This is an intro to Sphinx and PHP. It will take you through the very basics of how Sphinx works, how you can set up an index, and using the mysql client to search your index. Then, it culminates in a quick little PHP script that builds a small search interface around your index. I will be posting the example code into my github account soon.
This presentation was given to the LV PHP meetup on August 5th.
This is an intro to Sphinx and PHP. It will take you through the very basics of how Sphinx works, how you can set up an index, and using the mysql client to search your index. Then, it culminates in a quick little PHP script that builds a small search interface around your index. I will be posting the example code into my github account soon.
This presentation was given to the LV PHP meetup on August 5th.
Xephon K is a time series database using Cassandra as main backend. We talk about how to model time series data in Cassandra and compare its throughput with InfluxDB and KairosDB
Writing Well-behaved Unix Utilities
A talk given at the London Ruby Users Group in October 2014. It's about what makes a good Unix utility, and how we can use Ruby to write our own.
It covers things like working as part of text processing pipelines, reading from ARGF, handling command-line arguments, and lots more.
Presentation at LinuxCon Europe 2016 (Berlin). I introduced the concepts of logging for containers, aggregation patterns, distributted logging, data serialization, Fluentd: internals, architecture, Fluent Bit and it library API.
Interactive learning analytics dashboards with ELK (Elasticsearch Logstash Ki...Andrii Vozniuk
My workshop at the Learning Analytics Summer Institute (LASI) 2016: http://lasi16.snola.es/#!/schedule/113
Educational data continues to grow in volume, velocity and variety. Making sense of the educational data in such conditions requires deployment and usage of appropriate scalable, real-time processing tools supporting a flexible data schema. Elasticsearch is one of the popular open-source tools meeting the enlisted requirements. Initially envisioned as a search engine capable of operating at scale and in real time, Elasticsearch is used by organisations such as Wikimedia and Github, which deal with big data on daily basis. In addition, Elasticsearch is used increasingly often as analytics platform thanks to its scalable architecture and expressive query language. Until recently, the exploitation of Elasticsearch for (learning) analytical purposes by practitioners was hindered by a high entrance barrier due to the complexity of the query language and the query specificities. This is currently changing with the ongoing development of Kibana, an open-source tool that allows to conduct analysis and build visualisations of Elasticsearch data through a graphical user interface. Kibana does not require the user to dive into technical details of the queries (although it is still possible) and hence makes big educational data visualisations accessible to regular users. The additional value of Kibana comes in play whenever several visualisations are combined on a single dashboard, enabling to use multiple coordinated views for an interactive explorative analysis. Both Elasticsearch and Kibana, together with Logstash are part of an analytics stack often referred to as ELK. Logstash supports data acquisition from multiple sources (including twitter, RSS, event logs) thanks to its rich set of available connectors. Custom connectors can be developed for case-specific sources. In addition to the mentioned values, ELK enables building analytics infrastructures decoupled from the learning platform, i.e., it allows to host separately the learning environment (with the analytics functionalities) and the data storage without affecting the end-user experience.
Totango is an Analytics platform for Customer Success.
Our data pipeline converts usage information into actionable analytics. The pipeline is managed using Luigi workflow engine, and data transformations are done in Spark.
Xephon K is a time series database using Cassandra as main backend. We talk about how to model time series data in Cassandra and compare its throughput with InfluxDB and KairosDB
Writing Well-behaved Unix Utilities
A talk given at the London Ruby Users Group in October 2014. It's about what makes a good Unix utility, and how we can use Ruby to write our own.
It covers things like working as part of text processing pipelines, reading from ARGF, handling command-line arguments, and lots more.
Presentation at LinuxCon Europe 2016 (Berlin). I introduced the concepts of logging for containers, aggregation patterns, distributted logging, data serialization, Fluentd: internals, architecture, Fluent Bit and it library API.
