Data Science, Machine Learning, Natural Language Processing, Text Analysis, Recommendation Engine, R, Python
Thursday, 31 May 2018
Geek Trivia: To Protect Their Unique Makeup Styles, Professional Clowns Cleverly Copyrighted Which Of These?
Canon Officially Discontinues Its Last Film Camera

While some traditionalists still shoot film, the entire industry has been steadily shifting away from film since the early 2000s.
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Free Download: Sync Philips Hue Lights With Your PC or Mac
Why People Don’t Pick Up The Phone Anymore
How To Change Your Outlook.com Password
How to Exclude an App from Windows 10’s New Tabs
What is Pro Mode in the Samsung Galaxy Camera, and What Can You Do With It?
The Best Mechanical Pencils For Every Budget And Writing Style

Writing tools are like burritos: a cheap one will get the job done, but a premium one is more satisfying.
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How to Save Money on Flights With Kayak’s Price Alerts
What is Windows 10 in S Mode?
Wednesday, 30 May 2018
Geek Trivia: Which Of These Products Did Microsoft Design But Then Deny, Claiming It Was A Hoax?
7 Of The Best Turn-Based Multiplayer Games For Mobile

Turn-based (or asynchronous) multiplayer games are the greatest thing to hit mobile gaming since, well, ever.
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How to Use Apple’s New Multi-Room Audio Features in AirPlay 2
How To Use Reading View In Microsoft Edge
Pokémon Fans Rejoice: The Nintendo Switch Gets Two Fresh Titles

This November Pokémon fans will get a special treat: two new Pokémon releases on the Nintendo Switch that don’t just rehash old ground b…
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How to Disable Windows 10’s Tabs From Showing in Alt+Tab
Plex Media Center Now Supports Podcasts
Google Daydream vs. Gear VR: Which Mobile VR Headset is Better?
Elon Musk blames tough government rules for no Tesla in India
If Your Cellphone Is Paid For, Demand Your Cell Company Unlock It

If you buy a cellphone from your carrier, it’s almost always locked to their network.
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What is Focal Length in Photography?
What Is A Wi-Fi Hotspot (and Are They Safe to Use)?
Tuesday, 29 May 2018
Geek Trivia: Which Of These Common Household Items Was Invented By Accident?
The Best Chromebooks You Can Buy, 2018 Edition

There has never been a better time to get into the Chromebook scene, so you’re in a great position to make the leap.
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Loot Boxes Are Obviously Gambling
California Unveils New E-Ink License Plates In Limited Pilot Program

California is now testing a unique license plate option: a digital license plate that sports a Kindle-like E-ink display and host of features t…
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The Best Alternatives to Slack for Team Chat
CARROT, the Hilarious Misanthropic Weather Robot, Is Finally on Android
How to Turn Any File Into a Template in macOS
Hero Electronix enters IoT space with Zenatix acquisition
The Best 7 Bluetooth Key Finders To Ensure Your Keys Never Go Missing Again

How often do you find yourself misplacing your keys and totally forgetting where you left them?
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How to Install and Manage Fonts in Windows 10’s Settings App
How to Buy Kindle or Audible Books on iPhone or iPad
Why It’s Not a Big Deal That Google (and Facebook) Knows A Lot About You
Monday, 28 May 2018
The Best Oversized Mouse Pads And Desk Pads

A big mouse pad is good. So it follows that an absolutely enormous mouse pad is better, right?
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Geek Trivia: To Assist With Construction Of The Saturn V Rockets, Which Of These Groups Was Brought In As Consultants?
How to Listen to Spotify With Just Your Web Browser
8 Awesome BBQ and Grilling Accessories For All Your Cookout Needs

It’s BBQ and grilling season for many of us, and a successful cookout is far easier with the right tools.
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What is the Latest Version of macOS?
Why You Should Consider Adding a TV to Your Computer Setup
Sunday, 27 May 2018
Geek Trivia: Alexander Graham Bell Believed Which Of These To Be His Greatest Invention?
Social Networks Are Great, But They’re a Terrible Place to Get News
Saturday, 26 May 2018
Geek Trivia: The Odd And Rigid Positioning Of The Arms Often Seen After A Concussion Is Called The?
How to View and Improve Your Game’s Frame Per Second (FPS)
Friday, 25 May 2018
Geek Trivia: A Heat Burst Is An Incredibly Rare Atmospheric Phenomenon Associated With?
Steam Link Isn’t Coming to iPad and iPhone
Instapaper and Some US Newspapers Are Blocked in Europe Now, Here’s How to Access Them Anyway
How to Stop Your Roku From Talking in Menus
A Wild Series of Coincidences Made an Echo Eavesdrop, But It Probably Won’t Happen to You

