In this presentation we consider how to resolve Firebird performance problems: what Firebird database parameters we need to monitor and how we need to tune Firebird configuration and adjust client applications.
There are more and more companies have big Firebird databases, from 100Gb till 1Tb. Maintenance and optimization tasks for such databases are different from small, and database administrators need take into account several important things about big Firebird databases.
How We Reduced Performance Tuning Time by Orders of Magnitude with Database O...ScyllaDB
Doing performance tuning on a massively distributed database is never an easy task. This is especially true for TiDB, an open-source, cloud-native NewSQL database for elastic scale and real-time analytics, because it consists of multiple components and each component has plenty of metrics.
Like many distributed systems, TiDB uses Prometheus to store the monitoring and performance metrics and Grafana to visualize these metrics. Thanks to these two open source projects, it is easy for TiDB developers to add monitoring and performance metrics. However, as the metrics increase, the learning curve becomes steeper for TiDB users to gain performance insights. In this talk, we will share how we measure latency in a distributed system using a top-down (holistic) approach, and why we introduced "tuning by database time" and "tuning by color" into TiDB. The new methodologies and Grafana dashboard help reduce the time and the requirement of expertise in performance tuning by orders of magnitude.
Analyzing big data quickly and efficiently requires a data warehouse optimized to handle and scale for large datasets. Amazon Redshift is a fast, petabyte-scale data warehouse that makes it simple and cost-effective to analyze big data for a fraction of the cost of traditional data warehouses. By following a few best practices, you can take advantage of Amazon Redshift’s columnar technology and parallel processing capabilities to minimize I/O and deliver high throughput and query performance. This webinar will cover techniques to load data efficiently, design optimal schemas, and use work load management.
Learning Objectives:
• Get an inside look at Amazon Redshift's columnar technology and parallel processing capabilities
• Learn how to migrate from existing data warehouses, optimize schemas, and load data efficiently
• Learn best practices for managing workload, tuning your queries, and using Amazon Redshift's interleaved sorting features
Who Should Attend:
• Data Warehouse Developers, Big Data Architects, BI Managers, and Data Engineers
There are more and more companies have big Firebird databases, from 100Gb till 1Tb. Maintenance and optimization tasks for such databases are different from small, and database administrators need take into account several important things about big Firebird databases.
How We Reduced Performance Tuning Time by Orders of Magnitude with Database O...ScyllaDB
Doing performance tuning on a massively distributed database is never an easy task. This is especially true for TiDB, an open-source, cloud-native NewSQL database for elastic scale and real-time analytics, because it consists of multiple components and each component has plenty of metrics.
Like many distributed systems, TiDB uses Prometheus to store the monitoring and performance metrics and Grafana to visualize these metrics. Thanks to these two open source projects, it is easy for TiDB developers to add monitoring and performance metrics. However, as the metrics increase, the learning curve becomes steeper for TiDB users to gain performance insights. In this talk, we will share how we measure latency in a distributed system using a top-down (holistic) approach, and why we introduced "tuning by database time" and "tuning by color" into TiDB. The new methodologies and Grafana dashboard help reduce the time and the requirement of expertise in performance tuning by orders of magnitude.
Analyzing big data quickly and efficiently requires a data warehouse optimized to handle and scale for large datasets. Amazon Redshift is a fast, petabyte-scale data warehouse that makes it simple and cost-effective to analyze big data for a fraction of the cost of traditional data warehouses. By following a few best practices, you can take advantage of Amazon Redshift’s columnar technology and parallel processing capabilities to minimize I/O and deliver high throughput and query performance. This webinar will cover techniques to load data efficiently, design optimal schemas, and use work load management.
Learning Objectives:
• Get an inside look at Amazon Redshift's columnar technology and parallel processing capabilities
• Learn how to migrate from existing data warehouses, optimize schemas, and load data efficiently
• Learn best practices for managing workload, tuning your queries, and using Amazon Redshift's interleaved sorting features
Who Should Attend:
• Data Warehouse Developers, Big Data Architects, BI Managers, and Data Engineers
Real-time, Exactly-once Data Ingestion from Kafka to ClickHouse at eBayAltinity Ltd
LIVE WEBINAR: October 21, 2021 | 10 am PT
SPEAKERS: Jun Li, Principal Architect, eBay & Robert Hodges, CEO, Altinity
eBay depends on Kafka to solve the impedance mismatch between rapidly arriving messages in event streams and efficient block insert into ClickHouse clusters. Naïve loading procedures from Kafka to ClickHouse generate non-deterministic blocks, which can lead to data loss and incorrect results in applications. The eBay team solved this problem with a block aggregator that leverages Kafka to store message processing metadata as well as ClickHouse deduplication to ensure blocks being loaded to ClickHouse exactly once. The block aggregator allows eBay to support a sharded ClickHouse architecture across multiple data centers that can tolerate failures in any individual part of the system. Join us to learn how eBay developed this unique architecture and how they use it to deliver low-latency analytics to users.
Maximizing performance via tuning and optimizationMariaDB plc
Ensuring that your end users get the performance they expect from your system requires an organized approach to performance management. This session will cover the planning and measurement necessary to ensure satisfied customers, and will also include tips and tricks learned from MariaDB’s years of supporting many of the most demanding installations in the world.
MyRocks is an open source LSM based MySQL database, created by Facebook. This slides introduce MyRocks overview and how we deployed at Facebook, as of 2017.
Learn best practices for taking advantage of Amazon Redshift's columnar technology and parallel processing capabilities to improve your data warehouse performance.
Grafana Loki is a newly developed logs aggregation system that integrated very nicely with Grafana dashboard to link metrics with logs or just use logs as a separate panel. It is open-source and has a growing community.
How to use histograms to get better performanceMariaDB plc
Sergei Petrunia and Varun Gupta, software engineers MariaDB, show how histograms can be used to improve query performance. They begin by introducing histrograms and explaining why they’re needed by the query optimizer. Next, they discuss how to determine whether or not histrograms are needed, and if so, how to determine which tables and columns they should be applied. Finally, they cover best practices and recent improvements to histograms.
(BDT401) Amazon Redshift Deep Dive: Tuning and Best PracticesAmazon Web Services
Get a look under the covers: Learn tuning best practices for taking advantage of Amazon Redshift's columnar technology and parallel processing capabilities to improve your delivery of queries and improve overall database performance. This session explains how to migrate from existing data warehouses, create an optimized schema, efficiently load data, use work load management, tune your queries, and use Amazon Redshift's interleaved sorting features. Finally, learn how TripAdvisor uses these best practices to give their entire organization access to analytic insights at scale.
Why My Streaming Job is Slow - Profiling and Optimizing Kafka Streams Apps (L...confluent
Kafka Streams performance monitoring and tuning is important for many reasons, including identifying bottlenecks, achieving greater throughput, and capacity planning. In this talk we’ll share the techniques we used to achieve greater performance and save on compute, storage, and cost. We’ll cover: Identifying design bottlenecks in by reviewing logs, metrics, and serdes. State store access patterns, design, and optimization Using profiling tools such as JMX, YourKit etc. Performance tuning of Kafka and Kafka Streams configuration and properties. JVM optimization for correct heap size and garbage collection strategies. Functional programming and imperative programming trade offs.
Scylla allows us to create highly performant and scalable systems. However, to achieve good results and prevent our Scylla cluster from being overloaded, we need to properly write our client application and configure the driver. Join this session to learn some practical tips that can help you make your applications faster and more available.
GTIDs were introduced to solve replication problems and improve database consistency in MySQL database replication.
When, accidentally, transactions occur on a replica, this introduces GTIDs on that replica that don't exist on the master. When, on a master failover, this replica becomes the new master, and the corresponding binlogs of the errant GTIDs are already purged, replication breaks on the replicas of this new master, because those missing GTIDs can't be retrieved from the binlogs of this new master.
This presentation will talk about GTIDs and how to detect errant GTIDs on a replica (before the corresponding binlogs are purged) and how to look at the corresponding transactions in the binlogs. I'll give some examples of transactions that could happen on a replica that didn't originate from a primary node, explain how this is possible and share some tips on how to avoid this.
Basic understanding of MySQL database replication is assumed.
This presentation was at Percona Live 2019 in Austin, Texas.
https://www.percona.com/live/19/sessions/errant-gtids-breaking-replication-how-to-detect-and-avoid-them
Talk for PerconaLive 2016 by Brendan Gregg. Video: https://www.youtube.com/watch?v=CbmEDXq7es0 . "Systems performance provides a different perspective for analysis and tuning, and can help you find performance wins for your databases, applications, and the kernel. However, most of us are not performance or kernel engineers, and have limited time to study this topic. This talk summarizes six important areas of Linux systems performance in 50 minutes: observability tools, methodologies, benchmarking, profiling, tracing, and tuning. Included are recipes for Linux performance analysis and tuning (using vmstat, mpstat, iostat, etc), overviews of complex areas including profiling (perf_events), static tracing (tracepoints), and dynamic tracing (kprobes, uprobes), and much advice about what is and isn't important to learn. This talk is aimed at everyone: DBAs, developers, operations, etc, and in any environment running Linux, bare-metal or the cloud."
MySQL Parallel Replication (LOGICAL_CLOCK): all the 5.7 (and some of the 8.0)...Jean-François Gagné
Since 5.7.2, MySQL implements parallel replication in the same schema, also known as LOGICAL_CLOCK (DATABASE based parallel replication is also implemented in 5.6 but this is not covered in this talk). In early 5.7 versions, parallel replication was based on group commit (like MariaDB) and 5.7.6 changed that to intervals.
Intervals are more complicated but they are also more powerful. In this talk, I will explain in detail how they work and why intervals are better than group commit. I will also cover how to optimize parallel replication in MySQL 5.7 and what improvements are coming in MySQL 8.0. I will also explain why Group Replication is replicating faster than standard asynchronous replication.
Come to this talk to get all the details about MySQL 5.7 Parallel Replication.
