HN user

hglaser

2,540 karma

cofounder of kitewing // www.kitewing.ai

previously cofounder of periscope data

Posts57
Comments93
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www.kitewing.ai 5mo ago

Building a Resilient, Multi-User Agentic Streaming Application

hglaser
1pts0
frankbear.substack.com 9mo ago

A 127-year old ham sandwich ekiben

hglaser
2pts0
www.harryglaser.com 11mo ago

Our relationship to technology is broken

hglaser
3pts1
www.harryglaser.com 2y ago

Don't Start an Analytics Company

hglaser
2pts0
www.harryglaser.com 2y ago

What I learned selling my company

hglaser
275pts98
www.modelbit.com 4y ago

Snowflake Snowpark Python First Impressions

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1pts1
www.modelbit.com 4y ago

How to call a Lambda function in another account from AWS Redshift

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1pts0
www.modelbit.com 4y ago

How to deploy an ML model to production with one line of code

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2pts0
dataconomy.com 8y ago

A Whole New World for Data Teams

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1pts0
community.periscopedata.com 8y ago

Periscope Data Community for Data Analysts

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techcrunch.com 9y ago

Microsoft Launches Azure Database for MySQL and PostgresSQL

hglaser
3pts0
aws.amazon.com 10y ago

User Defined Functions for Amazon Redshift

hglaser
2pts0
cdixon.org 11y ago

Come for the tool, stay for the network

hglaser
55pts9
www.periscope.io 11y ago

Demystifying Redshift – What's Up with My Disks?

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1pts0
github.com 11y ago

FizzBuzz Enterprise Edition

hglaser
135pts49
www.femalefounderstories.com 11y ago

YC Female Founder Stories

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4pts1
statico.github.io 11y ago

Everything I Missed in “Vim After 11 Years” (2013)

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1pts0
spacekatgal.tumblr.com 11y ago

Legal Defense Fund for Women Targeted by GamerGate

hglaser
5pts0
blog.samaltman.com 11y ago

Applying to YC

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178pts112
periscope.io 11y ago

Beyond Random() – Normal Distributions in SQL

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2pts0
standardmarkdown.com 11y ago

Standard Markdown

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1167pts366
periscope.io 12y ago

Use Subqueries and Window Functions to Compute Running Averages

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1pts0
periscope.io 12y ago

Computing Day-Over-Day Changes With Window Functions

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1pts0
periscope.io 12y ago

Ascii Art Charts in the Terminal

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1pts0
periscope.io 12y ago

Using Self Joins To Calculate Retention, Churn, And Reactivation Metrics

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1pts0
www.periscope.io 12y ago

How To Optimize Lifetime Distinct Counts Using Window Functions

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1pts0
periscope.io 12y ago

Calculate Your Lifetime Metrics in Milliseconds

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1pts0
www.periscope.io 12y ago

Predicting Exponential Growth With SQL

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2pts0
imgur.com 12y ago

Distribution of Scores in Poland's HS Exit Exam

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1pts0
blog.ycombinator.com 12y ago

The YC Board of Overseers

hglaser
85pts41

Agreed. From firsthand experience, it's accurate, captures the feeling of being there at that time, and is more restrained than I would have been.

Once again, a moment of gratitude for the San Francisco Chronicle. In a time when local news is mostly gutted, I'm grateful to live in the rare mid-size city that has a robust local paper. Real investigative reporting, a serious local political beat, and features that win Pulitzer prizes. Plus a great sports section and restaurant critics!

It is incredible how far the overton window has moved on this issue.

When I graduated in 2007, it was common for tech companies to refuse to let their systems be used for war, and it was an ordinary thing when some of my graduating classmates refused to work at companies that did let their systems be used for war. Those refusals were on moral grounds.

Now Anthropic wants to have two narrow exceptions, on pragmatic and not moral grounds. To do so, they have to couch it in language clarifying that they would love to support war, actually, except for these two narrow exceptions. And their careful word choice suggests that they are either navigating or expect to navigate significant blowback for asking for two narrow exceptions.

My, the world has changed.

It was indeed originally conceived as 5 seasons, but the creator Tony Gilroy has consistently said shortening it was his decision because the production was too long and taxing:

"We were halfway through shooting season 1, coming through Covid, and the monumental size of the show, the effort, and everything else was just dawning on us. We realized that I didn't have enough calories to do it, and Diego's face couldn't take the timing, because it just takes too long to make it."

https://www.gamesradar.com/entertainment/star-wars-tv-shows/...