An Amazon Echo is in trouble for recording a conversation and sending it to a user’s employee.
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How Big Are Gigabytes, Terabytes, and Petabytes?
Announcing the General Availability of Hortonworks Data Platform (HDP) 2.6.5, Apache Ambari 2.6.2 and SmartSense 1.4.5
We are excited to make several product announcements including the general availability of : HDP 2.6.5 Apache Kafka 1.0 Apache Spark 2.3 Apache Ambari 2.6.2 SmartSense 1.4.5 HDP 2.6.5 is an important release for Hortonworks given it is the first release that enables Apache Kafka 1.0 and Apache Spark 2.3 Hortonworks Data Platform 2.6.5 With […]
The post Announcing the General Availability of Hortonworks Data Platform (HDP) 2.6.5, Apache Ambari 2.6.2 and SmartSense 1.4.5 appeared first on Hortonworks.
How to Force Reboot Your Oculus Go (When It Stops Working)
The Best Must-Have Exclusive Games For the Nintendo Switch

“Exclusive Nintendo game” is almost a redundant phrase, since most of Nintendo’s best games are the ones the company makes it…
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How to Change the Chat Background in WhatsApp
What is the GDPR Privacy Law and Why Should You Care?
How to Monitor Humidity Levels in Your Home
Thursday, 24 May 2018
Use StumbleUpon One Last Time Before It Disappears Forever
Geek Trivia: The Only Region On Earth Where Scientists Have Found No Evidence Of Active Microbial Life Is?
7 Accessories to Turn Your iPad into a Productivity Powerhouse

While iPads are still a way off replacing computers for everyone, they are incredibly capable devices.
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Chrome Has a Hidden Password Creation Tool, Here’s How To Use It
How To Change Your Gmail or Google Password
Modern macOS Is Now Older Than Classic Mac OS Was In 2001
Amazon’s Map Tracker Lets You Obsess About Your Package Even More

Amazon has been testing a feature that allows you to track your package on a map, and now the company is rolling it out widely to more users.</…
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Amazon partners Embassy group for Alexa-enabled smart homes
What’s the Latest Version of iOS for iPhones and iPads?
Protecting Data: How to Adapt to the GDPR
After the advent of the GDPR, companies that are smart about protecting data will find themselves at a distinct competitive advantage.
The post Protecting Data: How to Adapt to the GDPR appeared first on Hortonworks.
Containerized Apache Spark on YARN in Apache Hadoop 3.1
This is the 6th blog of the Hadoop Blog series (part 1, part 2, part 3, part 4, part 5). In this blog, we will explore how to leverage Docker for Apache Spark on YARN for faster time to insights for data intensive workloads at unprecedented scale. Apache Spark applications usually have a complex set […]
The post Containerized Apache Spark on YARN in Apache Hadoop 3.1 appeared first on Hortonworks.
Quickly Check Where Any Downloaded File Came From in macOS
The Best Cast-Iron Skillets For The Traditional Cooking Experience