Real-time, Exactly-once Data Ingestion from Kafka to ClickHouse at eBayAltinity Ltd
LIVE WEBINAR: October 21, 2021 | 10 am PT
SPEAKERS: Jun Li, Principal Architect, eBay & Robert Hodges, CEO, Altinity
eBay depends on Kafka to solve the impedance mismatch between rapidly arriving messages in event streams and efficient block insert into ClickHouse clusters. Naïve loading procedures from Kafka to ClickHouse generate non-deterministic blocks, which can lead to data loss and incorrect results in applications. The eBay team solved this problem with a block aggregator that leverages Kafka to store message processing metadata as well as ClickHouse deduplication to ensure blocks being loaded to ClickHouse exactly once. The block aggregator allows eBay to support a sharded ClickHouse architecture across multiple data centers that can tolerate failures in any individual part of the system. Join us to learn how eBay developed this unique architecture and how they use it to deliver low-latency analytics to users.
Maximizing performance via tuning and optimizationMariaDB plc
Ensuring that your end users get the performance they expect from your system requires an organized approach to performance management. This session will cover the planning and measurement necessary to ensure satisfied customers, and will also include tips and tricks learned from MariaDB’s years of supporting many of the most demanding installations in the world.
MyRocks is an open source LSM based MySQL database, created by Facebook. This slides introduce MyRocks overview and how we deployed at Facebook, as of 2017.
Learn best practices for taking advantage of Amazon Redshift's columnar technology and parallel processing capabilities to improve your data warehouse performance.
Grafana Loki is a newly developed logs aggregation system that integrated very nicely with Grafana dashboard to link metrics with logs or just use logs as a separate panel. It is open-source and has a growing community.
How to use histograms to get better performanceMariaDB plc
Sergei Petrunia and Varun Gupta, software engineers MariaDB, show how histograms can be used to improve query performance. They begin by introducing histrograms and explaining why they’re needed by the query optimizer. Next, they discuss how to determine whether or not histrograms are needed, and if so, how to determine which tables and columns they should be applied. Finally, they cover best practices and recent improvements to histograms.
(BDT401) Amazon Redshift Deep Dive: Tuning and Best PracticesAmazon Web Services
Get a look under the covers: Learn tuning best practices for taking advantage of Amazon Redshift's columnar technology and parallel processing capabilities to improve your delivery of queries and improve overall database performance. This session explains how to migrate from existing data warehouses, create an optimized schema, efficiently load data, use work load management, tune your queries, and use Amazon Redshift's interleaved sorting features. Finally, learn how TripAdvisor uses these best practices to give their entire organization access to analytic insights at scale.
Why My Streaming Job is Slow - Profiling and Optimizing Kafka Streams Apps (L...confluent
Kafka Streams performance monitoring and tuning is important for many reasons, including identifying bottlenecks, achieving greater throughput, and capacity planning. In this talk we’ll share the techniques we used to achieve greater performance and save on compute, storage, and cost. We’ll cover: Identifying design bottlenecks in by reviewing logs, metrics, and serdes. State store access patterns, design, and optimization Using profiling tools such as JMX, YourKit etc. Performance tuning of Kafka and Kafka Streams configuration and properties. JVM optimization for correct heap size and garbage collection strategies. Functional programming and imperative programming trade offs.
Scylla allows us to create highly performant and scalable systems. However, to achieve good results and prevent our Scylla cluster from being overloaded, we need to properly write our client application and configure the driver. Join this session to learn some practical tips that can help you make your applications faster and more available.
GTIDs were introduced to solve replication problems and improve database consistency in MySQL database replication.
When, accidentally, transactions occur on a replica, this introduces GTIDs on that replica that don't exist on the master. When, on a master failover, this replica becomes the new master, and the corresponding binlogs of the errant GTIDs are already purged, replication breaks on the replicas of this new master, because those missing GTIDs can't be retrieved from the binlogs of this new master.
This presentation will talk about GTIDs and how to detect errant GTIDs on a replica (before the corresponding binlogs are purged) and how to look at the corresponding transactions in the binlogs. I'll give some examples of transactions that could happen on a replica that didn't originate from a primary node, explain how this is possible and share some tips on how to avoid this.
Basic understanding of MySQL database replication is assumed.
This presentation was at Percona Live 2019 in Austin, Texas.
https://www.percona.com/live/19/sessions/errant-gtids-breaking-replication-how-to-detect-and-avoid-them
Talk for PerconaLive 2016 by Brendan Gregg. Video: https://www.youtube.com/watch?v=CbmEDXq7es0 . "Systems performance provides a different perspective for analysis and tuning, and can help you find performance wins for your databases, applications, and the kernel. However, most of us are not performance or kernel engineers, and have limited time to study this topic. This talk summarizes six important areas of Linux systems performance in 50 minutes: observability tools, methodologies, benchmarking, profiling, tracing, and tuning. Included are recipes for Linux performance analysis and tuning (using vmstat, mpstat, iostat, etc), overviews of complex areas including profiling (perf_events), static tracing (tracepoints), and dynamic tracing (kprobes, uprobes), and much advice about what is and isn't important to learn. This talk is aimed at everyone: DBAs, developers, operations, etc, and in any environment running Linux, bare-metal or the cloud."
MySQL Parallel Replication (LOGICAL_CLOCK): all the 5.7 (and some of the 8.0)...Jean-François Gagné
Since 5.7.2, MySQL implements parallel replication in the same schema, also known as LOGICAL_CLOCK (DATABASE based parallel replication is also implemented in 5.6 but this is not covered in this talk). In early 5.7 versions, parallel replication was based on group commit (like MariaDB) and 5.7.6 changed that to intervals.
