README.rmd

---
title: "Table summarizer for large tables in databases"
author: "Henry Luan"
output: rmarkdown::github_document
vignette: >
  %\VignetteIndexEntry{Vignette Title}
  %\VignetteEngine{knitr::rmarkdown}
  %\VignetteEncoding{UTF-8}
---

```{r setup, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)
```



## About this web app
This RShiny app summarizes large tables stored in database servers. It allows large, high-dimensional datasets to be summarized in R (size of local RAM <<< size of tables) in a way that R can't handle with your computer's local RAM. 

If you want to understand the core functions used to create this web app, you can go to my other [github page](https://github.com/casualcomputer/sql.mechanic) for understanding the package `sql.mechanic` that I created. 

To use the RShiny app, just download this folder and run "table-summarizer.R".


## Limitations

-   You probably want to understand how [**Example 2**](https://github.com/casualcomputer/sql.mechanic#example-2-automatically-summarize-tables-in-your-databases) (part of my package called "sql.mechanic") affects the CPU and disk usage of your database server, to avoid bad surprises on your server's resource usage.

-   If you use the setup of [**Example 2**](https://github.com/casualcomputer/sql.mechanic#example-2-automatically-summarize-tables-in-your-databases) (part of my package called "sql.mechanic") on a cloud database, you **MUST** do some testing, to understand how the example affects the CPU and disk usage of your cloud resource. Please avoid potentially expensive mistakes.

-   Currently, I designed the app to work only with Microsoft SQL Server and Netezza databases. Feel free to contribute to the codes, if interested.