A cast-iron skillet is a commitment and involves care and attention, but it’s a valuable part of an avid chef’s arsenal.
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How to Change Your Default Credit Card on Amazon (And Clean Up the List)
What’s New in Windows 10’s Redstone 5 Update, Available Fall 2018
Announcing Databricks Runtime 4.1
We have recently shipped the new Databricks Runtime version 4.1 powered by Apache Spark™. Version 4.1 brings improved performance on read/write from sources like S3 or Parquet, improved caching, and a great deal of quality and feature improvements for the preview of Databricks Delta focused on faster query execution and adaptive schema and type validation.
If you are participating in our preview of Databricks Delta on Azure Databricks or Amazon’s AWS, it is highly recommended that you upgrade to version 4.1 today.
Let’s take a closer look at some of the improvements:
- Faster Query Execution: There are a number of improvement in this area that benefit all queries like code generation enhancements. Here are a few specific highlights.
- Stats & Indexing (Delta): Databricks Delta stats collection makes query execution smarter. In this release, collecting these stats has gotten more efficient. In our measurements internally, we see over 40% improvement in stats collections time.
- Faster OPTIMIZE (Delta):
OPTIMIZEcommand improves reads by consolidating files. With this release,OPTIMIZEnow executes in parallel – greatly speeding up the time it takes to optimize a table. - Lower Latencies with
LIMIT(Delta): There are also improvements in limit pushdown that reduce intermediate result sets size. - Improved Streaming Throughput (Delta): With this release, we are also pushing filters further down for improved streaming efficiency.
- Faster
UPDATE, DELETE andMERGE(Delta): Writes withUPDATE,DELETEandMERGEstatements in Delta can now use stats and perform data skipping for lower latency executions.
- Managing Schema Validation and Evolution (Delta): Validating data is an important part of keeping your data pipelines robust. However the structure of real world data changes over time. Databricks Delta now provides two forms of schema evolution: automatic, which can generate the required DDL as new columns appear; or static, which provides greater control using standard
ALTER TABLEDDL. You can learn more about Schema Validation here. - Faster Reads and Writes:
- Faster Parquet: We now have an improved decoder that is turned on by default in version 4.1. In our internal measurements done on AWS S3, the new parquet reader, combined with IO caching is about 3x faster in MB/sec!
- Improved S3 Access: S3 Select brings efficiency to the retrieval of S3 data. With selective retrieval, less data is on the wire when you read a subset of JSON or CSV attributes. You can read more about S3 Select here.
Databricks Delta remains in Private Preview, but the updates on version 4.1 represent a candidate release in anticipation of the upcoming general availability (GA) release. If you are not already participating in the Databricks Delta preview, you can still sign up here.
This post touches on only a few select improvements in the 4.1 release. If you’d like to go over the full set of improvements, please visit the release notes for version 4.1 here.
If you’d like to hear more about the features here and more about Databricks Runtime, stop by our booth at the Spark + AI Summit in San Francisco.
Come find out what’s new in Spark, Data, and AI! Register now.
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Try Databricks for free. Get started today.
The post Announcing Databricks Runtime 4.1 appeared first on Databricks.
How (and Why) You Should Be Cleaning Your Phone and Other Electronics
Facebook Upgrades Two Factor Authentication: Here’s How to Set It Up
DISCOVER with Data Steward Studio (DSS): Understand your your hybrid data lakes to exploit their business value!
If data is the new bacon, data stewardship supplies its nutrition label! This is the first part of a two part blog introducing Data Steward Studio (DSS) and discusses the problems that DSS addresses in the enterprise data landscape. Part 2 of this blog will cover a detailed capability walkthrough. Data lakes, which promise to […]
The post DISCOVER with Data Steward Studio (DSS): Understand your your hybrid data lakes to exploit their business value! appeared first on Hortonworks.
Wednesday, 23 May 2018
Geek Trivia: The First Science Fiction Serial Film Was?
The Best Smarthome Products That Are Rental Friendly

