by Team AHT | Oct 20, 2024 | Pyspark
When working with PySpark, there are several common issues that developers face. These issues can arise from different aspects such as memory management, performance bottlenecks, data skewness, configurations, and resource contention. Here’s a guide on troubleshooting...
by Team AHT | Oct 11, 2024 | Pyspark
Q1.–We are working with large datasets in PySpark, such as joining a 30GB table with a 1TB table or Various Transformation on 30 GB Data, we have 100 cores limit to use per user , what can be best configuration and Optimization strategy to use in pyspark ? will...
by Team AHT | Oct 11, 2024 | Pyspark
To determine the optimal number of CPU cores, executors, and executor memory for a PySpark job, several factors need to be considered, including the size and complexity of the job, the resources available in the cluster, and the nature of the data being processed....
by Team AHT | Oct 2, 2024 | SQL
Partitioning in SQL, HiveQL, and Spark SQL is a technique used to divide large tables into smaller, more manageable pieces or partitions. These partitions are based on a column (or multiple columns) and help improve query performance, especially when dealing with...
by Team AHT | Oct 2, 2024 | SAS, SQL
PIVOT Clause in Spark sql or Mysql or Oracle Pl sql or Hive QL The PIVOT clause is a powerful tool in SQL that allows you to rotate rows into columns, making it easier to analyze and report data. Here’s how to use the PIVOT clause in Spark SQL, MySQL, Oracle...
by Team AHT | Sep 6, 2024 | SQL
SQL query flows through the Oracle engine in the following steps: Step 1: Parsing The SQL query is parsed to check syntax and semantics. The parser breaks the query into smaller components, such as keywords, identifiers, and literals. Step 2: Optimization The parsed...
by Team AHT | Aug 29, 2024 | Pyspark
PySpark is a powerful Python API for Apache Spark, a distributed computing framework that enables large-scale data processing. Spark History Spark was initially started by Matei Zaharia at UC Berkeley’s AMPLab in 2009, and open sourced in 2010 under a BSD...
by Team AHT | Aug 26, 2024 | Pyspark
Deploying a PySpark job can be done in various ways depending on your infrastructure, use case, and scheduling needs. Below are the different deployment methods available, including details on how to use them: 1. Running PySpark Jobs via PySpark Shell How it Works:...
by Team AHT | Aug 26, 2024 | Tutorials
Hive a Data warehouse infra Hive is an open-source data warehouse infrastructure built on top of Hadoop for providing data summarization, query, and analysis. It allows users to query and manage large datasets residing in distributed storage using a SQL-like language...
by Team AHT | Aug 24, 2024 | Pyspark
In PySpark, jobs, stages, and tasks are fundamental concepts that define how Spark executes distributed data processing tasks across a cluster. Understanding these concepts will help you optimize your Spark jobs and debug issues more effectively. At First Let us go...
by Team AHT | Aug 24, 2024 | Pyspark
Apache Spark is a powerful distributed computing system that handles large-scale data processing through a framework based on Resilient Distributed Datasets (RDDs). Understanding how Spark partitions data and distributes it via shuffling or other operations is crucial...
by Team AHT | Aug 15, 2024 | Pyspark
In Apache Spark, data types are essential for defining the schema of your data and ensuring that data operations are performed correctly. Spark has its own set of data types that you use to specify the structure of DataFrames and RDDs. Understanding and using Spark’s...
by Team AHT | Aug 6, 2024 | Python
Merge sort is a classic divide-and-conquer algorithm that efficiently sorts a list or array by dividing it into smaller sublists, sorting those sublists, and then merging them back together. Here’s a step-by-step explanation of how merge sort works, along with...
by Team AHT | Aug 2, 2024 | SQL
Let’s list all possible places where subqueries in MySQL or Hive QL or Pyspark SQL Query can be used: 1. In the SELECT Clause Subqueries can compute a value for each row. SELECT employee_id, (SELECT COUNT(*) FROM project_assignments pa WHERE pa.employee_id =...
by Team AHT | Jul 29, 2024 | AI & ML
Data preprocessing is a crucial step in machine learning. It involves cleaning and transforming raw data into a format suitable for modeling. Data Cleaning Data cleaning involves identifying and correcting errors, inconsistencies, and inaccuracies in the data such as...
by Team AHT | Jul 29, 2024 | AI & ML
In this lesson, we’ll cover essential Python libraries for machine learning: NumPy, Pandas, Matplotlib, and Scikit-Learn. NumPy NumPy is a library for numerical computations in Python. It provides support for arrays, matrices, and many mathematical functions....
by Team AHT | Jul 29, 2024 | AI & ML
What is AI? Artificial Intelligence (AI) is the simulation of human intelligence in machines that are programmed to think and learn like humans. AI systems can perform tasks such as visual perception, speech recognition, decision-making, and language translation. What...
by Team AHT | Jul 29, 2024 | AI & ML
My Posts in this series will follow below said topics. Introduction to AI and ML What is AI? What is Machine Learning? Types of Machine Learning Supervised Learning Unsupervised Learning Reinforcement Learning Key Terminologies Python for Machine Learning Introduction...
by Team AHT | Jul 29, 2024 | AI & ML
What is AI? Artificial Intelligence (AI) refers to the simulation of human intelligence in machines that are programmed to think and learn. These systems can perform tasks that typically require human intelligence, such as visual perception, speech recognition,...
by Team AHT | Jul 28, 2024 | Python
Python provides various libraries and functions to manipulate dates and times. Here are some common operations: DateTime Library The datetime library is the primary library for date and time manipulation in Python. datetime.date: Represents a date (year, month, day)...
