arjunnarayan
Joined 17 years ago
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Mar 10
Recent submissions
Comment · 1 year ago
1/4. The max number of recipients of any prize is 3, but it can be split into a half, and then one of those halves into two further halves, for a 1/2 + 1/4 + 1/4 split. (It can also be split equally into 1/3 + 1/3 + 1/3).
Comment · 3 years ago
[disclosure, former cockroachdb engineer]
you can get expected "single shard" performance in CockroachDB by manually splitting the shards (called "ranges" in CockroachDB) along the lines of the expected single shard queries (what you call a "properly shared database"). This is easy to do with a single SQL command. (This is what we do today; we use CockroachDB for strongly consistent metadata).
The difference between CockroachDB and a manually sharded database is that when you _do_ have to perform some cross-shard transactions (which you inevitably have to do at some point), in CockroachDB you can execute them (with a reasonable performance penalty) with strong consistency and 2PC between the shards, whereas in your manually sharded database... good luck! Hope you implement 2PC correctly.
Comment · 3 years ago
This disconnect is called the "Tullock Paradox" in Economics, after Gordon Tullock who first asked it in "The Purchase of Politicians" (1972) [couldn't find an online link].
You'll find a more recent discussion in "Why is There so Little Money in U.S. Politics?" (2003). [1]
[1] https://www.aeaweb.org/articles?id=10.1257/08953300332116497...
Comment · 5 years ago
Materialize | Engineering, Product, Marketing | NYC HQ + North America Remote + Europe Remote | https://materialize.com/careers
Materialize is a streaming database for real-time applications. Materialize lets you ask questions about your data, and then get low-latency, correct answers, which are kept incrementally updated as the underlying data changes. Materialize is built on Timely Dataflow, a low-latency cyclic dataflow computational model, first introduced in the paper "Naiad: a timely dataflow system".
Materialize is co-founded by Frank McSherry, the primary author of Timely Dataflow (http://timelydataflow.com) and Differential Dataflow (http://differentialdataflow.com), the two open source projects that power Materialize. Materialize itself is source-available and entirely written in Rust: https://github.com/MaterializeInc/materialize
Materialize is a team of over thirty, primarily based in New York City but also open to remote positions in the EU and NA. We are hiring in all engineering positions (eng. manager, engineers from new grad to principal) as well as several non-engineering positions - for the full list, see https://materialize.com/careers
We are a team of significantly experienced individuals in databases and distributed systems, and looking to add more folks with that interest and/or experience to our team. Materialize recently raised a $32m Series B led by Kleiner Perkins, which was lovingly hacker newsed: https://news.ycombinator.com/item?id=25277511
Comment · 5 years ago
A high speed collision in low orbit can change a circular low orbit into an elliptical eccentric orbit that intersects a higher circular orbit, but unless there is an additional accelerating event at that higher altitude, it cannot recircularize its orbit at that higher altitude.
There are thus two takeaways:
1. By definition, this means that part of the orbit will always be at low altitude, regardless of the collision dynamics. So this means that it will continue to decay over time, albeit perhaps at a slower rate (decay being proportional to the time spent at lower altitude).
2. While that eccentric orbit will intersect with a higher circular orbital plane, it does so in a predictable fashion that can be routed around. The higher orbits are also much sparser, so the chance of this intersecting with a satellite that is already present is very, very small.
Comment · 5 years ago
Materialize | Engineering, Product, Marketing | NYC HQ + North America Remote + Europe Remote | https://materialize.com/careers
Materialize is a streaming database for real-time applications. Materialize lets you ask questions about your data, and then get low-latency, correct answers, which are kept incrementally updated as the underlying data changes. Materialize is built on Timely Dataflow, a low-latency cyclic dataflow computational model, first introduced in the paper "Naiad: a timely dataflow system".
Materialize is co-founded by Frank McSherry, the primary author of Timely Dataflow (http://timelydataflow.com) and Differential Dataflow (http://differentialdataflow.com), the two open source projects that power Materialize. Materialize itself is source-available and entirely written in Rust: https://github.com/MaterializeInc/materialize
Materialize is a team of over thirty, primarily based in New York City but also open to remote positions in the EU and NA. We are hiring in all engineering positions (eng. manager, engineers from new grad to principal) as well as several non-engineering positions - for the full list, see https://materialize.com/careers
We are a team of significantly experienced individuals in databases and distributed systems, and looking to add more folks with that interest and/or experience to our team. Materialize recently raised a $32m Series B led by Kleiner Perkins, which was lovingly hacker newsed: https://news.ycombinator.com/item?id=25277511
My interests are databases, operating systems, distributed systems, networks, new hardware, and security.
[ my public key: https://keybase.io/arjun; my proof: https://keybase.io/arjun/sigs/_gK6yYpV47uu1y9XC9DoM5AV3q8HBud_1xfF-71LJeY ]