Article Categories
- All Categories
-
Data Structure
-
Networking
-
RDBMS
-
Operating System
-
Java
-
MS Excel
-
iOS
-
HTML
-
CSS
-
Android
-
Python
-
C Programming
-
C++
-
C#
-
MongoDB
-
MySQL
-
Javascript
-
PHP
-
Economics & Finance
Big Data Analytics Articles
Page 114 of 135
What are different types of recoverability of schedules(DBMS)?
If any transaction that performs a dirty read operation from an uncommitted transaction and also its committed operation becomes delayed till the uncommitted transaction is either committed or rollback such type of schedules is called as Recoverable Schedules.Types of recoverable schedulesThere are three types of recoverable schedules which are explained below with relevant examples −Cascading schedulesCascadeless SchedulesStrict Schedules.The types of recoverable schedules are given below in form of a chart −Recoverable scheduleFirst, let us see an example of a recoverable schedule.T1T2R(X)W(X)W(X)R(X)commitCommitHere, transaction T2 is reading value written by transaction T1 and the commit of T2 occurs after the commit of ...
Read MoreDifference between Data Mining and Big Data
Big Data represents the vast amount of data that can be structured, semi−structured, and unstructured sets of data ranging in terms of terabytes. In contrast, Data Mining is the process of discovering meaningful new correlations, patterns, and trends by sifting through a large amount of data stored in repositories, using pattern recognition technologies as well as statistical and mathematical techniques. Data mining utilizes tools like machine learning, visualization, statistical models, etc. to extract the useful data from the Big Data. Read this article to find out more about Data Mining and Big Data and how they are different from each ...
Read MoreDifference between Normalization and Denormalization
The process to alter the structure of a database is basically categorized into two ways, one is Normalization and the other is Denormalization. The basic difference between normalization and denormalization is that the database normalization removes the redundancy of data and anomalies in a poorly designed table, while denormalization combines multiple table data into one so that it can be queried quickly. Read through this article to find out more about normalization and denormalization and how they are different from each other. What is Normalization? Normalization is used to remove redundant data from the database and to store non-redundant and ...
Read MoreWhat is Bucketing in Hive?
Bucketing is a method in Hive which is used for organizing the data. It is a concept of separating data into ranges known as buckets. Bucketing in hives comes helpful when the use of partitioning becomes hard. A user can determine the range of a specific bucket by the hash value. Partitioned tables can be bucketed to separate the data further to perform queries more efficiently. Every bucket is stored as a file within the table or the partition’s directories on HDFS. The records having a similar value within a column are always stored in the same bucket. Bucketing can ...
Read MoreDifference between IoT and Big Data
Both the Internet of Things (IoT) and Big Data are currently the trending topics that are frequently discussed in the context of the information technology industry. It is practically impossible to discuss one of these topics without also bringing up the other. Both are the wave of the future when it comes to data, and by data, we mean enormous amounts of data. We are now living in a digital age in which new things are constantly being linked to the Internet in an effort to make people's lives easier.Read through this article to get an overview of IoT and ...
Read MoreDifference between Big Data and Cloud Computing
Big Data is the process of managing massive amounts of data in an efficient manner, while Cloud Computing is the process of storing and managing the data resources and models that are stored on distant servers and infrastructures.Data from social media platforms, e-commerce platforms and enterprises, methods for determining the weather, Internet of Things sensors, and other domains are all examples of applications for big data. With the help of big data, platforms can be centralized, backups can be made, and maintenance can be handled in a way that saves money.What is Big Data?"Big Data" is short for very large ...
Read MoreDifference between Abstraction and Virtualization
The meaning of the word "abstraction" varies subtly depending on the surrounding words and phrases that are used in conjunction with it. In a general sense, an abstraction offers a picture of an item that has fewer specifics and reveals the features that are inherent to the thing from the perspective of the observer.Let's pretend that we have a MariaDB database in addition to a PostgreSQL database. An abstract look at it could reveal that it has a number of characteristics in common with other systems, such as a tabular representation of the data and a network-facing interface that its ...
Read MoreWhat are the differences between HBase and Cassandra?
Let us understand the concepts of HBase and Cassandra before learning the differences between them.CassandraCassandra has a different infrastructure. Cassandra uses different DBMS along with their infrastructure. When Cassandra uses different DBMS then time complexity will increase.Cassandra supports ordered partitioning. This can lead to row size up to 10 megabytes.In Cassandra, we use seed nodes. These nodes perform inter-cluster communication. Here, we use internal communication. Casandra has lightweight transactions.Cassandra is based on the Jbury shell. But it has a specific Query language. That is CQL, it is modelled after SQL. It is better than HBase in Documentation. It uses the ...
Read MoreWhat is Hierarchical architecture in parallel databases?
In parallel database system data processing performance is improved by using multiple resources in parallel. In this CPU, disks are used parallel to enhance the processing performance.Operations like data loading and query processing are performed parallel. Centralized and client server database systems are not powerful enough to handle applications that need fast processing.Parallel database systems have great advantages for online transaction processing and decision support applications. Parallel processing divides a large task into multiple tasks and each task is performed concurrently on several nodes. This gives a larger task to complete more quickly.Architectural ModelsThere are several architectural models for parallel ...
Read MoreWhat is a parallel database and explain how it works?
A parallel database is one which involves multiple processors and working in parallel on the database used to provide the services.A parallel database system seeks to improve performance through parallelization of various operations like loading data, building index and evaluating queries parallel systems improve processing and I/O speeds by using multiple CPU’s and disks in parallel.Working of parallel databaseLet us discuss how parallel database works in step by step manner −Step 1 − Parallel processing divides a large task into many smaller tasks and executes the smaller tasks concurrently on several CPU’s and completes it more quickly.Step 2 − The ...
Read More