A quality product by Brainheaters education solutions Pvt. Ltd. Brainheaters Notes. Revised (A.Y )

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1 A quality product by Brainheaters education solutions Pvt. Ltd Brainheaters Notes ADBMS IT Semester-5 Revised (A.Y ) Proudly Powered by MRP Rs. 70

2 The Goal Not to be in the same position next year By: Akshita Team Brainheaters TM Page no - 1

3 Syllabus.BH Exam T.T -1 T.T -2 AVG Term Work Oral End of Exam Total Marks Distribution 20 M 20 M 20 Marks 25 Marks 25 Marks 80 marks 150 marks Sr. No Module Detailed content 1 Introduction Reviewing basic concepts of a relational database, Basic SQL 2 Advanced SQL 3 Advanced Transaction Processing & Recovery Complex Retrieval Queries using Group By, Recursive Queries, nested Queries ; Specifying Constraints as Assertions; Event Condition Action (ECA) model (Triggers) in SQL; Creating and working with Views in SQL; Database Programming: Embedded SQL, Dynamic SQL and SQLJ, Database Programming with Function Calls: JDBC; Stored Procedures in SQL, Embedded SQL, Dynamic SQL. Review of ACID properties and Serializability; Multiversion Concurrency Control Techniques; Granularity of Data Items and Multiple Granularity Locking ; Advanced Database Recovery techniques like Write Ahead Logging (WAL), ARIES, Checkpoints. 4 Data Security Introduction to Database Security Issues; Discretionary Access Control Based on Granting and Revoking Privileges; Mandatory Access Control and Role-Based Access Control for Multilevel Security; SQL Injection; Introduction to Statistical Database Security Introduction to Flow Control Page no - 2

4 Large Slowly Changing Dimensions, Junk Dimensions, Keys in the Data Warehouse Schema, Primary Keys, Surrogate Keys & Foreign Keys; Aggregate Tables; Fact Constellation Schema or Families of Star. 10 ETL Process Challenges in ETL Functions; Data Extraction; Identification of Data Sources; Extracting Data: Immediate Data Extraction, Deferred Data Extraction; Data Transformation: Tasks Involved in Data Transformation, Data Loading: Techniques of Data Loading, Loading the Fact Tables and Dimension Tables Data Quality; Issues in Data Cleansing. 11 Online Analytical Processing (OLAP) Need for Online Analytical Processing; OLTP vs OLAP; OLAP and Multidimensional Analysis; Hypercubes; OLAP Operations in Multidimensional Data Model; OLAP Models: MOLAP, ROLAP, HOLAP, DOLAP; Page no - 4

5 Object Query Language(OQL) - (5-10M) 2 1 Time 66 Object Definition Language ODL - (5-10M) Introduction to Data Warehousing (Weight Marks) Help of the diagram architecture of a data warehouse - (5-10M) Entity-relationship modelling not for DW data modelling di erent - (5-10M) Times Time 76 Di erent characteristics of a dw - (5M) 2 1 Time 83 Information Delivery Component of data warehouse architecture - (5-10M) 2 1 Time 84 Role of metadata in data warehouse - (5M) 2 1 Time 85 Compare Operational Decisional Support System - (5-10M) 3-86 Di erent Types of Architecture - (5-10M) 3-87 Classification of Metadata - (5-10M) Dimensional Modeling (Weight Marks) Factless table - (5-10M) 1 4 Times 101 Design a schema Library system Primary key or Foreign key - (10M) 2 2 Times 96 Snowflake Star schema - (5-10M) 2 2 Times 99 Referential integrity - (5M) 3 1 Time ETL Process (Weight Marks) Data loading and its types - (5-10M) 1 1 Time 105 Three reasons ETL functions challenging data warehouse environment - (10M) 1 1 Time 108 Page no - 7

6 Chapter No.1 : Advanced SQL: (Weightage Marks) Q1. Explain ECA model with example. P-2 (10M) Appeared: 1 Time (May 16) Ans: A trigger is a special kind of a store procedure that executes in response to certain action on the table like insertion, deletion or updating of data. ECA Model: Trigger is based on the model named ECA i.e. Event-Condition-Action. 1. Event: The rules are triggered by Event. These events can be database insert, update or delete statements. Changing an employee s manager can be an event on which trigger can be fired. 2. Condition: The condition that determines whether the rule action should be executed. Once the triggering event has occurred, an optional condition may be evaluated. If no condition is specified, the action will be executed once the event occurs. If a condition is specified, it is first evaluated, and only if it evaluates to true will the rule action be executed. 3. Action: The action is usually a sequence of SQL statements. It could also be a database transaction or an external program that will be automatically executed. For example, executing a stored procedure when a particular event occurs. Page no - 9

7 Q3. Explain Triggers in SQL with two examples. P-1 (10M) Appeared: 2 Times (May 15 & Dec 14) Ans: A trigger is a block of code that is executed automatically from a database statement. Triggers is generally executed for DML statements such as INSERT, UPDATE or DELETE. It resides in a database code and is fired automatically when the database code requires to perform the INSERT,UPDATE or DELETE statement. It is also stored in the database as stored procedures. It does not involve any COMMIT transaction rather it is a part of a transaction. SYNTAX : CREATE OR REPLACE TRIGGER <trigger-name> [BEFORE/AFTER] [INSERT/UPDATE/DELETE] OF<column-name> ON<table-name> [REFERENCING OLD AS O NEW AS N] [FOR EACH ROW] WHEN <trigger-condition> DECLARE BEGIN <sql-statement> END; 1. CREATE OR REPLACE TRIGGER <trigger-name>: It is used to create a new trigger or replace an existing trigger. 2. [BEFORE/AFTER]: It is used to mention the execution time of the trigger. It specifies whether the trigger should fire after or before the DML statement. 3. [INSERT/UPDATE/DELETE]: Triggers can be fired against any of these DML statements. Page no - 14

