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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

How to Write Complex Python Program Using Functions

Complex Python program using functions

Here is an example of complex python program written using functions. Many times, in job interviews, you need to give a written test. There, you may need to answer tricky programs. Historically, people are afraid to take a test. Especially in python

Complex Python programs

Below are the Complex Python Program Using Functions and examples of how to write the code.
  1. Counting lower and upper case letters
  2. Creating a list

1. Counting lower and upper case letters

Below program counts the upper and lower case letters.


def count_lower_upper(s): dlu = {'Lower': 0, 'Upper': 0} for ch in s: if ch.islower(): dlu['Lower'] += 1 elif ch.isupper(): dlu['Upper'] += 1 return(dlu) d = count_lower_upper('James BOnd') print(d) d = count_lower_upper('Anant Amrut Mahalle') print(d)


python function program


Also read: How to Lose Your Weight


2. Creating a List


Here it uses two input lists for creating a new list. Additionally, it uses the list built-in function. 


def create_list(l1, l2): l3 = list(set(l1) & set(l2)) return(l3) lst1 = [10, 20, 30, 40, 50] lst2 = [1, 2, 3, 40, 10] lst3 = create_list(lst1, lst2) print(lst3)


tricky python program


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