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CUSTOMER_CODE SMUDE DIVISION_CODE SMUDE EVENT_CODE APR2016 ASSESSMENT_CODE MCA3020_APR2016 QUESTION_TYPE DESCRIPTIVE_QUESTION QUESTION_ID 18252 QUESTION_TEXT Discuss Lorel Query Language. Differentiate between XML Oriented Databases and Native XML Databases. SCHEME OF EVALUATION Lorel Query Language:Lorel is considered as an early query language used for semi structured data. Lorel language makes use of the OEM (Object Exchange Model) as the data model for semi structured data. Lorel is utilized to expandOQL (Object Query Language) for the procedure of querying elements. This is done by depending on coercion at various levels to hold back the powerful typing of OQL. Lorel is also used to extend OQL with path expressions. This is done in order that user can state the patterns that are corresponding to actual paths in referred data.(4 marks) One of the advantages of Lorel language is its easy syntax which makes users to understand it more clearly. The drawback of Lorel language is that it is dependent on OQL parser. Also it comprises of limited functionalities. (2 marks) Differences between XML Oriented Databases and Native XML Databases: XML-oriented databases are typically relational and enclose model or pattern driven extensions for transporting data to and from XML documents and are usually intended for data-centric documents. Following are the differences between XML Oriented Databases and Native XML Databases: 1.A native XML database is used to maintain physical structure. An XML-oriented database can do so also, but practice shows a diverse story. 2.Native XML database can accumulate data without schema. We could make use of techniques to recognize structure in unprocessed documents to be accumulated in XML-oriented systems. These types of techniques are relatively limited. 3.XPath, DOM, or comparable XML-associates APIs are required to access data in native XML systems. Alternatively, XML-oriented systems provide direct access to the data via open-standard APIs, like open database connectivity (ODBC). (4 marks) QUESTION_T DESCRIPTIVE_QUESTION YPE QUESTION_ID 73630 QUESTION_T Discuss any five SQL features in detail. EXT 5 features - >2 marks each. Any 5 features among those mentioned below may be written SCHEME OF EVALUATION QUESTION_TYPE DESCRIPTIVE_QUESTION QUESTION_ID 125269 QUESTION_TEXT What is denormalization? Explain its techniques. Definition – 2 marks each SCHEME OF EVALUATION 4 techniques – 2 marks Denormalization is the process of converting higher normal norms to lower normal forms with the objective of getting faster access to database. (a) Duplicate data – method of adding duplicate data into relational table. This will minimize the number of joins required to execute a given query. It also minimizes the CPU and I/O resources being utilized as well as boosts up the performance (b) Summary data – records are summarized in some summary columns thereby reducing the number of records stored in a table. This enhances database performance as now the database server needs to process lesser records for a given query execution (c) Horizontal partitioning – table is split by rows thereby reducing the number of records paer table and hence drives the performance (d) Vertical fragmentation – breaks relations by columns. It makes more than 2 tables by allocating the original key to all and allocating a few of the non key columns to every newly made identical keyed table QUESTION_TYPE DESCRIPTIVE_QUESTION QUESTION_ID 125271 QUESTION_TEXT Differentiate between BCNF and 3 NF. Comparison of BCNF and 3NF We have seen BCNF and 3NF. It is always possible to obtain a 3NF design without sacrificing losslessjoin or dependency-preservation. SCHEME OF EVALUATION If we do not eliminate all transitive dependencies, we may need to use null values to represent some of the meaningful relationships. Repetition of information occurs. These problems can be illustrated with Banker-schema. As banker-name bname , we may want to express relationships between a banker and his or her branch. Figure : An instance of Banker-schema. Figure shows how we must either have a corresponding value for customer name, or include a null. Repetition of information also occurs. Every occurrence of the banker's name must be accompanied by the branch name. If we must choose between BCNF and dependency preservation, it is generally better to opt for 3NF. If we cannot check for dependency preservation efficiently, we either pay a high price in system performance or risk