8 2. Redo Pass The redo pass repeats history by replaying every action that is not already reflected In the page on disk.the redo pass scans the log forward from RedoLSN. Whenever it finds an update log record, it takes this action: If the page is not in DirtyPageTable or the LSN of the update log record is less than the RecLSN of the page in DirtyPageTable, then the redo pass skips the log record. Otherwise the redo pass fetches the page from disk, and if the PageLSN is less than the LSN of the log record, it redoes the log record. 3. Undo Pass and Transaction Rollback The undo pass is relatively straightforward. It performs a single backward scan of the log, undoing all transactions in undo-list. The undo pass examines only log records of transactions in undo-list; the last LSN recorded during the analysis pass is used to find the last log record for each transaction in undo-list. Whenever an update log record is found, it is used to perform an undo (whether for transaction rollback during normal processing, or during the restart undo pass). The undo pass generates a CLR containing the undo action performed (which must be physiological). It sets the UndoNextLSN of the CLR to the PrevLSN value of the update log record. Page no - 24

9 Why the multiple relationships between the two entities? Is this legitimate? In ITEM BOM, the two ITEM NOs are required. One ITEM NO represents the parent occurrence and the second ITEM NO represents the child occurrence. The combination of the two represents the relationship. Consequently, the two ITEM NOs play di erent roles. There are multiple relationships between the two entities. Multiple relationships are valid when any of the following conditions exists: the business rules are di erent, the cardinalities are di erent, or the occurrences are di erent. In this case, the occurrences would be di erent because one points to the parent occurrence, the other to the child occurrence. It does not matter which attribute is chosen to play which role parent or child. Page no - 79

10 Q8. Classification of Metadata. P-3 (5-10M) (Extra) Ans: Metadata can be broadly categorized into three categories: 1. Business Metadata - It has the data ownership information, business definition, and changing policies. 2. Technical Metadata - It includes database system names, table and column names and sizes, data types and allowed values. Technical metadata also includes structural information such as primary and foreign key attributes and indices. 3. Operational Metadata - It includes currency of data and data lineage. Currency of data means whether the data is active, archived, or purged. Lineage of data means the history of data migrated and transformation applied on it. Page no - 94

11 Constraint clause is used check that unique count of ID is less than 4 which mean not more than 3 transactions have occurred. Q3. Explain following concepts with examples: 1. Snowflake Schema P-2 (10M) Appeared: 1 Time (May 15) 2. Star Schema P-2 (10M) Appeared: 1 Time (May 16) Ans: Snowflake Schema The snowflake schema represents a dimensional model which is also composed of a central fact table and a set of constituent dimension tables which are further normalized into sub-dimension tables. In a snowflake schema implementation, Warehouse Builder uses more than one table or view to store the dimension data. Separate database tables or views store data pertaining to each level in the dimension. Some dimension tables in the Snowflake schema are normalized. Page no - 99

12 Question paper December 2015 Q1. Attempt all the question it's compulsory. (a) Justify Write-Ahead Logging (WAL) protocol for a recovery algorithm that requires both UNDO and REDO. - Chap no.5 Q2 pg no:51) (5M) (b) What is a view? Discuss the di erence between a view and base relation. - Chap no.1 Q4 pg no:11) (5M) (c) Explain Factless Fact Table. - Chap no.8 Q4 pg no:101) (5M) (d) What is the role of metadata in warehouse? - Chap no.7 Q5 pg no:85) (5M) Q2.Attempt Both (a) What are the di erent types of SQL injection attacks? What risks are associated with it? Explain any one attack in detail. - Chap no.3 Q3 pg no:28) (10M) (b) Vaidehi Foods and beverages is a new company which produces Dairy, Bread and cookies products with production unit located at Kharghar, Navi Mumbai. These products are sold in selected regions of India. They have sales units at Mumbai, Pune, satara, Sangli and Kolhapur. The President of the company wants sales information. 1. Find the dimensions of data warehouse for given problem statement and justify your answer. 2. State and represent the concept hierarchy for each dimension. 3. If the president of company wants the report: The number of items sold and income in each region for each product with time. a. Explain at which concept hierarchy level the query will be? b. Write ROLAP/MOLAP query 4. Describe the Rollup and Drilldown OLAP operations. - Chap no.10 (N.A) (10M) Q3. Attempt Both (a) What are the roles of Analysis, Redo and Undo phases in ARIES? Explain with suitable in example. - Chap no.2 Q3 pg no:23) (10M) (b) Consider the following database that has to be distributed. 1. Show 2 examples of horizontal fragmentation. 2. Show 1 example of Derived fragmentation. Page no - 124

13 Clear the subject easily Just follow this guidelines. Guidelines by Team Brainheaters Hello student, ADBMS deals with advanced database systems, distributed systems and data warehousing techniques. For scoring good marks easily focus on relational schema, queries related to the schema, OOP concepts and related queries, EER diagram and concepts, data warehousing, Triggers(Syntax and examples). Following this you can easily attempt % of the paper. Learn as per the priority order, you can skip the questions which are least important (Lowest Priority). Secondly just refer the blueprints which will help you to predict questions and lastly don t forget to refer question papers. You will get those on Brainheaters. We will send you a Free soft copy of Importance at your address. As per scheduled date. With love Team Brainheaters You can also enjoy trips, share projects, write a Blog, Be a Author at Brainheaters. We support our students everywhere. Visit: Page no - 131