Abstract
The expansion of data and its efficient handling is becoming a more popular tendency in recent times bringing new difficulties to learn new avenues. Data analytics can be done more proficiently with the availability of distributed architecture of not only SQL (NoSQL) databases. Technological advancements around us are changing very rapidly, and major shift is being carried out, a switch from relational to non-relational world. When moving from relational to non-relational models, database administrators face common problems due to the fact that NoSQL is a no-schema database. The purpose of conducting this research is to propose a mechanism by which the schema of a relational database management system and its data can be transformed into big data by following some standardize guidelines. This model can be quite useful for relational database administrators by enabling them to give attention to logical modeling rather than procedural writing for each and every SQL to NoSQL transition.
TopLarge plane platforms are shown in Figure 1. During the flight, the flight data will move according to civil air craft in real time transferring large data platforms to the Civil Aircraft platform or through an open-ended data link. Statistics include aircraft position data and aircraft health monitoring data. After logging in, data from all parameter data will be sent offline. In real-time flight data is analyzed by Data Center and the plane's health decision’s resultssent back. The database sends data recovery data and recovery recommendations to the airport maintenance center, which results in the maintenance of data center. To provide the aircraft’s real-time tracing the aircraft flight data and the airport’s operational data is used by data centerand provide advice for flight settings.
Figure 1. Scenario of civil aircraft big data platform
Key Terms in this Chapter
BASE: Basically available, soft-state, eventual consistent.
Structured Query Language: A domain-specific language used in programming and designed for managing data held in a relational database management system (RDBMS), or for stream processing in a relational data stream management system (RDSMS).
HUSH: HBase URL shorten.
NoSQL: Not only structured query language.
ACID: Atomicity, consistency, isolation, durability.
Metadata: Is data that provides information about other data.
HBase: An open-source, non-relational, distributed database modeled after Google's Bigtable and written in Java.
CAP: Consistency, availability, partition tolerance.
Database: An organized collection of data stored and accessed electronically.
PHM: Prognostics and health monitoring.
Big Data: A term used to refer to the study and applications of data sets that are too complex for traditional data-processing application software to adequately deal with.
SQL: Structured query language.
HDFS: Hadoop distributed file system.