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Showing posts with the label regular-expressions

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8 Ways to Optimize AWS Glue Jobs in a Nutshell

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  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
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How to Search for Single CHAR in Python Using Regular-expression

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Here is the logic for searching single CHAR using regular expression(Regex). For instance, we use wildcards to search for anything on our computers. The Regex in Python works similarly. Regular expression People use asterisk * for searching any document. For instance, if you type *.pdf, it returns all the pdfs available in the location (where you are conducting your search). Similar way, in Python, you can search using regular expressions. Import Regex  The first thing you need to do is import 're' if you want to work with regular expressions. import re The Python regular expression library, you can use to improve your skills. Example program: search for single CHAR To match any single character, you can use  [….] . Below, you will find an example to search for: 'l' or 'a' or 'b' import re pattern = r'[lab]' sequence = 'we love python' obj = re.search(pattern,sequence) if obj: print("We found a match here @",obj.group()) else: p
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How to write Regular expression Quickly in python and Examples

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Regular Expressions purpose is to find matching string in another string. You will get either 'True' or 'False' as a response. I am not sharing here how to play tennis. My intention is if you just follow ideas, you can play tennis today.   Python Regular Expressions What is a regular expression How does python support Best examples 1. What is regular expression >>> haystack = 'My phone number is 213-867-5309.'  >>> '213-867-5309' in haystack True This is just a fundamental use of the regular expression. The real use of Regular Expression comes here. That is - to find if the main has any valid phone number. Regular expressions also called regexes. 2. Why do we need regx Data mining - to get required data if it is present are not Data validations - to get an answer if the received string is valid or not. Python support Python has its own regular expression library. That is called re . What you need to do is just import it. >>>imp
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