TiDB is an open-source distributed SQL database developed by PingCAP that is compatible with MySQL. It provides horizontal scalability, high availability, and consistent distributed transactions. Mobike, which has 200 million users and 9 million bikes, uses TiDB to handle over 30 TB of data per day. While TiDB aims to be compatible with MySQL, some features like stored procedures work differently or are still in development.
Presentation at SF Kubernetes Meetup (10/30/18), Introducing TiDB/TiKVKevin Xu
This deck was presented at the SF Kubernetes Meetup held at Microsoft's downtown SF office, introducing the architecture of TiDB and TiKV (a CNCF project), key use cases, a user story with Mobike (one of the largest bikesharing platforms in the world), and how TiDB is deployed across different cloud environment using TiDB Operator.
Iceberg: a modern table format for big data (Ryan Blue & Parth Brahmbhatt, Netflix)
Presto Summit 2018 (https://www.starburstdata.com/technical-blog/presto-summit-2018-recap/)
Since its inception, Scylla has offered a compelling alternative to Apache Cassandra, providing better performance for a lower cost of ownership.
With Scylla Open Source 4.0 we continue to extend our CQL interface features and capabilities and also now provide an open source alternative to DynamoDB, allowing you to run your workloads anywhere, on any cloud provider, or on premises.
Join ScyllaDB co-founders, CTO Avi Kivity and CEO Dor Laor, for a look at the new features in Scylla Open Source 4.0, and architectural and cost comparisons with the coming Cassandra 4.0.
Topics will include:
Improved consistency with our new Lightweight Transactions
Scylla Operator for Kubernetes
How we stack up against Apache Cassandra 4.0
Our “run anywhere” DynamoDB alternative
The document discusses Reactive Slick, a new version of the Slick database access library for Scala that provides reactive capabilities. It allows parallel database execution and streaming of large query results using Reactive Streams. Reactive Slick is suitable for composite database tasks, combining async tasks, and processing large datasets through reactive streams.
Mongo DB Monitoring - Become a MongoDB DBASeveralnines
This presentation was presented by Art van Scheppingen at Percona Live 2017 in Santa Clara CA and covers what you need to know to effectively monitor MongoDB
Introducing TiDB [Delivered: 09/25/18 at Portland Cloud Native Meetup]Kevin Xu
This deck introduces TiDB, an open source distributed NewSQL database, to the Portland Cloud Native meetup on September 25, 2018. It includes materials on technical architecture, core features, using TiDB Operator to deploy in any cloud environment, and appendix on transaction model and join support.
Scylla Summit 2022: New AWS Instances Perfect for ScyllaDBScyllaDB
In this talk AWS’ Ken Krupa, Head of Specialized Solutions Architecture, will describe the architecture and capabilities of two new AWS EC2 instance types perfect for data-intensive storage and IO-heavy workloads like ScyllaDB: the Intel-based I4i and the Graviton2-based I4g series.
The Intel Xeon Ice Lake-based I4i series provides unparalleled raw horsepower for your most demanding workloads. Meanwhile, the Graviton2-powered I4g instances provide lower cost per storage on a power-efficient platform to deploy your cloud-native applications.
Ken will also describe the AWS Nitro SSD, a new form of high-speed NVMe storage with a Flash Translation Layer built with Nitro controllers, which powers both of these instance families.
ScyllaDB VP of Product Tzach Livyatan will then share benchmarking results showing how ScyllaDB behaves under load on these two instance types, providing maximum system utility and efficiency.
To watch all of the recordings hosted during Scylla Summit 2022 visit our website here: https://www.scylladb.com/summit.
Running a DynamoDB-compatible Database on Managed Kubernetes ServicesScyllaDB
With the release of Alternator, Scylla’s DynamoDB-compatible API, you can now take your locked-in DynamoDB workloads and run them anywhere. Scylla provides a cost-effective open source alternative to Amazon’s DynamoDB, deployable wherever a user would want: on-premises, on other public clouds like Microsoft Azure or Google Cloud Platform, still on AWS (such as the high-density i3en instances) or as a fully managed DBaaS.