Intervals are more complicated but they are also more powerful. In this talk, I will explain in detail how they work and why intervals are better than group commit. I will also cover how to optimize parallel replication in MySQL 5.7 and what improvements are coming in MySQL 8.0. I will also explain why Group Replication is replicating faster than standard asynchronous replication.
Come to this talk to get all the details about MySQL 5.7 Parallel Replication.
Firebird recovery tools and techniques by IBSurgeonAlexey Kovyazin
Presentation "Firebird recovery tools and techniques", by Alexey Kovyazin (IBSurgeon). This presentation is devoted to Firebird corruptions: why they occur, what are their symptoms, how to fix corruptions with Firebird standard tools and with advanced IBSurgeon tools and services.
Best practices for MySQL High AvailabilityColin Charles
The MariaDB/MySQL world is full of tradeoffs, and choosing a high availability (HA) solution is no exception. This session aims to look at all the alternatives in an unbiased way. Preference is of course only given to open source solutions.
How do you choose between: asynchronous/semi-synchronous/synchronous replication, MHA (MySQL high availability tools), DRBD, Tungsten Replicator, or Galera Cluster? Do you integrate Pacemaker and Heartbeat like Percona Replication Manager? The cloud brings even more fun, especially if you are dealing with a hybrid cloud and must think about geographical redundancy.
What about newer solutions like using Consul for MySQL HA?
When you’ve decided on your solution, how do you provision and monitor these solutions?
This and more will be covered in a walkthrough of MySQL HA options and when to apply them.
(WEB401) Optimizing Your Web Server on AWS | AWS re:Invent 2014Amazon Web Services
Tuning your EC2 web server will help you to improve application server throughput and cost-efficiency as well as reduce request latency. In this session we will walk through tactics to identify bottlenecks using tools such as CloudWatch in order to drive the appropriate allocation of EC2 and EBS resources. In addition, we will also be reviewing some performance optimizations and best practices for popular web servers such as Nginx and Apache in order to take advantage of the latest EC2 capabilities.
Reduced instruction set computing, or RISC (pronounced 'risk', /ɹɪsk/), is a CPU design strategy based on the insight that a simplified instruction set provides higher performance when combined with a microprocessor architecture capable of executing those instructions using fewer microprocessor cycles per instruction.
This is a summary of the sessions I attended at PASS Summit 2017. Out of the week-long conference, I put together these slides to summarize the conference and present at my company. The slides are about my favorite sessions that I found had the most value. The slides included screenshotted demos I personally developed and tested alike the speakers at the conference.
Scality CTO Giorgio Regni and Software Engineer Lauren Spiegel talk about the open source S3 clone, written in Node.js. This presentation was given at a meetup on September 1, 2016 in San Francisco.
Streaming in Practice - Putting Apache Kafka in Productionconfluent
This presentation focuses on how to integrate all these components into an enterprise environment and what things you need to consider as you move into production.
We will touch on the following topics:
- Patterns for integrating with existing data systems and applications
- Metadata management at enterprise scale
- Tradeoffs in performance, cost, availability and fault tolerance
- Choosing which cross-datacenter replication patterns fit with your application
- Considerations for operating Kafka-based data pipelines in production
Stephan Ewen - Experiences running Flink at Very Large ScaleVerverica
This talk shares experiences from deploying and tuning Flink steam processing applications for very large scale. We share lessons learned from users, contributors, and our own experiments about running demanding streaming jobs at scale. The talk will explain what aspects currently render a job as particularly demanding, show how to configure and tune a large scale Flink job, and outline what the Flink community is working on to make the out-of-the-box for experience as smooth as possible. We will, for example, dive into - analyzing and tuning checkpointing - selecting and configuring state backends - understanding common bottlenecks - understanding and configuring network parameters
Kafka is becoming an ever more popular choice for users to help enable fast data and Streaming. Kafka provides a wide landscape of configuration to allow you to tweak its performance profile. Understanding the internals of Kafka is critical for picking your ideal configuration. Depending on your use case and data needs, different settings will perform very differently. Lets walk through performance essentials of Kafka. Let's talk about how your Consumer configuration, can speed up or slow down the flow of messages to Brokers. Lets talk about message keys, their implications and their impact on partition performance. Lets talk about how to figure out how many partitions and how many Brokers you should have. Let's discuss consumers and what effects their performance. How do you combine all of these choices and develop the best strategy moving forward? How do you test performance of Kafka? I will attempt a live demo with the help of Zeppelin to show in real time how to tune for performance.
Similar to Resolving Firebird performance problems (20)
Fail-Safe Cluster for FirebirdSQL and something moreAlexey Kovyazin
With Firebird HQbird it is possible to create high available cluster or warm standby solution. This presentation defines the problem and describes ways how to create such solutions.
This presentation is devoted to in-depth details of transactions implementation in Firebird database. If you are interesting to know how Firebird multi-version engine work with records, how record versions occur, what are main differences between snapshot and read commited transactions - this is waht you are looking for. Of course, this ppt does not cover all details, but gives an understanding what are transaction markers in Firebird, and why to important to keep transactions as short as possible.
Professional tools for Firebird optimization and maintenance from IBSurgeonAlexey Kovyazin
How to create better environment for big Firebird databases? How DBA can recognize and solve problems with Firebird performance, backups or corruptions (and better prevent corruptions)? This session was devoted to professional Firebird tools from IBSurgeon which help to solve all these problems.
