Database management concepts Database Management Systems (DBMS) An

Database management concepts Database Management Systems (DBMS) An example of a database (relational) Database schema (e.g. relational) Data independence Architecture of a DBMS Types of DBMS Basic DBMS types Retrieving and manipulating data: query processing Database views Data integrity Client-Server architectures Knowledge Bases and KBS (and area of AI) DBMS tasks:

Managing large quantity of structured data Efficient retrieval and modification: query processing and optimization Sharing data: multiple users use and manipulate data Controlling the access to data: maintaining the data integrity An example of a database (relational): Relations (tables) Attributes (columns) Tuples (rows) Example query: Salesperson='Mary' AND Price>100. Database schema (e.g. relational): Names and types of attributes Addresses Indexing

Statistics Authorization rules to access data etc. Data independence: separation of the physical and logical data Particularly important for distributed systems The mapping between them is provided by the schema Architecture of a DBMS - three levels: external, conceptual and internal schema Types of DBMS The data structures supported: tables (relational), trees, networks, objects Type of service provided: high level query language, programming primitives Basic DBMS types Linear files Sequence of records with a fixed format usually stored on a single file Limitation: single file

Example query: Salesperson='Mary' AND Price>100 Hierarchical structure Trees of records: one-to-many relationships Limitations: Requires duplicating records (e.g. many-to-many relationship) Problems when updated Retrieval requires knowing the structure (limited data independence): traversing the tree from top to bottom using a procedural language Network structure: similar to the hierarchical database with the implementation of many-to-many relationships Relational structure Object-Oriented structure Objects (collection of data items and procedures) and interactions between them. Is this really a new paradigm, or a special case of network structure?

Separate implementation vs. implementation on top of a RDBMS Relational structure Relations, attributes, tuples Primary key (unique combination of attributes for each tuple) Foreign keys: relationships between tuples (many-to-many). Example: SUPPLIES defines relations between ITEM and SUPPLIER tuples. Advantages: many-to-many relationships, high level declarative query language (e.g. SQL) SQL example (retrieve all items supplied by a supplier located in Troy): SELECT ItemName FROM ITEM, SUPPLIES, SUPPLIER WHERE SUPPLIER.City = "Troy" AND SUPPLIER.Supplier# = SUPPLIES.Supplier# AND SUPPLIES.Item# = ITEM.Item#

Programming language interfaces: including SQL queries in the code Retrieving and manipulating data: query processing Parsing and validating a query: data dictionary - a relation listing all relations and relations listing the attributes Plans for computing the query: list of possible way to execute the query, estimated cost for each. Example: SELECT ItemNames, Price FROM ITEM, SALES WHERE SALES.Item# = ITEM.Item# AND Salesperson="Mary" Index: B-tree index, drawbacks - additional space, updating; indexing not all relations (e.g. the keys only) Estimating the cost for computing a query: size of the relation, existence/size of the indices. Example: estimating Attribute=value with a given number of tuples and the size of the index.

Query optimization: finding the best plan (minimizing the computational cost and the size of the intermediate results), subsets of tuples, projection and join. Static and dynamic optimization Database views Creating user defined subsets of the database Improving the user interface Example: CREATE VIEW MarySales(ItemName,Price) AS SELECT ItemName, Price FROM ITEM, SALES WHERE ITEM.Item#=SALES.Item# AND Salesperson="Mary" Then the query: SELECT ItemName

FROM MarySales WHERE Proce>100 translates to: SELECT ItemName FROM ITEM, SALES WHERE ITEM.Item#=SALES.Item# AND Salesperson="Mary" AND Price>100 Data integrity Integrity constraints: semantic conditions on the data Individual constraints on data items Uniqueness of the primary keys Dependencies between relations Concurrency control

Steps in executing a query Concurrent users of the database, interfering the execution of one query by another Transaction: a set of operations that takes the database from one consistent state to another Solving the concurrency control problem: making transactions atomic operations (one at a time) Concurrent transactions: serializability theory (two-phase locking), read lock (many), write lock (one). Serializible transactions: first phase - accumulating locks, second phase - releasing locks. Deadlocks: deadlock detection algorithms. Distributed execution problems: release a lock at one node (all locks accumulated at the other node?) strict two-phase locking The Transaction Model Primitive

Description BEGIN_TRANSACTION Make the start of a transaction END_TRANSACTION Terminate the transaction and try to commit ABORT_TRANSACTION Kill the transaction and restore the old values

READ Read data from a file, a table, or otherwise WRITE Write data to a file, a table, or otherwise Examples of primitives for transactions. The Transaction Model BEGIN_TRANSACTION reserve WP -> JFK; reserve JFK -> Nairobi;

reserve Nairobi -> Malindi; END_TRANSACTION (a) a) b) BEGIN_TRANSACTION reserve WP -> JFK; reserve JFK -> Nairobi; reserve Nairobi -> Malindi full => ABORT_TRANSACTION (b)

Transaction to reserve three flights commits Transaction aborts when third flight is unavailable Distributed Transactions a) b) A nested transaction A distributed transaction Writeahead Log x = 0; y = 0;

BEGIN_TRANSACTION; x = x + 1; y=y+2 x = y * y; END_TRANSACTION; (a) Log Log

Log [x = 0 / 1] [x = 0 / 1] [y = 0/2] [x = 0 / 1] [y = 0/2] [x = 1/4] (b) (c)

(d) a) A transaction b) d) The log before each statement is executed Concurrency Control (1) General organization of managers for handling transactions. Serializability BEGIN_TRANSACTION x = 0; x = x + 1;

END_TRANSACTION (a) BEGIN_TRANSACTION x = 0; x = x + 2; END_TRANSACTION BEGIN_TRANSACTION x = 0; x = x + 3; END_TRANSACTION (b)

(c) Schedule 1 x = 0; x = x + 1; x = 0; x = x + 2; x = 0; x = x + 3 Legal Schedule 2 x = 0; x = 0; x = x + 1; x = x + 2; x = 0; x = x + 3; Legal

Schedule 3 x = 0; x = 0; x = x + 1; x = 0; x = x + 2; x = x + 3; Illegal (d) a) c) Three transactions T1, T2, and T3 d) Possible schedules Two-Phase Locking (1) Two-phase locking.

Two-Phase Locking (2) Strict two-phase locking. Data integrity Backup and recovery The problem of keeping a transaction atomic: successful or failed What if some of the intermediate steps failed? Log of database activity: use the log to undo a failed transaction. More problems: when to write the log, failure of the recovery system executing the log. Security and access control Access rules for relations or attributes. Stored in a special relation (part of the data dictionary).

Content-independent and content-dependent access control Content-dependent control: access to a view only or query modification (e.g. and-ing a predicate to the WHERE clause) Discretionary and mandatory access control Knowledge Bases and KBS (and area of AI) Information, Data, Knowledge (data in a form that allows reasoning) Basic components of a KBS Knowledge base Inference (reasoning) mechanism (e.g. forward/backward chaining) Explanation mechanism/Interface Rule-based systems (medical diagnostics, credit evaluation etc.)

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