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Showing posts with the label SQL Queries

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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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SQL Interview Success: Unlocking the Top 5 Frequently Asked Queries

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 Here are the five top commonly asked SQL queries in the interviews. These you can expect in Data Analyst, or, Data Engineer interviews. Top SQL Queries for Interviews 01. Joins The commonly asked question pertains to providing two tables, determining the number of rows that will return on various join types, and the resultant. Table1 -------- id ---- 1 1 2 3 Table2 -------- id ---- 1 3 1 NULL Output ------- Inner join --------------- 5 rows will return The result will be: =============== 1  1 1   1 1   1 1    1 3    3 02. Substring and Concat Here, we need to write an SQL query to make the upper case of the first letter and the small case of the remaining letter. Table1 ------ ename ===== raJu venKat kRIshna Solution: ========== SELECT CONCAT(UPPER(SUBSTRING(name, 1, 1)), LOWER(SUBSTRING(name, 2))) AS capitalized_name FROM Table1; 03. Case statement SQL Query ========= SELECT Code1, Code2,      CASE         WHEN Code1 = 'A' AND Code2 = 'AA' THEN "A" | "A
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How to Call SQL Query from Python

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Python's top supported database is MySQL. You can run SQL queries from Python. Here're best examples of how to connect to MYSQL and access MYSQL tables from Python. Read:  How to Print String in Next Line Easily Here are Steps Import MySQL connecter Give user id, password details Issue SQL query Python Logic to import MySQL connector import mysql.connector Note: If the MySQL connecter not installed in python, you need to install it using the below command. pip3 install mysql-connector-python --allow-external mysql-connector-python Supply user id and Password conn=mysql.connector.connect(user='root', password='password', host='localhost', database='sakila') mycursor=conn.cursor() Issue SQL Query mycursor.execute("show tables") # you won't see any result. You need to give print. print(mycursor.fetchall()) mycursor.execute("select * from customer") # you won't see any result. You need to give print. print(mycursor.fetchal
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