yaooqinn opened a new pull request #28673:
URL: https://github.com/apache/spark/pull/28673
### What changes were proposed in this pull request?
the new datetime formatter introduces silent data change like,
```sql
spark-sql> select from_unixtime(1, 'yyyyyyyyyyy-MM-dd');
NULL
spark-sql> set spark.sql.legacy.timeParserPolicy=legacy;
spark.sql.legacy.timeParserPolicy legacy
spark-sql> select from_unixtime(1, 'yyyyyyyyyyy-MM-dd');
00000001970-01-01
spark-sql>
```
For patterns that support `SignStyle.EXCEEDS_PAD`, e.g. `y..y`(len >=4),
when using the `NumberPrinterParser` to format it
```java
switch (signStyle) {
case EXCEEDS_PAD:
if (minWidth < 19 && value >= EXCEED_POINTS[minWidth]) {
buf.append(decimalStyle.getPositiveSign());
}
break;
....
```
the `minWidth` == `len(y..y)`
the `EXCEED_POINTS` is
```java
/**
* Array of 10 to the power of n.
*/
static final long[] EXCEED_POINTS = new long[] {
0L,
10L,
100L,
1000L,
10000L,
100000L,
1000000L,
10000000L,
100000000L,
1000000000L,
10000000000L,
};
```
So when the `len(y..y)` is greater than 10, `
ArrayIndexOutOfBoundsException` will be raised.
And at the caller side, for `from_unixtime`, the exception will be
suppressed and silent data change occurs. for `date_format`, the
`ArrayIndexOutOfBoundsException` will continue.
In this PR, for `EXCEPTION` mode, we wrapped exceptions from the new
formatter during formatting to `SparkUpgradeException` for end-users to make
proper decisions.
### Why are the changes needed?
fix silent data change.
### Does this PR introduce _any_ user-facing change?
Yes, SparkUpgradeException will take place of `null` result when something
is wrong during new formatter's formatting phase.
### How was this patch tested?
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add unit tests,
the
`sql/core/src/test/resources/sql-tests/results/datetime-corrected.sql.out` is
added for different behaviors from the caller sides.
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