In this session, we will cover:
- Scylla Alternator: Scylla’s Amazon DynamoDB-compatible API
- Scylla Operator: Running Scylla Alternator on Kubernetes
- Demo Alternator - Demo and explain DynamoDB on GKE
This document discusses PingCAP's Kubernetes operator for TiDB, an open source distributed SQL database. It provides a brief history of PingCAP and the TiDB community. It then gives a technical overview of TiDB's architecture before explaining how the TiDB operator works. The operator allows users to deploy and manage TiDB clusters on Kubernetes through custom resources that are controlled by custom controllers. This provides capabilities like automated scaling, updates, and failover for stateful applications running on Kubernetes. The operator is open source and TiDB is also available as a managed service on GCP Marketplace.
Webinar 2017. Supercharge your analytics with ClickHouse. Alexander ZaitsevAltinity Ltd
Alexander Zaitsev presented on LifeStreet's experience implementing ClickHouse for their ad analytics platform. Some key points:
- LifeStreet processes over 10 billion events per day from their ad exchange and needed a high performance analytics solution.
- They tried various databases but migrated fully to ClickHouse due to its performance for analytics workloads.
- Major challenges included designing an efficient schema, sharding and replication strategy, and reliable data ingestion.
- ClickHouse's dictionary feature allowed them to implement normalized dimensions tables while supporting updates, improving storage efficiency and query performance.
Lookout on Scaling Security to 100 Million DevicesScyllaDB
The massive increase of security-related data requires companies to respond with new approaches to ingestion. Learn how Lookout has changed its approach for ingesting telemetry to meet their goal of growing from 1.5 million devices to 100 million devices and beyond, using Kafka Connect and switching from AWS DynamoDB to Scylla.
Shen Li, VP engineering at PingCAP, shares the slides about TiDB with the Big Data Ecosystem. Enjoy~
TiDB, an open source distributed HTAP database. Inspired by Google Spanner/F1, PingCAP develops TiDB, an open source distributed Hybrid Transactional/Analytical Processing (HTAP) database. TiDB features infinite horizontal scalability, strong consistency, and high availability. The goal of TiDB is to serve as a one-stop solution for online transactions and analysis.
Webinar slides: Migrating to Galera Cluster for MySQL and MariaDBSeveralnines
This document provides an overview of online and offline migration strategies for migrating from a standalone MySQL or MySQL master-slave setup to a Galera Cluster. It discusses preparation steps like database schema checks and compatibility. It then outlines the process for offline migration using backups and restore, as well as online migration using MySQL replication to sync data between the existing and new Galera clusters before cutting over. Testing strategies like A/B testing in read-only mode are also presented.
Introduction to Data Engineer and Data Pipeline at Credit OKKriangkrai Chaonithi
The document discusses the role of data engineers and data pipelines. It begins with an introduction to big data and why data volumes are increasing. It then covers what data engineers do, including building data architectures, working with cloud infrastructure, and programming for data ingestion, transformation, and loading. The document also explains data pipelines, describing extract, transform, load (ETL) processes and batch versus streaming data. It provides an example of Credit OK's data pipeline architecture on Google Cloud Platform that extracts raw data from various sources, cleanses and loads it into BigQuery, then distributes processed data to various applications. It emphasizes the importance of data engineers in processing and managing large, complex data sets.
Webinar slides: Designing Open Source Databases for High AvailabilitySeveralnines
It is said that if you are not designing for failure, then you are heading for failure. How do you design a database system from the ground up to withstand failure? This can be a challenge as failures happen in many different ways, sometimes in ways that would be hard to imagine. This is a consequence of the complexity of today’s database environments.
At Severalnines we’re big fans of high availability databases and have seen our fair share of failure scenarios across the thousands of database deployments we enable every year.
In this webinar replay, we’ll look at the different types of failures you might encounter and what mechanisms can be used to address them. We will also look at some of popular HA solutions used today, and how they can help you achieve different levels of availability.
AGENDA
- Why design for High Availability?
- High availability concepts
- CAP theorem
- PACELC theorem
- Trade offs
- Deployment and operational cost
- System complexity
- Performance issues
- Lock management
- Architecting databases for failures
- Capacity planning
- Redundancy
- Load balancing
- Failover and switchover
- Quorum and split brain
- Fencing
- Multi datacenter and multi-cloud setups
- Recovery policy
- High availability solutions
- Database architecture determines Availability
- Active-Standby failover solution with shared storage or DRBD
- Master-slave replication
- Master-master cluster
- Failover and switchover mechanisms
- Reverse proxy
- Caching
- Virtual IP address
- Application connector
SPEAKER
Ashraf Sharif is System Support Engineer at Severalnines. He was previously involved in hosting world and LAMP stack, where he worked as principal consultant and head of support team and delivered clustering solutions for large websites in the South East Asia region. His professional interests are on system scalability and high availability.
