WarcDB
sqlite-parquet-vtable
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WarcDB | sqlite-parquet-vtable | |
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7 | 4 | |
383 | 261 | |
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7.2 | 10.0 | |
2 months ago | almost 3 years ago | |
Python | C++ | |
Apache License 2.0 | Apache License 2.0 |
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WarcDB
sqlite-parquet-vtable
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Universal Database
Sqlite3 has parquet extension that support parquet (https://github.com/cldellow/sqlite-parquet-vtable) as virtual table. I use sqlite3 a lot, for work and personally. It's really good, but I do have issue with large datasets, mainly due VACUUM operations. Insertion rate drops significantly when single table hits around 20M rows. Indexing is important for your query speed, but it'll impact your write speed.
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Show HN: Easily Convert WARC (Web Archive) into Parquet, Then Query with DuckDB
Well there's a virtual table extension to read parquet files in SQLite. I've not tried it myself. https://github.com/cldellow/sqlite-parquet-vtable
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One-liner for running queries against CSV files with SQLite
/? sqlite arrow
- "Comparing SQLite, DuckDB and Arrow with UN trade data" https://news.ycombinator.com/item?id=29010103 ; partial benchmarks of query time and RAM requirements [relative to data size] would be
- https://arrow.apache.org/blog/2022/02/16/introducing-arrow-f... :
> Motivation: While standards like JDBC and ODBC have served users well for decades, they fall short for databases and clients which wish to use Apache Arrow or columnar data in general. Row-based APIs like JDBC or PEP 249 require transposing data in this case, and for a database which is itself columnar, this means that data has to be transposed twice—once to present it in rows for the API, and once to get it back into columns for the consumer. Meanwhile, while APIs like ODBC do provide bulk access to result buffers, this data must still be copied into Arrow arrays for use with the broader Arrow ecosystem, as implemented by projects like Turbodbc. Flight SQL aims to get rid of these intermediate steps.
> - One cannot create a trigger on a virtual table.
Just posted about eBPF a few days ago; opcodes have costs that are or are not costed: https://news.ycombinator.com/item?id=31688180
> - One cannot create additional indices on a virtual table. (Virtual tables can have indices but that must be built into the virtual table implementation. Indices cannot be added separately using CREATE INDEX statements.)
It looks like e.g. sqlite-parquet-vtable implements shadow tables to memoize row group filters. How does JOIN performance vary amongst sqlite virtual table implementations?
> - One cannot run ALTER TABLE ... ADD COLUMN commands against a virtual table.
Are there URIs in the schema? Mustn't there thus be a meta-schema that does e.g. nested structs with portable types [with URIs], (and jsonschema, [and W3C SHACL])?
/? sqlite arrow virtual table
- sqlite-parquet-vtable reads parquet with arrow for SQLite virtual tables https://github.com/cldellow/sqlite-parquet-vtable :
$ sqlite/sqlite3
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Show HN: WarcDB: Web crawl data as SQLite databases
https://github.com/cldellow/sqlite-parquet-vtable
But for my use case virtual would be too complicated.
What are some alternatives?
ArchiveBox - 🗃 Open source self-hosted web archiving. Takes URLs/browser history/bookmarks/Pocket/Pinboard/etc., saves HTML, JS, PDFs, media, and more...
duckdb - DuckDB is an in-process SQL OLAP Database Management System
q - q - Run SQL directly on delimited files and multi-file sqlite databases
zsv - zsv+lib: world's fastest (simd) CSV parser, bare metal or wasm, with an extensible CLI for SQL querying, format conversion and more
WARCTools - A list of tools related to W(eb)ARC(hive)
sqlite_protobuf - A SQLite extension for extracting values from serialized Protobuf messages
visidata - A terminal spreadsheet multitool for discovering and arranging data
datasette - An open source multi-tool for exploring and publishing data
qhs - SQL queries on CSV and TSV files
tidy-viewer - 📺(tv) Tidy Viewer is a cross-platform CLI csv pretty printer that uses column styling to maximize viewer enjoyment.
csvq - SQL-like query language for csv
octosql - OctoSQL is a query tool that allows you to join, analyse and transform data from multiple databases and file formats using SQL.