With Galera 4, MariaDB 10.4 cluster further extends the capabilities of the synchronous Galera replication. The most prominent feature in Galera 4 version, is streaming replication technology, which implements distributed transaction processing within the cluster. With streaming replication, a transaction can be launched to execute in all cluster nodes in parallel. With this, a large transaction can be executed in small fragments due out the transaction life time, and cluster will not choke with the replication of one large transaction write set, as happened in earlier Galera Cluster versions.
Streaming replication works as a foundation for many more features, to be released in short term. e.g. XA transaction support will now be possible thanks to streaming replication technology.
MariaDB 10.4 will come with new Galera Replication version 4. This presentation will outline the new features of Galera 4 Replication as present in MariaDB 10.4 and share the early user experiences with it.
Galera Cluster will be later released supporting MySQL 8.
MySQL Administrator
Basic course
- MySQL 개요
- MySQL 설치 / 설정
- MySQL 아키텍처 - MySQL 스토리지 엔진
- MySQL 관리
- MySQL 백업 / 복구
- MySQL 모니터링
Advanced course
- MySQL Optimization
- MariaDB / Percona
- MySQL HA (High Availability)
- MySQL troubleshooting
네오클로바
http://neoclova.co.kr/
Common Strategies for Improving Performance on Your Delta LakehouseDatabricks
The Delta Architecture pattern has made the lives of data engineers much simpler, but what about improving query performance for data analysts? What are some common places to look at for tuning query performance? In this session we will cover some common techniques to apply to our delta tables to make them perform better for data analysts queries. We will look at a few examples of how you can analyze a query, and determine what to focus on to deliver better performance results.
MySQL 8.0.18 latest updates: Hash join and EXPLAIN ANALYZENorvald Ryeng
This presentation focuses on two of the new features in MySQL 8.0.18: hash joins and EXPLAIN ANALYZE. It covers how these features work, both on the surface and on the inside, and how you can use them to improve your queries and make them go faster.
Both features are the result of major refactoring of how the MySQL executor works. In addition to explaining and demonstrating the features themselves, the presentation looks at how the investment in a new iterator based executor prepares MySQL for a future with faster queries, greater plan flexibility and even more SQL features.
MySQL Administrator
Basic course
- MySQL 개요
- MySQL 설치 / 설정
- MySQL 아키텍처 - MySQL 스토리지 엔진
- MySQL 관리
- MySQL 백업 / 복구
- MySQL 모니터링
Advanced course
- MySQL Optimization
- MariaDB / Percona
- MySQL HA (High Availability)
- MySQL troubleshooting
네오클로바
http://neoclova.co.kr/
Common Strategies for Improving Performance on Your Delta LakehouseDatabricks
The Delta Architecture pattern has made the lives of data engineers much simpler, but what about improving query performance for data analysts? What are some common places to look at for tuning query performance? In this session we will cover some common techniques to apply to our delta tables to make them perform better for data analysts queries. We will look at a few examples of how you can analyze a query, and determine what to focus on to deliver better performance results.
MySQL 8.0.18 latest updates: Hash join and EXPLAIN ANALYZENorvald Ryeng
This presentation focuses on two of the new features in MySQL 8.0.18: hash joins and EXPLAIN ANALYZE. It covers how these features work, both on the surface and on the inside, and how you can use them to improve your queries and make them go faster.
Both features are the result of major refactoring of how the MySQL executor works. In addition to explaining and demonstrating the features themselves, the presentation looks at how the investment in a new iterator based executor prepares MySQL for a future with faster queries, greater plan flexibility and even more SQL features.
Spencer Christensen
There are many aspects to managing an RDBMS. Some of these are handled by an experienced DBA, but there are a good many things that any sys admin should be able to take care of if they know what to look for.
This presentation will cover basics of managing Postgres, including creating database clusters, overview of configuration, and logging. We will also look at tools to help monitor Postgres and keep an eye on what is going on. Some of the tools we will review are:
* pgtop
* pg_top
* pgfouine
* check_postgres.pl.
Check_postgres.pl is a great tool that can plug into your Nagios or Cacti monitoring systems, giving you even better visibility into your databases.
PostgreSQL, performance for queries with groupingAlexey Bashtanov
The talk will cover PostgreSQL grouping and aggregation facilities and best practices of using them in fast and efficient manner.
In 40 minutes the audience will learn several techniques to optimise queries containing GROUP BY, DISTINCT or DISTINCT ON keywords.
This presentation covers MySQL data encryption at disk. How to encrypt all tablespaces and MySQL related files for the compliances ? The new releases in MySQL 8.0 take care of the encryption of the system tablespace and supporting tables unlike MySQL 5.7.
We talk a lot about Galera Cluster being great for High Availability, but what about Disaster Recovery (DR)? Database outages can occur when you lose a data centre due to data center power outages or natural disaster, so why not plan appropriately in advance?
