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[GitHub] [spark] MichaelChirico opened a new pull request #28372: [R] vectorize schema validation for arrow in types.R
MichaelChirico opened a new pull request #28372:
URL: https://github.com/apache/spark/pull/28372
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### What changes were proposed in this pull request?
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Repeated `sapply` avoided in internal `checkSchemaInArrow`
### Why are the changes needed?
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Current implementation is doubly inefficient:
1. Repeatedly doing the same (95%) `sapply` loop
2. Doing scalar `==` on a vector (`==` should be done over the whole vector for efficiency)
### Does this PR introduce any user-facing change?
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No
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[GitHub] [spark] HyukjinKwon commented on a change in pull request #28372: [SPARK-31578][R] Vectorize schema validation for arrow in types.R
Posted by GitBox <gi...@apache.org>.
HyukjinKwon commented on a change in pull request #28372:
URL: https://github.com/apache/spark/pull/28372#discussion_r416251165
##########
File path: R/pkg/R/types.R
##########
@@ -94,27 +94,23 @@ checkSchemaInArrow <- function(schema) {
}
# Both cases below produce a corrupt value for unknown reason. It needs to be investigated.
- if (any(sapply(schema$fields(), function(x) x$dataType.toString() == "FloatType"))) {
+ field_strings <- sapply(schema$fields(), function(x) x$dataType.toString())
+ if (any(field_strings == "FloatType")) {
stop("Arrow optimization in R does not support float type yet.")
}
- if (any(sapply(schema$fields(), function(x) x$dataType.toString() == "BinaryType"))) {
+ if (any(field_strings == "BinaryType")) {
stop("Arrow optimization in R does not support binary type yet.")
}
- if (any(sapply(schema$fields(),
- function(x) startsWith(x$dataType.toString(),
- "ArrayType")))) {
+ if (any(startsWith(field_strings, "ArrayType"))) {
stop("Arrow optimization in R does not support array type yet.")
}
# Arrow optimization in Spark does not yet support both cases below.
- if (any(sapply(schema$fields(),
- function(x) startsWith(x$dataType.toString(),
- "StructType")))) {
+ if (any(startsWith(field_strings, "StructType"))) {
stop("Arrow optimization in R does not support nested struct type yet.")
}
- if (any(sapply(schema$fields(),
- function(x) startsWith(x$dataType.toString(),
- "MapType")))) {
+ if (any(startsWith(field_strings, "MapType"))) {
stop("Arrow optimization in R does not support map type yet.")
}
+ return(invisible())
Review comment:
I think this is fine. Let's just remove unless this is explicitly recommended, conventional or consistent across the codebase :-).
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[GitHub] [spark] MichaelChirico commented on a change in pull request #28372: [SPARK-31578][R] Vectorize schema validation for arrow in types.R
Posted by GitBox <gi...@apache.org>.
MichaelChirico commented on a change in pull request #28372:
URL: https://github.com/apache/spark/pull/28372#discussion_r416249467
##########
File path: R/pkg/R/types.R
##########
@@ -94,27 +94,23 @@ checkSchemaInArrow <- function(schema) {
}
# Both cases below produce a corrupt value for unknown reason. It needs to be investigated.
- if (any(sapply(schema$fields(), function(x) x$dataType.toString() == "FloatType"))) {
+ field_strings <- sapply(schema$fields(), function(x) x$dataType.toString())
+ if (any(field_strings == "FloatType")) {
stop("Arrow optimization in R does not support float type yet.")
}
- if (any(sapply(schema$fields(), function(x) x$dataType.toString() == "BinaryType"))) {
+ if (any(field_strings == "BinaryType")) {
stop("Arrow optimization in R does not support binary type yet.")
}
- if (any(sapply(schema$fields(),
- function(x) startsWith(x$dataType.toString(),
- "ArrayType")))) {
+ if (any(startsWith(field_strings, "ArrayType"))) {
stop("Arrow optimization in R does not support array type yet.")
}
# Arrow optimization in Spark does not yet support both cases below.
- if (any(sapply(schema$fields(),
- function(x) startsWith(x$dataType.toString(),
- "StructType")))) {
+ if (any(startsWith(field_strings, "StructType"))) {
stop("Arrow optimization in R does not support nested struct type yet.")
}
- if (any(sapply(schema$fields(),
- function(x) startsWith(x$dataType.toString(),
- "MapType")))) {
+ if (any(startsWith(field_strings, "MapType"))) {
stop("Arrow optimization in R does not support map type yet.")
}
+ return(invisible())
Review comment:
Just to be explicit about a void return value. Not strictly necessary. Happy to remove.
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URL: https://github.com/apache/spark/pull/28372#issuecomment-620060135
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[GitHub] [spark] HyukjinKwon commented on pull request #28372: [SPARK-31578][R] Vectorize schema validation for arrow in types.R
Posted by GitBox <gi...@apache.org>.
