When considering adding indexes, several rules of thumb can help guide the decision. However, remember that each database environment and workload is unique. These rules can serve as a starting point, but it’s crucial to test and monitor the impact of any indexing changes in your specific environment. Here are some general guidelines:

  1. Primary and Foreign Keys:
    • Always index primary keys. Most database systems automatically create an index for primary keys.
    • Foreign keys should typically be indexed, especially if you frequently join associated tables.
  2. Highly Queried Columns:
    • Columns that are frequently used in WHERE clauses, JOIN operations, or ORDER BY statements are strong candidates for indexing.
  3. Selectivity:
    • Indexes are most effective on columns with high selectivity, where the column values are mostly unique.
    • Low selectivity columns (like a gender column with values ‘M’ or ‘F’) might not benefit as much from indexing, but they could benefit from bitmap indexes in some databases.
  4. Avoid Indexing on Highly Volatile Columns:
    • Columns that are frequently updated can make indexes on those columns expensive to maintain.
  5. Covering Indexes:
    • If certain queries select a specific subset of columns, consider creating a “covering” index that includes all of those columns. This allows the query to be satisfied entirely using the index, avoiding the need to access the table data.
  6. Composite Indexes:
    • If specific queries frequently filter or sort on multiple columns together, consider a composite index that includes those columns. However, the order of columns in the index matters, so it should match the order in which they’re used in queries.
    • Avoid making composite indexes too wide, as they consume more space and are more expensive to maintain.
  7. Write-heavy Tables:
    • If a table has a significant amount of insert, update, or delete operations, be cautious with indexing. Indexes can slow down write operations because they need to be updated every time data changes.
  8. Read vs. Write Considerations:
    • Indexes generally speed up read operations at the expense of slower write operations. The more indexes you have, the slower your write operations might become.
  9. Avoid Over-indexing:
    • Every index adds overhead to the system. It consumes additional storage and can impact write performance. Review indexes periodically to remove those that are not being used.
  10. Monitor and Analyze:
  • Use database-specific tools to analyze query plans and see how indexes are being used.
  • Monitor the performance impact of added or removed indexes.
  • Some databases provide automated index recommendation tools that can suggest potential indexes based on the workload.
  1. Maintenance:
  • Indexes can become fragmented over time, especially in environments with many data modifications. Regularly monitor and defragment or rebuild indexes as needed.
  • Also, keep statistics updated, as outdated statistics can lead to suboptimal query plans.
  1. Storage Considerations:
  • Indexes consume disk space. Ensure you have adequate storage and consider the disk I/O performance.

In conclusion, while these rules of thumb provide general guidance, always base indexing decisions on empirical evidence. Regularly review query performance, monitor index usage, and adjust your indexing strategy as your data and workload evolve.

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