FBScanner: IBSurgeon's tool to solve all types of performance problems with F...Alexey Kovyazin
FBScanner can be used to profile database applications, monitor user activity, manage database connections (including client disconnection on both Classic and SuperServer architecture). It’s also ideal for troubleshooting INET errors (INET/inet_error: send errno = 10054), as well as auditing existing applications and performance tuning.
Firebird: cost-based optimization and statistics, by Dmitry Yemanov (in English)Alexey Kovyazin
Basic introduction to internal mechanism of Firebird optimizer. How it works, how it decides to use this or that index, why sometimes it fails and what you can do to improve performance? Definitely this presentation will not answer all these questions but it gives you a basic knowledge of Firebird optimizer internals. This is not for all developers and requires some qualification, definitely.
СУБД Firebird: Краткий обзор, Дмитрий Еманов (in Russian)Alexey Kovyazin
Небольшая презентация Дмитрия Еманова, ведущего разработчика Firebird, посвящена обзору СУБД Firebird, в том числе текущему состоянию и планам развития.
Open Source: взгляд изнутри, Дмитрий Еманов (The Firebird Project) (in Russian)Alexey Kovyazin
Презентация ведущего разработчика проекта Firebird Дмитрия Еманова посвящена современным моделям Open Source: бизнес-моделям, способам организации коммьюнити, а также рассказывает о месте и основных вехах развития СУБД с открытым кодом Firebird
Firebird Scalability, by Dmitry Yemanov (in English)Alexey Kovyazin
In-depth presentation regarding key concepts of Firebird scalability, including SuperServer vs Classic discussion, memory usage for page and sorting buffers, CPU and concurrency, multi-CPU and multi-core, TPC-C figure, etc.
Firebird 2.1 What's New by Vladislav Khorsun (English)Alexey Kovyazin
Detailed presentation devoted to new features of Firebird 2.1 by Vladislav Khorsun, core Firebird Developer. Main features are covered, including tips and tricks and often usage scenarios.
Firebird: Универсальная СУБД. Краткая презентация на Интероп 2008, Дмитрий Ем...Alexey Kovyazin
Дмитрий Еманов представил краткую презентацию, посвященную Firebird на конференции Интероп 2008. Презентация рассматривает место Firebird среди других СУБД с открытым кодом, описывает текущее состояние дел и представляет планы на будущее.
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.
First Steps with Globus Compute Multi-User EndpointsGlobus
In this presentation we will share our experiences around getting started with the Globus Compute multi-user endpoint. Working with the Pharmacology group at the University of Auckland, we have previously written an application using Globus Compute that can offload computationally expensive steps in the researcher's workflows, which they wish to manage from their familiar Windows environments, onto the NeSI (New Zealand eScience Infrastructure) cluster. Some of the challenges we have encountered were that each researcher had to set up and manage their own single-user globus compute endpoint and that the workloads had varying resource requirements (CPUs, memory and wall time) between different runs. We hope that the multi-user endpoint will help to address these challenges and share an update on our progress here.
How to Position Your Globus Data Portal for Success Ten Good PracticesGlobus
Science gateways allow science and engineering communities to access shared data, software, computing services, and instruments. Science gateways have gained a lot of traction in the last twenty years, as evidenced by projects such as the Science Gateways Community Institute (SGCI) and the Center of Excellence on Science Gateways (SGX3) in the US, The Australian Research Data Commons (ARDC) and its platforms in Australia, and the projects around Virtual Research Environments in Europe. A few mature frameworks have evolved with their different strengths and foci and have been taken up by a larger community such as the Globus Data Portal, Hubzero, Tapis, and Galaxy. However, even when gateways are built on successful frameworks, they continue to face the challenges of ongoing maintenance costs and how to meet the ever-expanding needs of the community they serve with enhanced features. It is not uncommon that gateways with compelling use cases are nonetheless unable to get past the prototype phase and become a full production service, or if they do, they don't survive more than a couple of years. While there is no guaranteed pathway to success, it seems likely that for any gateway there is a need for a strong community and/or solid funding streams to create and sustain its success. With over twenty years of examples to draw from, this presentation goes into detail for ten factors common to successful and enduring gateways that effectively serve as best practices for any new or developing gateway.
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/
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.
Exploring Innovations in Data Repository Solutions - Insights from the U.S. G...Globus
The U.S. Geological Survey (USGS) has made substantial investments in meeting evolving scientific, technical, and policy driven demands on storing, managing, and delivering data. As these demands continue to grow in complexity and scale, the USGS must continue to explore innovative solutions to improve its management, curation, sharing, delivering, and preservation approaches for large-scale research data. Supporting these needs, the USGS has partnered with the University of Chicago-Globus to research and develop advanced repository components and workflows leveraging its current investment in Globus. The primary outcome of this partnership includes the development of a prototype enterprise repository, driven by USGS Data Release requirements, through exploration and implementation of the entire suite of the Globus platform offerings, including Globus Flow, Globus Auth, Globus Transfer, and Globus Search. This presentation will provide insights into this research partnership, introduce the unique requirements and challenges being addressed and provide relevant project progress.
OpenFOAM solver for Helmholtz equation, helmholtzFoam / helmholtzBubbleFoamtakuyayamamoto1800
In this slide, we show the simulation example and the way to compile this solver.
In this solver, the Helmholtz equation can be solved by helmholtzFoam. Also, the Helmholtz equation with uniformly dispersed bubbles can be simulated by helmholtzBubbleFoam.
Check out the webinar slides to learn more about how XfilesPro transforms Salesforce document management by leveraging its world-class applications. For more details, please connect with sales@xfilespro.com
If you want to watch the on-demand webinar, please click here: https://www.xfilespro.com/webinars/salesforce-document-management-2-0-smarter-faster-better/
Accelerate Enterprise Software Engineering with PlatformlessWSO2
Key takeaways:
Challenges of building platforms and the benefits of platformless.
Key principles of platformless, including API-first, cloud-native middleware, platform engineering, and developer experience.
How Choreo enables the platformless experience.
How key concepts like application architecture, domain-driven design, zero trust, and cell-based architecture are inherently a part of Choreo.
Demo of an end-to-end app built and deployed on Choreo.
Custom Healthcare Software for Managing Chronic Conditions and Remote Patient...Mind IT Systems
Healthcare providers often struggle with the complexities of chronic conditions and remote patient monitoring, as each patient requires personalized care and ongoing monitoring. Off-the-shelf solutions may not meet these diverse needs, leading to inefficiencies and gaps in care. It’s here, custom healthcare software offers a tailored solution, ensuring improved care and effectiveness.
Developing Distributed High-performance Computing Capabilities of an Open Sci...Globus
COVID-19 had an unprecedented impact on scientific collaboration. The pandemic and its broad response from the scientific community has forged new relationships among public health practitioners, mathematical modelers, and scientific computing specialists, while revealing critical gaps in exploiting advanced computing systems to support urgent decision making. Informed by our team’s work in applying high-performance computing in support of public health decision makers during the COVID-19 pandemic, we present how Globus technologies are enabling the development of an open science platform for robust epidemic analysis, with the goal of collaborative, secure, distributed, on-demand, and fast time-to-solution analyses to support public health.
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.
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.
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.
Enterprise Resource Planning System includes various modules that reduce any business's workload. Additionally, it organizes the workflows, which drives towards enhancing productivity. Here are a detailed explanation of the ERP modules. Going through the points will help you understand how the software is changing the work dynamics.
To know more details here: https://blogs.nyggs.com/nyggs/enterprise-resource-planning-erp-system-modules/
Experience our free, in-depth three-part Tendenci Platform Corporate Membership Management workshop series! In Session 1 on May 14th, 2024, we began with an Introduction and Setup, mastering the configuration of your Corporate Membership Module settings to establish membership types, applications, and more. Then, on May 16th, 2024, in Session 2, we focused on binding individual members to a Corporate Membership and Corporate Reps, teaching you how to add individual members and assign Corporate Representatives to manage dues, renewals, and associated members. Finally, on May 28th, 2024, in Session 3, we covered questions and concerns, addressing any queries or issues you may have.
For more Tendenci AMS events, check out www.tendenci.com/events
Prosigns: Transforming Business with Tailored Technology SolutionsProsigns
Unlocking Business Potential: Tailored Technology Solutions by Prosigns
Discover how Prosigns, a leading technology solutions provider, partners with businesses to drive innovation and success. Our presentation showcases our comprehensive range of services, including custom software development, web and mobile app development, AI & ML solutions, blockchain integration, DevOps services, and Microsoft Dynamics 365 support.
Custom Software Development: Prosigns specializes in creating bespoke software solutions that cater to your unique business needs. Our team of experts works closely with you to understand your requirements and deliver tailor-made software that enhances efficiency and drives growth.
Web and Mobile App Development: From responsive websites to intuitive mobile applications, Prosigns develops cutting-edge solutions that engage users and deliver seamless experiences across devices.
AI & ML Solutions: Harnessing the power of Artificial Intelligence and Machine Learning, Prosigns provides smart solutions that automate processes, provide valuable insights, and drive informed decision-making.
Blockchain Integration: Prosigns offers comprehensive blockchain solutions, including development, integration, and consulting services, enabling businesses to leverage blockchain technology for enhanced security, transparency, and efficiency.
DevOps Services: Prosigns' DevOps services streamline development and operations processes, ensuring faster and more reliable software delivery through automation and continuous integration.
Microsoft Dynamics 365 Support: Prosigns provides comprehensive support and maintenance services for Microsoft Dynamics 365, ensuring your system is always up-to-date, secure, and running smoothly.
Learn how our collaborative approach and dedication to excellence help businesses achieve their goals and stay ahead in today's digital landscape. From concept to deployment, Prosigns is your trusted partner for transforming ideas into reality and unlocking the full potential of your business.
Join us on a journey of innovation and growth. Let's partner for success with Prosigns.
How Recreation Management Software Can Streamline Your Operations.pptxwottaspaceseo
Recreation management software streamlines operations by automating key tasks such as scheduling, registration, and payment processing, reducing manual workload and errors. It provides centralized management of facilities, classes, and events, ensuring efficient resource allocation and facility usage. The software offers user-friendly online portals for easy access to bookings and program information, enhancing customer experience. Real-time reporting and data analytics deliver insights into attendance and preferences, aiding in strategic decision-making. Additionally, effective communication tools keep participants and staff informed with timely updates. Overall, recreation management software enhances efficiency, improves service delivery, and boosts customer satisfaction.
