[SPARK-54463][SQL] Add CSV serialization and deserialization support for TIME type #53175
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dongjoon-hyun
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Nov 23, 2025
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+1, LGTM. Merged to master for Apache Spark 4.2.0.
huangxiaopingRD
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Nov 25, 2025
…for TIME type
### What changes were proposed in this pull request?
This PR adds CSV serialization and deserialization support for Spark's TIME type
### Why are the changes needed?
TIME type currently lacks CSV support, preventing users from:
- Reading/writing CSV files with TIME columns
- Using `from_csv()` and `to_csv()` functions with TIME type
- Integrating TIME data with external CSV-based systems
### Does this PR introduce _any_ user-facing change?
Yes.
Users can now:
- Read CSV with TIME: `spark.read.schema("time TIME(6)").csv("data.csv")`
- Write CSV with TIME: `df.write.csv("output.csv")` → `14:30:45.123456`
- Use from_csv/to_csv:
```sql
SELECT from_csv('14:30:45.123456', 'time TIME(6)');
SELECT to_csv(named_struct('time', TIME'14:30:45'));
```
- Custom format: `spark.read.option("timeFormat", "HH-mm-ss.SSSSSS").csv("data.csv")`
- New option: `timeFormat` - controls TIME formatting/parsing (default: `HH:mm:ss` with fractional seconds)
### How was this patch tested?
Added new test cases in `CsvExpressionsSuite`, `CsvFunctionsSuite`, SQL tests (`csv-functions.sql`), and `CsvSuite`
### Was this patch authored or co-authored using generative AI tooling?
Yes.
Generated-by: Claude 3.5 Sonnet
AI assistance was used for:
- Code pattern analysis and design discussions
- Implementation guidance following Spark conventions
- Test case generation and organization
- Documentation and examples
Closes apache#53175 from vinodkc/br_time_csv_read_write.
Authored-by: vinodkc <vinod.kc.in@gmail.com>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
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What changes were proposed in this pull request?
This PR adds CSV serialization and deserialization support for Spark's TIME type
Why are the changes needed?
TIME type currently lacks CSV support, preventing users from:
from_csv()andto_csv()functions with TIME typeDoes this PR introduce any user-facing change?
Yes.
Users can now:
spark.read.schema("time TIME(6)").csv("data.csv")df.write.csv("output.csv")→14:30:45.123456spark.read.option("timeFormat", "HH-mm-ss.SSSSSS").csv("data.csv")timeFormat- controls TIME formatting/parsing (default:HH:mm:sswith fractional seconds)How was this patch tested?
Added new test cases in
CsvExpressionsSuite,CsvFunctionsSuite, SQL tests (csv-functions.sql), andCsvSuiteWas this patch authored or co-authored using generative AI tooling?
Yes.
Generated-by: Claude 3.5 Sonnet
AI assistance was used for: