now
go-sstables
Our great sponsors
now | go-sstables | |
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8 | 4 | |
588 | 253 | |
- | - | |
9.7 | 4.0 | |
12 months ago | about 2 months ago | |
Python | Go | |
Apache License 2.0 | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
now
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A Guide to Using OpenTelemetry in Jina for Monitoring and Tracing Applications
💡In this post we’re just building out a backend, and not touching on a frontend. To build your own low-code backend+frontend neural search solution, check out Jina NOW.
- I want to dive into how to make search engines
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Best stack/service for user generated content site.
Check out Jina NOW for an end-to-end text-to-image search
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Sophisticated neural search system using < 5 lines of code.
try it out for yourself now: https://examples.jina.ai/now/. Or if you'd prefer to go through the repo and see the magic behind the scenes: https://github.com/jina-ai/now
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No code solution for neural search. Build a search application using < 5 lines of code
Here's the link to try it out for yourself: https://now.jina.ai
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Deep-learning powered image search in just one line code
Github Repo
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Built a nocode solution for text to image search engine. Checkout live demo
And here's the open-source code for developer friends here in the community - https://github.com/jina-ai/now
- Show HN: Jina NOW – lowcode solution for multimodal neural search
go-sstables
- GitHub - thomasjungblut/go-sstables: Go library for protobuf compatible sstables, a skiplist, a recordio format and other database building blocks like a write-ahead log. Ships now with an embedded key-value store.
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I want to dive into how to make search engines
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.
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What's the big deal about key-value databases like FoundationDB ands RocksDB?
I highly recommend people comfortable with Go checkout the building blocks at https://github.com/thomasjungblut/go-sstables
This codebase shows how SSTables, WAL, memtables, skiplists, segment files, and plenty of other storage engine components work in a digestible way. Includes a demo database showing how it all comes together.
- Understanding LSM Trees: What Powers Write-Heavy Databases
What are some alternatives?
search-engines - Reviewing alternative search engines
markov - Materials for book: "Markov Chains for programmers"
phalanx - Phalanx is a cloud-native distributed search engine that provides endpoints through gRPC and traditional RESTful API.
grub-2.0 - Grub is an AI powered Web crawler.
pytai - Kaitai Struct: Visualizer and Hex Viewer GUI in Python
finetuner - :dart: Task-oriented embedding tuning for BERT, CLIP, etc.
hse - HSE: Heterogeneous-memory storage engine
docarray - Represent, send, store and search multimodal data
mitta-screenshot - Mitta's Chrome extension for saving the current view of a website.
MeiliSearch - A lightning-fast search API that fits effortlessly into your apps, websites, and workflow
search-lib - A library of classes which can be used to build a search engine.