If you rent your home, you could feel left out of the current smart home renaissance. Fear not, though.
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PassProtect Tells You If Your Password Is Compromised
A Guide to Developer, Apache Spark Use Cases, and Deep Dives Talks at Spark + AI Summit
Apache Spark is tackling new frontiers through innovations by unifying new workloads. This enables developers to combine data and AI to develop intelligent applications. Developers come to this summit not just to hear about innovations from contributors. They come to share their use cases, experiences, and absorb knowledge.
@matei_zaharia just announced support of #kubernetes in #Spark 2.3 at the keynote of @spark_summit pic.twitter.com/XGbRZbg3wW
— Yann Vanderstockt (@yannvds) October 25, 2017
In this final blog, we shift our focus to these developers who make a difference, not only in their contributions to the Spark ecosystem but also in use of Spark at scale in their respective industries.
Let’s start with large-scale feature aggregation using Apache Spark at Uber Inc. that enables several thousand features to account for ML-based decision making and risk analysis. Developers Pulkit Bhanot and Amit Nene will reveal data’s transformational journey, show its architecture and the Spark ecosystem, and share how aggregated features reduce turnaround times for machine learning models.
As of 2018 Facebook has close to 2.18 billion users, one-third of the world’s population. This global usage generates tons of data that need processing with reliable architecture. Facebook software engineers Brian Cho and Ergin Seyfe will share how they handle shuffle reads when data reaches 300TB. And they will discuss what type of architecture can support such scale. Find out in their talks: SOS: Optimizing Shuffle I/O and Taking Advantage of a Disaggregated Storage and Computer Architecture.
The term über data processing aptly takes its meaning in this session: Efficiently Triaging CI Pipelines with Apache Spark: Mixing 52 Billion Events/Day of Streaming with 40 TB/Hour of Batch Processing. In this fascinating talk about Spark at scale, software engineer Ivan Jibaja from Pure Storage will share how to write single application for both streaming and batch jobs at scale. Also, learn about building state-of-the-art Continuous Integration(CI) pipelines at scale, as his title suggests.
Now, the human genome and its sequencing have been at the forefront among scientists in the Health and Life Sciences (HLS). Thanks to advancement in big data analytics at scale, in particular because of Spark’s ability to process distributed data at scale and because of cheap cloud storage. Software Engineers Ram Sriharsha and Frank Austin Nothaft from Databricks have a novel solution to build genomic ETL pipelines in the cloud atop Apache Spark. As a biochemist or molecular biologist or a developer in the HLS industry, you will want to attend their session: Scaling Genomics Pipelines in the Cloud.
For developers interested in understanding the design motivations behind the evolution of Spark’s DataSource v2 APIs in Apache Spark 2.3, this deep-dive session from Databricks Spark committer and contributor Wenchen Fan and Gengliang Wang is for you. One notable usage of its new source and sink API enabled Continuous Processing in Structured Streaming, which will be discussed in another session from Jose Torres. Related to structured streaming is another immersive talk Deep Dive into Stateful Stream Processing in Structured Streaming from Spark committer Tathagata Das.
One of the big community contributions to Apache Spark 2.3 was the ability to run Spark natively on Kubernetes. With a native scheduler for Kubernetes within Apache Spark, you can now run Spark jobs natively. In their session, Apache Spark on Kubernetes Clusters, Messrs Anirudh Ramanathan and Sean Suchter will not only discuss how to build modern data pipelines in a Kubernetes native way but also unravel the future roadmap for native scheduler within Apache Spark.
Another community contribution in Spark 2.3 is Pandas UDF in Pyspark, which developer Jin Lin will talk in his session: Vectorized UDF: Scalable Analysis with Python and PySpark
Processing data at scale with Spark seems the underlying theme in these aforementioned sessions. Consider Apple’s case: Their requirements to handle data at speed and scale replace and augment traditional MapReduce workloads with Spark. In this talk, Apache Spark at Apple, software developers Sam Maclennan and Vishwanath Lakkundi will cover challenges of working at scale and lessons learned from managing large multi-tenant clusters, consisting of exabyte storage and million cores.
Finally, to comprehend what’s blockchain and why it matters, MIT Technology Review dedicated a quarterly issue on this subject. In blockchain we trust, its authors argue that you have to look beyond wild speculation and focus on what’s being built underneath. Even better, you can find out how the underlying infrastructure and its awesome technology is built atop Apache Spark in the Analyzing Blockchain Transactions in Apache Spark session from software developer Jiri Kremser: A fascinating talk, to say the least!
What’s Next
Take advantage of this promo code JulesPicks for a $300 discount and register now. Come find out what’s new in Spark, Data, and AI, and see you in San Francisco!
Read More
- Find out 5 Reasons to Attend Spark + AI Summit.
- Read a Few Picks from the New Tracks
- Check out Few Picks From TensorFlow Sessions
- Read a Few Picks From the AI, Machine Learning, and Data Sciences Sessions
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Try Databricks for free. Get started today.
The post A Guide to Developer, Apache Spark Use Cases, and Deep Dives Talks at Spark + AI Summit appeared first on Databricks.
Amazon Might Shut Down Your Account If You Return Too Much Stuff

Amazon screws up every once in a while and you have to send a package back.
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How to Choose Which GPU a Game Uses on Windows 10
Firefox Finally Offers Two Factor Auth to Protect Your Passwords
How to Enable Copy and Paste Keyboard Shortcuts in Windows 10’s Bash Shell
How to Set Per-App Sound Outputs in Windows 10
How to Check Your MacBook’s Battery Health
Using Windows 10’s New Screenshot Tool: Clips and Annotations
Which Smart Light Switch Should You Buy?
Tuesday, 22 May 2018
Geek Trivia: Rock’s Law Is An Observational Rule Of Computing That Covers?
The Best Bullet Blenders For Super Fast and Convenient Smoothies

Full size kitchen blenders are great for big recipes (and big pitchers of Margaritas) but they’re not so great for a quick smoothie or s…
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Patch for New Spectre-Like CPU Bug Could Affect Your Performance
How To Reverse Picture Search With Google Images
Comcast Leaked Customer Wi-Fi Logins in Plaintext, Change Your Passcode Now
Apollo Hospitals adopts IBM Watson for oncology and genomics
Akamai, MUFG announce blockchain-based payments network
Can You Use FaceTime on Windows?
Everything You Can Do With Google Pay
The Best Triple Monitor Mounts And Stands

You’ve finally built that monster triple monitor desktop setup you’ve been dreaming about.
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How to Customize Window Borders and Shadows on Windows 10
How to Find Official Windows Drivers for Any Device
Download GlassWire FREE to See Who’s Connecting to Your Wi-Fi Network! [Sponsored]
Enough With All the Smarthome Hubs Already
Monday, 21 May 2018
The Best Bluetooth Adapters To Use Your Wired Headphones With Your New Phone

The world of smartphones may prefer small bezels over headphone jacks, but you can still use your beloved wired headphones with fancy new phones…
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Resident Evil 7 Will Be On the Switch as a Streaming Game, Somehow

