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Registration is now open for JavaOne 2025
- Registration is now open for JavaOne 2025
- Early registration opens today and offers a $100 discount on three-day conference passes if registered before February 10, 2025
- Top three reasons to register early: guarantee your seat, connect with Java experts, and meet Duke the Java mascot
- JavaOne is a unique opportunity to improve Java skills, meet talented Java experts, and celebrate Java's past and future
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Amazon
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Image Credit: Amazon
Capture data changes while restoring an Amazon DynamoDB table
- The automated PITR restoration process introduces a new challenge of data changes during the restoration process that needs to be captured and incorporated to maintain data consistency and avoid data loss.
- In this post, we present a solution that automates PITR restoration and handles data changes occurring during the restoration process, providing a smooth transition back to the restored DynamoDB table with near-zero downtime.
- Automated PITR solutions provide not just data recovery but also increased business continuity, data integrity, and operational efficiency.
- Challenges with alternative solutions including version numbers and optimistic locking include the identification of affected items and data loss issues when deployments change several versions of the same item.
- Industries such as e-commerce, content management systems, and IoT data collection systems can benefit from automated PITR solutions.
- The solution architecture uses DynamoDB, DynamoDB Streams, AWS Lambda, Amazon SQS, AWS EventBridge and AWS Step Functions.
- AWS CDK is used to create an AWS EventBridge, Step Functions state machine, SQS queue, and backfilling functions.
- The process consists of the source table serving live traffic, restoration to a timepoint, DynamoDB streams, queuing, and backfilling reproduced changes.
- After deploying the solution, PITR restore can be initiated. The process captures and replicates changes in near real-time during the restore process.
- Additional future upgrades to the solution include an idempotency layer, incremental changes made to the table and retrieval, and processing of CDC writes once.
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Insider
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Image Credit: Insider
Stock market today: Indexes slip as investors brace for November inflation report
- Stocks fell as investors await Wednesday's CPI report, which could impact the Fed's interest rate decision next week.
- Major US indexes slipped in Tuesday's session, with the Dow Jones Industrial Average losing over 150 points.
- Economists expect November's consumer price index to show a 2.7% increase on an annual basis.
- Google-parent Alphabet saw a stock jump of 6% after announcing a quantum computing breakthrough.
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Cloudblog
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Image Credit: Cloudblog
Unleash a new era of PostgreSQL: AlloyDB redefines what's possible
- AlloyDB redefines what's possible with PostgreSQL by offering superior performance, availability, and scale.
- It includes a scale-out architecture, built-in analytics, and AI/ML-powered management for a modern data experience.
- AlloyDB brings faster performance, stronger functionality, better migration options, and smarter AI capabilities to PostgreSQL.
- Download the AlloyDB e-book to learn more about its transformative features and how it revolutionizes the PostgreSQL experience.
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Dev
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Image Credit: Dev
CRUD Simples Utilizando PHP + MySql + Bootstrap 4
- This article explains how to create CRUD operations in PHP using MySql and Bootstrap 4.
- To start with, create a table in the database called 'usuario'.
- The article then provides instructions on how to configure the 'Conexao.php' file inside the 'app/conexao' folder.
- The article provides the code for connecting to MySql and PostgreSql databases.
- A sample code for the 'index.php' file is provided which has the form for inserting new users and displaying the list of users.
- The 'Usuario.php' and 'UsuarioDAO.php' files are used to get and set the user details, and to perform CRUD operations.
- Lastly, the 'UsuarioController.php' file is used for handling the requests from the view and performing CRUD operations accordingly.
- This article serves as a good starting point for anyone looking to create a simple CRUD application in PHP using MySql and Bootstrap 4.
- The code is concise and well-explained, making it easy for beginners to follow along.
- Overall, this article does a great job of explaining how to create a simple CRUD application in PHP using MySql and Bootstrap 4.
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Dev
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Image Credit: Dev
How to Monitor SQL Performance in Spring Boot
- Slow SQL queries can cripple your Spring Boot application. Monitoring SQL performance is essential to keep your app running smoothly, and tools like Spring Boot Actuator, Hibernate Statistics, and Micrometer make it easier.
- This guide explains how to set up these tools, monitor key metrics (e.g., query times, connection pool usage), and optimize your database performance effectively.