Scylla Summit 2022: Operating at Monstrous Scales: Benchmarking Petabyte Work...ScyllaDB
ScyllaDB is a distributed database designed to scale horizontally and vertically — in theory. What about in practice? ScyllaDB’s Benny Halevy, Director, Software Engineering, will take you through the process and results of benchmarking our NoSQL database at the petabyte level, showing how you can use advanced features like workload prioritization to control priorities of transactional (read-write) and analytic (read-only) queries on the same cluster with smooth and predictable performance.
To watch all of the recordings hosted during Scylla Summit 2022 visit our website here: https://www.scylladb.com/summit.
Virtual training Intro to the Tick stack and InfluxEnterpriseInfluxData
In this webinar, we will provide an introduction to the components of the TICK Stack and a review the features of InfluxEnterprise and InfluxCloud. We also demo how to install the TICK stack.
Challenges in Building a Data PipelineManish Kumar
The document discusses challenges in building a data pipeline including making it highly scalable, available with low latency and zero data loss while supporting multiple data sources. It covers expectations around real-time vs batch processing and streaming vs batch data. Implementation approaches like ETL vs ELT are examined along with replication modes, challenges around schema changes and NoSQL. Effective implementations should address transformations, security, replays, monitoring and more. Reference architectures like Lambda and Kappa are briefly outlined.
This document introduces TiDB, an open source distributed SQL database developed by PingCAP. It provides a 3-part summary:
1) TiDB is a hybrid transactional/analytical database inspired by Google Spanner/F1 that provides horizontal scalability, MySQL compatibility, and ACID transactions. It consists of TiDB, TiKV, and Placement Driver.
2) Mobike, a bike sharing platform with 200 million users, uses TiDB to power operations like bike locking/unlocking tracking and real-time analytics to handle high concurrency and permanent storage needs.
3) Over 200 companies use TiDB for two major uses - MySQL scalability and hybrid OLTP/OLAP architecture
This slide was delivered at the Kubernetes/Docker meetup in Cologne, Germany, hosted by Giant Swarms on how TiDB, an open source NewSQL distributed database, is deployed and managed on any Kubernetes-enabled cloud environment by applying the Operator pattern.
"Smooth Operator" [Bay Area NewSQL meetup]Kevin Xu
This slide was delivered at the Bay Area NewSQL meetup in California on how TiDB, an open source NewSQL distributed database, is deployed and managed on any Kubernetes-enabled cloud environment by applying the Operator pattern.
TiDB is a NewSQL database that provides horizontal scalability, ACID transactions, high availability, and SQL support. It aims to be an HTAP (Hybrid Transactional/Analytical Processing) database by supporting both OLTP and OLAP workloads on the same database using the same SQL interface.
TiDB achieves horizontal scalability through its distributed architecture with the TiKV storage engine and PD for metadata management. It supports ACID transactions through MVCC and Raft consensus. The database is available through replication of regions across nodes. TiDB also supports real-time analytics on the same dataset as transactions through its cost-based optimizer and distributed query processing engine.
Spark can run queries directly against the
A Brief Introduction of TiDB (Percona Live)PingCAP
TiDB is an open-source distributed SQL database that supports high availability, horizontal scalability, and consistent distributed transactions. It provides a MySQL compatible API and seamless online expansion. TiDB uses Raft for consensus and implements the MVCC model to support high concurrency. It also provides distributed transactions through a two-phase commit protocol. The architecture consists of a stateless SQL layer (TiDB) and a distributed transactional key-value storage (TiKV).
When Apache Spark Meets TiDB with Xiaoyu MaDatabricks
During the past 10 years, big-data storage layers mainly focus on analytical use cases. When it comes to analytical cases, users usually offload data onto Hadoop cluster and perform queries on HDFS files. People struggle dealing with modifications on append only storage and maintain fragile ETL pipelines.
On the other hand, although Spark SQL has been proven effective parallel query processing engine, some tricks common in traditional databases are not available due to characteristics of storage underneath. TiSpark sits directly on top of a distributed database (TiDB)’s storage engine, expand Spark SQL’s planning with its own extensions and utilizes unique features of database storage engine to achieve functions not possible for Spark SQL on HDFS. With TiSpark, users are able to perform queries directly on changing / fresh data in real time.
The takeaways from this two are twofold:
— How to integrate Spark SQL with a distributed database engine and the benefit of it
— How to leverage Spark SQL’s experimental methods to extend its capacity.
