Assignment No: Create a College database and apply different queries on it. 2. Implement GUI for SQL queries and display result of the query

Transcription

1 Assignment No: 1 GUI Implementation for SQL queries Learning Outcomes: At the end of this assignment students will be able to To create a simple table Write queries for the manipulation of the table Design a GUI for query processing Problem Statement: 1. Create a College database and apply different queries on it. 2. Implement GUI for SQL queries and display result of the query on it. Description : Design College database with different tables. Write different SQL queries for creating table, inserting values in it. Apply different SELECT, UPDATE and DELETE queries. Design a GUI for any SQL query execution using JAVA Swing. Display the result of the query accordingly. Display the SELECT query result in a tabular format. Use SQL, JDBC Concepts and also use DBE Concepts.

2 GUI with Input/Output :

3 Assignment No: 2 Implementation of Two phase commit protocoll Learning Outcomes: At the end of this assignment students will be able to Write the working of 2PC protocol List out the messages generated for 2PC protocol Design a GUI for 2PC protocol Problem Statement: 1. Implementation of two phase commit protocol 2. Implement GUI for server and clients (atleast for four sites). Description : 2-Phase commit protocol is one type of commit protocol which is used in distributed databases. Server will send the <Prepare T> message to all Clients. After receiving <Prepare T> message, client can reply back with <Ready T> or <Abort T>. Client reply with <Ready T> if it is ready for the transaction otherwise it will reply with <Abort T>. Server will receive reply of all clients. Then it takes decision either to commit the transaction or to abort the transaction. If all clients send <Ready T> message then only server take decision to commit the transaction otherwise it will take decision to abort the transaction. Server will send its decision to all clients with either <Commit T>or <Abort T>. Client will receive that message and behave according to server s decision.

4 GUI with Input/Output : Server : Clients :

5 Assignment No: 3 Implementation of Bully Algorithm for coordinator selection Learning Outcomes: At the end of this assignment students will be able to Explain the working of Bully algorithm Identify the new coordinator in the distributedd databases environment in case of a coordinator failure Problem Statement: Implementation of Bully algorithm for a new coordinator selection in case of a failure of coordinator in a distributed database environment. Description : Bully algorithm is used for the election of the coordinator in a distributed database if the coordinator fails in the network. Consider at least 4 clients for the implementation. Here election is based on Si value of different site. The highest Si value site is the coordinator always. Each site sends the signal to the current coordinator. If it will not get reply from coordinator, it assumes that coordinator is failed. So that site start Bully algorithm and try to select itself as a new coordinator. This site sends its election message to its higher valued sites. If the high valued site is active it replies back to the previous site about its coordinator ship. Bully algorithm will check different value of Si of different sites and elect a site as new coordinator which has highest Si value. After the coordinator selection send message to other sites.

6 GUI with Input/Output : Example screen for Site 1: (Similarly do it for other four sites considering total five sites for implementation)

7 Assignment No: 4 Implementation of semi-join algorithm for distributed database d Learning Outcomes: At the end of this assignment students will be able to List & Explain the five steps of Semijoin algorithm Demonstrate and produce the partial results of all the steps of semijoin algorithm Problem Statement: Implement the five steps of Semijoin algorithms for two sitess (consider the proper database for its implementation). Description : Design two different relations r1 and r2 on two different sites. Compute the common attribute of two relations. Compute Temp1 π 1 2(r1) at S1 i.e. select only common attribute values from relation r1 of site S1 as Temp1. Ship Temp1 from site S1 to site S2. Compute Temp2 r2 >< Temp1 at S2 i.e. select the tuples of the common attributes from r2 as temp2. Ship Temp2 from site S2 to site S1. Compute r1 >< Temp2 at S1 i.e. compute join of Temp2 and relation r1 at site S1.

