[SPARK-31790][DOCS] cast(long as timestamp) show different result between Hive and Spark #28605
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@GuoPhilipse, let's file a JIRA although it's doc only, it's user-facing. |
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fine, i will create a JIRA for it. |
GuoPhilipse
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HyukjinKwon
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HyukjinKwon
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HyukjinKwon
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@HyukjinKwon cast(ts as long) may change to cast(long as timestamp) ? |
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@GuoPhilipse, feel free to fix the PR title and PR description with examples. It's your PR :-) |
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:) have corrected and added examples in JIRA |
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@HyukjinKwon what else did i need to do to close the jira and merge the patch ? |
HyukjinKwon
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May 22, 2020
docs/sql-migration-guide.md
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| * `SQRT(n)` If n < 0, Hive returns null, Spark SQL returns NaN. | ||
| * `ACOS(n)` If n < -1 or n > 1, Hive returns null, Spark SQL returns NaN. | ||
| * `ASIN(n)` If n < -1 or n > 1, Hive returns null, Spark SQL returns NaN. | ||
| * `CAST(n as timestamp)` If n is Byte/Short/Int/Long data type, Hive treat n as milliseconds unit , while Spark SQL as seconds unit. |
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Let's rephrase a bit more:
CAST(n AS TIMESTAMP) If n is integral numbers, Hive treats n as milliseconds, Spark SQL treats n as seconds .
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cool , have improved it.
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ok to test |
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Test build #122995 has finished for PR 28605 at commit
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Test build #122998 has finished for PR 28605 at commit
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Merged to master and branch-3.0. |
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May 22, 2020
…ween Hive and Spark ### What changes were proposed in this pull request? add docs for sql migration-guide ### Why are the changes needed? let user know more about the cast scenarios in which Hive and Spark generate different results ### Does this PR introduce _any_ user-facing change? no ### How was this patch tested? no need to test Closes #28605 from GuoPhilipse/spark-docs. Lead-authored-by: GuoPhilipse <[email protected]> Co-authored-by: GuoPhilipse <[email protected]> Signed-off-by: HyukjinKwon <[email protected]> (cherry picked from commit 892b600) Signed-off-by: HyukjinKwon <[email protected]>
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What changes were proposed in this pull request?
add docs for sql migration-guide
Why are the changes needed?
let user know more about the cast scenarios in which Hive and Spark generate different results
Does this PR introduce any user-facing change?
no
How was this patch tested?
no need to test