Build gen AI apps with an all-in-one modern database: MongoDB Atlas
MongoDB Atlas provides built-in vector search and a flexible document model so developers can build, scale, and run gen AI apps without stitching together multiple databases. From LLM integration to semantic search, Atlas simplifies your AI architecture—and it’s free to get started.
Start Free
Keep company data safe with Chrome Enterprise
Protect your business with AI policies and data loss prevention in the browser
Make AI work your way with Chrome Enterprise. Block unapproved sites and set custom data controls that align with your company's policies.
...And for ETL alike work like Load and filter files -> Extract -> Transform output.
For replacing files, you can preview and backup, in multiple directories and files or pipe, with plain text matching or using general Regex as C++, C#, Java, Scala; So msr is a good tool to learn and test Regex since it has different colors for matched groups captured by the Regex pattern.
osDQ dedicated to create apache spark based data pipeline using JSON
This is an offshoot project of open source data quality (osDQ) project https://sourceforge.net/projects/dataquality/
This sub project will create apache spark based data pipeline where JSON based metadata (file) will be used to run data processing , data pipeline , data quality and data preparation and data modeling features for big data. This uses java API of apache spark. It can run in local mode also.
Get json example at https://github.com/arrahtech/osdq-spark
How to run
Unzip the zip file
Windows : java -cp .\lib\*;osdq-spark-0.0.1.jar org.arrah.framework.spark.run.TransformRunner -c .\example\samplerun.json
Mac UNIX
java -cp ./lib/*:./osdq-spark-0.0.1.jar org.arrah.framework.spark.run.TransformRunner -c ....