8 GUI with Input/Output Site-S1: Site-S2:

9 Assignment No: 5 Implementation of Partitioning Techniques in parallel databases d Learning Outcomes: At the end of this assignment students will be able to List & Elaborate the three partitioning techniques in parallel databases Differentiate the working of the three partitioning techniques Problem Statement: 1. Implement the three partitioning techniques (Round Robin Partitioning, Hash Partitioning & Range Partitioning). 2. Partition the given table contenets according to the selected partitioning technique. Description : Read the relation name from user. Consider three partitioning techniques as: Round robin, Hash or Range. Partition the given relation by using different partitioning techniques. Round Robin partitioning: Scans the relation in any orderr and sends i th tuple to disk d i mod n. Hash partitioning: Use a partitioning attribute and calculate hash value using a Hash function. Send the tuple to appropriate hash Bucket. Range partitioning: Use a partitioning attribute; check the range of each tuple with partitioning attribute.and send the tuple to appropriate range partition.

10 GUI with Input/Output:

11 Assignment No: 6 Implementation of Inter Query Parallelism Learning Outcomes: At the end of this assignment students will be able to Analyze the query execution and its parallel working Design & implement a multithreaded program for inter query parallelism Problem Statement: 1. Implement interquery parallelism for a database 2. Execute multiple queries parallely using threads Description : Consider 3 or more sites and relations. Design three different relations r1, r2 and r3 on three different sites as Clients. Implement GUI for one Server site and three different Client sites Read three different queries from queries at server site Send three queries to three respective client sites. At each client site execute query and display the result at client side and send back the query result at server site. Collect the respectivee query result from every client and display at server site.

12 GUI with Input/Output Server: Client:

13 Assignment No: 7 Implementation of Parallel Sort algorithm (Intra-operation parallelism) Learning Outcomes: At the end of this assignment students will be able to Illustrate Parallel sort algorithm Design & implement a multithreaded program for intra operation parallelism Problem Statement: 1. Implement intra operation parallelism using parallel sort algorithm 2. Partition the data using range partitioning in to partitions and parallely sort all partition and merge the contents. (Use multithreading) Description : In Intra-operation parallelism one operation executes in parallel on different processors. Consider the operation as sorting the tuples of a big relation Parallelize this sorting using Parallel Sort technique. Take the sorting attribute as the partitioning attribute. Read a relation and partition its tuples using range partitioning technique. Consider three or more clients (processors) and send each partition to different client. Sort the partition at client side locally. (or consider three threads) Send each local sorted runs at server.

14 Finally merge the sorted partitions to obtain the final sorted relation at server. Here as range partitioning is used to partition the relation the sorted runs are directly concatenated finally at the server side. Can Use multithreading to implement this program. GUI with Input/Output: Using multithreading on a single site:

15 Assignment No: 8 Implement Partitio oned Join (Intra-operation paralleli ism) Learning Outcomes: At the end of this assignment students will be able to Describe Partitioned join operation Design & implement a multithreaded program for intra operation parallelism for join operation Problem Statement: 1. Implement intra operation parallelism for partitioned join operation 2. Partition the data using range partitioning in to partitions and parallely join the partition and merge the contents. (Use multithreading) Description : Partitioned Join is using Intra-operation parallelism. Consider two relations as r & s. Consider the join attribute as the partitioning attribute. Partition the two relations (3 or more partitions) using range (or any other) partitioning technique. Consider one server and three clients as S1, S2 and S3. Send partition r1, s1 at site S1, r2, s2 at site S2 and r2,s2 at site S3. Each processor (or site or thread) will do the Join operation locally between two respective partitions of relations r & s. (means Join of r 0 & s 0, r 1 & s 1, and r3 & s3). Finally merge all Join results to obtain the final result of Join operation between relations r & s.

16 Here join attribute is taken as partitioning attribute the tuples of same join attribute value will be separated in a same partition for both relations. So, it is not necessary to check each join attribute value with all tuples in another relation only every tuple in the partition is compared with all tuples of the same partition and finally the result is concatenated. GUI with Input/Output:

17 Assignment No: 9 Implementation of Partitioned Parallel Hash Join Learning Outcomes: At the end of this assignment students will be able to Describe Partitioned parallel hash join operation Design & implement a multithreaded program for partitioning Problem Statement: 1. Implement partitioned parallel hash join operation 2. Double Partition the data using Hash partitioning in to partitions and parallely join the partition and merge the contents. (Use multithreading) Description : Partitioned Parallel Hash Join is one of the Intra-operation parallelism. Consider the two big relations as r & s and one server and three clients as three different processors. Partition the two relations in three partitions using a hash partitioning technique with hash function H1( ). At each client or processor again partition the two partitions by another Hash functionh2( ) say sub partitions. Each processor takes out the Join operation locally between two respective partitions of relations r & s. Use multithreading at each processor to parallelize every sub partition. Finally merge different Join results to obtain the final result of Join operation between relations r & s.