This presentation provides an overview of the architecture and technology of TiDB, an open-source distributed NewSQL database, and how it helps Mobike, one of the largest dockless bikeshare platform, scale its infrastructure to achieve hyper-growth.
At TiDB DevCon 2020, Max Liu, CEO at PingCAP, gave a keynote speech. He believes that today’s database should be more real-time, more flexible, and easier to use, and TiDB, an elastic, cloud-native, real-time HTAP database, is exactly that kind of database.
TiDB and Amazon Aurora can be combined to provide analytics on transactional data without needing a separate data warehouse. TiDB Data Migration (DM) tool allows migrating and replicating data from Aurora into TiDB for analytics queries. DM provides full data migration and incremental replication of binlog events from Aurora into TiDB. This allows joining transactional and analytical workloads on the same dataset without needing ETL pipelines.
This deck was the keynote speech delivered by Kevin Xu (GM of Global Strategy at Operations) and Shen Li (VP of Engineering at PingCAP) on TiDB architecture, tools and migration path, and TiDB Cloud fully-managed offering at Percona Live Europe 2018 in Frankfurt, Germany.
DPDK Summit 2015 - NTT - Yoshihiro NakajimaJim St. Leger
DPDK Summit 2015 in San Francisco.
NTT presentation by Yoshihiro Nakajima.
For additional details and the video recording please visit www.dpdksummit.com.
The document discusses using Lagopus software-defined networking (SDN) switches to demonstrate an SDN internet exchange (IX) at the Interop Tokyo 2015 technology show. Key points:
- Two Lagopus SDN switches were deployed as the core switches in an SDN IX to enable automated provisioning of inter-autonomous system layer 2 connectivity and on-demand packet filtering between internet service providers.
- The Lagopus switches achieved an average throughput of 2Gbps with no packet drops over a week during the show, demonstrating the potential for software switches in next-generation SDNs.
- Previous work to optimize the Lagopus switch performance through techniques like hardware offloading to FPGAs helped enable its
Data-at-scale-with-TIDB Mydbops Co-Founder Kabilesh PR at LSPE EventMydbops
Explore the world of TiDB with Kabilesh PR, Co-Founder of Mydbops, as he unveils the potential of this open-source distributed SQL database. Dive into the architecture, scalability solutions, and production readiness of TiDB, and discover how it addresses MySQL scalability bottlenecks through sharding. Gain insights into its stateless SQL interface, transactional storage with TiKV, and analytical capabilities with TiFlash. Learn about TiDB's native sharding features, use cases across various industries, and its readiness for production environments. Delve into its limitations and discover how TiDB can transform your data management landscape.
MySQL Transformation Case Study: 80% Cost Savings & Uninterrupted Availabilit...Mydbops
Discover how Mydbops achieved an impressive 80% cost savings and ensured uninterrupted availability through a transformative MySQL database case study. Join Vinoth Kanna RS, Co-Founder of Mydbops, as he shares insights into optimizing infrastructure, enhancing observability, and navigating critical technology decisions. Learn from real-world challenges, innovative solutions, and valuable takeaways for your own database management endeavors.
The Nitty Gritty of Advanced Analytics Using Apache Spark in PythonMiklos Christine
Apache Spark is the next big data processing tool for Data Scientist. As seen on the recent StackOverflow analysis, it's the hottest big data technology on their site! In this talk, I'll use the PySpark interface to leverage the speed and performance of Apache Spark. I'll focus on the end to end workflow for getting data into a distributed platform, and leverage Spark to process the data for advanced analytics. I'll discuss the popular Spark APIs used for data preparation, SQL analysis, and ML algorithms. I'll explain the performance differences between Scala and Python, and how Spark has bridged the gap in performance. I'll focus on PySpark as the interface to the platform, and walk through a demo to showcase the APIs.
Talk Overview:
Spark's Architecture. What's out now and what's in Spark 2.0Spark APIs: Most common APIs used by Spark Common misconceptions and proper techniques for using Spark.
Demo:
Walk through ETL of the Reddit dataset. SparkSQL Analytics + Visualizations of the Dataset using MatplotLibSentiment Analysis on Reddit Comments
RESTful Machine Learning with Flask and TensorFlow Serving - Carlo MazzaferroPyData
Those of us who use TensorFlow often focus on building the model that's most predictive, not the one that's most deployable. So how to put that hard work to work? In this talk, we'll walk through a strategy for taking your machine learning models from Jupyter Notebook into production and beyond.