In this webinar, we will discuss the business considerations including achieving the highest possible uptime, analysis business impact as well as risk, focus on disaster recovery itself, as well as discussing various scenarios, from having no offsite data to having synchronous replication to another data centre.
This webinar will cover MySQL with Galera Cluster, as well as branches MariaDB Galera Cluster as well as Percona XtraDB Cluster (PXC). We will focus on architecture solutions, DR scenarios and have you on your way to success at the end of it.
QuestDB: ingesting a million time series per second on a single instance. Big...javier ramirez
In this session I will show you the technical decisions we made when building QuestDB, the open source, Postgres compatible, time-series database, and how we can achieve a million row writes per second without blocking or slowing down the reads.
Distributed Databases Deconstructed: CockroachDB, TiDB and YugaByte DBYugabyteDB
Slides for Amey Banarse's, Principal Data Architect at Yugabyte, "Distributed Databases Deconstructed: CockroachDB, TiDB and YugaByte DB" webinar recorded on Oct 30, 2019 at 11 AM Pacific.
Playback here: https://vimeo.com/369929255
MySQL Load Balancers - Maxscale, ProxySQL, HAProxy, MySQL Router & nginx - A ...Severalnines
This presentation by Krzysztof Książek at Percona Live 2017 in Santa Clara, California gives detailed descriptions and comparisons of the leading open source database load balancing technologies
Hyperspace: An Indexing Subsystem for Apache SparkDatabricks
At Microsoft, we store datasets (both from internal teams and external customers) ranging from a few GBs to 100s of PBs in our data lake. The scope of analytics on these datasets ranges from traditional batch-style queries (e.g., OLAP) to explorative, ‘finding needle in a haystack’ type of queries (e.g., point-lookups, summarization etc.).
Percona XtraDB Cluster vs Galera Cluster vs MySQL Group ReplicationKenny Gryp
What are the implementation differences between Percona XtraDB Cluster 5.7, Galera Cluster 5.7 and MySQL Group Replication?
- How do each of these work?
- How do they behave differently?
- Are there any major issues with any of these?
This talk will describe these differences and also shed some light on how QA is done for each of these different technologies.
Tuning Apache Kafka Connectors for Flink.pptxFlink Forward
Flink Forward San Francisco 2022.
In normal situations, the default Kafka consumer and producer configuration options work well. But we all know life is not all roses and rainbows and in this session we’ll explore a few knobs that can save the day in atypical scenarios. First, we'll take a detailed look at the parameters available when reading from Kafka. We’ll inspect the params helping us to spot quickly an application lock or crash, the ones that can significantly improve the performance and the ones to touch with gloves since they could cause more harm than benefit. Moreover we’ll explore the partitioning options and discuss when diverging from the default strategy is needed. Next, we’ll discuss the Kafka Sink. After browsing the available options we'll then dive deep into understanding how to approach use cases like sinking enormous records, managing spikes, and handling small but frequent updates.. If you want to understand how to make your application survive when the sky is dark, this session is for you!
by
Olena Babenko
FPGA-Based Acceleration Architecture for Spark SQL Qi Xie and Quanfu Wang Spark Summit
In this session we will present a Configurable FPGA-Based Spark SQL Acceleration Architecture. It is target to leverage FPGA highly parallel computing capability to accelerate Spark SQL Query and for FPGA’s higher power efficiency than CPU we can lower the power consumption at the same time. The Architecture consists of SQL query decomposition algorithms, fine-grained FPGA based Engine Units which perform basic computation of sub string, arithmetic and logic operations. Using SQL query decomposition algorithm, we are able to decompose a complex SQL query into basic operations and according to their patterns each is fed into an Engine Unit. SQL Engine Units are highly configurable and can be chained together to perform complex Spark SQL queries, finally one SQL query is transformed into a Hardware Pipeline. We will present the performance benchmark results comparing the queries with FGPA-Based Spark SQL Acceleration Architecture on XEON E5 and FPGA to the ones with Spark SQL Query on XEON E5 with 10X ~ 100X improvement and we will demonstrate one SQL query workload from a real customer.
MySQL InnoDB Cluster - Advanced Configuration & OperationsFrederic Descamps
MySQL InnoDB Cluster is a very easy HA solution to deploy. However it's also a very customizable solution able to respond to most needs. During this session I will give an overview of settings that you may tune like those related to quorum lost, level of consistency, but also some you may not know like how to change recovery system, effect of increasing the event horizon. We will also discus about maintenance operations like how to stream large transactions, how to deal with DDL in multi-primary environments...
MySQL and MariaDB though they share the same roots for replication .They support parallel replication , but they diverge the way the parallel replication is implemented.