Resident Evil 7 is an incredible horror game that can’t run on the Switch.
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Geek Trivia: The Only Place The IRS Allows You To Make Cash Payments Is?
Resident Evil 7 Will Be On the Switch as a Streaming Game, Japan Only For Now

Resident Evil 7 is an incredible horror game that can’t run on the Switch.
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Chrome Has a Built In Malware Scanner, Here’s How to Use It
How to Convert a Microsoft Word Document to a PDF
Ather Energy unveils its charging infrastructure network AtherGrid
The Best Portable Bluetooth Speakers with Google Assistant

Google Assistant is growing rapidly, getting new features and more smarthome support every day.
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How Android P Will Increase Battery Life
How to Disable the Pointless People Icon on Windows 10’s Taskbar
How to Create, Edit, and View Microsoft Word Documents for Free
Sunday, 20 May 2018
Geek Trivia: The Only U.S. President Who Spoke English As A Second Language Was?
Which Streaming TV Service is Right for You? (Sling, Hulu, YouTube TV, Vue, or DirecTV)
Saturday, 19 May 2018
Geek Trivia: Originally, Star Trek Writers Intended To Make Which Planet Spock’s Home World?
What’s the Best Antivirus for iPhone? None!
How to Fix Oculus Go Battery Life Problems
Friday, 18 May 2018
Geek Trivia: The Tiny Colored Dots That Give Old Comic Books Their Iconic Look Are Called?
Google Is Shipping Almost As Many Smart Speakers As Amazon These Days

Amazon may have gotten a head start on the smart speaker market, but if a third-party analytics company is to be believed, Google is catching up fast.
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You Can Now @ People in Gmail
How to Use the Reader View in Firefox
Why Restarting Your Phone Makes it Perform Better and Fixes Common Issues
Accelerated Path to the Value of Data with Hortonworks University
You have probably heard of the 3Vs of big data – Volume, Variety, and Velocity. They define the three dimensions of big data, and the challenges that the hyper-connected digital world has produced over the last decade – the massive volume and increasing variety of data generated at rapid velocity that companies can’t keep up […]
The post Accelerated Path to the Value of Data with Hortonworks University appeared first on Hortonworks.
10 Best Lawn Games Kits for Summer Fun and Backyard Gatherings

Looking for some entertainment to go with your summer gatherings? Add to the festivities with…
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How to Stop All of Twitter’s Annoying Emails
How to Get Started With Usenet, the Best Alternative to Torrents
Basic Home Maintenance Tasks That Most People Overlook
Thursday, 17 May 2018
Geek Trivia: The “Woodpecker” Was A Cold War Era Tool Used To Detect?
Introducing Tracy Miranda as the CloudBees Open Source Program Lead
I’m Tracy Miranda, and I’m really excited to have joined CloudBees this month leading the open source program. CloudBees’ contributions to Jenkins include developing Pipeline and Blue Ocean, staffing the infrastructure team, advocacy and events work, as well as security efforts. My focus is on making sure there is a great relationship between the Jenkins community and CloudBees, which means strong communication, help get traction on things the community wants, and generally working to make Jenkins and the community thrive and stay awesome in an ever-changing tech landscape.
Here’s a little background on me: I come from an electronics/EDA background but switched to software early in my career when I first got involved with open source software. I’ve been part of the Eclipse community for around 15 years, definitely from before git was even a thing. I love being involved with all levels: project committer, conference chair, steering committee for working groups and more recently board of directors.
On a personal note, I …
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Live in the UK with my husband and 2 young kids
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Grew up in Kenya
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Enjoy playing badminton, love good food & am always first at any buffets
I am looking forward to getting to know the Jenkins community well, and really getting a feel for your Jenkins stories, good and bad. Please feel free to let me know:
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What you love about the Jenkins community & how you are using Jenkins
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What you’re working on doing with Jenkins
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What you don’t like and want improved
You can find me on the mailing lists or via:
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Twitter @tracymiranda
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Email: tmiranda@cloudbees.com
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IRC: tracymiranda
Also I’ll be at the upcoming events: DevOps World - Jenkins World in San Francisco, California and Nice, France so if you plan to attend do come and say hi. The Jenkins community is the real force behind Jenkins. And in turn Jenkins powers so much of the software out there. It is an honour to be joining this wonderful community.
The Best Rugged Portable Bluetooth Speakers

Bluetooth speakers are great for portable music playback, but for those times that you want to take them somewhere a little more off the beate…
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Reminder: It’s Really Easy to Buy Fake Facebook Accounts
The New Xbox Adaptive Controller Takes Accessibility in Gaming to a New Level

