What are algorithms for select operations in database system.
In database systems, "select" operations are part of query execution where data is retrieved according to certain criteria specified by the query. Various algorithms can be used to perform select operations efficiently, depending on the data organization, indexing, and specific requirements of the query. Some common algorithms used for select operations in databases include:
1. Full Table Scan:
- Also called a Linear Scan or Sequential Scan.
- The system scans every row in the table to find the ones that match the selection criteria.
- Typically used when there is no index that can help in finding the required data or when the selectivity is so low that it's cheaper to read the whole table instead of using an index.
2. Index Scan:
- Uses an index to find rows quickly without scanning the entire table.
- Can be further classified into Index Lookups or Index Range Scans depending on whether a specific value or a range of values is being looked for.
3. Binary Search:
- Used on sorted arrays or columns, often in combination with index structures.
- This method repeatedly divides the searchable data in half to efficiently find the target data according to the criteria.
4. Bitmap Index Scan:
- Uses bitmap indexes that represent the presence or absence of a value with bits.
- Can efficiently merge bitmaps to perform quick searches for rows that match multiple criteria.
5. Hashed-Based Search:
- Common for equality searches where an equality criterion is applied to a hashed field.
- A hash function is used to locate the data without scanning the entire table.
6. Join Algorithms for Select Operations:
When the select operation includes joining tables, different algorithms are applied:
- Nested Loop Join: For each row of the first table, it scans all rows in the second table to find matching rows.
- Sort-Merge Join: Sorts both tables and then merges them, efficiently processing join conditions.
- Hash Join: Builds a hash table on the join key from one of the tables, then scans the second table to find matching rows.
These are some of the core algorithms employed for select operations in relational database systems. The database query optimizer typically decides which algorithm to use based on the characteristics of the query, the presence of indexes, the size of the data, and statistics about data distribution. The goal is to minimize the response time and the computational resources required to execute the query.