sqlite_protobuf
q
sqlite_protobuf | q | |
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2 | 46 | |
80 | 10,126 | |
- | - | |
0.0 | 2.1 | |
over 1 year ago | 11 days ago | |
C++ | Python | |
MIT License | GNU General Public License v3.0 only |
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sqlite_protobuf
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One-liner for running queries against CSV files with SQLite
SQLite's virtual table API (https://www.sqlite.org/vtab.html) makes it possible to access other data structures through the query engine. You don't need to know much if anything about how the database engine executes queries, you only need to implement the callbacks it needs to do its job. A few years ago I wrote an extension to let me search through serialized Protobufs which were stored as blobs in a regular database.
https://github.com/rgov/sqlite_protobuf
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SQLite Plus: all the missing SQLite functions
Some time ago I joined a project that was recording logs in Protobuf format. I demonstrated that we could log the serialized Protobuf structures to a SQLite database and then use a plugin to query across the message fields: https://github.com/rgov/sqlite_protobuf
Learning how to use the SQLite extension API was a little mind-expanding but it worked like a charm.
q
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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
- Segítség kérés Excel automatizáláshoz
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Show HN: ClickHouse-local – a small tool for serverless data analytics
I think they're talking about https://github.com/harelba/q, which is not very fast.
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sqly - execute SQL against CSV / JSON with shell
Apparently, there were many who thought the same thing; Tools to execute SQL against CSV were trdsql, q, csvq, TextQL. They were highly functional, hoewver, had many options and no input completion. I found it just a little difficult to use.
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Q – Run SQL Directly on CSV or TSV Files
Hi, author of q here.
Regarding the error you got, q currently does not autodetect headers, so you'd need to add -H as a flag in order to use the "country" column name. You're absolutely correct on failing-fast here - It's a bug which i'll fix.
In general regarding speed - q supports automatic caching of the CSV files (through the "-C readwrite" flag). Once it's activated, it will write the data into another file (with a .qsql extension), and will use it automatically in further queries in order to speed things considerably.
Effectively, the .qsql files are regular sqlite3 files (with some metadata), and q can be used to query them directly (or any regular sqlite3 file), including the ability to seamlessly join between multiple sqlite3 files.
http://harelba.github.io/q/#auto-caching-examples
- PostgreSQL alternative for Large amounts of data
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q VS trdsql - a user suggested alternative
2 projects | 25 Jun 2022
- One-liner for running queries against CSV files with SQLite
What are some alternatives?
dflat - Structured Data Store for Mobile
textql - Execute SQL against structured text like CSV or TSV
sqlite_ora_functions
csvq - SQL-like query language for csv
sqlite-plus - The ultimate set of SQLite extensions
octosql - OctoSQL is a query tool that allows you to join, analyse and transform data from multiple databases and file formats using SQL.
sqlite-parquet-vtable - A SQLite vtable extension to read Parquet files
InquirerPy - :snake: Python port of Inquirer.js (A collection of common interactive command-line user interfaces)
visidata - A terminal spreadsheet multitool for discovering and arranging data
xsv - A fast CSV command line toolkit written in Rust.
json2csv - Convert json to csv with column titles
ledger - Double-entry accounting system with a command-line reporting interface