GitLab’s Secret to Managing Employees in 160 Locations: Write Everything Down

Ali Rowghani, head of YC Continuity, talks to GitLab CEO Sid Sijbrandij (W15) about how GitLab has built a completely distributed company with 160 people (and growing). We filmed this conversation at GitLab’s SF headquarters, where Sid is the only local employee. Sid’s biggest tip for success in scaling a distributed company: write everything down.
Listen up for…
2:41 – GitLab values boring solutions: our product should be exceptional, but the company structure should be run-of-the-mill.
3:10 – “After a few days, they just started working from home” – Sid talks about how GitLab didn’t really set out to create a distributed company — it just evolved naturally.
3:46 – Take an extra minute to write things down, so that you can save time and give people the tools they need to succeed. Everything from who starts a video conference, to OKRs for the whole company.
8:28 – What has been the most difficult


Original URL: http://feedproxy.google.com/~r/feedsapi/BwPx/~3/TQrneW9X2Ks/

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PostgreSQL 9.6.2, 9.5.6, 9.4.11, 9.3.16 and 9.2.20 released

Posted on 2017-02-09
The PostgreSQL Global Development Group has released an update to all supported versions of our database system, including 9.6.2, 9.5.6, 9.4.11, 9.3.16, and 9.2.20. This release includes fixes that prevent data corruption issues in index builds and in certain write-ahead-log replay situations, which are detailed below. It also patches over 75 other bugs reported over the last three months.
Users should plan to apply this update at the next scheduled downtime.
Build corruption with CREATE INDEX CONCURRENTLY
There existed a race condition if CREATE INDEX CONCURRENTLY was called on a column that had not been indexed before, then rows that were updated by transactions running at the same time as the CREATE INDEX CONCURRENTLY command could have been indexed incorrectly.
If you suspect this may have happened, the most reliable solution is to rebuild affected indexes after installing this update.
This issue is present in the 9.2, 9.3, 9.4, 9.5, and 9.6 series


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Joining a billion rows 20x faster than Apache Spark

One of Databricks’ most well-known blogs is the blog where they describe joining a billion rows in a second on a laptop. Since this is a fairly easy benchmark to replicate, we thought, why not try it on SnappyData and see what happens? We found that for joining two columns with a billion rows, SnappyData is nearly 20x faster.

Let’s start with the benchmark as in the original post. The machine is a:

Dell Latitude E7450 laptop with Core(TM) i7-5600U CPU @ 2.60GHz having 16GB of RAM.

Start the SnappyData shell with some decent memory (required for the data load test):

(the GC options are similar to a default SnappyData cluster)

Define a simple benchmark util function

Let’s do a warmup first that will also initialize some Spark components and sum a billion numbers:

> Time taken in Spark 2.0 (sum of a billion): 0.70 seconds

Very impressive sub-second timing.

Let’s try the same using SnappySession (SnappyData’s entry point


Original URL: http://feedproxy.google.com/~r/feedsapi/BwPx/~3/-tZbI0QCqvY/joining-billion-rows-faster-than-apache-spark

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Intel: Cannonlake will be more than 15 percent faster than Kaby Lake

Upgrading CPU performance hasn’t been a priority for Intel in many years, but that could be changing.Intel’s upcoming Cannonlake chips will deliver a performance improvement of more than 15 percent compared to its Kaby Lake chips, said Venkata Renduchintala, president of the Intel Client and Internet of Things businesses and Systems Architecture Group.Intel didn’t provide exact numbers at the company’s annual investor day Thursday, but the projection is based on the SysMark benchmark. Detailed performance improvement numbers will emerge over time.[ To comment on this story, visit Computerworld’s Facebook page. ]The performance improvements from Skylake to Kaby Lake topped out at 15 percent. The CPU performance boost for Cannonlake should be at least that, Intel said.To read this article in full or to leave a comment, please click here


Original URL: http://www.computerworld.com/article/3168332/computer-processors/intel-cannonlake-will-be-more-than-15-percent-faster-than-kaby-lake.html#tk.rss_all

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How to Build a Raspberry Pi Retro Game Console for $35 

Since its release, the $35 Raspberry Pi mini-computer has been hailed as the perfect all-in-one retro game console. Now, it’s easier to do than ever, and it doesn’t take any Linux knowledge whatsoever. Here’s how to make your own retro game console in under 10 minutes.Read more…


Original URL: http://feeds.gawker.com/~r/lifehacker/full/~3/CzdEl8QXYaw/how-to-turn-your-raspberry-pi-into-a-retro-game-console-498561192

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PHP vs. Node.js: Epic battle for developer mind share

It’s a classic Hollywood plot: the battle between two old friends who went separate ways. Often the friction begins when one pal sparks an interest in what had always been the other pal’s unspoken domain. In the programming language version of this movie, it’s the introduction of Node.js that turns the buddy flick into a grudge match: PHP and JavaScript, two partners who once ruled the internet together but now duke it out for the mind share of developers.
In the old days, the partnership was simple. JavaScript handled little details on the browser, while PHP managed all the server-side tasks between port 80 and MySQL. It was a happy union that continues to support many crucial parts of the internet. Between WordPress, Drupal, and Facebook, people can hardly go a minute on the web without running into PHP.To read this article in full or to leave a comment, please click


Original URL: http://www.computerworld.com/article/3167857/application-development/php-vs-nodejs-epic-battle-for-developer-mind-share.html#tk.rss_all

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