"By that point, the work that was required to make the show, at its minimum, was just dazzlingly blinding to look at. And Diego was like ‘Oh my god, we told them we’d do five years.’ Nobody, if we were gonna do it like this, you couldn’t physically do it. It was just impossible."

https://screenrant.com/andor-tony-gilroy-original-five-seaso...

Am I the only one who feels like this is obviated by Docker?

uv is a clear improvement over pip and venv, for sure.

But I do everything in dev containers these days. Very few things get to install on my laptop itself outside a container. I've gotten so used to this that tools that uninstall/install packages on my box on the fly give me the heebie-jeebies.

Appreciate the feedback!

Yeah, the hack you described for CIs is typical of "80% charting". We have a list of probably thousands of longtail visualization requests and we're way past the 80/20 point.

These days customers who want to go 100% use the Python/R editors and do their custom visualization there. So you do your SQL query like usual, but then pipe it to Python/R for the visualization. Have you tried that, and has it worked for you? Or do you prefer another model?

Periscope Data cofounder here. I wouldn't say we're "allergic" necessarily. ;) Like a lot of startups, we're very young and haven't gotten around to building out the website as much as we'd like to.

`jplitz and `ajones are right. As of now we support MySQL, Postgres, Amazon Redshift, Vertica, SQL Server, Oracle, MemSQL, Sybase, Exasol and Google BigQuery. We add more all the time.

I'll just say upfront that I'm the cofounder of Periscope (https://www.periscope.io/) which is specifically marketed at data scientists, so I have a horse in this race. :)

There are two kinds of charts: Charts designed to find information, and charts designed to sell information. The latter are often gorgeous and many-dimensional: Heatmaps, animated bubble charts, charts with time sliders, etc. And by all means, if selling the data is required, then sell it with the best tool for the job.

As for actually investigating the data, it's usually a lot of tables, lines and bars. They're simple to understand, and there's no cleverness in the visualization that might hide critical information.

To answer your questions, at Periscope I've seen:

1. A line graph of amplitude over time. You should see the frequency emerge clear as day. If you want to calculate frequency explicitly, you could overlay a second line with its own axis. Again, super simple, but gives you the answer directly.

2. I've seen a lot of fancy graph visualizations, but nothing that makes me happy. Depending on what you want to know about your graph, maybe a simple table with a structure like:

  [node name][node name][weight]
Or:
  [timestamp][node name][node name][weight]
A pivot table on top of this data, transoforming the second node column into the table's horizontal axis, can also be useful.

3. OK, obviously I think Periscope is a great choice here. Loads of data analysts use it to visualize time series data on many tens/hundreds of billions of data points.

That said, other good choices are: Excel, R/Stata/Matlab, gnuplot, Apache Pig. And for the data storage itself, IMO Amazon Redshift is unparalleled.

(Periscope co-founder here.)

There needs to be a route from the internet to your DB, yes. Sometimes this works because the DB is in the cloud, or sometimes a port or SSH tunnel is opened into a local network.

Periscope co-founder here.

We plan to treat the email addresses as people who might be interested in our product, and at some point we'll reach out to everyone who signed up and ask if they'd like to try it out.

If you know you don't want to try Periscope, but would like to read the eBook, by all means use the link above. ;)

Periscope (https://www.periscope.io/) is a data visualization tool that automatically and transparently syncs customer data into a huge multitenant data cache that runs queries ~ 150X faster than customers' own databases.

In the long run, it is a data tool that will eliminate the need for data warehouses.

It turns out the hard problem is not running the queries fast, but keeping the cache accurate and up-to-date. Our cache coherence service is probably the piece of code we're most proud of.

And, yes, we're hiring in SF. :) Reach out to me, harry@periscope.io

I get so much love from customers when I email them a few days ahead of the renewal and let them know that they're over quota, that I didn't want them to be surprised by the CC bill, and give them an opportunity to pare back down if they want to.

This is one of those areas where "being a good person" is a competitive advantage and drives lots of retention. Plus, after a couple months of this, they'll all upgrade anyway as paring down gets harder and more time-consuming.

We switched periscope.io from DNSimple to Amazon Route 53. DNSimple doesn't have an exporter so it took about an hour, including having one engineer review the other engineer's work.

Many customers were able to resolve the domain in the minutes immediately following the switch, and the rest seem to be trickling in.

Board Members 12 years ago

It's pretty common to solve these problems with multiple votes per person.

E.g. 2 founders + 1 investor is very common for Series A stage startups right now. Those with one founder tend to have two votes for the founder and one vote for the investor.