[SPARK-48776] Fix timestamp formatting for json, xml and csv #47177
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milastdbx
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cloud-fan
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Jul 2, 2024
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/csv/CSVOptions.scala
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HyukjinKwon
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Jul 3, 2024
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thanks, merging to master! |
ericm-db
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Jul 10, 2024
### What changes were proposed in this pull request?
In this pull request i propose to change default ISO pattern we use for formatting timestamps when we are writing to json,xml and/or csv as well as when to_(xml|json|csv) is used.
Older timestamps sometimes have offsets that contain seconds part as well. Current default formatting used is omitting seconds hence providing wrong results.
e.g.
```
sql("SET spark.sql.session.timeZone=America/Los_Angeles")
sql("SELECT to_json(struct(CAST('1800-01-01T00:00:00+00:00' AS TIMESTAMP) AS ts))").show(false)
{"ts":"1799-12-31T16:07:02.000-07:52"}
```
### Why are the changes needed?
This is correctness issue.
### Does this PR introduce _any_ user-facing change?
Yes, users will now see different results for older timestamps (correct ones).
### How was this patch tested?
Tests
### Was this patch authored or co-authored using generative AI tooling?
No
Closes apache#47177 from milastdbx/dev/milast/fixJsonTimestampHandling.
Authored-by: milastdbx <milan.stefanovic@databricks.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
jingz-db
pushed a commit
to jingz-db/spark
that referenced
this pull request
Jul 22, 2024
### What changes were proposed in this pull request?
In this pull request i propose to change default ISO pattern we use for formatting timestamps when we are writing to json,xml and/or csv as well as when to_(xml|json|csv) is used.
Older timestamps sometimes have offsets that contain seconds part as well. Current default formatting used is omitting seconds hence providing wrong results.
e.g.
```
sql("SET spark.sql.session.timeZone=America/Los_Angeles")
sql("SELECT to_json(struct(CAST('1800-01-01T00:00:00+00:00' AS TIMESTAMP) AS ts))").show(false)
{"ts":"1799-12-31T16:07:02.000-07:52"}
```
### Why are the changes needed?
This is correctness issue.
### Does this PR introduce _any_ user-facing change?
Yes, users will now see different results for older timestamps (correct ones).
### How was this patch tested?
Tests
### Was this patch authored or co-authored using generative AI tooling?
No
Closes apache#47177 from milastdbx/dev/milast/fixJsonTimestampHandling.
Authored-by: milastdbx <milan.stefanovic@databricks.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
attilapiros
pushed a commit
to attilapiros/spark
that referenced
this pull request
Oct 4, 2024
### What changes were proposed in this pull request?
In this pull request i propose to change default ISO pattern we use for formatting timestamps when we are writing to json,xml and/or csv as well as when to_(xml|json|csv) is used.
Older timestamps sometimes have offsets that contain seconds part as well. Current default formatting used is omitting seconds hence providing wrong results.
e.g.
```
sql("SET spark.sql.session.timeZone=America/Los_Angeles")
sql("SELECT to_json(struct(CAST('1800-01-01T00:00:00+00:00' AS TIMESTAMP) AS ts))").show(false)
{"ts":"1799-12-31T16:07:02.000-07:52"}
```
### Why are the changes needed?
This is correctness issue.
### Does this PR introduce _any_ user-facing change?
Yes, users will now see different results for older timestamps (correct ones).
### How was this patch tested?
Tests
### Was this patch authored or co-authored using generative AI tooling?
No
Closes apache#47177 from milastdbx/dev/milast/fixJsonTimestampHandling.
Authored-by: milastdbx <milan.stefanovic@databricks.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
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What changes were proposed in this pull request?
In this pull request i propose to change default ISO pattern we use for formatting timestamps when we are writing to json,xml and/or csv as well as when to_(xml|json|csv) is used.
Older timestamps sometimes have offsets that contain seconds part as well. Current default formatting used is omitting seconds hence providing wrong results.
e.g.
Why are the changes needed?
This is correctness issue.
Does this PR introduce any user-facing change?
Yes, users will now see different results for older timestamps (correct ones).
How was this patch tested?
Tests
Was this patch authored or co-authored using generative AI tooling?
No