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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

RDBMS Vs Key-value Four Top Differences

This post tells you differences between rdbms and distributed key-value storage.

Rdbms is quite  different from key-value storage.

RDBMS Vs Key-value Four Top Differences

RDBMS (Relational Database)

  1. You have already used a relational database management system — a storage product that's commonly referred to as RDBMS
  2. It is basically a structured data.
  3. RDBMS systems are fantastically useful to handle moderate data.
  4. The BIG challenge is in scaling beyond a single server. 
  5. You can't maintain redundant data in rdbms.
  6. All the data available on single server.
  7. The entire database runs on single server. So when server is down then database may not be available to normal business operations.
  8. Outages and server downs are common in this rdbms model of database.

Key-Value Database

  1. Key-value storage systems often make use of redundancy within hardware resources to prevent outages. This concept is important when you're running thousands of servers because they're bound to suffer hardware breakdowns. 
  2. Multiple copies same data available on multiple servers.
  3. The use of redundancy makes the key-value system always available — and, more importantly, your data is always available because it's protected from hardware outages.
  4. Literally, dozens of key-value storage products are available. Many of them were first developed by so-called webscale companies, such as Facebook and LinkedIn, to ensure that they can handle massive amounts of traffic. 
  5. Currently key-value storages under open source licenses are available. Now you (or anyone else) can use them in other environments too.

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