elasticsearch-py VS phalanx

FD: I have a friend who works at Elastic, though he doesn't really colour my opinions of things.

> Firstly, dick moves like this: https://github.com/elastic/elasticsearch-py/pull/1623

I understand that this is unpopular, but you can make a very strong argument that it's to prevent weird errors in the future. I'm also guilty of littering my code with Asserts to ensure the universe is working fine.

The alternative is to allow it to work and then you end up with weird issues like when you connect mysql client to mariadb server (and vice-versa): https://stackoverflow.com/questions/50169576/mysql-8-0-11-er...

> Secondly, I don't buy the argument from Elastic any more. Yes, the ethical thing to do when you're making money from someone's work is at least contribute back. At the same time though, they're making money from packaging it up and selling it _as a service_. That "as a service" part is where they're making the bucks.

That's just an opinion, yes they have a service, and yes it competes with Amazon. Is it cool for Amazon to take a body of work and sell it without supporting it? Are amazon actually supporting it? Is it the same as Elastic using Lucene? (not really because Elastic submits a the majority of fixes to Lucene, but, you get it).

it's kinda gray, I'm sure Amazon thinks they're the good guy, but it's hard for me to look at Elastic as the bad guy in all this.

Oh man, https://github.com/elastic/elasticsearch-py/issues/1734 is a disappointing read. I know ES wants to save their business, but alienating users isn't exactly the path to success.

Somewhat related, this guy: https://github.com/mosuka/ seems to be very passionate about search service.

He built two distributed search services:

- https://github.com/mosuka/phalanx, written in Go.

- https://github.com/mosuka/bayard, written in Rust.

Don’t forget about Phalanx if you like Bleve/Bluge.

I've never worked on a project that encompasses as many computer science algorithms as a search engine. There are a lot of topics you can lookup in "Information Storage and Retrieval":

- Tries (patricia, radix, etc...)

- Trees (b-trees, b+trees, merkle trees, log-structured merge-tree, etc..)

- Consensus (raft, paxos, etc..)

- Block storage (disk block size optimizations, mmap files, delta storage, etc..)

- Probabilistic filters (hyperloloog, bloom filters, etc...)

- Binary Search (sstables, sorted inverted indexes, roaring bitmaps)

- Ranking (pagerank, tf/idf, bm25, etc...)

- NLP (stemming, POS tagging, subject identification, sentiment analysis etc...)

- HTML (document parsing/lexing)

- Images (exif extraction, removal, resizing / proxying, etc...)

- Queues (SQS, NATS, Apollo, etc...)

- Clustering (k-means, density, hierarchical, gaussian distributions, etc...)

- Rate limiting (leaky bucket, windowed, etc...)

- Compression

- Applied linear algebra

- Text processing (unicode-normalization, slugify, sanitation, lossless and lossy hashing like metaphone and document fingerprinting)

- etc...

I'm sure there is plenty more I've missed. There are lots of generic structures involved like hashes, linked-lists, skip-lists, heaps and priority queues and this is just to get 2000's level basic tech.

- https://github.com/quickwit-oss/tantivy

- https://github.com/valeriansaliou/sonic

- https://github.com/mosuka/phalanx

- https://github.com/meilisearch/MeiliSearch

- https://github.com/blevesearch/bleve

- https://github.com/thomasjungblut/go-sstables

A lot of people new to this space mistakenly think you can just throw elastic search or postgres fulltext search in front of terabytes of records and have something decent. The problem is that search with good rankings often requires custom storage so calculations can be sharded among multiple nodes and you can do layered ranking without passing huge blobs of results between systems.

For those curious, I'm on my 3rd search engine as I keep discovering new methods of compactly and efficiently processing and querying results.

There isn't a one-size-fits all approach, but I've never worked on a project that encompasses as many computer science algorithms as a search engine.

- Tries (patricia, radix, etc...)

- Trees (b-trees, b+trees, merkle trees, log-structured merge-tree, etc..)

- Consensus (raft, paxos, etc..)

- Block storage (disk block size optimizations, mmap files, delta storage, etc..)

- Probabilistic filters (hyperloloog, bloom filters, etc...)

- Binary Search (sstables, sorted inverted indexes)

- Ranking (pagerank, tf/idf, bm25, etc...)

- NLP (stemming, POS tagging, subject identification, etc...)

- HTML (document parsing/lexing)

- Images (exif extraction, removal, resizing / proxying, etc...)

- Queues (SQS, NATS, Apollo, etc...)

- Clustering (k-means, density, hierarchical, gaussian distributions, etc...)

- Rate limiting (leaky bucket, windowed, etc...)

- text processing (unicode-normalization, slugify, sanitation, lossless and lossy hashing like metaphone and document fingerprinting)

- etc...

I'm sure there is plenty more I've missed. There are lots of generic structures involved like hashes, linked-lists, skip-lists, heaps and priority queues and this is just to get 2000's level basic tech.

- https://github.com/quickwit-oss/tantivy

- https://github.com/valeriansaliou/sonic

- https://github.com/mosuka/phalanx

- https://github.com/meilisearch/MeiliSearch

- https://github.com/blevesearch/bleve

A lot of people new to this space mistakenly think you can just throw elastic search or postgres fulltext search in front of terabytes of records and have something decent. That might work for something small like a curated collection of a few hundred sites.

Is there a tool that automatically forwards every URL + HTML of the page you visit to a webhook so you could write an endpoint that would index everything?

If not, I would love to see this add a "forward to webhook" option. I would be happy to write up a real backend that parsed the content and indexed it.

Actually, there are lots of OS projects for this: https://github.com/quickwit-oss/tantivy, https://github.com/valeriansaliou/sonic, https://github.com/mosuka/phalanx, https://github.com/meilisearch/MeiliSearch, etc...