GPU data warehouse Sqream DB provides a massively parallel processing engine powered by GPUs that is faster and more efficient than CPU-based systems. It can ingest terabytes of data per hour onto a single GPU and handle petabytes of data stored in a compact 2U server. With familiar SQL queries and connectors, Sqream DB accelerates analytics by 100x over traditional warehouses through its GPU-accelerated processing and columnar storage.
Similar to Introducing TiDB - Percona Live Frankfurt (20)
This document discusses Spirit, an online schema change utility for MySQL 8.0. It begins by covering the state of DDL operations in MySQL and how Spirit works to perform schema changes without blocking reads or writes. It then discusses optimizations Spirit uses and features like checkpointing. Finally, it outlines some feature requests to make more operations instant or inplace in MySQL to reduce the need for Spirit in many cases.
The document outlines 10 usability guidelines for MySQL:
1) All features should be possible through SQL for consistency and discoverability.
2) Features, configurations, and errors should be intuitively obvious and discoverable without reading manuals cover-to-cover.
3) Too many similar configuration options without clear use cases can be paralyzing; only add options if use cases are known.
4) New configuration options must allow the effect to be measured through observability.
5) Features should work consistently across contexts for orthogonality.
6) The system should be safe to script against and avoid duplicate processing.
7) Extend functionality to match common use cases.
8) Preserve the ability to
The document is an introduction to the MySQL 8.0 optimizer guide. It includes a safe harbor statement noting that the guide outlines Oracle's general product direction but not commitments. The agenda lists 25 topics to be covered related to query optimization, diagnostic commands, examples from the "World Schema" sample database, and a companion website with more details.
The document discusses proposed changes to MySQL Server 8.0 and replication defaults. Some key areas discussed include changing the default character set to UTF8MB4, turning on the event scheduler by default, increasing some session buffer sizes, enabling security defaults, and enabling replication features like binary logging and GTIDs by default. The document seeks feedback from users on the proposed changes.
The document discusses Oracle's MySQL Cloud Service which provides MySQL as a database service on Oracle Public Cloud. Key features include automated backups, patching, monitoring, elastic scaling, high availability, security features from MySQL Enterprise Edition, and tools for data access, migration and restoration. The service runs MySQL 5.7 Enterprise Edition with an optimized configuration for the cloud environment.
MySQL 5.7 introduced native support for JSON data with a new JSON data type and JSON functions. The JSON type allows efficient storage and access of JSON documents compared to traditional text storage. JSON functions allow querying and manipulating JSON data through operations like extraction, search, and generation of JSON values. Developers now have more flexibility to work with hierarchical and unstructured data directly in MySQL.
This document discusses using MySQL in automated testing. It covers various tools that can be used to automate and manage database deployments as part of testing, including pt-online-schema-change, MySQL Sandbox, SYS, Outbrain Propagator, Liquibase, ORM migrations, and libeatmydata. It also discusses considerations for different MySQL versions, such as online DDL support being introduced in MySQL 5.6. The document aims to demonstrate that databases can and should be automated and treated as first-class citizens in testing environments.
The document discusses upcoming changes and new features in MySQL 5.7. Key points include:
- MySQL 5.7 development has focused on performance, scalability, security and refactoring code.
- New features include online DDL support for additional DDL statements, InnoDB support for spatial data types, and cost information added to EXPLAIN output.
- Benchmarks show MySQL 5.7 providing significantly higher performance than previous versions, with a peak of 645,000 queries/second on some workloads.
This document discusses query optimization in MySQL. It provides an introduction to how the MySQL query optimizer works to determine the most efficient execution plan for a SQL query. Several examples are shown using the EXPLAIN statement to analyze queries against sample data in the World Schema. Indexes are added and analyzed to demonstrate how they can improve query performance in different scenarios. The document also discusses some general strategies and rules of thumb used by the query optimizer.
This document discusses various MySQL performance metrics that are important to measure from within the database, operating system, and application. It outlines key InnoDB internal structures like the buffer pool and log system. Specific metrics that provide insight into buffer pool usage, page churn, and log writes are highlighted. Optimizing the working set size and ensuring sufficient free space in the log files are important factors for performance.
This document provides an overview of MySQL for Linux system administrators. It discusses MySQL architecture including storage engines, memory usage, the MySQL server process, and InnoDB transaction processing. It also covers topics like backups and replication, and the agenda includes performance and capacity planning. The goal is to help system administrators understand and manage MySQL databases.
