[SPARK-30681][PYTHON][FOLLOW-UP] Keep the name similar with Scala side in higher order functions#31062
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[SPARK-30681][PYTHON][FOLLOW-UP] Keep the name similar with Scala side in higher order functions#31062HyukjinKwon wants to merge 1 commit intoapache:masterfrom
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viirya
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…e in higher order functions ### What changes were proposed in this pull request? This PR is a followup of #27406. It fixes the naming to match with Scala side. Note that there are a bit of inconsistency already e.g.) `col`, `e`, `expr` and `column`. This part I did not change but other names like `zero` vs `initialValue` or `col1`/`col2` vs `left`/`right` looks unnecessary. ### Why are the changes needed? To make the usage similar with Scala side, and for consistency. ### Does this PR introduce _any_ user-facing change? No, this is not released yet. ### How was this patch tested? GitHub Actions and Jenkins build will test it out. Closes #31062 from HyukjinKwon/SPARK-30681. Authored-by: HyukjinKwon <gurwls223@apache.org> Signed-off-by: HyukjinKwon <gurwls223@apache.org> (cherry picked from commit ff284fb) Signed-off-by: HyukjinKwon <gurwls223@apache.org>
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Looks good, thanks for working on this @HyukjinKwon
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…e in higher order functions ### What changes were proposed in this pull request? This PR is a followup of #27433. It fixes the naming to match with Scala side, and this is similar with #31062. Note that: - there are a bit of inconsistency already e.g.) `x`, `y` in SparkR and they are documented together for doc deduplication. This part I did not change but the name `zero` vs `initialValue` looks unnecessary. - such naming matching seems already pretty common in SparkR. ### Why are the changes needed? To make the usage similar with Scala side, and for consistency. ### Does this PR introduce _any_ user-facing change? No, this is not released yet. ### How was this patch tested? GitHub Actions and Jenkins build will test it out. Also, I manually tested: ```r > df <- select(createDataFrame(data.frame(id = 1)),expr("CAST(array(1.0, 2.0, -3.0, -4.0) AS array<double>) xs")) > collect(select(df, array_aggregate("xs", initialValue = lit(0.0), merge = function(x, y) otherwise(when(x > y, x), y)))) aggregate(xs, 0.0, lambdafunction(CASE WHEN (x > y) THEN x ELSE y END, x, y), lambdafunction(id, id)) 1 2 ``` Closes #31226 from HyukjinKwon/SPARK-30682. Authored-by: HyukjinKwon <gurwls223@apache.org> Signed-off-by: HyukjinKwon <gurwls223@apache.org>
HyukjinKwon
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Jan 18, 2021
…e in higher order functions ### What changes were proposed in this pull request? This PR is a followup of #27433. It fixes the naming to match with Scala side, and this is similar with #31062. Note that: - there are a bit of inconsistency already e.g.) `x`, `y` in SparkR and they are documented together for doc deduplication. This part I did not change but the name `zero` vs `initialValue` looks unnecessary. - such naming matching seems already pretty common in SparkR. ### Why are the changes needed? To make the usage similar with Scala side, and for consistency. ### Does this PR introduce _any_ user-facing change? No, this is not released yet. ### How was this patch tested? GitHub Actions and Jenkins build will test it out. Also, I manually tested: ```r > df <- select(createDataFrame(data.frame(id = 1)),expr("CAST(array(1.0, 2.0, -3.0, -4.0) AS array<double>) xs")) > collect(select(df, array_aggregate("xs", initialValue = lit(0.0), merge = function(x, y) otherwise(when(x > y, x), y)))) aggregate(xs, 0.0, lambdafunction(CASE WHEN (x > y) THEN x ELSE y END, x, y), lambdafunction(id, id)) 1 2 ``` Closes #31226 from HyukjinKwon/SPARK-30682. Authored-by: HyukjinKwon <gurwls223@apache.org> Signed-off-by: HyukjinKwon <gurwls223@apache.org> (cherry picked from commit b5bdbf2) Signed-off-by: HyukjinKwon <gurwls223@apache.org>
skestle
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Feb 3, 2021
…e in higher order functions ### What changes were proposed in this pull request? This PR is a followup of apache#27433. It fixes the naming to match with Scala side, and this is similar with apache#31062. Note that: - there are a bit of inconsistency already e.g.) `x`, `y` in SparkR and they are documented together for doc deduplication. This part I did not change but the name `zero` vs `initialValue` looks unnecessary. - such naming matching seems already pretty common in SparkR. ### Why are the changes needed? To make the usage similar with Scala side, and for consistency. ### Does this PR introduce _any_ user-facing change? No, this is not released yet. ### How was this patch tested? GitHub Actions and Jenkins build will test it out. Also, I manually tested: ```r > df <- select(createDataFrame(data.frame(id = 1)),expr("CAST(array(1.0, 2.0, -3.0, -4.0) AS array<double>) xs")) > collect(select(df, array_aggregate("xs", initialValue = lit(0.0), merge = function(x, y) otherwise(when(x > y, x), y)))) aggregate(xs, 0.0, lambdafunction(CASE WHEN (x > y) THEN x ELSE y END, x, y), lambdafunction(id, id)) 1 2 ``` Closes apache#31226 from HyukjinKwon/SPARK-30682. Authored-by: HyukjinKwon <gurwls223@apache.org> Signed-off-by: HyukjinKwon <gurwls223@apache.org>
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What changes were proposed in this pull request?
This PR is a followup of #27406. It fixes the naming to match with Scala side.
Note that there are a bit of inconsistency already e.g.)
col,e,exprandcolumn. This part I did not change but other names likezerovsinitialValueorcol1/col2vsleft/rightlooks unnecessary.Why are the changes needed?
To make the usage similar with Scala side, and for consistency.
Does this PR introduce any user-facing change?
No, this is not released yet.
How was this patch tested?
GitHub Actions and Jenkins build will test it out.