Dataflow Under the Hood: the origin story

Google Cloud’s Dataflow, part of our smart analytics platform, is a streaming analytics service that unifies stream and batch data processing. To get a better understanding of Dataflow, it helps to also understand its history, which starts with MillWheel.

A history of Dataflow

Like many projects at Google, MillWheel started in 2008 with a tiny team and a bold idea. When this project started, our team (led by Paul Nordstrom), wanted to create a system that did for streaming data processing what MapReduce had done for batch data processing—provide robust abstractions and scale to massive size. In those early days, we had a handful of key internal Google customers (from Search and Ads ), who were driving requirements for the system and pressure-testing the latest versions. What MillWheel did was build pipelines operating on click logs to attempt to compute real-time session information in order to better understand how to improve systems like Search for our customers. Up until this point, session information was computed on a daily basis, spinning up a colossal number of machines in the wee hours of the morning to produce results in time for when engineers logged on that morning. MillWheel aimed to change that by spreading that load over the entire day, resulting in more predictable resource usage, as well as vastly improved data freshness. Since a session can be an arbitrary length of time, this Search use case helped provide early motivation for key MillWheel concepts like watermarks and timers.

Alongside this session’s use case, we started working with the Google Zeitgeist team—now Google Trends—to look at an early version of trending queries from search traffic. In order to do this, we needed to compare current traffic for a given keyword to historical traffic so that we could determine fluctuations compared to the baseline. This drove a lot of the early work that we did around state aggregation and management, as well as efficiency improvements to the system, to handle cases like first-time queries or one-and-done queries that we’d never see again.

#google cloud platform #data analytics #cloud

What is GEEK

Buddha Community

Dataflow Under the Hood: the origin story

Dataflow Under the Hood: the origin story

Google Cloud’s Dataflow, part of our smart analytics platform, is a streaming analytics service that unifies stream and batch data processing. To get a better understanding of Dataflow, it helps to also understand its history, which starts with MillWheel.

A history of Dataflow

Like many projects at Google, MillWheel started in 2008 with a tiny team and a bold idea. When this project started, our team (led by Paul Nordstrom), wanted to create a system that did for streaming data processing what MapReduce had done for batch data processing—provide robust abstractions and scale to massive size. In those early days, we had a handful of key internal Google customers (from Search and Ads ), who were driving requirements for the system and pressure-testing the latest versions. What MillWheel did was build pipelines operating on click logs to attempt to compute real-time session information in order to better understand how to improve systems like Search for our customers. Up until this point, session information was computed on a daily basis, spinning up a colossal number of machines in the wee hours of the morning to produce results in time for when engineers logged on that morning. MillWheel aimed to change that by spreading that load over the entire day, resulting in more predictable resource usage, as well as vastly improved data freshness. Since a session can be an arbitrary length of time, this Search use case helped provide early motivation for key MillWheel concepts like watermarks and timers.

Alongside this session’s use case, we started working with the Google Zeitgeist team—now Google Trends—to look at an early version of trending queries from search traffic. In order to do this, we needed to compare current traffic for a given keyword to historical traffic so that we could determine fluctuations compared to the baseline. This drove a lot of the early work that we did around state aggregation and management, as well as efficiency improvements to the system, to handle cases like first-time queries or one-and-done queries that we’d never see again.

#google cloud platform #data analytics #cloud

Jacky  Hoeger

Jacky Hoeger

1591239482

Single-SPA Starting From Scratch

Single-SPA Starting From Scratch
single-spa allows you to build micro frontends that coexist and can each be written with their own framework. If you’d like to learn how to use single-spa with Angular, Vue, or other frameworks, checkout this example. And if you’d rather use a different build system instead of webpack, check out this example Read more about separating applications using single-spa.

#article #javascript stories #stories #tech stories #javascript

Amara  Legros

Amara Legros

1597626399

Searching For the Unknown - The Curse of Eternity

After walking down the path of fire, captain Smith decided to visit the Earth realm and continue his exploration of the universe. The doorway he entered lead down a path that was seemingly endless.
Read Part 1
Read Part 2
The length of his journey made him question the value of it but just when he was about to give up, he finally saw her in the distance… Gaia was waiting, and she had a lot of information to share with our captain.
Captain’s log 003:
It feels like an eternity… I can’t even remember when was the last time I heard from general @niallon11 and general @gregory-f. I know that they instructed me to come here but was it worth it? I guess we shall find out very soon.