Memory management is at the heart of any data-intensive system. Spark, in particular, must arbitrate memory allocation between two main use cases: buffering intermediate data for processing (execution) and caching user data (storage). This talk will take a deep dive through the memory management designs adopted in Spark since its inception and discuss their performance and usability implications for the end user.
Delta from a Data Engineer's PerspectiveDatabricks
Take a walk through the daily struggles of a data engineer in this presentation as we cover what is truly needed to create robust end to end Big Data solutions.
Spencer Christensen
There are many aspects to managing an RDBMS. Some of these are handled by an experienced DBA, but there are a good many things that any sys admin should be able to take care of if they know what to look for.
This presentation will cover basics of managing Postgres, including creating database clusters, overview of configuration, and logging. We will also look at tools to help monitor Postgres and keep an eye on what is going on. Some of the tools we will review are:
* pgtop
* pg_top
* pgfouine
* check_postgres.pl.
Check_postgres.pl is a great tool that can plug into your Nagios or Cacti monitoring systems, giving you even better visibility into your databases.
PostgreSQL, performance for queries with groupingAlexey Bashtanov
The talk will cover PostgreSQL grouping and aggregation facilities and best practices of using them in fast and efficient manner.
In 40 minutes the audience will learn several techniques to optimise queries containing GROUP BY, DISTINCT or DISTINCT ON keywords.
This presentation covers MySQL data encryption at disk. How to encrypt all tablespaces and MySQL related files for the compliances ? The new releases in MySQL 8.0 take care of the encryption of the system tablespace and supporting tables unlike MySQL 5.7.
We talk a lot about Galera Cluster being great for High Availability, but what about Disaster Recovery (DR)? Database outages can occur when you lose a data centre due to data center power outages or natural disaster, so why not plan appropriately in advance?
In this webinar, we will discuss the business considerations including achieving the highest possible uptime, analysis business impact as well as risk, focus on disaster recovery itself, as well as discussing various scenarios, from having no offsite data to having synchronous replication to another data centre.
This webinar will cover MySQL with Galera Cluster, as well as branches MariaDB Galera Cluster as well as Percona XtraDB Cluster (PXC). We will focus on architecture solutions, DR scenarios and have you on your way to success at the end of it.
QuestDB: ingesting a million time series per second on a single instance. Big...javier ramirez
In this session I will show you the technical decisions we made when building QuestDB, the open source, Postgres compatible, time-series database, and how we can achieve a million row writes per second without blocking or slowing down the reads.
Distributed Databases Deconstructed: CockroachDB, TiDB and YugaByte DBYugabyteDB
Slides for Amey Banarse's, Principal Data Architect at Yugabyte, "Distributed Databases Deconstructed: CockroachDB, TiDB and YugaByte DB" webinar recorded on Oct 30, 2019 at 11 AM Pacific.
Playback here: https://vimeo.com/369929255
MySQL Load Balancers - Maxscale, ProxySQL, HAProxy, MySQL Router & nginx - A ...Severalnines
This presentation by Krzysztof Książek at Percona Live 2017 in Santa Clara, California gives detailed descriptions and comparisons of the leading open source database load balancing technologies
Hyperspace: An Indexing Subsystem for Apache SparkDatabricks
At Microsoft, we store datasets (both from internal teams and external customers) ranging from a few GBs to 100s of PBs in our data lake. The scope of analytics on these datasets ranges from traditional batch-style queries (e.g., OLAP) to explorative, ‘finding needle in a haystack’ type of queries (e.g., point-lookups, summarization etc.).
Percona XtraDB Cluster vs Galera Cluster vs MySQL Group ReplicationKenny Gryp
What are the implementation differences between Percona XtraDB Cluster 5.7, Galera Cluster 5.7 and MySQL Group Replication?
- How do each of these work?
- How do they behave differently?
- Are there any major issues with any of these?
This talk will describe these differences and also shed some light on how QA is done for each of these different technologies.
Tuning Apache Kafka Connectors for Flink.pptxFlink Forward
Flink Forward San Francisco 2022.
In normal situations, the default Kafka consumer and producer configuration options work well. But we all know life is not all roses and rainbows and in this session we’ll explore a few knobs that can save the day in atypical scenarios. First, we'll take a detailed look at the parameters available when reading from Kafka. We’ll inspect the params helping us to spot quickly an application lock or crash, the ones that can significantly improve the performance and the ones to touch with gloves since they could cause more harm than benefit. Moreover we’ll explore the partitioning options and discuss when diverging from the default strategy is needed. Next, we’ll discuss the Kafka Sink. After browsing the available options we'll then dive deep into understanding how to approach use cases like sinking enormous records, managing spikes, and handling small but frequent updates.. If you want to understand how to make your application survive when the sky is dark, this session is for you!
