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.gitmodules

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[submodule "redis/redis"]
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path = redis/redis
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url = https://github.com/redis/redis.git
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[submodule "index-type-analysis"]
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path = index-type-analysis
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url = https://github.com/abigalekim/index-type-analysis.git

README.md

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# Extension Analyzer
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This repository contains the code used to analyze the extension ecosystems of PostgreSQL, MySQL/MariaDB, SQLite, Redis, and DuckDB. The code for each of these systems and the instructions on how to run the analysis scripts can be found in their respective directories. Additionally, we have included our the CSVs
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used to run our plot scripts and our matplotlib scripts in these directories as well.
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This repository contains the code used to analyze the extension ecosystems of PostgreSQL, MySQL/MariaDB, SQLite, Redis, and DuckDB. The code for each of these systems and the instructions on how to run the analysis scripts can be found in their respective directories, except the PostgreSQL index-type analysis, which is included as a submodule.
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Additionally, we have included our the CSVs used to run our plot scripts and the plot scripts themselves in this repository.
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Feel free to submit PRs and offer feedback, we would love to hear it!
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# Specifications
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- This code runs on a machine with Ubuntu 22.04. Compatibility with other OSes is not supported.
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- All Python scripts should work with Python version 3.12.
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- All Python scripts should work with Python version 3.12.
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This repository includes submodules. To clone it, you need to use the `--recurse-submodules` option.

duckdb/README.md

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figure out gsheets
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# duckext-analyzer
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Python scripts for extension testing analysis for DuckDB.
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sudo apt-get install libgfortran5
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# Dependencies
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Here are the Ubuntu packages required to run our scripts:
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- libgfortran5
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Additionally, you need to install the DuckDB Python library with `pip`.
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# Scripts
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There are two scripts that can be run. First, `source-code-analysis.py` takes no arguments and outputs a CSV file containing source code statistics on DuckDB extensions. This script can be run with default Python
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(`python3 source-code-analysis.py`).
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`compatibility_analysis.py` is a draft of a script for DuckDB extension compatibility testing. It currently
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does not work. We have included it since it still may be useful reading material.
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The script that works is `compatibility_v2.py`. It can be run with default Python (`python3 compatibility_v2.py`). The output of this script is a CSV file with the compatibility results.

index-type-analysis

Submodule index-type-analysis added at 369e1ac

mariadb/README.md

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# dependencies
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- mariadb python library
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# mariaext-analyzer
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Python scripts for extension testing analysis for MariaDB. Since MySQL and MariaDB's extensibility ecosystems are remarkably similar, we decided to test them as one unit.
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# Dependencies
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Here are the Ubuntu packages required to run our scripts:
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- mariadb-plugin-connect
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- mariadb-plugin-cracklib-password-check
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- mariadb-plugin-gssapi-server
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- mariadb-plugin-oqgraph
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- mariadb-plugin-s3
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I could support an install list or something but instead I just killed the "so_name": "auth_gssapi" from gssapi.json :) academic code rocks
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Storage engines I did not test because it was 2am and they required extra set up and I wanted preliminary results
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- federated
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- federatedx
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- s3
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- oqgraph
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- sphinx
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- mrg_myisam
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- spider (distributed)
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Additionally, you need to install the MariaDB Python library with `pip`.
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no source: memory, s3
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# Scripts
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There are two scripts that can be run. First, `source-code-analysis.py` takes no arguments and outputs a CSV file containing source code statistics on MariaDB extensions. This script can be run with default Python
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(`python3 source-code-analysis.py`).
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things that i don't know where source is:
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- password_reuse_check
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- metadata_lock_info
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- auth_pipe
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In order to run the compatibility script, you will need to set up a MariaDB instance on Ubuntu. Then, you
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will type your username and password into the global variables on lines 12-13 of `compatibility-analysis.py`.
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This script runs compatibility testing on all pairs of extensions. The output of this script is a CSV file with the compatibility results. It can be run with default Python (`python3 compatibility-analysis.py`).

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