the integrity of the data. The limited amount of redundancy in 3NF is then a lesser evil. To summarize, our goal for a relational database design is BCNF. Lossless-join. Dependency-preservation. If we cannot achieve this, we accept 3NF Lossless-join. Dependency-preservation. A final point: there is a price to pay for decomposition. When we decompose a relation, we have to use natural joins or Cartesian products to put the pieces back together. This takes computational time. QUESTION_TYPE DESCRIPTIVE_QUESTION QUESTION_ID 125272 QUESTION_TEXT What is an external sort algorithm? Explain with an example. A sort can be classified as being internal if the records that it is sorting are in main memory, or external if some of the records that it is sorting in auxiliary storage. External Sorting: When the size of file to be sorted is bigger than that of available memory. External sorting algorithms are more device dependent than internal sorting. External Merge Sort is a relatively common used algorithm, based on the internal sorting and external merging principle. In general, this strategy is called Divide and Conquer : 1. Divide the data into parts that are as small as possible 2. After applying the sorting algorithm on those parts, remerge them SCHEME OF EVALUATION Those already sorted portions of data are called runs. For the working process, initial runs must be created. According to this strategy, all data is to be split into several smaller parts that fit to main memory completely: Assuming we have to sort n records of equal length stored in a file. The system’s main memory can hold exactly p records with p << n. So the source file is divided into [n / p] parts. After sorting all of them they represent the initial runs. At the end, for retrieving the complete sorted set, those parts need to be merged. 4marks External Sorting Algorithm carries out the operation in following 2 phases : Sorting Phase Merging Phase Sorting Phase: In this phase, the runs are read into the main memory. Over there the runs are sorted by using internal sorting algorithm and the result is written back to the disk as temporary sorted runs. The number of initial runs and the size of a run are governed by the number of file blocks and available buffer space. For Instance: If nB = 5 blocks b = 1024 blocks Then, nR =[(b/ nB ) =205 intial runs each of size 5 blocks Merging Phase In this phase, merging of the sorted runs is carried out over one or more phase. The number of runs that can be merged together in each pass is termed as the degree of merging. QUESTION_TYPE DESCRIPTIVE_QUESTION QUESTION_ID 125275 QUESTION_TEXT Discuss Semantic Query Optimization. What are the various Execution Strategies for SQL Sub Queries? Semantic Query Execution: Semantic Query Execution is a technique to modify one query into another query by using the relational database constraints. These constraints may be unique attributes or much more complex constraints. This technique is used for the efficient execution of the query. (1 mark) Consider the example below: Select E.LNAME, M.LNAME SCHEME OF EVALUATION FROM EMPLOYEE AS E, EMPLOYEE AS M WHERE E.SUPERNO=M.ENO AND E.SALARY>M.SALARY marks) (2 This query retrieves the names of employees who earn more than their supervisors. If a constraint is applied on the database schema to check that none of the employee can earn more than his reporting supervisor; the semantic query optimizer checks for this constraint and may not execute the query if it knows that the resultant query will be empty. If the constraint check is done efficiently then this approach can save a lot of time. (2 marks) Execution Strategies for SQL Sub Queries: Different physical execution strategies are employed by query optimizer for the various logical query plan options. Two types of strategies are there for sub query execution: 1. Navigational Strategies 2. Set-Oriented Processing (1 mark) 1. Navigational Strategies: For executing sub-query, navigational strategies depends on the nested loops joins. Basically there are two classes of navigational strategies: forward lookup and reverse lookup. Forward lookup firstly starts executing the outer query and when outer rows are generated then it invokes the sub-query. Reverse lookup starts with the sub-query and processes one sub-query row at a time. (2 marks) 2. Set-Oriented Processing: Set-Oriented Processing finally needs that the query could be effectively de-correlated. If this is the situation, set operations for example hash, merge and join can execute the query. (2 marks)