We know that Apache Hadoop is a framework that allows us to perform data processing in a distributed way on very large datasets using commodity computers. That is why, this framework is highly scalable and can scale up from a single machine to thousands of machines. Most importantly, Hadoop is an open source and provides […]
Difference between Hadoop 1.x, Hadoop 2.x and Hadoop 3.x Read More »
In this post, we will discuss an error/warning message “java.io.IOException: Failed to connect to”. This error keeps coming when we try to execute a hive query from spark-shell using spark SQL. This error occurs when Spark tries to execute a task in local mode (pseudo-distributed mode). It is caused because of a connection exception. The
ERROR Utils: Aborting task java.io.IOException: Failed to connect to – Local Spark Read More »
This post briefs how we can display the full contents of data frame columns in Apache Spark. The default behavior of Spark truncates the column values if it is more than 20 characters. However, sometimes we need to display the full values rather than the truncated data. Having truncated data might not be useful in
Suppose, we have a CSV file that contains some non-English characters (Spanish, Japanese, and etc.) and we want to read this file into a Spark data frame. If we read this file without using the right character encoding, we will end up with some junk characters (like �) in the data frame. So, the files
Spark read file with special characters using PySpark Read More »
Apache Spark is a Big Data cluster computing framework that can run on Standalone, Hadoop, Kubernetes, Mesos clusters, or in the cloud. We can read and write data from various data sources using Spark. For example, we can use CSV (comma-separated values), and TSV (tab-separated values) files as an input source to a Spark application.
This post will briefly discuss the difference and similarity between Sort By, Order By, Distribute By, and Cluster By in hive queries. This is one of the most important questions being asked in Big data/Hadoop interviews. These Sort By, Order By, Distribute By, and Cluster By clauses are available in the hive query language and
Sort By, Order By, Distribute By, and Cluster By in Hive Read More »
Data compression is a technique that encodes the original data in such a way so that it can be represented with fewer bits on the disk. The data compression process is used to reduce the size of the data files on the disk. We know that the Hadoop framework is meant for large scale data
Data compression in Hive – An Introduction to Hadoop Data Compression Read More »
Apache Hive is a big data query language which is used to read, transform and write large datasets in a distributed environment. It has a SQL like syntax which gets translated into a MapReduce job in order to execute on Hadoop clusters. In Hadoop ecosystem, we use Hive for batch processing to extract, transform and
