Handling large lists of mobile numbers in a database can be challenging, especially when querying, updating, or searching through millions of records. Poorly optimized queries can lead to slow performance, high resource consumption, and frustrated users. To ensure efficient operations, database queries must be carefully optimized with appropriate strategies and best practices.
1. Use Proper Indexing
Indexes are the backbone of query optimization, especially for large datasets:
Create Indexes on Mobile Number Columns:
Since queries on mobile numbers often involve filtering or searching by number, create an index on the mobile number column. This allows the database to quickly locate rows without scanning the entire table.
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CREATE INDEX idx_mobile_number ON users (mobile_number);
Use Unique Indexes If Possible:
If mobile numbers are unique in your table, a unique index or recent mobile phone number data constraint improves lookup speed and prevents duplicates.
Consider Composite Indexes:
If queries filter on mobile numbers along with other columns (e.g., status, region), composite indexes on multiple columns may boost performance.
2. Normalize Mobile Numbers
Normalize all mobile numbers to a consistent format (e.g., E.164) before storing. This allows:
Faster and More Accurate Queries:
No need for complex string manipulation or pattern matching in queries.
Simplified Index Usage:
Consistent formatting ensures the index is used efficiently.
Normalization reduces the risk of searching for multiple variants of the same number.
3. Avoid SELECT * Queries
Be explicit in your SQL queries:
Select Only Necessary Columns:
Instead of SELECT *, specify only the columns you need. This reduces I/O overhead and memory usage.
Example:
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SELECT mobile_number, user_name FROM users WHERE mobile_number = '+1234567890';
4. Use Batch Processing for Large Queries
When dealing with very large mobile number lists (e.g., millions), avoid loading or processing all data at once:
Batch Queries:
Break large queries into smaller batches using LIMIT and OFFSET or keyset pagination to process data incrementally.
Temporary Tables or Table Variables:
Store large mobile number lists in temporary tables to join with your main table efficiently.
5. Optimize WHERE Clauses
Use simple, sargable conditions that allow indexes to be used effectively. For example, avoid wrapping indexed columns in functions:
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-- Avoid this, because it disables index usage
WHERE LOWER(mobile_number) = '...'
-- Instead, store normalized lowercase numbers and query directly
WHERE mobile_number = '...'
6. Consider Using Full-Text or Specialized Search Indexes
If queries involve partial matches, prefixes, or fuzzy searching:
Implement full-text indexes or specialized search engines like Elasticsearch.
These are better optimized for searching substrings or patterns in large datasets than standard SQL indexes.
7. Leverage Caching
Cache frequent query results in application memory or caching layers like Redis.
Avoid repeated database hits for the same mobile number lookups.
8. Partition Large Tables
For extremely large datasets, consider table partitioning by ranges or hash of the mobile number.