by
Olena Babenko
FPGA-Based Acceleration Architecture for Spark SQL Qi Xie and Quanfu Wang Spark Summit
In this session we will present a Configurable FPGA-Based Spark SQL Acceleration Architecture. It is target to leverage FPGA highly parallel computing capability to accelerate Spark SQL Query and for FPGA’s higher power efficiency than CPU we can lower the power consumption at the same time. The Architecture consists of SQL query decomposition algorithms, fine-grained FPGA based Engine Units which perform basic computation of sub string, arithmetic and logic operations. Using SQL query decomposition algorithm, we are able to decompose a complex SQL query into basic operations and according to their patterns each is fed into an Engine Unit. SQL Engine Units are highly configurable and can be chained together to perform complex Spark SQL queries, finally one SQL query is transformed into a Hardware Pipeline. We will present the performance benchmark results comparing the queries with FGPA-Based Spark SQL Acceleration Architecture on XEON E5 and FPGA to the ones with Spark SQL Query on XEON E5 with 10X ~ 100X improvement and we will demonstrate one SQL query workload from a real customer.
MySQL InnoDB Cluster - Advanced Configuration & OperationsFrederic Descamps
MySQL InnoDB Cluster is a very easy HA solution to deploy. However it's also a very customizable solution able to respond to most needs. During this session I will give an overview of settings that you may tune like those related to quorum lost, level of consistency, but also some you may not know like how to change recovery system, effect of increasing the event horizon. We will also discus about maintenance operations like how to stream large transactions, how to deal with DDL in multi-primary environments...
MySQL and MariaDB though they share the same roots for replication .They support parallel replication , but they diverge the way the parallel replication is implemented.
Memory management is at the heart of any data-intensive system. Spark, in particular, must arbitrate memory allocation between two main use cases: buffering intermediate data for processing (execution) and caching user data (storage). This talk will take a deep dive through the memory management designs adopted in Spark since its inception and discuss their performance and usability implications for the end user.
Delta from a Data Engineer's PerspectiveDatabricks
Take a walk through the daily struggles of a data engineer in this presentation as we cover what is truly needed to create robust end to end Big Data solutions.
Topics covered in this presentation, which was used for user group meetings, conferences & webinars:
1. Galera Cluster for MySQL - overview
2. Release 3 New Features:
* WAN Replication
* 5.6 Global Transaction ID (GTID) Support
* MySQL Replication Support
* and more features
3. The Galera Cluster Project
From these slides you'll learn how Galera integrates with MySQL 5.6 and Global Transaction IDs to enable cross-datacenter and cloud replication over high latency networks.
ABOUT GALERA CLUSTER
Galera Cluster for MySQL is a true multi-master MySQL replication plugin, and has been proven in mission-critical infrastructures of companies like Ping Identity, AVG Technologies, KPN and HP Cloud DNS. In this webcast you¹ll learn about the following Galera Cluster capabilities, including the latest innovations in the new 3.0 release:
Galera Cluster features and benefits
Support for MySQL 5.6
Integration with MySQL Global Transaction Identifiers
Mixing Galera synchronous replication and asynchronous MySQL replication
Deploying in WAN and Cloud environments
Handling high-latency networks
Management of Galera
Webinar slides: Introducing Galera 3.0 - Now supporting MySQL 5.6Severalnines
You'll learn how Galera integrates with MySQL 5.6 and Global Transaction IDs to enable cross-datacenter and cloud replication over high latency networks. The benefits are clear; a globally distributed MySQL setup across regions to deliver Severalnines availability and real-time responsiveness.
Galera Cluster for MySQL is a true multi-master MySQL replication plugin, and has been proven in mission-critical infrastructures of companies like Ping Identity, AVG Technologies, KPN and HP Cloud DNS. In this webcast you¹ll learn about the following Galera Cluster capabilities, including the latest innovations in the new 3.0 release:
Galera Cluster features and benefits
Support for MySQL 5.6
Integration with MySQL Global Transaction Identifiers
Mixing Galera synchronous replication and asynchronous MySQL replication
Deploying in WAN and Cloud environments
Handling high-latency networks
Management of Galera
There are many Galera Cluster distributions and sometimes differences are well worth noting. We get a lot of queries about which Galera Cluster to use, or why one should use one distribution over the other.
Learn about Galera Cluster with MySQL 5.7 from Codership, and we’ll compare it with Galera Cluster 4 with MariaDB 10.4, and Percona XtraDB Cluster 5.7 with Galera 3. This is also the webinar where we preview Galera Cluster 4 with MySQL 8.0 as well as compare it with the preview release of Percona XtraDB Cluster 8.0.
Overall, learn why distributions exists, and how you can get the most out of your Galera Cluster experience.
Webinar slides: Migrating to Galera Cluster for MySQL and MariaDBSeveralnines
Galera Cluster is a mainstream option for high availability MySQL and MariaDB. And though it has established itself as a credible replacement for traditional MySQL master-slave architectures, it is not a drop-in replacement.
