apache/iceberg · error · UnsupportedOperationException

Expected value to be date or timestamp: ${valueType.catalogS

Error message

Expected value to be date or timestamp: ${valueType.catalogString()}

What it means

The days() SQL catalog function (year/month/day family — here DaysFunction) only accepts date or timestamp (incl. timestamp_ntz) values. Binding with any other value type throws UnsupportedOperationException including the actual type.

Source

Thrown at spark/v3.5/spark/src/main/java/org/apache/iceberg/spark/functions/DaysFunction.java:46

import org.apache.spark.sql.types.TimestampType;

/**
 * A Spark function implementation for the Iceberg day transform.
 *
 * <p>Example usage: {@code SELECT system.days('source_col')}.
 */
public class DaysFunction extends UnaryUnboundFunction {

  @Override
  protected BoundFunction doBind(DataType valueType) {
    if (valueType instanceof DateType) {
      return new DateToDaysFunction();
    } else if (valueType instanceof TimestampType) {
      return new TimestampToDaysFunction();
    } else if (valueType instanceof TimestampNTZType) {
      return new TimestampNtzToDaysFunction();
    } else {
      throw new UnsupportedOperationException(
          "Expected value to be date or timestamp: " + valueType.catalogString());
    }
  }

  @Override
  public String description() {
    return name()
        + "(col) - Call Iceberg's day transform\n"
        + "  col :: source column (must be date or timestamp)";
  }

  @Override
  public String name() {
    return "days";
  }

  private abstract static class BaseToDaysFunction extends BaseScalarFunction<Integer> {
    @Override

View on GitHub (pinned to 86d9c8fc54)

Solutions

1. Cast the value: system.days(CAST('2024-01-01' AS DATE)) or system.days(CAST(ts_str AS TIMESTAMP))
2. Convert epoch numbers to a timestamp first (timestamp_millis(col)) before applying days()
3. Use the matching function for the type (e.g. days for date/timestamp, not for strings)

Example fix

// before
spark.sql("SELECT system.days('2024-01-01')")
// after
spark.sql("SELECT system.days(CAST('2024-01-01' AS DATE))")

-- Cast non-temporal inputs first
SELECT system.days(CAST(ts_str AS TIMESTAMP)) FROM tbl;

boolean daysOk(DataType t) { return t instanceof DateType || t instanceof TimestampType || t instanceof TimestampNTZType; }

When it happens

Trigger: Calling system.days(ts) where ts is a string, long epoch, or other non-date/timestamp type.

Common situations: Passing string datetime literals ('2024-01-01') without a cast; passing epoch millis as bigint; mistakenly passing a date-typed column to hours() variant or vice versa.

Understand the failure class

Background: Type mismatch errors: IllegalArgumentException, TypeError and type guards across 150 open-source libraries — this error's family across 150 libraries.

Related errors

• Expected value to be timestamp: ${valueType.catalogString()}
• Expected value to be date or timestamp: ${valueType.catalogS
• Expected number of buckets to be tinyint, shortint or int
• Expected value to be date or timestamp: ${valueType.catalogS
• Expected value to be date or timestamp: ${valueType.catalogS

AI-assisted analysis of apache/iceberg@86d9c8fc54 (2026-09-12). Data as JSON: /api/errors/887b7863a9513f2d. Report an issue: GitHub.