Showing posts with the label Cleaning data

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8 Ways to Optimize AWS Glue Jobs in a Nutshell

  Improving the performance of AWS Glue jobs involves several strategies that target different aspects of the ETL (Extract, Transform, Load) process. Here are some key practices. 1. Optimize Job Scripts Partitioning : Ensure your data is properly partitioned. Partitioning divides your data into manageable chunks, allowing parallel processing and reducing the amount of data scanned. Filtering : Apply pushdown predicates to filter data early in the ETL process, reducing the amount of data processed downstream. Compression : Use compressed file formats (e.g., Parquet, ORC) for your data sources and sinks. These formats not only reduce storage costs but also improve I/O performance. Optimize Transformations : Minimize the number of transformations and actions in your script. Combine transformations where possible and use DataFrame APIs which are optimized for performance. 2. Use Appropriate Data Formats Parquet and ORC : These columnar formats are efficient for storage and querying, signif

10 Excusive Steps You need for Web Scrapping

Here're ten Python technics to clean the scraped data. The scraped  Text has unwanted hidden data . So, as part of cleaning it try to remove these ten in your data. 10 Steps for Web scrapping Data is prime input for  text analytics projects . After cleaning, you can feed to Machine/Deep Learning systems. Removing HTML tags Tokenization Removing unnecessary tokens and stop-words Handling contractions Correcting spelling errors Stemming Lemmatization Tagging Chunking Parsing 10 Technics to Clean Text in Python 1. Removing HTML tags The unstructured text contains a lot of noise ( data from web pages, blogs, and online repositories.)when you use web/screen scraping.  The HTML tags, JavaScript, and Iframe tags typically don't add much value to understanding and analyzing text. Our purpose is to remove HTML tags, and other noise. 2. Tokenization Tokens are independent and minimal textual components. And have a definite syntax and semantics. A paragraph of text or a text document has