David Mollitor created SPARK-59546:
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Summary: Avoid per-row exceptions when inferring TimeType in JSON,
CSV, and XM
Key: SPARK-59546
URL: https://issues.apache.org/jira/browse/SPARK-59546
Project: Spark
Issue Type: Improvement
Components: SQL
Affects Versions: 4.1.0
Reporter: David Mollitor
h2. Summary
JSON, CSV, and XML schema inference probe whether a string value is a {{TIME}}
by calling the throwing {{TimeFormatter.parse}} inside {{allCatch opt}}:
{code:scala}
if (isTimeTypeEnabled && (allCatch opt timeFormatter.parse(field)).isDefined) {
TimeType(TimeType.DEFAULT_PRECISION)
}
{code}
For the default (pattern-less) formatter, {{parse}} calls
{{SparkDateTimeUtils.stringToTimeAnsi}}, which throws a
{{SparkDateTimeException}} (filling in a stack trace) for every value that is
not a time. During inference of a non-time column, this is one
thrown-and-caught exception per row.
This is the same cost that SPARK-39193 / SPARK-39280 / SPARK-39281 removed for
timestamp and date inference by introducing a non-throwing {{parseOptional}}
(that change reported exception handling as more than 90% of type-inference
time). {{TimeType}} was added later and never got a {{parseOptional}}, so it is
the only datetime formatter still using the throwing probe -- the timestamp
probe immediately below the time probe already uses {{parseOptional}}.
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