While Galera Cluster has some characteristics that make it unsuitable for certain use cases, most applications can still be adapted to run on it.
The benefits are clear: multi-master InnoDB setup with built-in failover and read scalability.
But how do you migrate? Does the schema or application change? What are the limitations? Can a migration be done online, without service interruption? What are the potential risks?
In this webinar, Severalnines Support Engineer Bart Oles walks you through what you need to know in order to migrate from standalone or a master-slave MySQL/MariaDB setup to Galera Cluster.
AGENDA
- Application use cases for Galera
- Schema design
- Events and Triggers
- Query design
- Migrating the schema
- Load balancer and VIP
- Loading initial data into the cluster
- Limitations:
- Cluster technology
- Application vendor support
- Performing Online Migration to Galera
- Operational management checklist
- Belts and suspenders: Plan B
- Demo
SPEAKER
Bartlomiej Oles is a MySQL and Oracle DBA, with over 15 years experience in managing highly available production systems at IBM, Nordea Bank, Acxiom, Lufthansa, and other Fortune 500 companies. In the past five years, his focus has been on building and applying automation tools to manage multi-datacenter database environments.
The much anticipated release of Galera Cluster 4 for MySQL 8 is now Generally Available. Please join Codership, the developers of Galera Cluster, and learn how we improve MySQL High Availability with the new features in Galera Cluster 4, and how you can benefit from using them. We will also give you an idea of the Galera 4 short term road map, as well as an overview of Galera 4 in MariaDB, MySQL and Percona.
Learn about how you can load data faster with streaming replication, how to use the new system tables in the mysql database, how your application can benefit from the new synchronization functions, and how Galera Cluster is now so much more robust in handling a bad network for Geo-distributed Multi-master MySQL. We will go through a quick install of a 3-node Galera Cluster as well.
MySQL Scalability and Reliability for Replicated EnvironmentJean-François Gagné
You have a working application that is using MySQL: great! At the beginning, you are probably using a single database instance, and maybe – but not necessarily – you have replication for backups, but you are not reading from slaves yet. Scalability and reliability were not the main focus in the past, but they are starting to be a concern. Soon, you will have many databases and you will have to deal with replication lag. This talk will present how to tackle the transition.
We mostly cover standard/asynchronous replication, but we will also touch on Galera and Group Replication. We present how to adapt the application to become replication-friendly, which facilitate reading from and failing over to slaves. We also present solutions for managing read views at scale and enabling read-your-own-writes on slaves. We also touch on vertical and horizontal sharding for when deploying bigger servers is not possible anymore.
Are UNIQUE and FOREIGN KEYs still possible at scale, what are the downsides of AUTO_INCREMENTs, how to avoid overloading replication, what are the limits of archiving, … Come to this talk to get answers and to leave with tools for tackling the challenges of the future.
MariaDB Galera Cluster Webinar by Ivan Zoratti on 13.11.2013. Also available as on demand webinar at http://www.skysql.com/why-skysql/webinars/mariadb-galera-cluster-simple-transparent-highly-available
What to expect from MariaDB Platform X5, part 1MariaDB plc
MariaDB Platform X5 will be based on MariaDB Enterprise Server 10.5. This release includes Xpand, a fully distributed storage engine for scaling out, as well as many new features and improvements for DBAs and developers alike, including enhancements to temporal tables, additional JSON functions, a new performance schema, non-blocking schema changes with clustering and a Hashicorp Vault plugin for key management.
In this session, we’ll walk through all of the new features and enhancements available in MariaDB Enterprise Server 10.5. In addition, we will highlight those being backported to maintenance releases of MariaDB Enterprise Server 10.2, 10.3 and 10.4.
MariaDB 10 and Beyond - the Future of Open Source Databases by Ivan Zoratti.
Presented 24.6.2014 at the MariaDB Roadshow in Maarssen, Utrecht, The Netherlands.
Tips to drive maria db cluster performance for nextcloudSeveralnines
Nextcloud requires a database to store administrative data for the platform. A poorly performing database can have a serious impact on performance and availability of Nextcloud. MariaDB Cluster is the recommended database backend for production installations that require high availability and performance.
This talk is a deep dive into how to design and optimize MariaDB Galera Cluster for Nextcloud. We will cover 5 tips on how to significantly improve performance and stability.
Agenda:
Overview of Nextcloud architecture
Database architecture design
Database proxy
MariaDB and InnoDB performance tuning
Nextcloud performance tuning
Q&A
Enhancing Research Orchestration Capabilities at ORNL.pdfGlobus
Cross-facility research orchestration comes with ever-changing constraints regarding the availability and suitability of various compute and data resources. In short, a flexible data and processing fabric is needed to enable the dynamic redirection of data and compute tasks throughout the lifecycle of an experiment. In this talk, we illustrate how we easily leveraged Globus services to instrument the ACE research testbed at the Oak Ridge Leadership Computing Facility with flexible data and task orchestration capabilities.
top nidhi software solution freedownloadvrstrong314
This presentation emphasizes the importance of data security and legal compliance for Nidhi companies in India. It highlights how online Nidhi software solutions, like Vector Nidhi Software, offer advanced features tailored to these needs. Key aspects include encryption, access controls, and audit trails to ensure data security. The software complies with regulatory guidelines from the MCA and RBI and adheres to Nidhi Rules, 2014. With customizable, user-friendly interfaces and real-time features, these Nidhi software solutions enhance efficiency, support growth, and provide exceptional member services. The presentation concludes with contact information for further inquiries.
Paketo Buildpacks : la meilleure façon de construire des images OCI? DevopsDa...Anthony Dahanne
Les Buildpacks existent depuis plus de 10 ans ! D’abord, ils étaient utilisés pour détecter et construire une application avant de la déployer sur certains PaaS. Ensuite, nous avons pu créer des images Docker (OCI) avec leur dernière génération, les Cloud Native Buildpacks (CNCF en incubation). Sont-ils une bonne alternative au Dockerfile ? Que sont les buildpacks Paketo ? Quelles communautés les soutiennent et comment ?
Venez le découvrir lors de cette session ignite
Providing Globus Services to Users of JASMIN for Environmental Data AnalysisGlobus
JASMIN is the UK’s high-performance data analysis platform for environmental science, operated by STFC on behalf of the UK Natural Environment Research Council (NERC). In addition to its role in hosting the CEDA Archive (NERC’s long-term repository for climate, atmospheric science & Earth observation data in the UK), JASMIN provides a collaborative platform to a community of around 2,000 scientists in the UK and beyond, providing nearly 400 environmental science projects with working space, compute resources and tools to facilitate their work. High-performance data transfer into and out of JASMIN has always been a key feature, with many scientists bringing model outputs from supercomputers elsewhere in the UK, to analyse against observational or other model data in the CEDA Archive. A growing number of JASMIN users are now realising the benefits of using the Globus service to provide reliable and efficient data movement and other tasks in this and other contexts. Further use cases involve long-distance (intercontinental) transfers to and from JASMIN, and collecting results from a mobile atmospheric radar system, pushing data to JASMIN via a lightweight Globus deployment. We provide details of how Globus fits into our current infrastructure, our experience of the recent migration to GCSv5.4, and of our interest in developing use of the wider ecosystem of Globus services for the benefit of our user community.
Climate Science Flows: Enabling Petabyte-Scale Climate Analysis with the Eart...Globus
The Earth System Grid Federation (ESGF) is a global network of data servers that archives and distributes the planet’s largest collection of Earth system model output for thousands of climate and environmental scientists worldwide. Many of these petabyte-scale data archives are located in proximity to large high-performance computing (HPC) or cloud computing resources, but the primary workflow for data users consists of transferring data, and applying computations on a different system. As a part of the ESGF 2.0 US project (funded by the United States Department of Energy Office of Science), we developed pre-defined data workflows, which can be run on-demand, capable of applying many data reduction and data analysis to the large ESGF data archives, transferring only the resultant analysis (ex. visualizations, smaller data files). In this talk, we will showcase a few of these workflows, highlighting how Globus Flows can be used for petabyte-scale climate analysis.
Field Employee Tracking System| MiTrack App| Best Employee Tracking Solution|...informapgpstrackings
Keep tabs on your field staff effortlessly with Informap Technology Centre LLC. Real-time tracking, task assignment, and smart features for efficient management. Request a live demo today!
For more details, visit us : https://informapuae.com/field-staff-tracking/
Strategies for Successful Data Migration Tools.pptxvarshanayak241
Data migration is a complex but essential task for organizations aiming to modernize their IT infrastructure and leverage new technologies. By understanding common challenges and implementing these strategies, businesses can achieve a successful migration with minimal disruption. Data Migration Tool like Ask On Data play a pivotal role in this journey, offering features that streamline the process, ensure data integrity, and maintain security. With the right approach and tools, organizations can turn the challenge of data migration into an opportunity for growth and innovation.
Gamify Your Mind; The Secret Sauce to Delivering Success, Continuously Improv...Shahin Sheidaei
Games are powerful teaching tools, fostering hands-on engagement and fun. But they require careful consideration to succeed. Join me to explore factors in running and selecting games, ensuring they serve as effective teaching tools. Learn to maintain focus on learning objectives while playing, and how to measure the ROI of gaming in education. Discover strategies for pitching gaming to leadership. This session offers insights, tips, and examples for coaches, team leads, and enterprise leaders seeking to teach from simple to complex concepts.