Interactive learning analytics dashboards with ELK (Elasticsearch Logstash Ki...Andrii Vozniuk
My workshop at the Learning Analytics Summer Institute (LASI) 2016: http://lasi16.snola.es/#!/schedule/113
Educational data continues to grow in volume, velocity and variety. Making sense of the educational data in such conditions requires deployment and usage of appropriate scalable, real-time processing tools supporting a flexible data schema. Elasticsearch is one of the popular open-source tools meeting the enlisted requirements. Initially envisioned as a search engine capable of operating at scale and in real time, Elasticsearch is used by organisations such as Wikimedia and Github, which deal with big data on daily basis. In addition, Elasticsearch is used increasingly often as analytics platform thanks to its scalable architecture and expressive query language. Until recently, the exploitation of Elasticsearch for (learning) analytical purposes by practitioners was hindered by a high entrance barrier due to the complexity of the query language and the query specificities. This is currently changing with the ongoing development of Kibana, an open-source tool that allows to conduct analysis and build visualisations of Elasticsearch data through a graphical user interface. Kibana does not require the user to dive into technical details of the queries (although it is still possible) and hence makes big educational data visualisations accessible to regular users. The additional value of Kibana comes in play whenever several visualisations are combined on a single dashboard, enabling to use multiple coordinated views for an interactive explorative analysis. Both Elasticsearch and Kibana, together with Logstash are part of an analytics stack often referred to as ELK. Logstash supports data acquisition from multiple sources (including twitter, RSS, event logs) thanks to its rich set of available connectors. Custom connectors can be developed for case-specific sources. In addition to the mentioned values, ELK enables building analytics infrastructures decoupled from the learning platform, i.e., it allows to host separately the learning environment (with the analytics functionalities) and the data storage without affecting the end-user experience.
Totango is an Analytics platform for Customer Success.
Our data pipeline converts usage information into actionable analytics. The pipeline is managed using Luigi workflow engine, and data transformations are done in Spark.
Study: The Future of VR, AR and Self-Driving CarsLinkedIn
We asked LinkedIn members worldwide about their levels of interest in the latest wave of technology: whether they’re using wearables, and whether they intend to buy self-driving cars and VR headsets as they become available. We asked them too about their attitudes to technology and to the growing role of Artificial Intelligence (AI) in the devices that they use. The answers were fascinating – and in many cases, surprising.
This SlideShare explores the full results of this study, including detailed market-by-market breakdowns of intention levels for each technology – and how attitudes change with age, location and seniority level. If you’re marketing a tech brand – or planning to use VR and wearables to reach a professional audience – then these are insights you won’t want to miss.
Stitch Fix aspires to help you find the style that you will love. Data, the backbone of the business, is used to help with styling recommendations, demand modeling, user acquisition, and merchandise planning and also to influence business decisions throughout the organization. These decisions are backed by algorithms and data collected and interpreted based on client preferences. This talk offers an overview of the compute infrastructure used by the data science team at Stitch Fix, covering the architecture, tools within the larger ecosystem, and the challenges that the team overcame along the way.
Apache Spark plays an important role in Stitch Fix’s data platform, and the company’s data scientists use Spark for their ETL and Presto for their ad hoc queries. The goal for the team running the compute infrastructure is to understand and make the data scientists’ lives easier, particularly in terms of usability of Spark, by building tools that make it easier to get started with Spark and transition themselves to a daily workflow. The compute infrastructure is a part of the data platform that is responsible for all the needs of data scientists as Stitch Fix.
In this talk, we look at Stitch Fix’s journey, exploring its Spark setup, in-house tools and how they work in synergy with open source frameworks in a cloud environment. There are additional improvements to the infrastructure that help persist information for future use and optimization and we look at how the implementation of Amazon’s EMR FS has helped make it easier for us to read from the S3 source.
These slides were used by Mark from Jumping Bean at pgDay Asia 2016. He presented the noSQL features - JSON and JOSNB and related operators and functions to audience.
Postgrtesql as a NoSQL Document Store - The JSON/JSONB data typeJumping Bean
Our presentation from PGDay Asia 2016 on the JSON/JSONB data type in Postgres and how you can have the best of both the SQL and NoSQL worlds in one. There is JavaScript in my SQL.
t's time to think about content migration from TYPO3v4 to Phoenix. Therefore, last year a Google Summer of Code Project was initiated which was about figuring out whether XSLT-driven transformations of v4 XML contents to Phoenix-ready structures were feasible for production use. Until the T3DD12 workshop, a first prototype will be released which already brings some framework-alike structures, ready for testing on an existing v4-instance. Nonetheless, for covering the major part of all existing TYPO3v4 instances, there is still a lot of thoughts and development to be done. Thus, we want to recruit some interested developers and testers to the project for making the huge step forwards to Phoenix as nice and easy as it can possibly be. Therefore, we will introduce the audience to the problem, our general idea of solving it and provide some initial thoughts and directions to invest some work on.