- Spring Boot Actuator makes it easier to monitor SQL performance by tracking metrics like query execution times and connection pool usage.
- Key Actuator Endpoints for SQL Metrics are /metrics(endpoint is crucial for monitoring SQL-related data, including query execution times, connection pool activity, and database latency)
- Hibernate Statistics and Micrometer make it easier to monitor SQL performance by tracking query execution, cache usage, and resource consumption.
- Tools like Micrometer can help fine-tune your connection pool settings based on real-time load.
- Effective monitoring goes beyond data collection - it’s about acting on the insights gathered.
- Common questions about monitoring SQL performance in Spring Boot are answered in the FAQs section.
- Inspector is a Code Execution Monitoring tool specifically designed for software developers to Analyze your Spring Boot application for free.
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Infoq
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Image Credit: Infoq
Inside Netflix’s Distributed Counter: Scalable, Accurate, and Real-Time Counting at Global Scale
- Netflix engineers have developed a distributed counter abstraction service for tracking user interactions and business performance metrics globally.
- The system offers configurable counting modes, resilient data aggregation, and a globally distributed architecture.
- It processes close to 75K count requests/second globally with single-digit millisecond latencies.
- Netflix engineers are also experimenting with an Accurate Global Counter for real-time aggregation.
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Dbi-Services
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Image Credit: Dbi-Services
Help yourself out with the ‘log_reuse_wait_desc’ column
- The 'log_reuse_wait_desc' column helps determine why the log file is not shrinking.
- By querying the sys.databases table, the 'log_reuse_wait_desc' value for a database can be checked.
- In the case mentioned, the 'log_reuse_wait_desc' value was 'AVAILABILITY_REPLICA', indicating replication of transactions.
- Once the 'log_reuse_wait_desc' changes to 'ACTIVE_TRANSACTION', the log file can be shrunk.
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Dev
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Image Credit: Dev
🔧 Embed SQL Editor ✍️ in Your Internal Web Portal 💻
- Bytebase is an open-source database DevSecOps solution for Developer, Security, DBA, and Platform Engineering teams.
- Bytebase has a web-based SQL Editor, offering powerful features such as centralized access control, data masking, audit logs, AI assistance, and more.
- The tutorial explained how to embed the Bytebase SQL Editor into your application and configure the settings using the Bytebase API.
- Using Google OAuth SSO, this demo app simulates the process of opening the SQL Editor using an iframe upon authentication with Bytebase.
- This is helpful for SaaS providers who need to grant query permission to support teams on demand.
- The workflow involves setting up Google OAuth, a Bytebase instance with Google SSO, configuring environment variables, and running the sql-editor demo app.
- The demo app uses email from the internal portal to authenticate the user with Bytebase.
- The app then creates a project and a database for the user before granting them the necessary permissions.
- The tutorial includes code explanations and high-level overview.
- Overall, embedding the Bytebase SQL Editor in your own internal portal can save time and effort for your team's SQL-related tasks.
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Medium
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Image Credit: Medium
ORACLE SQL Window Functions
- Window functions are a powerful tool in Oracle SQL that allows you to perform calculations over a set of rows, often referred to as a window.
- They enable you to analyze data in a more granular and flexible way than traditional aggregate functions.
- Some commonly used window functions in Oracle SQL include ROW_NUMBER, RANK, DENSE_RANK, LEAD and LAG, FIRST_VALUE and LAST_VALUE, and NTILE.
- By mastering Oracle SQL window functions, you can unlock new insights from your data and gain a competitive edge in data analysis.
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Medium
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Image Credit: Medium
Understanding Combining WHERE and HAVING Clauses: Advanced Filtering Techniques
- Understanding how to combine WHERE and HAVING clauses effectively is crucial for optimizing SQL queries.
- The WHERE clause is used to filter records before any grouping or aggregation takes place.
- The HAVING clause is used to filter data after the aggregation process.
- When writing complex SQL queries, it is important to combine both WHERE and HAVING clauses for optimal results.
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Insider
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Image Credit: Insider
Oracle stock is down almost 8% after earnings miss and elevated cloud expectations
- Oracle's stock fell nearly 8% after missing earnings estimates and issuing weaker guidance.
- Oracle's cloud services, driven by AI demand, grew 12% in the last quarter, making up 77% of revenue.