A Comprehensive Look at Generative AI in Retail App Testing.pdfkalichargn70th171
Traditional software testing methods are being challenged in retail, where customer expectations and technological advancements continually shape the landscape. Enter generative AI—a transformative subset of artificial intelligence technologies poised to revolutionize software testing.
Large Language Models and the End of ProgrammingMatt Welsh
Talk by Matt Welsh at Craft Conference 2024 on the impact that Large Language Models will have on the future of software development. In this talk, I discuss the ways in which LLMs will impact the software industry, from replacing human software developers with AI, to replacing conventional software with models that perform reasoning, computation, and problem-solving.
Understanding Globus Data Transfers with NetSageGlobus
NetSage is an open privacy-aware network measurement, analysis, and visualization service designed to help end-users visualize and reason about large data transfers. NetSage traditionally has used a combination of passive measurements, including SNMP and flow data, as well as active measurements, mainly perfSONAR, to provide longitudinal network performance data visualization. It has been deployed by dozens of networks world wide, and is supported domestically by the Engagement and Performance Operations Center (EPOC), NSF #2328479. We have recently expanded the NetSage data sources to include logs for Globus data transfers, following the same privacy-preserving approach as for Flow data. Using the logs for the Texas Advanced Computing Center (TACC) as an example, this talk will walk through several different example use cases that NetSage can answer, including: Who is using Globus to share data with my institution, and what kind of performance are they able to achieve? How many transfers has Globus supported for us? Which sites are we sharing the most data with, and how is that changing over time? How is my site using Globus to move data internally, and what kind of performance do we see for those transfers? What percentage of data transfers at my institution used Globus, and how did the overall data transfer performance compare to the Globus users?
Innovating Inference - Remote Triggering of Large Language Models on HPC Clus...Globus
Large Language Models (LLMs) are currently the center of attention in the tech world, particularly for their potential to advance research. In this presentation, we'll explore a straightforward and effective method for quickly initiating inference runs on supercomputers using the vLLM tool with Globus Compute, specifically on the Polaris system at ALCF. We'll begin by briefly discussing the popularity and applications of LLMs in various fields. Following this, we will introduce the vLLM tool, and explain how it integrates with Globus Compute to efficiently manage LLM operations on Polaris. Attendees will learn the practical aspects of setting up and remotely triggering LLMs from local machines, focusing on ease of use and efficiency. This talk is ideal for researchers and practitioners looking to leverage the power of LLMs in their work, offering a clear guide to harnessing supercomputing resources for quick and effective LLM inference.
TROUBLESHOOTING 9 TYPES OF OUTOFMEMORYERRORTier1 app
Even though at surface level ‘java.lang.OutOfMemoryError’ appears as one single error; underlyingly there are 9 types of OutOfMemoryError. Each type of OutOfMemoryError has different causes, diagnosis approaches and solutions. This session equips you with the knowledge, tools, and techniques needed to troubleshoot and conquer OutOfMemoryError in all its forms, ensuring smoother, more efficient Java applications.
Unleash Unlimited Potential with One-Time Purchase
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How Does XfilesPro Ensure Security While Sharing Documents in Salesforce?XfilesPro
Worried about document security while sharing them in Salesforce? Fret no more! Here are the top-notch security standards XfilesPro upholds to ensure strong security for your Salesforce documents while sharing with internal or external people.
To learn more, read the blog: https://www.xfilespro.com/how-does-xfilespro-make-document-sharing-secure-and-seamless-in-salesforce/
3. C o d e r s h i p
Technology Company
Since 2007
Replication for Open Source
Databases
Galera Cluster
Business through MySQL /
MariaDB Support & Consulting
Technology Company, focus in R&D
Since 2007
Replication for Open Source Databases
Galera Cluster
Business through MySQL / MariaDB
Support & Consulting
Stable continuous growth,
team growing 3 → ~20
C o d e r s h i p
5. www.galeracluster.com
galera
●
Generic Replication Plugin for
database servers
●
Uses Replication API to interact with
DBMS (wsrep API project in github)
●
DBMS and Galera plugin must have same
wsrep API version
Galera Replication
6. 6
www.galeracluster.com
Galera Replication Versions
●
Major versions 1..2..3
●
Current production head version 3.26
●
