Merge pull request #55 from ddotta/ddotta/issue53

Add fugue + Polars benchmarking blog post

README.md

@@ -112,6 +112,7 @@ To see the latest entries in the list : <a href="https://www.trackawesomelist.co
 - [7 Easy Steps To Switch From Pandas to Lightning Fast Polars And Never Return](https://towardsdatascience.com/7-easy-steps-to-switch-from-pandas-to-lightning-fast-polars-and-never-return-b14c66fc85b9) - A cheat sheet blog post of the most common Pandas operations translated into Polars by [@BexTuychiev](https://github.com/BexTuychiev).
 - [Polars for initial data analysis, Polars for production](https://pythonspeed.com/articles/polars-exploratory-data-analysis-vs-production/) - A blog post that shows how to use Polars for initial data analysis and then effectively in production by [@itamarst](https://github.com/itamarst).
 - [DuckDB vs Polars vs Spark!](https://www.karnwong.me/posts/2023/04/duckdb-vs-polars-vs-spark/) - An article that performs a benchmark against duckdb/Polars/spark, with varying row count, with swap usage as another metric, in addition to runtime in seconds. Code used is available on Github [here](https://github.com/kahnwong/dataframe-frameworks-showdown).
+- [Benchmarking PySpark Pandas, Pandas UDFs, and Fugue Polars](https://medium.com/fugue-project/benchmarking-pyspark-pandas-pandas-udfs-and-fugue-polars-198c3109a226) - A blog post that compares the execution time of [fugue](https://github.com/fugue-project/fugue/) + Polars, Pandas UDFs and PySpark Pandas by [@kvnkho](https://github.com/kvnkho).
 
 ### Talks and videos