Tag: Big Data
PySpark : Dropping duplicate rows in Pyspark – A Comprehensive Guide with example
PySpark provides several methods to remove duplicate rows from a dataframe. In this article, we will go over the steps…
PySpark : Replacing null column in a PySpark dataframe to 0 or any value you wish.
To replace null values in a PySpark DataFrame column that contain null with a numeric value (e.g., 0), you can…
PySpark : unix_timestamp function – A comprehensive guide
One of the key functionalities of PySpark is the ability to transform data into the desired format. In some cases,…
PySpark : Reading parquet file stored on Amazon S3 using PySpark
To read a Parquet file stored on Amazon S3 using PySpark, you can use the following code: from pyspark.sql import…
Google Dataflow : Handling Late Data in Google Dataflow
Handling late-arriving data is a common challenge when working with streaming data processing systems like Google Dataflow. Late data refers…
Google Dataflow-An Overview and programming languages are supported by Google Dataflow
Google Dataflow is a cloud-based data processing service that allows developers to easily and efficiently process large volumes of data….
Hive : Hive Table Properties : How are Hive Table Properties used?
One of the key features of Hive is the ability to define table properties, which can be used to control…
Hive : Implementation of UDF in Hive using Python. A Comprehensive Guide
A User-Defined Function (UDF) in Hive is a function that is defined by the user and can be used in…
Hive : Hive metastore and its importance.
The Hive Metastore is an important component of the Apache Hive data warehouse software. It acts as a central repository…
Hive : Hive Optimizers: A Comprehensive Guide
Hive is a data warehousing tool that provides a SQL-like interface for querying large datasets stored in Hadoop Distributed File…