Apache Spark Toronto Meetup, July 27, 2016.
Wattpad talks about their experiences with Apache Spark. From starting in 2014 with Shark, to building distributed recommendation algorithms using ANN, to improving search results using a sessionized query log. We also talk about some of the issues we faced building our analytics pipeline, including getting spark to work with Luigi, an open source project by Spotify.
Your data is getting bigger while your boss is getting anxious to have insights! This tutorial covers Apache Spark that makes data analytics fast to write and fast to run. Tackle big datasets quickly through a simple API in Python, and learn one programming paradigm in order to deploy interactive, batch, and streaming applications while connecting to data sources incl. HDFS, Hive, JSON, and S3.
AWS Big Data Demystified #1: Big data architecture lessons learned Omid Vahdaty
AWS Big Data Demystified #1: Big data architecture lessons learned . a quick overview of a big data techonoligies, which were selected and disregard in our company
The video: https://youtu.be/l5KmaZNQxaU
dont forget to subcribe to the youtube channel
The website: https://amazon-aws-big-data-demystified.ninja/
The meetup : https://www.meetup.com/AWS-Big-Data-Demystified/
The facebook group : https://www.facebook.com/Amazon-AWS-Big-Data-Demystified-1832900280345700/
Threats to mobile devices are more prevalent and increasing in scope and complexity. Users of mobile devices desire to take full advantage of the features
available on those devices, but many of the features provide convenience and capability but sacrifice security. This best practices guide outlines steps the users can take to better protect personal devices and information.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
GridMate - End to end testing is a critical piece to ensure quality and avoid...ThomasParaiso2
End to end testing is a critical piece to ensure quality and avoid regressions. In this session, we share our journey building an E2E testing pipeline for GridMate components (LWC and Aura) using Cypress, JSForce, FakerJS…
GraphSummit Singapore | The Art of the Possible with Graph - Q2 2024Neo4j
Neha Bajwa, Vice President of Product Marketing, Neo4j
Join us as we explore breakthrough innovations enabled by interconnected data and AI. Discover firsthand how organizations use relationships in data to uncover contextual insights and solve our most pressing challenges – from optimizing supply chains, detecting fraud, and improving customer experiences to accelerating drug discoveries.
Communications Mining Series - Zero to Hero - Session 1DianaGray10
This session provides introduction to UiPath Communication Mining, importance and platform overview. You will acquire a good understand of the phases in Communication Mining as we go over the platform with you. Topics covered:
• Communication Mining Overview
• Why is it important?
• How can it help today’s business and the benefits
• Phases in Communication Mining
• Demo on Platform overview
• Q/A
Pushing the limits of ePRTC: 100ns holdover for 100 daysAdtran
At WSTS 2024, Alon Stern explored the topic of parametric holdover and explained how recent research findings can be implemented in real-world PNT networks to achieve 100 nanoseconds of accuracy for up to 100 days.
UiPath Test Automation using UiPath Test Suite series, part 6DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 6. In this session, we will cover Test Automation with generative AI and Open AI.
UiPath Test Automation with generative AI and Open AI webinar offers an in-depth exploration of leveraging cutting-edge technologies for test automation within the UiPath platform. Attendees will delve into the integration of generative AI, a test automation solution, with Open AI advanced natural language processing capabilities.
Throughout the session, participants will discover how this synergy empowers testers to automate repetitive tasks, enhance testing accuracy, and expedite the software testing life cycle. Topics covered include the seamless integration process, practical use cases, and the benefits of harnessing AI-driven automation for UiPath testing initiatives. By attending this webinar, testers, and automation professionals can gain valuable insights into harnessing the power of AI to optimize their test automation workflows within the UiPath ecosystem, ultimately driving efficiency and quality in software development processes.