MySQL: From Single Instance to Big DataMorgan Tocker
The document discusses various MySQL database architectures for different usage needs, from single server setups to high availability configurations. It begins with traditional single server and web/database tier setups. It then covers high availability options using MySQL replication, shared storage, and MySQL Cluster. Popular topologies include master-slave replication for scaling reads, read-write splitting between master and slaves, and using slaves for reporting queries to improve performance. Considerations like network latency, failure handling, and limitations of read-write splitting are also discussed.
The document discusses NoSQL APIs in MySQL. It provides an overview of the memcached caching system and the history of the HandlerSocket protocol. It then describes the NoSQL interface introduced in MySQL 5.6, which allows for memcached-style operations on MySQL data. It notes that MySQL 5.7 further improved the performance and scalability of this interface.
The document outlines changes and new features in MySQL versions 5.7 through upcoming releases. Key points include:
- MySQL 5.7 development follows a milestone release process to stabilize new features before general availability. Four development milestone releases have been completed so far.
- Notable 5.7 features include statement timeouts, change replication without stopping SQL threads, and performance improvements like optimized UNION ALL queries.
- Some existing functionality will change in 5.7, like making replication more durable by default and producing errors for queries with only partial GROUP BY clauses.
- Ongoing efforts include refactoring and improving InnoDB, the optimizer, and other components for better performance and scalability. New features in development
MySQL 5.6 - Operations and Diagnostics ImprovementsMorgan Tocker
This document discusses MySQL 5.6 and its improvements to operational and diagnostic capabilities. Key enhancements include online DDL operations that do not block reads or writes, buffer pool dump and restore for faster startup, import/export of partitioned tables, and transportable tablespaces. Diagnostic tools were improved with EXPLAIN showing more details, the ability to EXPLAIN updates and deletes, optimizer tracing, and the performance schema providing detailed query level instrumentation and monitoring by default.
The document discusses locking and concurrency control in databases, demonstrating how table locks, row locks, and multi-version concurrency control work through examples of a database being backed up while concurrent changes are made. It shows how different locking strategies, like those used in MyISAM and InnoDB, allow for concurrent access to data while maintaining consistency and isolation. A live demo then highlights deadlocks and lock waits that can occur with concurrent access and how they are handled.
The document provides an overview of the InnoDB storage engine used in MySQL. It discusses InnoDB's architecture including the buffer pool, log files, and indexing structure using B-trees. The buffer pool acts as an in-memory cache for table data and indexes. Log files are used to support ACID transactions and enable crash recovery. InnoDB uses B-trees to store both data and indexes, with rows of variable length stored within pages.
MySQL 5.7 proposes several changes to improve performance and consistency including:
1. Making replication durable by default by setting sync_binlog and repository options.
2. Deprecating features like INNODB monitor tables and ALTER IGNORE TABLE in favor of newer standards.
3. Simplifying and restricting SQL modes to encourage stricter querying and remove ambiguous options. Explanations for errors and modes will also be improved.
Upcoming Changes in MySQL 5.7
Morgan Tocker, MySQL Community Manager
The presentation outlines several proposed changes and deprecations in MySQL 5.7, including making replication more durable by default, replacing some InnoDB monitor tables with performance schema instrumentation, simplifying SQL modes, and deprecating features like ALTER IGNORE TABLE, the \N NULL synonym, and the Federated storage engine. Feedback is sought on these proposed changes to help guide MySQL's future development.
This document discusses various methods for optimizing performance of MySQL databases, including upgrading hardware and software, optimizing configuration settings, optimizing queries, and optimizing database schemas. It provides an example of using EXPLAIN plans and adding indexes to optimize queries on a database table to improve performance. The author recommends focusing on query optimization as the best method, using profilers and slow query logs to identify queries to optimize.
Generative AI The Key to Smarter, Faster IT Development.pdfayushiqss
Discover how generative AI is transforming IT development in this blog. Learn how using AI software development, artificial intelligence tools, and generative AI tools can lead to smarter, faster, and more efficient software creation. Explore real-world applications and see how these technologies are driving innovation and cutting costs in IT development.
Drona Infotech is one of the Best Mobile App Development Company in Noida. Discover the latest mobile app development frameworks to streamline your app creation process. Choose from a variety of tools and technologies to build innovative apps.
