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DBMS → Introduction to DBMS 31

Recoverable schedule ensures
T_j commits only AFTER all transactions whose data it read have committed
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Cascadeless schedule prevents
Cascading rollbacks by allowing reads ONLY of committed data
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ARIES Redo pass
Repeats ALL logged operations to bring DB to exact crash-time state
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ARIES Undo pass
Reverses loser (uncommitted at crash) transaction operations in reverse log order
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Log Sequence Number (LSN)
Uniquely identifies and orders each log record (monotonically increasing)
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Fuzzy checkpoint allows
Active transactions to continue while checkpoint record written to log
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The 'lost update' problem occurs when
Two transactions update same item and one update is overwritten by the other
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ARIES uses which buffer management policy combination
No-Force + Steal
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Rigorous 2PL holds
ALL locks (S and X) until transaction commits or aborts
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A database block/page is
Unit of data transfer between disk and memory (fixed-size)
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Seek time is
Time to move disk arm to the correct track
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Rotational latency is
Time for correct sector to rotate under read/write head
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Buffer pool is
Portion of main memory caching database pages
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LRU buffer replacement replaces
LEAST recently used page (oldest access time)
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Query cost is primarily measured by
Number of disk I/O operations
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Query optimization selects
Most efficient (lowest cost) execution plan from equivalent alternatives
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Pushing selection (σ) down operator tree
Reduces intermediate result sizes - fewer tuples flow to expensive operators
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Pipelining in query processing
Passes tuples directly from one operator to next without full materialization
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External sort is needed when
Data too large for main memory - disk used for intermediate sorting
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Heap file stores records
In insertion order with no particular ordering
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Static hashing limitation is
Bucket overflow and degradation with data growth or shrinkage
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RAID 1 provides
Data mirroring full redundancy across two disks
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RAID 5 uses
Striping with distributed parity (can recover from one disk failure)
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A covering index
Satisfies query entirely from index without accessing base table
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Bitmap index is efficient for columns with
Low cardinality (few distinct values like gender, status)
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Function-based index allows
Indexing result of expression/function applied to columns
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Composite index on (A,B) benefits queries on
A alone OR A+B together (NOT B alone without A)
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REBUILD INDEX vs REORGANIZE: REBUILD
Drops and recreates the index completely eliminating all fragmentation
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Partial (filtered) index includes
Only rows satisfying a WHERE filter condition
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Sequential file organization
Stores records in sorted order based on key field
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Statistics in query optimizer are used to
Estimate data distribution and cardinality for cost estimation
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DBMS → Transactions 1

Transaction state 'aborted' means
Rolled back and database restored to pre-transaction state
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DBMS → Indexes 6

A clustered index stores
Data in same sorted order as the index
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A dense index has
One index entry for EVERY record in the data file
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A sparse index has
Index entries for ONLY SOME records (typically one per data block)
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B+ tree supports
Both equality AND range queries with O(log n) performance
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Hash index is best for
Equality queries (exact match =)
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In B+ tree all data records are stored at
Leaf nodes
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DBMS → Joins 2

Sort-Merge Join requires
Both relations sorted on join attribute
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Hash Join build phase
Hashes SMALLER relation into memory hash table
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