Imagination applies also to how we organize society and “rights” we hold over nature and natural resources. Reforming outdated water law is the true fix no pipeline needed.
138 MW is also nameplate capacity multiply that by effective utilization rate for ex solar (~20%) and it’s meaningless compared to the scale of the project.
Oil products are a fractional distillate of a barrel of oil. How are you going to pave the roads all these EV’s are going to drive on, or produce the plastic they consume (EV’s require ~40-50% more plastic)? If gasoline demands softens it doesn’t necessarily mean that other oil product demand will decrease at similar rates. Oil production declines over time so you need constant development even in a declining consumption scenario, and I think we are heading into a world where domestic supply will command a premium.
Most every (analytic) RDMS database system can model sparse arrays. A sparse array is modeled by defining a clustered index on the table "array" dimensions and defining a uniqueness constraint on that clustered index. This works well with columnar storage because the data needs to have (and assumed to naturally have) a total sort order on the dimensions. Ex. Vertica, Clickhouse, Bigquery... all allow you to do this. TileDB allows for efficient range queries through an R-Tree like index on the specified dimensions.
Most real world data though is messy and defining a uniqueness constraint upfront (upon ingestion) is often limiting, so for practical use cases this gets relaxed to a multi-set rather than sparse array model for storage, and uniqueness imposed in some way after the fact (if required).
Unfortunately "its just geography" is kind of one of the talking points for not really addressing the problem. Although true, concerted reductions in pollution have happened when there was political will to make it happen (mostly through the federal gov. / EPA clean air regulations).
Ogden and Provo are some of the worst offenders for per household air pollution emissions. Like many western cities they have longish commutes (everywhere) in large cars (trucks / suv's) with a high number of cars / household and almost non-functional public transport system. For the Salt Lake Metro area, per capita carbon emissions doubled between 1980 and 2015 because of increasing sprawl. Air regulations here are spotty for personal vehicles and I'm guessing almost non-existent for commercial vehicles. Oh and the state governments solution to this is to push a publicly subsidized "inland port" that will bring increased truck and rail traffic to the valley. The leaders of these tech companies are starting to point out that terrible air pollution for parts of the year is hurting recruitment so it seems like as the money flows into this sector maybe there will be political will on the state and local side to address some of these issues.
There are a lot of issues though with S3, latency, poor performance for small reads / writes, timeouts, api rate limits, api costs, and consistency issues poorly understood by third party developers.
A "thick-client" also doesn't perform well unless that client is located on a node in the same region. I think as with everything it works well in some cases and not well in others.
This is a good description, except that TileDB (the open source client) is not transactional but eventually consistent at least for S3 and other object stores.
I like your point about consuming S3 cleverly, it's often difficult to get good out of the box performance from S3 so abstracting that to the degree possible is good for end-users. The cloud vendors though are always one or two steps ahead of companies that build upon their services. AWS Redshift for instance already can pre-index objects stored on S3 to accelerate queries at the storage layer. It's difficult as a third party vendor to compete with that.
Underrated it is not, just search for Cottonwood Canyon traffic jams to see what skiing really is like here when the snow flies. 30 minutes no traffic, can easily be 3+ hours now.