wsrep API versions 1..25
●
Next major version is Galera 4 and using wsrep
API #26
●
wsrep API change requires rolling upgrade path
8. 8
www.galeracluster.com
Galera 4 in MariaDB 10.4
●
MariaDB 10.4 RC has Galera 4 Replication
●
wsrep API #26
●
Impacts upgrading
●
wsrep patch integration in 10.4 codebase
●
Impacts code stability
●
bug fix & new features turnover
9. 9
www.galeracluster.com
Galera 4 in MariaDB 10.4
●
Streaming Replication
●
Support for large transactions
●
Platform for other new features
●
Group commit support
●
10.4 Backup locks
●
mariabackup SST with “light weight lock”
11. 11
www.galeracluster.com
Streaming Replication
●
Originally developed for supporting huge
transactions
●
In Galera 3, transaction processes in master node
until commit time
●
For large transactions, the write size will be big,
and is hard to handle
●
There are means to prevent too large transactions
●
wsrep_max_ws_size
13. 13
www.galeracluster.com
Streaming Replication
●
Transaction is replicated, gradually in small
fragments, during transaction processing
●
i.e. before actual commit, we replicate a number of small size
fragments
●
Size threshold for fragment replication is configurable
●
Replicated fragments are applied in slave threads
preserving transaction’s state in all cluster nodes
●
Fragments hold locks in all nodes and cannot be conflicted later
26. 26
www.galeracluster.com
Configuring Streaming Replication
wsrep_trx_fragment_unit Unit metrics for fragmenting, options are:
●
bytes WS size in bytes
●
rows # of rows modified
●
statements # of SQL statements issued
wsrep_trx_fragment_size ●
Threshold size (in units), when fragment will be
replicated
●
0 = no streaming
Session variables and can be dynamically set
27. 27
www.galeracluster.com
Using Streaming Replication
●
Due to excessive logging and elevated
replication overhead, streaming replication will
cause degraded transaction throughput rate
●
Best use case is to use streaming replication for
cutting large transactions
●
Set fragment size to ~10K rows
●
Fragment variables are session variables and
can be dynamically set
●
Intelligent application can set streaming
replication on/off on need basis
29. 29
www.galeracluster.com
wsrep Tables in mysql database
MariaDB [(none)]> show tables in mysql like 'wsrep%';
+--------------------------+
| Tables_in_mysql (wsrep%) |
+--------------------------+
| wsrep_cluster |
| wsrep_cluster_members |
| wsrep_streaming_log |
+--------------------------+
3 rows in set (0.005 sec)
30. 30
www.galeracluster.com
wsrep Tables in mysql database
MariaDB [(none)]> select * from mysql.wsrep_clusterG
*************************** 1. row ***************************
cluster_uuid: 0be6f4d6-35da-11e9-b8a0-d6501fb08579
view_id: 2
view_seqno: 2
protocol_version: 4
capabilities: 184703
1 row in set (0.005 sec)
41. 41
www.galeracluster.com
4.0 Release Status
●
Part of Galera 4 feature set was merged in
MariaDB 10.4 beta 2 release and is now in the
10.4 RC and later releases
●
Schedule of remaining Galera 4 features is not
yet confirmed
42. 42
www.galeracluster.com
Features Missed in MariaDB 10.4
●
Gcache encryption
●
Data at rest encryption for full replication pipeline
●
XA transaction support
●
Will be needed in sharding cluster
●
Non blocking DDL
●
Co-incides with other MariaDB non-locking DDL work
●
Cluster error voting
●
Galera library feature, may be in later 10.4.* releases
46. 46
www.galeracluster.com
Features Missed in MariaDB 10.4
●
Gcache encryption
●
Data at rest encryption for full replication pipeline
●
XA transaction support
●
Will be needed in sharding cluster
●
Non blocking DDL
●
Co-incides with other MariaDB non-locking DDL work
●
Cluster error voting
●
Galera library feature, may be in later 10.4.* releases
48. 48
www.galeracluster.com
XA Transactions with Galera 3
TM
RM RM
XA start ‘foo’ XA start ‘bar’
foo bar
Work on ‘foo’ Work on ‘bar’XA prepare ‘foo’ XA prepare ‘bar’XA commit ‘foo’ XA commit ‘bar’
foo bar
MariaDB
49. 49
www.galeracluster.com
XA Transactions with Galera 3
●
Galera replication is eager to replicate in
MariaDB 2PC prepare stage
●
Prepared XA transaction cannot be rolled back
anymore
71. 71
www.galeracluster.com
Features Missed in MariaDB 10.4
●
Gcache encryption
●
Data at rest encryption for full replication pipeline
●
XA transaction support
●
Will be needed in sharding cluster
●
Non blocking DDL
●
Co-incides with other MariaDB non-locking DDL work
●
Cluster error voting
●
Galera library feature, may be in later 10.4.* releases
73. 73
www.galeracluster.com
Galera 4 on MySQL
●
Galera 4 is integrated in MySQL 5.6 and 5.7
and 8.0 versions
●
Public releases after MariaDB 10.4 GA is
released
74. 74
www.galeracluster.com
Summary
●
MariaDB 10.4.5 has significant new
Galera 4 features
●
Streaming Replication implements new replication
protocol opening possibilities for many unforeseen
replication features
●
Other new Galera 4 related features to come with
later 10.4 and 10.5 releases
●
MySQL version is coming
●
Rolling cluster upgrade supported and requires care