fix: Support more type conversion for decimal partition value

[PingLiuPing]

Description

Previously, PartitionData.getValue() always used decimalValue().setScale()
when deserializing DECIMAL partition values from JSON, which could fail
or produce incorrect results when the JSON contains integer representations
(long, int, or BigInteger) of decimal values.

This change adds type-specific handling for decimal deserialization:

• Use BigDecimal.valueOf(long, scale) when JSON contains a long value
• Use BigDecimal.valueOf(int, scale) when JSON contains an int value
• Use BigDecimal(BigInteger, scale) when JSON contains a BigInteger value
• Fall back to decimalValue().setScale() for other numeric types

Motivation and Context

Impact

Test Plan

Added comprehensive unit tests covering all code paths including:

• Decimal from long values
• Decimal from int values
• Decimal from BigInteger values
• Decimal from decimal values (fallback)
• Edge cases (zero scale, large scale, negative values, very large numbers)
• JSON round-trip tests with mixed types

Contributor checklist

• Please make sure your submission complies with our contributing guide, in particular code style and commit standards.
• PR description addresses the issue accurately and concisely. If the change is non-trivial, a GitHub Issue is referenced.
• Documented new properties (with its default value), SQL syntax, functions, or other functionality.
• If release notes are required, they follow the release notes guidelines.
• Adequate tests were added if applicable.
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Release Notes

Please follow release notes guidelines and fill in the release notes below.

== RELEASE NOTES ==

Iceberg Connector Changes
* Add more type conversion for decimal partition value.

[sourcery-ai]

Reviewer's Guide

Enhanced DECIMAL partition value deserialization in PartitionData.getValue with type-specific handling and added comprehensive unit tests covering all numeric input scenarios and JSON round-trip cases.

Flow diagram for DECIMAL partition value deserialization logic

flowchart TD
    A["partitionValue.isLong()"] -->|true| B["BigDecimal.valueOf(partitionValue.asLong(), scale)"]
    A -->|false| C["partitionValue.isInt()"]
    C -->|true| D["BigDecimal.valueOf(partitionValue.asInt(), scale)"]
    C -->|false| E["partitionValue.isBigInteger()"]
    E -->|true| F["new BigDecimal(partitionValue.bigIntegerValue(), scale)"]
    E -->|false| G["partitionValue.decimalValue().setScale(scale)"]

Loading

File-Level Changes

Change	Details	Files
Enhanced DECIMAL partition value deserialization with type-specific handling	Handle JSON long nodes via BigDecimal.valueOf(long, scale) Handle JSON int nodes via BigDecimal.valueOf(int, scale) Handle JSON BigInteger nodes via new BigDecimal(BigInteger, scale) Fallback to decimalValue().setScale() for other numeric types	presto-iceberg/src/main/java/com/facebook/presto/iceberg/PartitionData.java
Added comprehensive unit tests for decimal partition value conversion and JSON round-trip	Test null input handling across types Test decimal from long, int, BigInteger and fallback paths Validate edge cases: zero scale, large scale, negative and very large numbers JSON round-trip tests for decimals and mixed-type partitions	presto-iceberg/src/test/java/com/facebook/presto/iceberg/TestPartitionData.java

Possibly linked issues

• #Parquet Decimal Metadata Issue: The PR resolves the issue by correctly handling decimal precision and scale during deserialization of partition values.

---

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[sourcery-ai]

Hey there - I've reviewed your changes - here's some feedback:

• In the DECIMAL branch, extract the DecimalType cast and its scale into local variables up front to avoid repeated casts and improve readability.
• The fallback uses setScale without a RoundingMode, which will throw if the input has more fractional digits than the target scale—consider specifying an explicit RoundingMode or validating precision to make deserialization behavior clearer.

Prompt for AI Agents

Please address the comments from this code review:

## Overall Comments
- In the DECIMAL branch, extract the DecimalType cast and its scale into local variables up front to avoid repeated casts and improve readability.
- The fallback uses setScale without a RoundingMode, which will throw if the input has more fractional digits than the target scale—consider specifying an explicit RoundingMode or validating precision to make deserialization behavior clearer.

## Individual Comments

### Comment 1
<location> `presto-iceberg/src/main/java/com/facebook/presto/iceberg/PartitionData.java:197-187` </location>
<code_context>
+                else if (partitionValue.isBigInteger()) {
+                    return new BigDecimal(partitionValue.bigIntegerValue(), ((DecimalType) type).scale());
+                }
+                else {
+                    return partitionValue.decimalValue().setScale(((DecimalType) type).scale());
+                }
         }
</code_context>

<issue_to_address>
**suggestion (bug_risk):** Consider specifying rounding mode when setting scale on BigDecimal.

Omitting the rounding mode can cause ArithmeticException if the value cannot be exactly represented at the desired scale. Specify a rounding mode to prevent this.

Suggested implementation:

```java
                    return partitionValue.decimalValue().setScale(((DecimalType) type).scale(), java.math.RoundingMode.HALF_UP);

```

If `RoundingMode` is not already imported at the top of the file, add:
```java
import java.math.RoundingMode;
```
You may want to choose a different rounding mode depending on your requirements.
</issue_to_address>

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[sourcery-ai]

suggestion (bug_risk): Consider specifying rounding mode when setting scale on BigDecimal.

Omitting the rounding mode can cause ArithmeticException if the value cannot be exactly represented at the desired scale. Specify a rounding mode to prevent this.

Suggested implementation:

                    return partitionValue.decimalValue().setScale(((DecimalType) type).scale(), java.math.RoundingMode.HALF_UP);

If RoundingMode is not already imported at the top of the file, add:

import java.math.RoundingMode;

You may want to choose a different rounding mode depending on your requirements.

[PingLiuPing]

@hantangwangd Not sure if you are interested in reviewing this PR, this PR is motivated when reviewing PR #26174 (comment) and I was suggested to move this part and submit a new PR.

[PingLiuPing]

@aditi-pandit Can you please take a look. This PR is per your comments in #26174 (comment)

[hantangwangd]

@PingLiuPing have you ever encountered this problem during real usage? If so, could you also add a similar test case which would fail without this change in IcebergDistributedTestBase or IcebergDistributedSmokeTestBase? Thanks.

[PingLiuPing]

@hantangwangd Thanks for the comment.
Yes, these code are needed for Prestissimo iceberg scenario when writing partitioned iceberg table.
When passing partition value (part of the commit message) from velox to Presto coordinator, depends on the actual decimal value we have to cover all the possible conversions.
The logic here is, in Velox decimal is represented as integer (int64/int128). But when we passing the partition value back to Presto, it is encoded in json format, and here when decode the value, based on value it will be treated as different integer types.

[PingLiuPing]

@hantangwangd Just want to split this piece of code separately. The purpose of this PR is serving the native iceberg write. I have test cases to cover this from E2E point of view. And I will deliver those testcases once the partition transform related code is merged.
#26182 (comment)