HyukjinKwon commented on pull request #28372:
URL: https://github.com/apache/spark/pull/28372#issuecomment-620332859
Merged to master and branch-3.0.
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* This patch passes all tests.
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* This patch **fails some tests**.
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[GitHub] [spark] HyukjinKwon commented on pull request #28372: [SPARK-31578][R] Vectorize schema validation for arrow in types.R
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HyukjinKwon commented on pull request #28372:
URL: https://github.com/apache/spark/pull/28372#issuecomment-620331533
I am going to merge. The tests are already passed, and I don't believe removing the return causes any test or build to break.
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[GitHub] [spark] HyukjinKwon commented on a change in pull request #28372: [SPARK-31578][R] Vectorize schema validation for arrow in types.R
Posted by GitBox <gi...@apache.org>.
HyukjinKwon commented on a change in pull request #28372:
URL: https://github.com/apache/spark/pull/28372#discussion_r416247772
##########
File path: R/pkg/R/types.R
##########
@@ -94,27 +94,23 @@ checkSchemaInArrow <- function(schema) {
}
# Both cases below produce a corrupt value for unknown reason. It needs to be investigated.
- if (any(sapply(schema$fields(), function(x) x$dataType.toString() == "FloatType"))) {
+ field_strings <- sapply(schema$fields(), function(x) x$dataType.toString())
+ if (any(field_strings == "FloatType")) {
stop("Arrow optimization in R does not support float type yet.")
}
- if (any(sapply(schema$fields(), function(x) x$dataType.toString() == "BinaryType"))) {
+ if (any(field_strings == "BinaryType")) {
stop("Arrow optimization in R does not support binary type yet.")
}
- if (any(sapply(schema$fields(),
- function(x) startsWith(x$dataType.toString(),
- "ArrayType")))) {
+ if (any(startsWith(field_strings, "ArrayType"))) {
stop("Arrow optimization in R does not support array type yet.")
}
# Arrow optimization in Spark does not yet support both cases below.
- if (any(sapply(schema$fields(),
- function(x) startsWith(x$dataType.toString(),
- "StructType")))) {
+ if (any(startsWith(field_strings, "StructType"))) {
stop("Arrow optimization in R does not support nested struct type yet.")
}
- if (any(sapply(schema$fields(),
- function(x) startsWith(x$dataType.toString(),
- "MapType")))) {
+ if (any(startsWith(field_strings, "MapType"))) {
stop("Arrow optimization in R does not support map type yet.")
}
+ return(invisible())
Review comment:
Quick question, why do we need this?
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[GitHub] [spark] MichaelChirico commented on pull request #28372: [SPARK-31578][R] Vectorize schema validation for arrow in types.R
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MichaelChirico commented on pull request #28372:
URL: https://github.com/apache/spark/pull/28372#issuecomment-620331958
linter failure looks transient to me:
> E: The repository 'https://cloud.r-project.org/bin/linux/ubuntu bionic-cran35/ Release' does not have a Release file.
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[GitHub] [spark] SparkQA commented on pull request #28372: [SPARK-31578][R] Vectorize schema validation for arrow in types.R
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SparkQA commented on pull request #28372:
URL: https://github.com/apache/spark/pull/28372#issuecomment-620316474
**[Test build #121937 has started](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/121937/testReport)** for PR 28372 at commit [`0c2718b`](https://github.com/apache/spark/commit/0c2718bdfc73c6913bf2d612910744a4591eb1f8).
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Test FAILed.
Refer to this link for build results (access rights to CI server needed):
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Test FAILed.
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[GitHub] [spark] SparkQA commented on pull request #28372: [SPARK-31578][R] vectorize schema validation for arrow in types.R
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SparkQA commented on pull request #28372:
URL: https://github.com/apache/spark/pull/28372#issuecomment-620068202
**[Test build #121915 has finished](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/121915/testReport)** for PR 28372 at commit [`8004d22`](https://github.com/apache/spark/commit/8004d221bf860faf057d2f997d5b15f1592eb5c8).
* This patch **fails R style tests**.
* This patch merges cleanly.
* This patch adds no public classes.
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**[Test build #121918 has started](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/121918/testReport)** for PR 28372 at commit [`03b7898`](https://github.com/apache/spark/commit/03b7898acf2443bafab687043b494e1006615c40).
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[GitHub] [spark] SparkQA commented on pull request #28372: [SPARK-31578][R] vectorize schema validation for arrow in types.R
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URL: https://github.com/apache/spark/pull/28372#issuecomment-620055491
**[Test build #121913 has started](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/121913/testReport)** for PR 28372 at commit [`0fc8513`](https://github.com/apache/spark/commit/0fc8513fb407fa6b532b5a0bbbe61dcabc92298b).
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