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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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Hyderabad Based Startup Built Largest Ever Big data Electoral Repository

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I was gone through an email from my friend saying that they are creating a Hadoop project to analyze voters data. This project in my view is both academic and research oriented.
hadoop project
The real challenge was extraction of voter info from 2.5 crore PDF pages and translation of the same into English to fuse with other sources. The technology was a big hurdle. 

Hadoop Project

The infrastructure, built especially for the project, included 64 node Hadoop, PostgreSQL and servers that process a master file containing over 8 Terabytes of Data.

Besides, Testing and Validation was another big task. ‘First of a Kind’ Heuristic (machine learning) algorithms were developed for people classification based on name, geography etc., which help in the identification of religion, caste, and even ethnicity.

Data from Sources

“Data from multiple sources like census, economic and social surveys were mapped to polling booths. Simultaneously, external and propriety data sources had to be fused with individual voters’ data,” informed Joshi. 



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