18 GUI with Input/Output:

19 Assignment No: 10 Implementation of Independent Parallelism for Inter-operation Parallelism Learning Outcomes: At the end of this assignment students will be able to Analyze independent Parallelism for inter operation Design & implement a multithreaded program for join operation Problem Statement: 1. Implement independent parallelism for join operation 2. Use multiple threads for independent operations Description : Independent parallelism of inter-operation parallelism splits the single operation in to different small parts in such a way that, every small operation is independent of each other and performs the operation in parallel& finally combines the result as required by the operation. Considering the join operation of four relations as r1, r2, r3 & r4 as: r1 r2 r3 r4and three processors as P1, P2 & P3. Perform r1 r2 at site P1 and store the result as Temp1. Perform r3 r4 at site P2 parallelly with P2 and store the result as Temp2. Finally perform Temp1 r4 Temp2 at site P3 as the output of r1 r2 r3

20 GUI with Input/Output: Site S1 GUI for Site S2:

21 GUI for Site S3:

22 Assignment No: 11 Implementation of OLAP Queries Learning Outcomes: At the end of this assignment students will be able to Write OLAP queries for a given requirement Demonstrate the working of OLAP using datacube Problem Statement: Consider a Sales table and do the OLAP operations on it. Description : Cube operator enables a SELECT statement to calculate subtotals for all possible combinationsns of a group of dimensions. It also calculates a grand total. This is the set of information typically needed for alll cross tabular,report with a single SELECT statement. Consider the table Sales(itemname,size,color,number) Example queries of OLAP: 1. select item_name,,color,sum(no) from sales group by cube(item_name,color); 2. select item_name, sum(no) from sales where item_name='skirt'; 3. select item_name, sum(no) from sales group by item_name; 4. select sum(no) from sales group by color; 5. select item_name,,color,sz,sum(no) from sales group by rollup (item_name,color,sz); 6. select item_name,,color,sz,sum(no)

23 from sales group by rollup (item_name,color,sz); 7. select std_marks.std_id,sec,rank() over (partition by sec order by marks desc) as sec_rank fromstd_marks,std_sec wherestd_marks.std_id=std_sec.std_id order by sec,sec_rank; 8. SQL> select acc no,date_time,sum(value) over (partition by acc no order by date_time rows unboundedpreceding) as balance from transaction order by acc_no,date_time; 9. select item_name,,color,sz,sum(no), grouping(item_name) as item_name_flag,grouping(color) as color_flag,grouping(sz) as sz_flag from sales1 group by cube(item_name,color,sz)

24 Implement an Assignment No: 12 algorithm for finding association rules Learning Outcomes: At the end of this assignment students will be able to Analyze the data for finding associations using data mining Demonstrate the association rules and claculate population & support for the selected item Problem Statement: For the given data find the association rule Calculate the population & support for the same Description : Association information can be used in several ways for associating one attribute with another attribute values. Like, when a customer buys a particular book, an online shop can suggest more associated books. Consider the shop offering discounts on its items. Show the Population, Support and Confidence for a relation.

25 GUI with Input/Output:

26 Assignment No: 13 Implement Decision Tree of Data Mining problem Learning Outcomes: At the end of this assignment students will be able to Analyze the data for using data mining Identify the decision using decision tree classifier Problem Statement: For the given data generate decision tree classifier Identify the category of a given data using decision tree classifier Description : Decision tree classifier is widely used technique for classification. Its each leaf node has an associated class and each internal node has a predicate associated with it. For classifying the instance, start at root and traverse the tree to reach a leaf. Consider the example of bank providing credit cards to its customer according to the criteria as : degree, income and age. Show the result as valid customers. Provide the grades as Excellent, Good, Average and Bad

27 GUI with Input/Output: