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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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Hadoop Skills Free Video Training

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Are you interested in the world of Big data technologies, but find it a little cryptic and see the whole thing as a big puzzle. The hadoop free video training really useful to learn quickly.

Are you looking to understand how Big Data impact large and small business and people like you and me?
Do you feel many people talk about Big Data and Hadoop, and even do not know the basics like history of Hadoop, major players and vendors of Hadoop. Then this is the course just for you!
This course builds a essential fundamental understanding of Big Data problems and Hadoop as a solution. This course takes you through:
  1. Understanding of Big Data problems with easy to understand examples.
  2. History and advent of Hadoop right from when Hadoop wasn’t even named Hadoop.
  3. What is Hadoop Magic which makes it so unique and powerful.
  4. Understanding the difference between Data science and data engineering, which is one of the big confusions in selecting a carrier or understanding a job role.
  5. And most importantly, demystifying Hadoop vendors like Cloudera, MapR and Hortonworks by understanding about them.
What are the requirements
  • Interest in new technical field of Big Data
  • Interest in a new technology: Hadoop.
  • What am I going to get from this course?
  • Over 8 lectures and 44 mins of content!
  • To build fundamental knowledge of Big Data and Hadoop
  • To build essential understanding about Big Data and Hadoop.
What is the target audience
  • Big Data and Hadoop Enthusiast
  • Non-geeks and any one who wants to know about Big Data.

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