Friday, 7 February 2020

Query Processing and Optimization


Query Processing and Optimization

? In this unit, you have study query processing and evaluation.
? A query in a DBMS is a very important operation, as it needs to be efficient.
? Query processing involves query parsing, representing query in alternative forms, finding
the best plan of evaluation of a query and then actually evaluating it.
? The major query evaluation cost is the disk access time.
? In this unit, we have discussed the cost of different operations in details.
? However, an overall query cost will not be a simple addition of all such costs.

Index scan: Search algorithms that use an index are restricted because the selection condition
must be on the search-key of the index.
Indexing: A database index is a data structure that improves the speed of operations on a database
Join: Join operation is considered as the real power behind the relational database
Query cost: Cost is generally measured as total elapsed time for answering the query.

Parallel Databases? Parallel database machine architectures have evolved from the use of exotic hardware to a software parallel dataflow architecture based on conventional shared-nothing hardware.
? These new designs provide impressive speedup and scale-up when processing relational database queries.

Horizontal Partitioning: Horizontal partitioning a fact table speed up queries without indexing, by minimizing the set of data to be scanned.
Inter-query Parallelism: Inter-query parallelism is the ability to use multiple processors to
execute several independent queries simultaneously.
Intra-query Parallelism: Intra-query parallelism is the ability to break a single query into
subtasks and to execute those subtasks in parallel using a different processor for each.
OLTP: Online Transactional Processing
Parallel Database: Parallel database system is one that seeks to improve performance through
parallel implementation of various operations such as loading data, building indexes, and
evaluating queries.

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