json-buffet
xsv
json-buffet | xsv | |
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2 | 64 | |
0 | 10,089 | |
- | - | |
3.0 | 0.0 | |
about 1 year ago | 2 months ago | |
C++ | Rust | |
MIT License | The Unlicense |
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json-buffet
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Analyzing multi-gigabyte JSON files locally
And here's the code: https://github.com/multiversal-ventures/json-buffet
The API isn't the best. I'd have preferred an iterator based solution as opposed to this callback based one. But we worked with what rapidjson gave us for the proof of concept.
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Show HN: Up to 100x Faster FastAPI with simdjson and io_uring on Linux 5.19
Ha! Thanks to you, Today I found out how big those uncompressed JSON files really are (the data wasn't accessible to me, so i shared the tool with my colleague and he was the one who ran the queries on his laptop): https://www.dolthub.com/blog/2022-09-02-a-trillion-prices/ .
And yep, it was more or less they way you did with ijson. I found ijson just a day after I finished the prototype. Rapidjson would probably be faster. Especially after enabling SIMD. But the indexing was a one time thing.
We have open sourced the codebase. Here's the link: https://github.com/multiversal-ventures/json-buffet . Since this was a quick and dirty prototype, comments were sparse. I have updated the Readme, and added a sample json-fetcher. Hope this is more useful for you.
Another unwritten TODO was to nudge the data providers towards a more streaming friendly compression formats - and then just create an index to fetch the data directly from their compressed archives. That would have saved everyone a LOT of $$$.
xsv
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Show HN: TextQuery – Query and Visualize Your CSV Data in Minutes
I realize it's not really that comparable since these tools don't support SQL, but a more fully functioned CLI tool is - https://github.com/BurntSushi/xsv
They are both fairly good
- Qsv: Efficient CSV CLI Toolkit
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Joining CSV Data Without SQL: An IP Geolocation Use Case
I have done some similar, simpler data wrangling with xsv (https://github.com/BurntSushi/xsv) and jq. It could process my 800M rows in a couple of minutes (plus the time to read it out from the database =)
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Qsv: CSVs sliced, diced and analyzed (fork of xsv)
xsv, which seems to be why qsv was created.
[1] https://github.com/BurntSushi/xsv/issues/267
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I wrote this iCalendar (.ics) command-line utility to turn common calendar exports into more broadly compatible CSV files.
CSV utilities (still haven't pick a favorite one...): https://github.com/harelba/q https://github.com/BurntSushi/xsv https://github.com/wireservice/csvkit https://github.com/johnkerl/miller
- Icsp – Command-line iCalendar (.ics) to CSV parser
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ripgrep is faster than {grep, ag, git grep, ucg, pt, sift}
$ git remote -v origin [email protected]:rust-lang/rust (fetch) origin [email protected]:rust-lang/rust (push) $ git rev-parse HEAD 3b0d4813ab461ec81eab8980bb884691c97c5a35 $ time grep -ri burntsushi ./ ./src/tools/cargotest/main.rs: repo: "https://github.com/BurntSushi/ripgrep", ./src/tools/cargotest/main.rs: repo: "https://github.com/BurntSushi/xsv", grep: ./target/debug/incremental/cargotest-2dvu4f2km9e91/s-gactj3ma2j-1b10l4z-2l60ur55ixe6n/query-cache.bin: binary file matches grep: ./target/debug/incremental/cargotest-38cpmhhbdgdyq/s-gactj3luwq-1o12vgp-t61hd8qdyp7t/query-cache.bin: binary file matches grep: ./target/debug/incremental/cargotest-17632op6djxne/s-gawuq5468i-1h69nfw-4gm0s8yhhiun/query-cache.bin: binary file matches grep: ./target/debug/incremental/cargotest-2trm4kt5yom3r/s-gawuq53qqg-bjiezj-lo0gha8ign8w/query-cache.bin: binary file matches grep: ./target/debug/deps/libregex_automata-c74a6d9fd0abd77b.rmeta: binary file matches grep: ./target/debug/deps/libsame_file-a0e0363a2985455d.rlib: binary file matches grep: ./target/debug/deps/libsame_file-a0e0363a2985455d.rmeta: binary file matches grep: ./target/debug/deps/libsame_file-7251d8d3586a319b.rmeta: binary file matches grep: ./build/x86_64-unknown-linux-gnu/stage0-sysroot/lib/rustlib/x86_64-unknown-linux-gnu/lib/libaho_corasick-999a08e2b700420d.rlib: binary file matches grep: ./build/x86_64-unknown-linux-gnu/stage0-sysroot/lib/rustlib/x86_64-unknown-linux-gnu/lib/libregex_automata-0d168be5d25b3ac5.rlib: binary file matches grep: ./build/x86_64-unknown-linux-gnu/stage0-tools/x86_64-unknown-linux-gnu/release/deps/libregex_automata-7d6bec0156f15da1.rlib: binary file matches grep: ./build/x86_64-unknown-linux-gnu/stage0-tools/x86_64-unknown-linux-gnu/release/deps/libregex_automata-7d6bec0156f15da1.rmeta: binary file matches grep: ./build/x86_64-unknown-linux-gnu/stage0-tools/x86_64-unknown-linux-gnu/release/deps/libaho_corasick-07dee4514b87d99b.rmeta: binary file matches grep: ./build/x86_64-unknown-linux-gnu/stage0-tools/x86_64-unknown-linux-gnu/release/deps/libaho_corasick-07dee4514b87d99b.rlib: binary file matches grep: ./build/x86_64-unknown-linux-gnu/stage0-rustc/x86_64-unknown-linux-gnu/release/deps/libaho_corasick-999a08e2b700420d.rlib: binary file matches grep: ./build/x86_64-unknown-linux-gnu/stage0-rustc/x86_64-unknown-linux-gnu/release/deps/libaho_corasick-999a08e2b700420d.rmeta: binary file matches grep: ./build/x86_64-unknown-linux-gnu/stage0-rustc/x86_64-unknown-linux-gnu/release/deps/libregex_automata-0d168be5d25b3ac5.rlib: binary file matches grep: ./build/x86_64-unknown-linux-gnu/stage0-rustc/x86_64-unknown-linux-gnu/release/deps/libregex_automata-0d168be5d25b3ac5.rmeta: binary file matches grep: ./build/bootstrap/debug/deps/libaho_corasick-992e1ba08ef83436.rmeta: binary file matches grep: ./build/bootstrap/debug/deps/libignore-54d41239d2761852.rmeta: binary file matches grep: ./build/bootstrap/debug/deps/libsame_file-9a5e3ddd89cfe599.rlib: binary file matches grep: ./build/bootstrap/debug/deps/libregex_automata-8e700951c9869a66.rlib: binary file matches grep: ./build/bootstrap/debug/deps/libignore-54d41239d2761852.rlib: binary file matches grep: ./build/bootstrap/debug/deps/libaho_corasick-992e1ba08ef83436.rlib: binary file matches grep: ./build/bootstrap/debug/deps/libregex_automata-8e700951c9869a66.rmeta: binary file matches grep: ./build/bootstrap/debug/deps/libsame_file-9a5e3ddd89cfe599.rmeta: binary file matches real 16.683 user 15.793 sys 0.878 maxmem 8 MB faults 0
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Any Linux admins willing to try Pygrep?
Unrelated, are you the same burntsushi that wrote xsv?
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Analyzing multi-gigabyte JSON files locally
If it could be tabular in nature, maybe convert to sqlite3 so you can make use of indexing, or CSV to make use of high-performance tools like xsv or zsv (the latter of which I'm an author).
https://github.com/BurntSushi/xsv
https://github.com/liquidaty/zsv/blob/main/docs/csv_json_sql...
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What monitoring tool do you use or recommend?
Oh and there's rad cli shit out there for CSV files too, like xsv
What are some alternatives?
japronto - Screaming-fast Python 3.5+ HTTP toolkit integrated with pipelining HTTP server based on uvloop and picohttpparser.
csvtk - A cross-platform, efficient and practical CSV/TSV toolkit in Golang
semi_index - Implementation of the JSON semi-index described in the paper "Semi-Indexing Semi-Structured Data in Tiny Space"
miller - Miller is like awk, sed, cut, join, and sort for name-indexed data such as CSV, TSV, and tabular JSON
is2 - embedded RESTy http(s) server library from Edgio
ripgrep - ripgrep recursively searches directories for a regex pattern while respecting your gitignore
reddit_mining
Servo - Servo, the embeddable, independent, memory-safe, modular, parallel web rendering engine
json_benchmark - Python JSON benchmarking and "correctness".
Fractalide - Reusable Reproducible Composable Software
Apache Arrow - Apache Arrow is a multi-language toolbox for accelerated data interchange and in-memory processing
svgcleaner - svgcleaner could help you to clean up your SVG files from the unnecessary data.