Unit 1

DATABASE MODELLING, MANAGEMENT AND DEVELOPMENT

Database design and modelling - Business Rules and Relationship; Java database Connectivity (JDBC), Database connection Manager, Stored Procedures. Trends in Big Data systems including NoSQL - Hadoop HDFS, MapReduce, Hive, and enhancements.

Part A

# Question
1 Define Business Rules with an example
2 Contrast macros and stored procedures
3 Describe the connection object
4 Contrast JDBC and ODBC
5 Discuss OLEDB
6 Illustrate stored procedure with an example
7 Demonstrate ACID properties
8 Discover Map parameters
9 Analyze about Hive.
10 Point out any 2 features of Hadoop Cluster
11 Compare Map Stage and Reduce stage
12 Summarize the use of hadoop distributed file system.
13 Assess Hadoop MapReduce
14 Develop SSIS Connections
15 Prepare a query in HiveQL

Part B

# Question
1 T ell about the JDBC in detail (16)
2 D escribe the importance of Data Modeling.Illustrate with a simple case study. (16)
3 E xplain the following SELECT statement syntax with examples in HiveQL i) Computing with Columns (4) ii) WHERE Clauses (4) iii) GROUP BY Clauses(4) iv) HAVING Clauses (4)
4 i) Define NoSQL and is it the next big trend in databases?(8) ii) Tabulate SQL vsNoSQL (8)
5 i) Explain Data organization in HDFS(8) ii) BrieflyexplainlimitationsandRestrictionsinStored procedures(8)
6 D escribe the following i) OLE DB Source (8) ii) OLE DB Destination (8)
7 i) Discuss MapR converged data platform (8) ii) Elaborate on the function of MapReduce framework(8)
8 Il lustrate SSIS Connections (16)
9 Il lustrate with a neat diagram the architecture of HDFS in detail (16)
10 A nalyse various databases used in NoSQL (16)
11 B riefly explain the following in NoSQL i) Multiple Queries (4) ii) Caching (4) iii) Nesting Data (4) iv) ACID and JOIN Support (4)
12 E xplain the following in MapReduce i) Enterprise Storage (6) ii) Database (6) iii) Event streaming (4)
13 E xplain Hive unit testing frameworks (16)
14 B riefly explain the following in NoSQL i) Multiple Queries (4) ii) Caching (4) iii) Nesting Data (4) iv) ACID and JOIN Support (4)
15 E xplain the following in MapReduce i) Enterprise Storage (6) ii) Database (6) iii) Event streaming (4)
16 E xplain Hive unit testing frameworks (16)