What will you get from this session?
1. Insights into integrating generative AI.
2. Understanding how this integration enhances test automation within the UiPath platform
3. Practical demonstrations
4. Exploration of real-world use cases illustrating the benefits of AI-driven test automation for UiPath
Topics covered:
What is generative AI
Test Automation with generative AI and Open AI.
UiPath integration with generative AI
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
UiPath Test Automation using UiPath Test Suite series, part 5DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 5. In this session, we will cover CI/CD with devops.
Topics covered:
CI/CD with in UiPath
End-to-end overview of CI/CD pipeline with Azure devops
Speaker:
Lyndsey Byblow, Test Suite Sales Engineer @ UiPath, Inc.
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...SOFTTECHHUB
The choice of an operating system plays a pivotal role in shaping our computing experience. For decades, Microsoft's Windows has dominated the market, offering a familiar and widely adopted platform for personal and professional use. However, as technological advancements continue to push the boundaries of innovation, alternative operating systems have emerged, challenging the status quo and offering users a fresh perspective on computing.
One such alternative that has garnered significant attention and acclaim is Nitrux Linux 3.5.0, a sleek, powerful, and user-friendly Linux distribution that promises to redefine the way we interact with our devices. With its focus on performance, security, and customization, Nitrux Linux presents a compelling case for those seeking to break free from the constraints of proprietary software and embrace the freedom and flexibility of open-source computing.
Goodbye Windows 11: Make Way for Nitrux Linux 3.5.0!SOFTTECHHUB
As the digital landscape continually evolves, operating systems play a critical role in shaping user experiences and productivity. The launch of Nitrux Linux 3.5.0 marks a significant milestone, offering a robust alternative to traditional systems such as Windows 11. This article delves into the essence of Nitrux Linux 3.5.0, exploring its unique features, advantages, and how it stands as a compelling choice for both casual users and tech enthusiasts.
Enchancing adoption of Open Source Libraries. A case study on Albumentations.AIVladimir Iglovikov, Ph.D.
Presented by Vladimir Iglovikov:
- https://www.linkedin.com/in/iglovikov/
- https://x.com/viglovikov
- https://www.instagram.com/ternaus/
This presentation delves into the journey of Albumentations.ai, a highly successful open-source library for data augmentation.
Created out of a necessity for superior performance in Kaggle competitions, Albumentations has grown to become a widely used tool among data scientists and machine learning practitioners.
This case study covers various aspects, including:
People: The contributors and community that have supported Albumentations.
Metrics: The success indicators such as downloads, daily active users, GitHub stars, and financial contributions.
Challenges: The hurdles in monetizing open-source projects and measuring user engagement.
Development Practices: Best practices for creating, maintaining, and scaling open-source libraries, including code hygiene, CI/CD, and fast iteration.
Community Building: Strategies for making adoption easy, iterating quickly, and fostering a vibrant, engaged community.
Marketing: Both online and offline marketing tactics, focusing on real, impactful interactions and collaborations.
Mental Health: Maintaining balance and not feeling pressured by user demands.
Key insights include the importance of automation, making the adoption process seamless, and leveraging offline interactions for marketing. The presentation also emphasizes the need for continuous small improvements and building a friendly, inclusive community that contributes to the project's growth.
Vladimir Iglovikov brings his extensive experience as a Kaggle Grandmaster, ex-Staff ML Engineer at Lyft, sharing valuable lessons and practical advice for anyone looking to enhance the adoption of their open-source projects.
Explore more about Albumentations and join the community at:
GitHub: https://github.com/albumentations-team/albumentations
Website: https://albumentations.ai/
LinkedIn: https://www.linkedin.com/company/100504475
Twitter: https://x.com/albumentations
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
Climate Impact of Software Testing at Nordic Testing DaysKari Kakkonen
My slides at Nordic Testing Days 6.6.2024
Climate impact / sustainability of software testing discussed on the talk. ICT and testing must carry their part of global responsibility to help with the climat warming. We can minimize the carbon footprint but we can also have a carbon handprint, a positive impact on the climate. Quality characteristics can be added with sustainability, and then measured continuously. Test environments can be used less, and in smaller scale and on demand. Test techniques can be used in optimizing or minimizing number of tests. Test automation can be used to speed up testing.
GraphSummit Singapore | The Future of Agility: Supercharging Digital Transfor...Neo4j
Leonard Jayamohan, Partner & Generative AI Lead, Deloitte
This keynote will reveal how Deloitte leverages Neo4j’s graph power for groundbreaking digital twin solutions, achieving a staggering 100x performance boost. Discover the essential role knowledge graphs play in successful generative AI implementations. Plus, get an exclusive look at an innovative Neo4j + Generative AI solution Deloitte is developing in-house.
In his public lecture, Christian Timmerer provides insights into the fascinating history of video streaming, starting from its humble beginnings before YouTube to the groundbreaking technologies that now dominate platforms like Netflix and ORF ON. Timmerer also presents provocative contributions of his own that have significantly influenced the industry. He concludes by looking at future challenges and invites the audience to join in a discussion.
Sphinx && Perl Houston Perl Mongers - May 8th, 2014
1. Indexing Stuff &&
Things with Sphinx and Perl
Houston Perl Mongers
May 8th, 2014
Hosted by cPanel, Inc.
Brett Estrade <estrabd@gmail.com>
2. Sphinx
● full text search indexer and daemon
● indexer - builds indexes
● searchd - services search requests
● very easy to install and configure
3. Sphinx Data Sources
● Directly from MySQL (MariaDB), PostgreSQL
○ Indexing data from arbitrary SQL
○ Excellent for fast reading of expensive JOINs
● XMLPipe2
○ General intermediate data understood by Sphinx
4. Search Interface
● Native protocol (e.g., Sphinx::Search)
● Supports MySQL protocol (4.1)
○ Subset of SQL supported is called SphinxQL
10. Some Common Use Cases
● Rebuild index from database regularly
● Incrementally add to existing index
● Query Sphinx for DB primary keys, make DB
call for related rows
● Query Sphinx for wanted data (no DB at all)
== my use case
11. Real Life Examples
1. Indexing MariaDB
2. Filtering on string using CRC32
3. Creating sources w/Sphinx::XML::Pipe2
4. Dynamic config w/Sphinx::Config::Builder
12. Indexing MariaBD ~2.25 Million Rows
● Use case - saving eBay auction data in DB
● Providing search interface to it
● Demo run of indexer
13. How to Filter on Strings
● Requires CRC32 hashing (strings to ints)
● When indexing, use MySQL’s CRC32 function
● Use Perl’s String::CRC32 to encode string,
○ then set filter
14. And inside of client, use Perl’s String::CRC32 to encode to the same integer
15. Transforming Things to XMLPipe2
● XMLPipe2 is Sphinx’s generic data format
● Extract/Transform scripts -> XMLPipe2
● use Sphinx::XML::Pipe2; #’nuff said
18. Example XMLPipe2 Use Case
● Monitor ephemera,e.g. active eBay listings
● Don’t want to use a database
● Many data partitions (i.e., indexes)
○ e.g., by store, by category, etc
○ > 250 (yikes!)
● Data partitions change over time (slowly)
19. Dynamic Indexing of XMLPipe2 Stuff
● Fact - Sphinx partitions data by indexes
● Problem - each index uses its own data file
○ data as XMLPipe2
● Challenge - how to manage a changing set
of indexes?
20. Sphinx’s --config to the Rescue!
● Config files are typically static, right?
● Sphinx can handle executables via --config
● indexer --config ./generate-config.pl --all
21. Sphinx::Config::Builder
● Module I created specifically for this case
○ uploaded to CPAN
● Why? No Sphinx config builders were a fit
● Module is low level and does what I need
○ i.e., dynamically builds a XMLPipe2 specific config
● A+ 100 Passing
○ http://cpantesters.org/distro/S/Sphinx-Config-Builder.html
22. Solution
● Expects XML2Pipe data files to already exist
● Iterate over array of indexes to build
● Creates “source” entries for XMLPipe2 data
● Creates “index” entries for each “source”
24. Tip of the Iceberg
● Sphinx has TONs of options and modes
● Tons of areas of application
● Many clients, Simple interface
● Super easy to install and maintain