The Ledger

Every statement that passed quotation and attribution checks. Mix any filter with any other: certainty 1/5, debate potential 5/5, or both at once.

clear all ✕

why aren't all 10 resolved? a statement only gets an assessment when the public record can support or contradict it. opinions and what-ifs never can, and 0 checkable ones are still open, waiting for their date. predictions held up or didn't; assertions are supported or contradicted. on every card: ▮▮▮▮▮ certainty · ▮▮▮▮▮ debate potential. speakers are clickable

Opinion
Leibert: Writing Visual Basic is more joyful than writing Go applications
“And frankly, it's more joyful to write Visual Basic than it is to write Go, right? That you actually achieve Business results. I mean, seriously, right? Like, writing a Spark job, you see the output right away, whereas if you write a large Go application, I me…”
Florian Leibert Jan 2, 2019 ▶ 2:21 a16z Podcast | Containing the Monolith -- From Microservices to DevOps
Assertion Supported
Hirasaki: Spark acquisition vaulted Roche forward in gene therapy platform technology
“And then with the Spark acquisition same thing BMS, I'm sorry Roche was a laggard in the space, and now suddenly leaped ahead with not only a marketed gene therapy, but this AAV platform that it could use for delivering other gene therapies.”
Koki Hirasaki Feb 28, 2019 ▶ 5:59 What’s with All the Bio M&A in 2019?: A Quick Take
Insight
Stanek: Business users prefer spreadsheet interfaces over Spark and Hadoop
“Some of the most frequently used kind of data analytics tools extremely basic, because they actually look and feel like sheet of paper, like two-dimensional sheet of paper, and you know, so that's the problem with analytics, that on one hand, we have, you know…”
Roman Stanek Jan 2, 2019 ▶ 20:55 a16z Podcast | Making the Most of the Data That Matters
Assertion Not checkable as stated
Moghe: Spark and Hadoop do not replace existing data warehouses
“Spark doesn't subsume data warehousing. Hadoop doesn't subsume, you know, streaming. So they're just like different technologies for different jobs.”
Prat Moghe Jan 2, 2019 ▶ 23:39 a16z Podcast | Making the Most of the Data That Matters
Assertion Not publicly verifiable
Zaharia: Apache Spark is the most active open-source data processing project
“It's actually the most active open source project in data processing in general as far as we can tell.”
Matei Zaharia Jan 2, 2019 ▶ 9:15 a16z Podcast | A Conversation With the Inventor of Spark
What-if
Nguyen: Apache Spark Would Have Failed Earlier Due to Memory Costs
“Now Spark, if it was created six, five, six years before its time would have completely failed because memory was so much more expensive.”
Christopher Nguyen Jan 2, 2019 ▶ 14:45 a16z Podcast | Making Sense of Big Data, Machine Learning, and Deep Learning
Assertion Supported
Hirasaki: Roche Allows Acquired Companies Like Spark to Operate Semi-Autonomously
“Some big pharma companies will just tend to fully integrate the company whereas others will like Roche and Spark will allow the acquired companies to operate semi-autonomously.”
Koki Hirasaki Feb 28, 2019 ▶ 16:10 What’s with All the Bio M&A in 2019?: A Quick Take
Assertion Not checkable as stated
Zaharia: Apache Spark is easier to use than prior big data systems
“So Spark is software for processing large volumes of data on a cluster, and the things that make it unique are, first of all, it has a very powerful programming model that lets you do many kinds of advanced analytics and processing, such as machine learning or…”
Matei Zaharia Jan 2, 2019 ▶ 0:29 a16z Podcast | A Conversation With the Inventor of Spark
Disclosure
Zaharia: Spark was originally designed to run Netflix Prize recommendation algorithms
“So it's actually one of the applications that I first tried to support in Spark was you know, the recommendation algorithm he was working on.”
Matei Zaharia Jan 2, 2019 ▶ 16:41 a16z Podcast | A Conversation With the Inventor of Spark
Assertion Supported
Analytics frameworks like Spark and Hadoop assume exclusive resource access
“Most things, Hadoop, Spark, Storm, they think they're running by themselves. And so they compete for resources in really interesting ways.”
Chandra Krintz Jul 15, 2017 ▶ 11:52 Chandra Krintz
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