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duckdb

Added functionality to support fetching entire column as vector for supporting RadixSpline Index as an extension in DuckDB

https://github.com/jishrup/duckdb

Science Score: 26.0%

This score indicates how likely this project is to be science-related based on various indicators:

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    CITATION.cff file
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    Found codemeta.json file
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    Scientific vocabulary similarity
    Low similarity (17.0%) to scientific vocabulary
Last synced: 10 months ago · JSON representation

Repository

Added functionality to support fetching entire column as vector for supporting RadixSpline Index as an extension in DuckDB

Basic Info
  • Host: GitHub
  • Owner: jishrup
  • License: mit
  • Language: C++
  • Default Branch: main
  • Size: 303 MB
Statistics
  • Stars: 0
  • Watchers: 1
  • Forks: 0
  • Open Issues: 0
  • Releases: 0
Created over 1 year ago · Last pushed over 1 year ago
Metadata Files
Readme Contributing License Code of conduct Citation

README.md

DuckDB logo


Github Actions Badge discord Latest Release

DuckDB

DuckDB is a high-performance analytical database system. It is designed to be fast, reliable, portable, and easy to use. DuckDB provides a rich SQL dialect, with support far beyond basic SQL. DuckDB supports arbitrary and nested correlated subqueries, window functions, collations, complex types (arrays, structs, maps), and several extensions designed to make SQL easier to use.

DuckDB is available as a standalone CLI application and has clients for Python, R, Java, Wasm, etc., with deep integrations with packages such as pandas and dplyr.

For more information on using DuckDB, please refer to the DuckDB documentation.

Installation

If you want to install DuckDB, please see our installation page for instructions.

Data Import

For CSV files and Parquet files, data import is as simple as referencing the file in the FROM clause:

sql SELECT * FROM 'myfile.csv'; SELECT * FROM 'myfile.parquet';

Refer to our Data Import section for more information.

SQL Reference

The documentation contains a SQL introduction and reference.

Development

For development, DuckDB requires CMake, Python3 and a C++11 compliant compiler. Run make in the root directory to compile the sources. For development, use make debug to build a non-optimized debug version. You should run make unit and make allunit to verify that your version works properly after making changes. To test performance, you can run BUILD_BENCHMARK=1 BUILD_TPCH=1 make and then perform several standard benchmarks from the root directory by executing ./build/release/benchmark/benchmark_runner. The details of benchmarks are in our Benchmark Guide.

Please also refer to our Build Guide and Contribution Guide.

Support

See the Support Options page.

Owner

  • Name: Jishnu Suresh Kumar Meena Kumari
  • Login: jishrup
  • Kind: user

System Development is the key to everything

GitHub Events

Total
  • Push event: 1
  • Create event: 2
Last Year
  • Push event: 1
  • Create event: 2

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