2. Usually big production database runs at
• Firebird 2.5
• Classic or SuperClassic architecture
• They can scale accross multiple CPU/cores!
• In Firebird 3 SuperServer is the better choice…
• but now let’s talk about 2.5 Classic and SuperClassic
3. What are performance indicators to
monitor in Firebird 2.5?
1. Lock table parameters
2. Monitoring record versions and garbage collection
3. Transactions
1. Long running transactions
2. Rolled back transactions
4. Temporary files – quantity and size
5. Connections, SQL queries and transactions
5. fb_inet_serverfb_inet_server
How lock table works
fb_inet_server
Firebird
Page cache Page cache Page cache
Page X
How to resolve a
write conflict when
changing the same
page?
6. How lock table works
fb_inet_server fb_inet_server fb_inet_server
mapped
Lock table
mapped mapped
shared memory
All requests to access
internal database objects go
through lock table
7. Why should we monitor lock table
parameters?
• Lock table is a critical part of Classic and SuperClassic
architectures
• Access to shared objects is implemented through locks in
Lock table…
Analysis of lock table parameters is the easiest
way to reveal problems with concurrent access
10. Thresholds and recommendations
Essential values: Firebird.conf params to tune:
Length: 6291456 LockMemSize - default is 1Mb
Set at least:
Cache_pages * max_connections_count
* 100
Hash slots: 2003, Hash lengths
(min/avg/max): 2/ 11/ 26
LockHashSlots = 1009
Prime number. Set x20, like 20011
Mutex wait: 4.1% No parameter to adjust. More than 10%
could be a problem, check hardware and
concurrency settings
Owners (107) Number of connections for server
Use optimized Firebird configuration files from IBSurgeon:
http://ib-aid.com/en/optimized-firebird-configuration/
11. How to monitor lock table
• 1) Command prompt (on the server only), run every N min
fb_lock_print -d E:OLTP-EMULoltp30.fdb
• 2) Alerts and automatic
recommendations
13. What is a record version?
TR50 TR60
UPDATE
set data =200read
N Tx Data
1 10 100
60 200
...
read
write
Different transactions can see different versions of
the record.
14. Why many record versions are bad
The more
versions record
has, the more
scan operations
server does to
find necessary
version
After data load or
restore – no
versions
15. • When UPDATE changes indexed fields, indices also must
be updated, and - UPDATE does not update keys in the
index, it adds new keys for new record version!
• DELETE does not delete index keys!
N Tx Data
1 10 100
60 200
...
Index key
= 100
Index key
= 200
Why many record versions are bad
16. What to monitor?
Database statistics
• Database statistics shows information about Record
Versions and Max Versions
• Taking database statistics can be long!
17. How to monitor
1. With gstat command line tool
2. With HQbird Firebird Database Analyst
More details: https://www.youtube.com/watch?v=_KZqXcgwN98
18. Goal of every Firebird developer is
to avoid creating versions for records!
Not only because server slowly reads
multiple record versions, but also
because of
GARBAGE COLLECTION
19. What is garbage and how it is collected
• When record versions become obsolete and non-
interested by any transaction, it is considered as
garbage and need to be cleaned.
• Garbage collection is a process of removing
unnecessary records versions
• It can be cooperative (Classic or SuperClassic) or
background (SuperServer)
20. Why should we monitor garbage
collection?
• It consumes resources.
• We should locate and fix those parts of the
application(s) which produce many record
versions which increase an intensity of GC
21. How to monitor GC?
• 1) Manual SQL queries to MON$ tables
• 2) HQbird Firebird MonLogger
22. How to decrease number of garbage
versions?
1. Use as short write transactions as possible
2. For read-only operations use (if possible)
transactions READ COMMITTED READ-ONLY
If you see a lot of record versions, and you are not
sure how to fix it, consider to order our Database
Optimization service:
http://ib-aid.com/en/firebird-interbase-performance-
optimization-service/
24. Why to monitor transactions?
Transactions are key indicators of versioning
processes in Firebird database.
2 main problems
1. Long-running [writeable] transactions
2. Rolled back transactions
25. Gstat –h gives us snaphot of transactions
Database header page information:
Flags 0
Checksum 12345
Generation 1564
Page size 4096
ODS version 10.1
Oldest transaction 10009
Oldest active 20001
Oldest snapshot 20001
Next transaction 25007
Bumped transaction 1
Sequence number 0
Next attachment ID 1
Implementation ID 16
Shadow count 0
Page buffers 3000
Next header page 0
Database dialect 1
Creation date Nov 1, 2015 15:55:55
26. Long-running transactions
• All transactions have sequential numbers from 1 to…
• Oldest Active Transaction – currently active transaction
with the minimal number
Oldest transaction 10009
Oldest active 20001
Oldest snapshot 20001
Next transaction 25007
Interval NEXT – OAT shows number of potentially active
transactions – server cannot clean versions created by
transactions with numbers > OAT
27. How to track long running active transactions
in Firebird?
