Apache Hive Analytical Functionsavailable since Hive 0.11.0, are a special group of functions that scan the multiple input rows to compute each output value. Apache Hive Analytical Functions are usually...
Apache Hive Vectorization was introduced newly in Apache Hive to improve query performance. By default, the Apache Hive query execution engine processes one row of a table at a time....
Apache Hive Release 3.1.1 is the version which is compatible with Hadoop 3.x.y and fixes 4 bugs and one new Feature Apache Hive Release 3.1.1 Release Note Following Bug Fixes...
Apache Hive Cheat Sheet is a summary of all functions and syntax for big data engineers and developers reference. It is divided into 5 parts. Apache Hive Cheat Sheet -...
As big data engineer, you must know the apachehive best practices.As you know Apache Hive is not an RDBMS, but it pretends to be one most of the time. It...
Apache Hive development has shifted from the original Hive server (HiveServer1) to the new server (HiveServer2), and hence users and developers need to move to the new access tool. However,...
Immutability and RDD Interface in Spark are key concepts and it must be understood in detail.Spark defines an RDD interface with the properties that each type of RDD mustimplement. These...
Spark In-Memory Persistence and Memory Management must be understood by engineering teams.Sparks performance advantage over MapReduce is greatest in use cases involvingrepeated computations. Much of this performance increase is due...
Spark Model of Parallel Computing and sometimes also called RDD is an important API.Spark Model of Parallel Computing internally uses RDD and part of Spark Core library.
Why you should be worried about how Apache Spark works? To get the most out of Spark, it is important to understand some of the principlesused to design Spark and,...