storyinmemo

What model monitor is this?

PM 2.5 seems to be like radiation: the more you get, the more you're likely to be affected, even at lowish levels.

https://qz.com/1166010/air-pollution-even-at-levels-that-mee...

This project would take 2-3 days to filter the volume of air in a 1,000 sq foot apartment... which is to say it would do nothing of significance. To be effective, you want to change the air something closer to once every 30 minutes.

Meanwhile, four years ago at Facebook :)

http://rachelbythebay.com/w/2016/02/21/malloc/

The dictionary is only useful in independently compressing lots of small data chunks. Tiny files, rows in a database, VCS commits kind of things where each is independently compressed and extricable. If you tarball them so you're compressing ~100kb+, there's really no benefit to the dictionary step.

My suggestion for learning: re-write this using futures. Here's a quick example of using similar parallelism to search structured json in gzip'd files: https://github.com/autocracy/snippets/blob/master/search_clo...

Can you elaborate on what it is that slows down your app performance? Is it bottle-necking on writing to the database? Does the database have read activity? Does the application slow down when there is read activity?

With some basic assumptions on my part including that you can have a delay in writing data to the database (since it's archival and analysis), but you don't want the application to be delayed, putting a fast queue like Kafka or RabbitMQ in place could help. It'll buffer when the database is under load, isolating your application from that.

Offline analysis might also skip the database entirely: columnar data formats (parquet) or log structured merge / sorted string tables (rocksdb) could work very well for archival or offline analysis in MR type environments.

The paper on the algorithm is here: http://www.vldb.org/pvldb/vol8/p1816-teller.pdf

Somebody implemented the algorithm in go based on the paper here: https://github.com/dgryski/go-tsz

A short answer that may work for your question: the bits that are set in RAM are xor values relative to previous values. To provide an answer as to what the value is, a series of read|xor operations are performed.

Yes, they move the entire cohort together.

They bought Nimbula back in 2013 as well: https://en.wikipedia.org/wiki/Nimbula

The naming was always confusing because both companies were based within a mile of each other, never mind the product overlap.

Any employee can grab a crappy phone. Some of the Messenger crowd have 20+ phones on their desks.

Most don't stay with them for too long, though. It does really take an extra push to advance this. I had a Galaxy Young for two days after I cracked my normal phone's screen. It was kind of hellish.