Today, Microsoft announced a new kind of game controller, called the Xbox Adaptive Controller, that features an impressive 19 ports to connec…
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Free Download: Fender’s Riffstation Shows You Chords For Any Song
Being The Product Isn’t Necessarily Bad
How Android P’s Gesture Navigation Works
How to Change Your iPhone Ringtone
Avoid iTunes Bloat With the Windows Store Version
What Are Hot-Swappable and Cold-Swappable Devices?
Wednesday, 16 May 2018
Geek Trivia: What Popular Snack Was Originally Created For The Wives Of U.S. Servicemen?
Trying out Containerized Applications on Apache Hadoop YARN 3.1
This is the 5th blog of the Hadoop Blog series (part 1, part 2, part 3, part 4). In this blog, we will explore running Docker containers on YARN for faster time to market and faster time to insights for data intensive workloads at scale. For over half a decade, the Apache Hadoop YARN […]
The post Trying out Containerized Applications on Apache Hadoop YARN 3.1 appeared first on Hortonworks.
Soon screening near you? Blockchain tech premieres at Cannes
5 Great Selfie Accessories For The Perfect Selfie

Taking a selfie is a fun exercise in capturing moments with our friends and sneaking ourselves into cool sites we visit, but there’s mor…
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Amazon Prime Members Will Get 10% Off Sale Items at Whole Foods Starting This Summer

Amazon just keeps making Whole Foods more appealing to Prime members.
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Stop Your Friends From Changing Your Whatsapp Group Names With New Admin Tools
Amazon Prime Members Will Get 10% Off at Whole Foods Starting This Summer

Amazon just keeps making Whole Foods more appealing to Prime members.
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Mumbai based ION Energy unveils first product UDYR
How to See or Clear the Browsing History on Your PlayStation 4
Google Maps vs. Waze: Which One Is Really Better?
How to Connect to a Wireless Network in Windows 10
What is the New EasyMesh Wi-Fi Standard? (and Why It Doesn’t Matter Yet)
Centre proposes charging points for electric vehicles every 3 km
Why India needs AI to work for agriculture, healthcare and education
Why You Shouldn’t Bother Repairing Damaged Charging Cables
Tuesday, 15 May 2018
The Best Laptop Docking Stations for Every Laptop

There’s nothing quite like plugging in a single cable to turn your portable laptop into a full blown workstation.
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Geek Trivia: Which Iconic Video Game Character Was Created As A Result Of An Internal Company Contest?
A Guide to AI, Machine Learning, and Data Science Talks at Spark + AI Summit
By any measurement today, in the digital media, technical conferences and citations, or searches on Google trends, the frequency of terms like artificial intelligence, machine learning, deep learning or data science is on the rise. A special report
in The Economist makes the case that Artificial Intelligence (AI) and Machine Learning (ML), and its purported tectonic shifts, is spreading beyond the technology sector, with big consequences in different market segments, affecting workers and consumers and generating a potential economic-value from AI in the next couple of decades.