Visit Us For: https://www.dronainfotech.com/mobile-application-development/
Old Tools, New Tricks: Unleashing the Power of Time-Tested Testing ToolsBenjamin Bischoff
In the rapidly evolving landscape of software development and testing, it is tempting to chase the latest tools and technologies. However, some of the most effective solutions have been in existence for decades. In this talk, we’ll delve into the enduring value of these timeless testing tools.
We’ll explore how established tools like Selenium, GNU Make, Maven, and Bash remain vital in today’s software development and testing toolkit even though they have been around for a long time (some were even invented before I was born). I’ll share examples of how these tools have addressed our testing and automation challenges, showcasing their adaptability, versatility, and reliability in various scenarios. I aim to demonstrate that sometimes, the “old” ways can indeed be the best ways.
BitLocker Data Recovery | BLR Tools Data Recovery SolutionsAlina Tait
BLR Tools provides an advanced BitLocker Data Recovery Tool specifically engineered to recover lost or inaccessible data from BitLocker-encrypted drives. Whether you're dealing with accidental deletion, encryption key problems, or system crashes, our cutting-edge software guarantees a secure and efficient recovery process. Rely on BLR Tools for dependable BitLocker data recovery and effortlessly restore access to your essential files.
pgroll - Zero-downtime, reversible, schema migrations for PostgresTudor Golubenco
pgroll is an open source command-line tool that offers safe and reversible schema migrations for PostgreSQL by serving multiple schema versions simultaneously. It takes care of the complex migration operations to ensure that client applications continue working while the database schema is being updated. This includes ensuring changes are applied without locking the database, and that both old and new schema versions work simultaneously (even when breaking changes are being made!). This removes risks related to schema migrations, and greatly simplifies client application rollout, also allowing for instant rollbacks.
Unlocking the Future of Artificial IntelligencedorinIonescu
Unlock the Future: Dive into AI Today! Videnda AI specializes in developing advanced artificial intelligence solutions, including visual dictionaries and language learning tools that leverage immersive virtual travel experiences. Stay Ahead of the Curve: Master AI Now! Our AI technology integrates machine learning and neural networks to enhance education and business applications. AI: The Next Frontier. Are You Ready to Explore? With a focus on real-time AI solutions and deep learning models, Videnda AI provides innovative tools for multilingual communication and immersive learning.
In this course, you'll find a series of engaging videos packed with vibrant animations that break down complex AI concepts into digestible pieces. Our curriculum covers AI models such as Convolutional Neural Networks (CNN), Multi-Layer Perceptrons (MLP), Generative Adversarial Networks (GAN), and Transformers, providing a solid understanding of these models and their real-world applications. We also offer hands-on experience with Generative AI tools like ChatGPT and Midjourney, and Python programming tutorials to help you implement AI algorithms and build your own AI applications.
We are proud participants in the Nvidia Inception Program, driving AI innovation across various industries. By the end of our course, you'll have a strong understanding of AI principles, enhanced Python programming skills, and practical experience with state-of-the-art Generative AI tools. Whether you're looking to kickstart a career in AI or simply curious about this revolutionary technology, Videnda AI is your partner in mastering the future of artificial intelligence.
Test Polarity: Detecting Positive and Negative Tests (FSE 2024)andrehoraa
Positive tests (aka, happy path tests) cover the expected behavior of the program, while negative tests (aka, unhappy path tests) check the unexpected behavior. Ideally, test suites should have both positive and negative tests to better protect against regressions. In practice, unfortunately, we cannot easily identify whether a test is positive or negative. A better understanding of whether a test suite is more positive or negative is fundamental to assessing the overall test suite capability in testing expected and unexpected behaviors. In this paper, we propose test polarity, an automated approach to detect positive and negative tests. Our approach runs/monitors the test suite and collects runtime data about the application execution to classify the test methods as positive or negative. In a first evaluation, test polarity correctly classified 117 tests as as positive or negative. Finally, we provide a preliminary empirical study to analyze the test polarity of 2,054 test methods from 12 real-world test suites of the Python Standard Library. We find that most of the analyzed test methods are negative (88%) and a minority is positive (12%). However, there is a large variation per project: while some libraries have an equivalent number of positive and negative tests, others have mostly negative ones.
A Step-by-Step Guide to Selecting the Right Automated Software Testing Tools.pdfkalichargn70th171
Software testing is highly essential in the software development lifecycle. Selecting the appropriate testing tool is pivotal for effective test automation and project success. As technology advances, the demands of the software market escalate, pushing industry players to deliver high-quality products swiftly through agile methodologies.