• 1. Manual tracking of gstat –h output (check every N
minutes)
• 2. Alerts from HQbird FBDataGuard
28. How to fix long running active
transactions in Firebird?
It is possible to find who is running long-
running transaction and CANCEL it
1. Manual query to MON$ tables
2. HQbird Firebird MON$Logger (GUI)
29. Rolled back transactions
• When some transaction is marked in transaction inventory
as rolled back, it prevents record versions beeing
cleaned by collective or background garbage collection
Oldest transaction 10009
Oldest active 20001
Oldest snapshot 20001
Next transaction 25007
Interval Oldest Snapshot – Oldest Interesting
determines the need for sweep
30. Sweep
• Sweep reads whole database from the beginning
to the end and cleans garbage record versions
• Sweep is necessary when OST-OIT interval
becomes big
31. How to make sweep
• Autosweep
• by default 20000
• Starts immediately when interval > threshold
• It causes slowness at unpredicted moments
• Manual sweep
• Scheduled sweep during the inactivity period of
time
• Can be run manually with gfix –sweep or
scheduled in HQbird FBDataGuard
32. Sweep must be controlled!
• If sweep did not succeed to align
transaction markers, it can happen due to
the serious problem/corruption!
• HQbird FBDataGuard checks sweep status
34. Temp files
• Temp files are created in the default temp folder
or in folders specified by TempDirectories in
firebird.conf
• Actually they are written to the disk only if size of
all sort files is more than TempCacheLimit
parameter
• It is better to have sorting in memory
35. How to track Temp files
1. Manually check size and quantity of temp files
(fb_sortxxx) in all temp folders
2. HQbird FBDataGuard monitors temp files size and
quantity, and sends warnings if necessary
36. How to move temp files to memory
• Increase TempCacheLimit parameter
• Warnings:
• At Classic TempCacheLimit is allocated for each
process
• 32bit processes have 2Gb limitation of memory to
address
Use optimized configuration files from IBSurgeon and
HQbird!
http://ib-aid.com/en/optimized-firebird-configuration/
38. Why to monitor Firebird connections?
• Number of connections should be constantly monitored:
• Peaks of connections
• Firebird Classic/SuperClassic consume RAM as
Number_Of_Connections x Page Buffers
• In case of peaks can consume all RAM and go to swap – slowness!
• Application can do more than 1 connection to the database
• By mistake
• By design
• In case of connection pool – adjust the size of the pool and its
increment
• Suspicious connections
• Long running connections and connections from developer tools
• Connections from non-standard applications
39. How to monitor connections
1. Manually run SELECT count(*) FROM
MON$ATTACHMENTS
2. Use HQbird
1. FBDataGuard constantly monitors number of connections and
send alerts if their number grows too much
2. MonLogger can be used to go deep and get detailed information
about connections: memory, IO, garbage collection
40. Transactions
• Yes, again!
• Besides monitoring of intervals between transactions
markers (Next-OAT, OIT-OST), also we should check
these important things, which can affect Firebird
performance:
1. Transaction’s parameters (isolation level, wait/nowait)
2. Transactions flows and their relation with business
logic
3. Transaction-level statistics (IO, time to live)
41. Transaction’s parameters
• Transactions parameters must correspond to business
logic.
• Several often mistakes
• Non-modyfing queries (SELECT) are started in read-write mode
• Should be in READ ONLY
• Snapshot are used for operational queries, instead of read-
commited
• It should be used only for queries where consistency is really required
(snapshots)
42. Transactions flows mistakes
• Transaction (other then read-committed read only) never
ends, expires due to connection closing, and leads to
ROLLBACK
• Only 1 sentence in the transaction
• For example, refreshing query with timer:
• Quickly exhausts 2 billion limit of transactions
• it should be run in permanent read committed read only transaction
• Using the only read-write transaction for all operations
• Better split read-only and write operations
43. How to track transactions flows and
transactions parameters? - FBScanner
HQbird FBScanner allows to track transactions
flows: parameters, containing queries, plans, etc.
44. How to track transactions flows and
transactions parameters? - PerfMon
• HQbird Firebird Performance Monitor (PerfMon) uses
TraceAPI to capture all engine events – connections,
queries, transactions, stored procedures, triggers,
execution plans, execution statistics
• Works correctly only at Firebird 2.5.3+ versions
45. Quick check of problems with transactions
• HQbird MonLogger gives a fast and detailed overview of
active transactions in the system
46. HQbird tools for SQL and transactions
monitoring and optimization
HQbird FBScanner
+ works as a proxy, non-invasive tool, can be installed on
separate server and track only selected workstations
— cannot track stored procedures and triggers
HQbird PerfMon
+ works with TraceAPI, can monitor everything
— TraceAPI significantly supresses performance
HQbird MonLogger
+ Great ad-hoc tool, fast
— Captures only snapshots, lack of important information
47. IBSurgeon Firebird Optimization service
We can increase the performance of your database
http://ib-aid.com/en/firebird-interbase-performance-
optimization-service/
48. Thank you and don’t forget these links:
IBSurgeon optimized configuration files
http://ib-aid.com/en/optimized-firebird-configuration/
Firebird Hardware Guide
http://ib-aid.com/download/docs/Firebird_Hardware_Guide_IBSurgeon.pdf
Contact us: support@ib-aid.com