But doing AI and ML are not so much of a problem as managing and processing big data at massive scale and its infrastructure is. And the problem is not so much in the machine learning code or algorithms as it is in the technical debt in supporting the infrastructure.
For the Spark + AI Summit, we expanded new tracks to attract talks that speak of AI use cases, data science, and productionizing machine learning to address how practitioners operate in the real world and manage their infrastructure for these use cases. In this blog, we point to a few sessions that speak volumes in their endeavors in combining the immense value of data and AI.
Let’s start to examine how Mastercard productionizes their AI as a service platform using distributed deep learning techniques and productizing User-Items Propensity Models with Apache Spark at scale. Suqiang Song will share with the community their technical journey and AI architecture design principles for this service in his talk, AI as a Service, Build Shared AI Service Platforms Based on Deep Learning Technologies.
At some point, we all have inadvertently interacted with AI assistants, chatbots. What is the technical mystery behind them? How do you build and operate them? David Low of Pand.ai reveals the finer technical details of building and deploying LSTM machine learning models as well as discuss the current and future state of chatbots in his talk, The Rise of Conversational AI.
It’s one thing to build an ML model; it’s another to manage and deploy it in production. In his talk, Productionizing Apache Spark ML Pipelines with the Portable Format for Analytics, IBM’s Nick Pentreath will discuss a portable format to productionize Apache Spark ML pipelines.
Similarly, Databricks’ Joseph Bradley will discuss developments in Apache Spark to deploy MLlib models and pipelines within Structured Streaming. In the session, Deploying MLlib for Scoring in Structured Streaming, he will share how new developments in Apache Spark 2.3 and MLlib support deploying MLlib models and Pipelines for scoring and predicting in Structured Streaming and why it simplifies many production cases.
Now, if you live in a metropolitan area, you have likely taken an Uber at some point to reach your desired destination. Ever wonder how they compute prices in real-time for over 600 cities? Or curious what machine learning algorithms they use, or how data scientists work to do feature engineering? Messrs Peng Du and Felix Cheung from Uber will reveal technical details of their machine learning infrastructure in their session, Building Intelligent Applications, Experimental ML with Uber’s Data Science Workbench.
And if you have traveled lately, you have likely stayed at an Airbnb rental. Behind that ease-of-use and comfort of selecting myriad rentals of your choice is a complex infrastructure supporting an end-to-end machine learning production life-cycle. Session talks form Airbnb, Bighead: Airbnb’s End-to-End Machine Learning Platform and Zipline: Airbnb’s Machine Learning Data Management Platform will expose Airbnb’s machine learning platforms that enable them to cover data collection at scale, do feature engineering, and train, deploy, productionize, and monitor their infrastructure.
For those using cloud computing for their infrastructure, cost management is as important as reliability. At Databricks, we invest heavily in cloud computing, because it’s our core business to offer unified analytics platform, powered by optimized Apache Spark, to our customers. Hence, cost management for our customers becomes an imperative function as part of the cost of goods (COGS) and operating expenses (OPEX). Data scientist Xuan Wang, from Databricks, will demonstrate how we detect changes and do forecasts to minimize costs and share some data science techniques in his talk, Cloud Cost Management and Apache Spark.
Finally, Natural Language Processing (NLP) as a way to parse spoken or written text is paramount to ML and AI applications. Building a complex NLP system requires an infrastructure and use of three software frameworks: machine learning, deep learning, and Apache Spark NLP libraries. Apache Spark NLP: Extending Spark ML to Deliver Fast, Scalable & Unified Natural Language Processing session by engineers Alexander Thomas and David Talby dives into all aspects of optimization, sentiment detection, lemmatization, language modeling, and pipeline building.
What’s Next
There is much to peruse and pick sessions that appeal to you from the schedule, too. In the final blog, we will share our picks from Developer, Spark Experience, Deep Dives, and related tracks.
If you have not registered yet, use JulesPicks code for a $300 discount. See you there!
Read More
- Check out Few Picks From TensorFlow Sessions
- Find out 5 Reasons to Attend Spark + AI Summit
--
Try Databricks for free. Get started today.
The post A Guide to AI, Machine Learning, and Data Science Talks at Spark + AI Summit appeared first on Databricks.
Amazon’s Checkout-Free Store Is Coming to Chicago and San Francisco

