data analysis

Apache Spark: Read Data from S3 Bucket

Reading Time: 2 minutes Well, a one working with spark is very much familiar with the ways of reading the file from local either from a Table or HDFS or from any file. But do you know how tricky it is to read data into spark from an S3 bucket? So, this blog makes you give a stepwise follow up to how to read data from an S3 bucket. Continue Reading

Apache Spark: Repartitioning v/s Coalesce

Reading Time: 3 minutes Does partitioning help you increase/decrease the Job Performance? Spark splits data into partitions and computation is done in parallel for each partition. It is very important to understand how data is partitioned and when you need to manually modify the partitioning to run spark applications efficiently. Now, diving into our main topic i.e Repartitioning v/s Coalesce What is Coalesce? The coalesce method reduces the number Continue Reading

Apache Spark

Deep Dive into Apache Spark Transformations and Action

Reading Time: 4 minutes In our previous blog of Apache Spark, we discussed a little about what Transformations & Actions are? Now we will get deeper into the topic and will understand what actually they are & how they play a vital role to work with Apache Spark? What is Spark RDD? Spark introduces the concept of an RDD (Resilient Distributed Dataset), an immutable fault-tolerant, distributed collection of objects Continue Reading

Big Data Evolution: Migrating on-premise database to Hadoop

Reading Time: 4 minutes We are now generating massive volumes of data at an accelerated rate. To meet business needs, address changing market dynamics as well as improve decision-making, sophisticated analysis of this data from disparate sources is required. The challenge is how to capture, store and model these massive pools of data effectively in relational databases. Big data is not a fad. We are just at the beginning Continue Reading

Data Analysis using Python: Pandas

Reading Time: 3 minutes In this blog, I am going to explain pandas which is an open source library for data manipulation, analysis, and cleaning. Pandas is a high-level data manipulation tool developed by Wes McKinney. The name Pandas is derived from the word Panel Data – an Econometrics from Multidimensional data. Pandas is built on the top of NumPy. Five typical steps in the processing and analysis of Continue Reading