Suppose That You Are A Manufacturer Of Product ABC
Suppose That You Are A Manufacturer Of Product Abc Which Is Composed
Suppose that you are a manufacturer of product ABC, which is composed of parts A, B, and C. Each time a new product ABC is created, it must be added to the product inventory, using the PROD_QOH in a table named PRODUCT. Also, each time the product is created, the parts inventory, using PART_QOH in a table named PART, must be reduced by one each of parts A, B, and C. The sample database contents are shown in the following tables.
Given the preceding information, answer questions a through e:
1. How many database requests can you identify for an inventory update for both PRODUCT and PART?
2. Using SQL, write each database request you identified in Step a.
3. Write the complete transaction(s).
4. Write the transaction log, using Table 10.1 as your template.
5. Using the transaction log you created in Step d, trace its use in database recovery.
Describe the three most common problems with concurrent transaction execution. Explain how concurrency control can be used to avoid those problems.
What DBMS component is responsible for concurrency control? How is this feature used to resolve conflicts?
Using a simple example, explain the use of binary and shared/exclusive locks in a DBMS.
Suppose that your database system has failed. Describe the database recovery process and the use of deferred-write and write-through techniques.
Paper For Above instruction
The management and maintenance of data consistency and integrity are fundamental to database systems. In an environment where a manufacturer produces products comprising multiple parts, maintaining accurate inventory data is critical. This paper explores the process of updating inventory when manufacturing a product, focusing on SQL requests, transaction management, concurrency control, and recovery processes, specifically within the context of a manufacturing scenario involving product ABC and its components A, B, and C.
When a new product ABC is manufactured, it necessitates updating the product inventory and adjusting the parts inventory accordingly. The key database requests include inserting or updating the product’s quantity in the PRODUCT table and decrementing the quantities of each part in the PART table. The primary SQL requests involve increasing the product count and decreasing the stock of parts A, B, and C by one unit each. These requests are executed as part of a transaction to ensure atomicity and consistency.
The core SQL requests identified are as follows:
- Increment the product quantity in the PRODUCT table for product ABC
- Decrement the quantity of Part A in the PART table
- Decrement the quantity of Part B in the PART table
- Decrement the quantity of Part C in the PART table
Combining these into a complete transaction ensures that either all inventory updates occur together or none are executed if an error happens. The transaction might be structured as follows:
BEGIN TRANSACTION;
UPDATE PRODUCT SET PROD_QOH = PROD_QOH + 1 WHERE PRODUCT_ID = 'ABC';
UPDATE PART SET PART_QOH = PART_QOH - 1 WHERE PART_ID = 'A';
UPDATE PART SET PART_QOH = PART_QOH - 1 WHERE PART_ID = 'B';
UPDATE PART SET PART_QOH = PART_QOH - 1 WHERE PART_ID = 'C';
COMMIT;
The transaction log records each of these actions, typically capturing the before and after states of each change, transaction IDs, timestamps, and status (commit/abort). An example log entry might detail the start of the transaction, each update, and the commit or rollback point, following a template similar to Table 10.1.
In recovery scenarios, the transaction log is essential for restoring database consistency after failures. The log allows for redo operations to reapply committed transactions and undo operations to revert uncommitted changes, maintaining durability and atomicity.
Concurrency issues such as lost updates, temporary inconsistency, and deadlocks are common in multi-transaction environments. Concurrency control mechanisms like locking, timestamp ordering, or multiversion concurrency control (MVCC) prevent such problems. For example, locks ensure that conflicting transactions do not overwrite each other's data, preserving data integrity.
The DBMS component responsible for concurrency control is typically the transaction manager or lock manager. It assigns locks to transactions, controlling access to data objects. When conflicts arise, such as simultaneous updates, the lock manager resolves them by granting or waiting for locks based on lock compatibility and transaction priorities.
Locks in a DBMS manage concurrent access through different modes. Binary locks are simple, allowing either a lock or no lock. Shared (read) locks permit multiple transactions to read data concurrently, whereas exclusive (write) locks prevent others from reading or writing the data until the lock is released. For example, if Transaction A has a shared lock on a row, other transactions can also acquire shared locks but not exclusive locks on the same row.
In case of system failure, recovery processes involve restoring the database to a consistent state using backup copies and transaction logs. Deferred-write (lazy) techniques buffer changes in memory and write them to disk periodically, improving performance but risking data loss if a crash occurs before flushing. Write-through ensures each change is immediately written to disk, minimizing data loss but impacting performance.
References
- Database Design and Relational Theory: Normal Forms and All That Jazz. O'Reilly Media.
- Fundamentals of Database Systems. Pearson.