Lecture7 - ECS 165B: Database System Implementa6on Lecture...

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ECS 165B: Database System Implementa±on Lecture 7 UC Davis April 12, 2010 Acknowledgements: por±ons based on slides by Raghu Ramakrishnan and Johannes Gehrke.
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Class Agenda Last 6me: Dynamic aspects of B+ Trees Today: Summary: tree-structured indices Overview of query evalua6on Reading Chapter 12 in Ramakrishan and Gehrke (or Chapter 13 in Silberschatz, Korth, and Sudarshan)
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Announcements Expanded set of tests posted: /home/cs165b/DavisDB/TestRM.cpp Page Fle manager bugFxes: /home/cs165b/DavisDB/Page±ileManager.cpp, h /home/cs165b/DavisDB/±ileHandle.cpp Have you done an svn commit lately?
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Summary: Tree-Structured Indices
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Database Management Systems 3ed, R. Ramakrishnan and J. Gehrke 25 Summary Tree-structured indexes are ideal for range- searches, also good for equality searches. ISAM is a static structure. Only leaf pages modified; overflow pages needed. Overflow chains can degrade performance unless size of data set and data distribution stay constant. B+ tree is a dynamic structure. Inserts/deletes leave tree height-balanced; log F N cost. High fanout ( F ) means depth rarely more than 3 or 4. Almost always better than maintaining a sorted file.
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Database Management Systems 3ed, R. Ramakrishnan and J. Gehrke 26 Summary (Contd.) Typically, 67% occupancy on average. Usually preferable to ISAM, modulo locking considerations; adjusts to growth gracefully. If data entries are data records, splits can change rids! Key compression increases fanout, reduces height. Bulk loading can be much faster than repeated inserts for creating a B+ tree on a large data set. Most widely used index in database management systems because of its versatility. One of the most optimized components of a DBMS.
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Overview of Query Evalua6on Reading: Chapter 12 of Ramakrishnan and Gehrke (Chapter 13 of Silberschatz et al)
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2 Overview of Query Evaluation Plan : Tree of R.A. ops, with choice of alg for each op. Each operator typically implemented using a `pull’ interface: when an operator is `pulled’ for the next output tuples, it `pulls’ on its inputs and computes them. Two main issues in query optimization: For a given query, what plans are considered? • Algorithm to search plan space for cheapest (estimated) plan. How is the cost of a plan estimated? Ideally: Want to find best plan. Practically: Avoid worst plans! We will study the System R approach.
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This note was uploaded on 04/29/2010 for the course ECS 152 taught by Professor Mr. during the Spring '10 term at University of Great Falls.

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Lecture7 - ECS 165B: Database System Implementa6on Lecture...

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