MySQL raises ER_STD_UNDERFLOW_ERROR (error 3051, SQLSTATE HY000) when a numeric calculation produces a value too small for the target data type.
ER_STD_UNDERFLOW_ERROR in MySQL signals a numeric underflow during runtime math. Check data types, widen column precision, and guard calculations with CAST or ROUND to resolve the issue.
ER_STD_UNDERFLOW_ERROR
MySQL throws error 3051 ER_STD_UNDERFLOW_ERROR when a runtime arithmetic operation produces a result so small that it cannot be represented by the destination data type. The server stops the statement and returns SQLSTATE HY000.
Underflow differs from overflow: instead of exceeding the upper limit, the value approaches zero beyond the lower precision the type can hold. Fixing it is critical because silent truncation would corrupt analytical results.
The error appears in MySQL 5.7.5 and later during SELECT, INSERT, UPDATE, or stored program execution that involves division, exponential, or aggregation calculations on DECIMAL, DOUBLE, or FLOAT columns.
Developers commonly see it after migrating schemas to narrower numeric types or adding strict SQL mode settings that disallow silent underflow.
Unresolved underflow halts ETL pipelines, causes application exceptions, and prevents data from persisting. Addressing it quickly keeps dashboards current and avoids downstream nulls.
Consistent handling also preserves numeric accuracy, protecting financial and scientific computations.
Division of very small numbers (e.g., 1e-20) stored in FLOAT(6) can underflow to zero, triggering the error when strict SQL mode is active.
Storing high-precision scientific or monetary values in DECIMAL columns with insufficient scale frequently causes the issue during aggregation.
Casting from DOUBLE to FLOAT without ROUND or CEILING results in intermediate values smaller than the minimum FLOAT positive number.
First, identify the offending expression by reviewing the stack in the error log or isolating columns until the failing operation is found.
Next, widen the destination data type or use higher precision expressions with CAST. For one-off queries, ROUND the result to a representable scale.
Scenario: dividing sums of very small decimal values. Solution: switch to DECIMAL(38,20) or DOUBLE and wrap the expression in CAST to guarantee capacity.
Scenario: migrating data into a FLOAT column. Solution: migrate into DOUBLE or DECIMAL and adjust application code to reference the new column.
Design schemas with ample precision by estimating the smallest expected positive value and adding safety margin.
Enable automated tests that run boundary value inserts and computations in CI to detect underflows early.
Use Galaxy's semantic layer to store endorsed high-precision query building blocks so teammates reuse safe numeric definitions.
ER_DATA_OUT_OF_RANGE (1264) - occurs on overflow, fix by widening type or clamping input.
ER_DIVISION_BY_ZERO (1365) - raised when divisor is zero, resolve with NULLIF or CASE guards.
ER_TRUNCATED_WRONG_VALUE (1292) - fired on invalid numeric literal, correct the format or use CAST.
Floating-point division that returns numbers smaller than the minimum positive value of FLOAT or DOUBLE under strict SQL mode triggers underflow.
DECIMAL columns defined with too few fractional digits reject results that cannot be rounded into the specified scale.
MySQL silently casts higher precision operands to the lower precision type of the result column, producing an underflow.
SUM, AVG, or STDDEV on columns populated with very small numbers can create underflow during intermediate calculations.
Raised on numeric overflow rather than underflow. Fix by enlarging data type or using numeric checks.
Occurs when divisor equals zero. Guard with CASE or NULLIF.
Triggered by invalid numeric format. Resolve by correcting literal formats or using CAST.
No. It was introduced in MySQL 5.7.5. Earlier versions silently truncated underflow.
You can remove strict settings, but this hides data problems. Prefer fixing precision.
Galaxy's AI copilot inspects column definitions and suggests widening precision or adding CAST before you run the query, reducing runtime failures.
The impact is minimal for most workloads; numeric accuracy gains typically outweigh any slight storage increase.
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