SQL ignore part of WHERE if parameter is null

-

 

SQL ignore part of WHERE if parameter is null




Comments

Post a Comment

Popular posts from this blog

Indexing

-
Image
  Indexing MySQL supports several types of indexes, each designed for a specific scenario or use case. The most common types of indexes in MySQL are: B-tree Indexes: This is the most commonly used index type in MySQL, which stores data in a sorted tree structure. B-tree indexes work best for columns with high selectivity, meaning columns with a large number of unique values. B-tree indexes are suitable for queries that use comparison operators (such as =, >, <, etc.) on indexed columns. Hash Indexes: Hash indexes are designed for exact matches and work best for columns with low cardinality (few unique values). Hash indexes are faster than B-tree indexes for exact matches, but they cannot be used for range queries or partial matches. Full-Text Indexes: Full-text indexes are designed for searching large amounts of text data, such as articles or documents. Full-text indexes tokenize text data and create an index of the tokens, which allows for fast text searching. Full-text inde...
Read more

Handling Decimal Numbers in Java and PostgreSQL

-
  Handling Decimal Numbers in Java and PostgreSQL Background When working with decimal numbers such as percentages, monetary values, or other precise quantities, choosing the correct data types in both Java and PostgreSQL is critical to avoid precision loss and rounding errors. Java Data Types: Float vs BigDecimal Float and Double Use binary floating-point representation. Can introduce subtle rounding errors (e.g., 0.1 stored as 0.10000000000000001 ). Suitable for approximate scientific calculations or measurements where minor inaccuracies are acceptable. BigDecimal Uses exact decimal representation. Ideal for financial calculations, percentages, or anywhere exact decimal precision is required. Stores scale (number of digits after the decimal point) explicitly. PostgreSQL Data Types: FLOAT vs NUMERIC FLOAT (or DOUBLE PRECISION ) Approximate, binary floating-point storage. Can cause precision errors similar to Java Float / Double . ...
Read more