- Oracle expects revenue growth between 7% and 9% for the current quarter, below analyst estimates.
- Oracle's stock has surged 80% this year, with a market value exceeding $500 billion.
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Dev
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Image Credit: Dev
Why Is MySQL the Best Database?
- MySQL is an open-source and economical database solution, making it a compelling choice for startups and small enterprises.
- MySQL has a longstanding reputation for dependability and is used by major companies like Facebook, YouTube, and Twitter.
- MySQL offers high efficiency and velocity, particularly for applications with heavy reading requirements, and it ensures data integrity through ACID compliance.
- MySQL is highly scalable and can handle increased demand as data and traffic grow, making it adaptable for businesses of all sizes.
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Siliconangle
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Image Credit: Siliconangle
Oracle’s rampant cloud growth wasn’t enough for Wall Street, and its stock slides after-hours
- Oracle missed Wall Street’s earnings and sales targets as decline elsewhere in its business outweighed the impressive rate of cloud revenue growth.
- Oracle reported second-quarter earnings of $1.47 per share, just shy of the $1.48 analyst consensus estimate. Revenue for the period rose 9% to $14.06bn, missing the $14.1bn expectation.
- The impressive growth in Oracle's cloud unit comes as more companies move computing workloads out of their own data centres due to increased need for computing power for their artificial intelligence projects.
- Oracle reported growth in the AI segment of its cloud infrastructure business, with graphics processing unit consumption up 336% from a year earlier.
- Oracle revealed that it has signed another agreement with Meta Platforms Inc. to use its cloud infrastructure to power various generative AI projects related to its Llama large language models.
- Despite the impressive cloud growth, Oracle's cautious guidance for the current quarter led investors to drop the stock almost 8% in the extended trading session.
- Oracle's growth engine is cloud infrastructure business, which specializes in providing computing services for enterprises.
- Oracle launched its cloud infrastructure business in 2016, but it struggled to gain much traction until about 2022.
- Oracle's biggest challenge going forward will be to move beyond their technical pitch, focused on speed and performance, to tell a broader story about how integrated apps running on the same infrastructure can deliver better decision-making insights and stronger foundations for AI.
- Despite the miss on guidance, Oracle's stock is up more than 80% in the year to date.
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Amazon
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Image Credit: Amazon
How Firmex used AWS SCT and AWS DMS to move 65,000 on-premises Microsoft SQL Server databases to an Amazon Aurora PostgreSQL cluster
- Firmex is an online data room provider that offers a strict data isolation strategy of individual databases. They had around 65,000 Microsoft SQL Servers' databases deployed following this architecture and were fast approaching the database limit. This led Firmex to develop a solution that fit their data model in the cloud to contain customer data and eventually decided to migrate to Amazon Aurora PostgreSQL.
- Firmex’s engineers proceeded with the approach of shifting tenant isolation from a database-based isolation solution to a schema-based isolation solution, allowing the application to operate within database limit restrictions. They selected Aurora PostgreSQL as the migration option as it had very attractive price-performance ratios, multi-AZ failovers, and could use Graviton processors.
- Firmex migrated their Microsoft SQL Server databases from on-premises data centers to Amazon Aurora for PostgreSQL in AWS. They used AWS SCT and AWS DMS tools for this process, which allowed migration of data as well as transformation of stored procedures, DDL, and data isolation. They also refactored and re-targeted T-SQL stored procedures to increase efficiency.
- Firmex engineers created one-shot migration tasks on an as-needed basis using AWS DMS due to exceeding the quota of 600 tasks per account and limits on the number of tasks allowed to create. To work around API limit and bandwidth constraints, custom tools were developed. Migration windows were also carefully analyzed for minimizing downtime and SLA targets.
- Post-migration, Firmex was able to reduce its operating costs by using Amazon Aurora for PostgreSQL in AWS and Aurora’s automatic and fast failovers helped them meet their availability targets and simplify disaster recovery.
- Eric Boyer and Maria Hristova of Firmex, Kiran Singh and Radhika Chakravarty of AWS, and Dylan Souvage and Daniel Rios of Amazon worked collaboratively towards the solution.
- Future improvements include database connection management using RDS Proxy, reducing temporary table usage, auto-vacuum tuning, and using more expressive type systems.
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