Crowd Strike\Windows Update Issue: Overview and Current Statusramaganesan0504
Crowd Strike\Windows Update Issue: Overview and Current Status
Discover the latest on the CrowdStrike Windows update issue, including an overview, current status, and support steps for affected customers. Learn about the identified defect, its impact on Windows hosts, and CrowdStrike's committed actions to ensure ongoing security and stability.
What is CrowdStrike?
CrowdStrike is a prominent cybersecurity technology company that specializes in providing advanced threat intelligence and endpoint protection solutions. Founded in 2011 by George Kurtz, Dmitri Alperovitch, and Gregg Marston, CrowdStrike has quickly established itself as a leader in the cybersecurity industry. Here are some key aspects of
Laravel has quickly become one of the leading PHP frameworks. Its elegant syntax, powerful features, and strong community backing make it a top choice for developers. This article delves into what makes Laravel development stand out and why it is considered the best PHP framework for modern web applications.
Unlocking value with event-driven architecture by Confluentconfluent
Sfrutta il potere dello streaming di dati in tempo reale e dei microservizi basati su eventi per il futuro di Sky con Confluent e Kafka®.
In questo tech talk esploreremo le potenzialità di Confluent e Apache Kafka® per rivoluzionare l'architettura aziendale e sbloccare nuove opportunità di business. Ne approfondiremo i concetti chiave, guidandoti nella creazione di applicazioni scalabili, resilienti e fruibili in tempo reale per lo streaming di dati.
Scoprirai come costruire microservizi basati su eventi con Confluent, sfruttando i vantaggi di un'architettura moderna e reattiva.
Il talk presenterà inoltre casi d'uso reali di Confluent e Kafka®, dimostrando come queste tecnologie possano ottimizzare i processi aziendali e generare valore concreto.
2. Agenda
● History and Community
● Technical Walkthrough
● Use Case with Mobike
● MySQL Compatibility
3. A little about me
● Senior Product / Community Manager
● ~15 years MySQL Experience
○ MySQL AB, Sun, Percona, Oracle
● Previously Product Manager for MySQL Server
4. A little about PingCAP
● Founded in April 2015 by 3 infrastructure
engineers
● Offices in China and North America
● Remote Friendly!
○ I work from here ➡
6. PingCAP.com
Our Product is the TiDB Platform
● TiDB Platform (Ti = Titanium)
○ TiDB (SQL Layer)
○ TiKV (Storage)
○ TiSpark (Apache Spark plugin to TiKV)
● Open source from Day 1
○ GA 1.0: October 2017
○ GA 2.0: April 2018
7. PingCAP.com
TiDB is a NewSQL Database
RDBMS NoSQL NewSQL
1970s 2010 2015
MySQL
PostgreSQL
Oracle
DB2...
Redis
HBase
Cassandra
MongoDB
Present
Google
Spanner
Google F1
TiDB
8. Common Use Cases
1. MySQL Scalability
2. Hybrid OLTP/OLAP Architecture
3. Unifying Data Storage/Management
14. PingCAP.com
TiKV: The Storage Foundation
RocksDB
Raft
Transaction
Txn KV API
Coprocessor
API
RocksDB
Raft
Transaction
Txn KV API
Coprocessor
API
RocksDB
Raft
Transaction
Txn KV API
Coprocessor
API
Raft
Group
Client
gRPC
TiKV Instance TiKV Instance TiKV Instance
gRPC gRPC
PD Cluster
15. PingCAP.com
TiDB: The SQL Layer
Node1 Node2 Node3 Node4
MySQL Network Protocol
SQL Parser
Cost-based Optimizer
Distributed Executor (Coprocessor)
ODBC/JDBC MySQL Client
Any ORM which
supports MySQL
TiDB
TiKV
21. PingCAP.com
Summary
● Compatibility with MySQL 5.7
○ Joins, subqueries, DML, DDL etc.
● On the roadmap:
○ Views, CTEs, Window Functions, GIS
● Missing:
○ Stored Procedures, Triggers, Events,
Fulltext pingcap.com
/docs/sql/mysql-compatibility/
22. PingCAP.com
Nuanced
● Some features work differently
○ Auto Increment
○ Optimistic Locking
● TiDB works better with smaller
transactions
○ Recommended to batch updates,
deletes, inserts to 5000 rows pingcap.com
/docs/sql/mysql-compatibility/