload performance with consistent, low-latency network flows.
- Arista CloudVision Universal Network Observability (CV UNO) now offers AI observability for improved troubleshooting and issue inferencing.
- Cluster Load Balancing is based on RDMA queue pairs to improve bandwidth utilization between spines and leaves in AI clusters.
- CLB resolves uneven traffic distribution and high tail latency issues by optimizing bidirectional traffic flow.
- Arista's CLB and CV UNO allow the network to impact AI performance at the application level, providing insights for network engineers to address performance issues.
- CLB delivers significant performance improvements, increasing throughput and reducing job completion times for organizations utilizing AI clusters.
- Arista's CV UNO offers end-to-end AI job visibility, unifying network data within the Arista Network Data Lake (NetDL) for real-time insights.
- EOS NetDL Streamer provides AI job monitoring, deep-dive analysis, flow visualization, and proactive issue resolution to ensure efficient AI workload execution.
- Arista's CLB is available on select platforms now, with plans for wider support by 2025, while CV UNO is currently available with AI observability enhancements expected later in 2025.
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