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DBMS → Introduction to DBMS 37

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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Pinning a buffer page means
Marking it as do-not-evict (currently in use)
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Multi-level index builds
Index on the index to reduce levels needed to find record
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Selectivity of a predicate is
Fraction of tuples satisfying the predicate (between 0 and 1)
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Equivalence rules in query optimization allow
Transforming one RA expression to another producing same result
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The iterator (volcano) model implements pipelining using
Open(), GetNext(), Close() interface on each operator
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Materialization in query processing
Fully computes and stores intermediate result before passing to next operator
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External sort complexity for n blocks, B buffer frames is approximately
O(n log_B n) passes
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ISAM supports
Both sequential access AND indexed access (but static overflow)
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Histogram in query optimizer stores
Distribution of attribute values for better cardinality estimation
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Why is sequential disk access faster than random?
No seek time or rotational latency between consecutive blocks
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Index seek vs index scan: index SEEK
Traverses B+tree to find specific key (fast for selective queries)
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Fill factor in index creation specifies
Percentage of each index page to fill leaving space for future inserts
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Linear hashing
Splits buckets incrementally in linear order without sudden doubling
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Extendible hashing solves static hashing by
Dynamically doubling directory size and splitting buckets as needed
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Double buffering allows
I/O of next block to overlap with CPU processing of current block
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The Selinger optimizer uses
Dynamic programming to find optimal join ordering with estimated costs
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Laravel Eloquent is
ORM using Active Record pattern mapping tables to PHP classes
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php artisan make:model Question creates
New Eloquent model class in app/Models
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Eloquent assumes table name is
Plural snake_case of model (User→users, Question→questions)
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To override Eloquent table name
Set protected $table = 'custom_name'
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Question::all() returns
Collection of all Question model instances
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Question::find(1) returns
Question with PK=1 or NULL if not found
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findOrFail($id) when ID not found
Throws ModelNotFoundException
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Eager loading with('posts') prevents
N+1 query problem by loading related models in 2 queries instead of N+1
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DBMS → Indexes 1

In B+ tree all data records are stored at
Leaf nodes
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DBMS → Joins 1

A left-deep join tree has
All inner (right) inputs as base tables
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DBMS → Relational Model 1

Primary key in MySQL InnoDB automatically creates
Clustered index
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