#storytelling #ai #story #artificial-intelligence #artificial-intelligence-hype #latest-tech-stories #ai-top-story #musings

Alverta  Crist

Alverta Crist

1599149075

The Trouble with User Stories

User Stories are a vague, subjective and generic way of requirements gathering and analysis. This article examines their negative impact and what we can do to make it better.
Does Anyone Know What a User Story Is?
So, we all know what a user story is, right? I mean, we all use them because that’s the ‘agile’ thing to do (although neither the agile manifesto nor the scrum guide mentions anything about user stories). So, we should at least all agree on what a user story is. Let’s have a look at what’s the definition of a user story: “User stories are short, simple descriptions of a feature”

#agile methodology #user stories #behavior driven development #requirements analysis #user story #requirement gathering #impact map

CleaTech LLC

CleaTech LLC

1591873975

5 Types Of Laboratory Fume Hoods

Original Source: https://www.writerscafe.org/writing/Cleatech/2177724/


Laboratory Fume hoods are found in many different patterns and sizes-small benchtop units are available for space-challenged laboratories, and wider cabinet-type units are available for storage and space-consuming experiments. For example, specially built units are designed to protect users from radioisotopes, and units with a wash-down system of water spray nozzles scattered throughout the hood are required for perchloric acid work. Consider special user requirements, energy consumption, available space, and types of filters required when choosing a suitable hood for their lab. Fume hoods are a form of regulation in ecosystems exposed to dangerous chemicals and fumes. With the aim of protecting people from the negative effects of these fumes, fume hoods are used to get rid of the harmful aspects and enable employees to work safe. Working with substances that let off a harmful fume or odor, laboratories use fume hoods.

Laboratory staff can work straight under the fume hood with substances, or simply place the substance in the fume hood after the work has been done. Labor technicians will also ensure that the exhaust is working before work starts. Exhausting fumes is a hood's main job, so if that part of the ventilation system doesn't work, the hood won't work effectively. Check the baffles to ensure the exhaust is operating. These are movable partitions that create openings in the hood’s back. They maintain uniform airflow, which increases efficiency. Check for any impediments that may impede airflow. For other items such as paper towels, chemical wipes, and aluminum foil, be extra vigilant. These lightweight materials can be quickly drawn into the exhaust, thus impeding airflow. Use the sliding sash barrier when using a top fume hood on the bench. It's there for security and let them keep their face outside the worksite.

Here are the 5 Types of laboratory fume hoods

Ductless Smoking Hoods: A Ductless fume hood uses carbon filters in a laboratory to eliminate fumes and vapors. Carbon filtration, a cutting-edge technology used in a ductless fume hood, is an environmentally friendly option for both the consumer and the environment. The fume hood filters out the harmful fumes instead of funneling the fumes outside and then gets back the clean air back into the laboratory. Ductless fume hoods are also energy-efficient and cost-effective, and even provide electronic monitoring to consistently test filtration system performance.

Hoods for Chemical Fume: A Chemical fume hood is used in laboratories where workplace hazardous chemicals are being handled. This form of the hood is specially designed laboratory staff to work with these chemicals without revealing themselves to their associated harmful drawbacks. Featuring quality products and a design that goes beyond SEFA requirements, this device will ensure that staff can work safely with chemicals. The innovative fume hood design allows users to get a complete overview of their work and laboratory through a sash.

ADA Fume Hoods: An ADA Fume Hood is designed and built to be completely ADA-compliant in order to ensure a safe work environment. Every feature including lights, switches, epoxy-coated steel exterior, and digital airflow monitors is expertly engineered to meet the necessary safety requirements. ADA fume hoods can also be hand-operated and come with a standard stationary glass viewing panel with a safety glass counterbalanced sash.

Cabinets for Biosafety: In laboratories that deal with infections, have an enclosed, ventilated workspace, biosafety cabinets, and fume hoods are used. People can work with these units on materials contaminate with pathogens requiring levels of biosafety. This equipment ensures that the employees remain safe from dangerous chemicals or materials, and includes total recirculation and partial exhaust.

Hoods of polypropylene Fume: A Polypropylene Fume Hood is invented for laboratories that use products and materials rich in acids. These devices ventilate the indoor, air, avoid chemical damage, and are non-porous for healthy use for food testing. Reduced backflow of air also permits a much smooth production.

Above mentioned information regarding laboratory Fume Hood isvery useful for decreasing the pollution and many harmful chemicals. Besides this, the one who is a desire to be healthy during the laboratory experiments must use laboratory Fume Hoods in their laboratories.

The user who wants to be aware of the different types of laboratory fume hoods can contact us.

If there are any concerns or questions regarding the lab fume hoods don’t hesitate to integrate us. We are always happy to sort out the quarries of the customers.


Author Bio

Cleatech LLC, the leading company manufactures laboratory and cleanroom equipment. Buy the top-quality Laboratory Fume Hoods and other laboratory equipment such as Cleanroom Storage at Cleatech.com.

``` ```

#cleanroom storage #fume hoods #laboratory fume hoods