Amazon’s trial of a checkout-less store, Amazon Go, seems to be going well.
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How To Enable Offline Support in the New Gmail
How Google’s New Storage Pricing Compares to Microsoft, Apple, and Dropbox*
Automatic deployment of “incremental” commits to Jenkins core and plugins
A couple of weeks ago, Tyler mentioned some developer improvements in Essentials that had been recently introduced: the ability for ci.jenkins.io builds to get deployed automatically to an “Incrementals” Maven repository, as described in JEP-305. For a plugin maintainer, you just need to turn on this support and you are ready to both deploy individual Git commits from your repository without the need to run heavyweight traditional Maven releases, and to depend directly on similar commits of Jenkins core or other plugins. This is a stepping stone toward continuous delivery, and ultimately deployment, of Jenkins itself.
Here I would like to peek behind the curtain a bit at how we did this, since the solution turns out to be very interesting for people thinking about security in Jenkins. I will gloss over the Maven arcana required to get the project version to look like 1.40-rc301.87ce0dd8909b (a real example from the Copy Artifact plugin) rather than the usual 1.40-SNAPSHOT, and why this format is even useful. Suffice it to say that if you had enough permissions, you could run
mvn -Dset.changelist -DskipTests clean deploy
from your laptop to publish your latest commit. Indeed as mentioned in the JEP, the most straightforward server setup would be to run more or less that command from the buildPlugin function called from a typical Jenkinsfile, with some predefined credentials adequate to upload to the Maven repository.
Unfortunately, that simple solution did not look very secure. If you offer deployment credentials to a Jenkins job, you need to trust anyone who might configure that job (here, its Jenkinsfile) to use those credentials appropriately. (The withCredentials step will mask the password from the log file, to prevent accidental disclosures. It in no way blocks deliberate misuse or theft.) If your Jenkins service runs inside a protected network and works with private repositories, that is probably good enough.
For this project, we wanted to permit incremental deployments from any pull request. Jenkins will refuse to run Jenkinsfile modifications from people who would not normally be able to merge the pull request or push directly, and those people would be more or less trustworthy Jenkins developers, but that is of no help if a pull request changes pom.xml or other source files used by the build itself. If the server administrator exposes a secret to a job, and it is bound to an environment variable while running some open-ended command like a Maven build, there is no practical way to control what might happen.
The lesson here is that the unit of access control in Jenkins is the job. You can control who can configure a job, or who can edit files it uses, but you have no control over what the job does or how it might use any credentials. For JEP-305, therefore, we wanted a way to perform deployments from builds considered as black boxes. This means a division of responsibility: the build produces some artifacts, however it sees fit; and another process picks up those artifacts and deploys them.
This worked was tracked in INFRA-1571. The idea was to create a “serverless function” in Azure that would retrieve artifacts from Jenkins at the end of a build, perform a set of validations to ensure that the artifacts follow an expected repository path pattern, and finally deploy them to Artifactory using a trusted token. I prototyped this in Java, Tyler rewrote it in JavaScript, and together we brought it into production.
The crucial bit here is what information (or misinformation!) the Jenkins build can send to the function. All we actually need to know is the build URL, so the call site from Jenkins is quite simple. When the function is called with this URL, it starts off by performing input validation: it knows what the Jenkins base URL is, and what a build URL from inside an organization folder is supposed to look like: https://ci.jenkins.io/job/Plugins/job/git-plugin/job/PR-582/17/, for example.
The next step is to call back to Jenkins and ask it for some metadata about that build. While we do not trust the build, we trust the server that ran it to be properly configured. An obstacle here was that the ci.jenkins.io server had been configured to disable the Jenkins REST API; with Tyler’s guidance I was able to amend this policy to permit API requests from registered users (or, in the case of the Incrementals publisher, a bot).
If you want to try this at home, get an API token, pick a build of an “incrementalified” plugin or Jenkins core, and run something like
curl -igu <login>:<token> 'https://ci.jenkins.io/job/Plugins/job/git-plugin/job/PR-582/17/api/json?pretty&tree=actions[revision[hash,pullHash]]'
You will see a hash or pullHash corresponding to the main commit of that build. (This information was added to the Jenkins REST API to support this use case in JENKINS-50777.) The main commit is selected when the build starts and always corresponds to the version of Jenkinsfile in the repository for which the job is named. While a build might checkout any number of repositories, checkout scm always picks “this” repository in “this” version. Therefore the deployment function knows for sure which commit the sources came from, and will refuse to deploy artifacts named for some other commit.
Next it looks up information about the Git repository at the folder level (again from JENKINS-50777):
curl -igu <login>:<token> 'https://ci.jenkins.io/job/Plugins/job/git-plugin/api/json?pretty&tree=sources[source[repoOwner,repository]]'
The Git repository now needs to be correlated to a list of Maven artifact paths that this component is expected to produce. The repository-permissions-updater (RPU) tool already had a list of artifact paths used to perform permission checks on regular release deployments to Artifactory; in INFRA-1598 I extended it to also record the GitHub repository name, as can be seen here. Now the function knows that the CI build in this example may legitimately create artifacts in the org/jenkins-ci/plugins/git/ namespace including 38c569094828 in their versions. The build is expected to have produced artifacts in the same structure as mvn install sends to the local repository, so the function downloads everything associated with that commit hash:
curl -sg 'https://ci.jenkins.io/job/Plugins/job/git-plugin/job/PR-582/17/artifact/**/*-rc*.38c569094828/*-rc*.38c569094828*/*zip*/archive.zip' | jar t
When all the artifacts are indeed inside the expected path(s), and at least one POM file is included (here org/jenkins-ci/plugins/git/3.9.0-rc1671.38c569094828/git-3.9.0-rc1671.38c569094828.pom), then the ZIP file looks good—ready to send to Artifactory.
One last check is whether the commit has already been deployed (perhaps this is a rebuild). If it has not, the function uses the Artifactory REST API to atomically upload the ZIP file and uses the GitHub Status API to associate a message with the commit so that you can see right in your pull request that it got deployed:

One more bit of caution was required. Just because we successfully published some bits from some PR does not mean they should be used! We also needed a tool which lets you select the newest published version of some artifact within a particular branch, usually master. This was tracked in JENKINS-50953 and is available to start with as a Maven command operating on a pom.xml:
mvn incrementals:update
This will check Artifactory for updates to relevant components. When each one is found, it will use the GitHub API to check whether the commit has been merged to the selected branch. Only matches are offered for update.
Putting all this together, we have a system for continuously delivering components from any of the hundreds of Jenkins Git repositories triggered by the simple act of filing a pull request. Securing that system was a lot of work but highlights how boundaries of trust interact with CI/CD.
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