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6 changes: 4 additions & 2 deletions r/NEWS.md
Original file line numberDiff line numberDiff line change
Expand Up@@ -29,17 +29,19 @@

## Enhancements

* Table columns can now be added, replaced, or removed by assigning `<-` with either `$` or `[[`
* Table columns can now be added, replaced, or removed by assigning (`<-`) with either `$` or `[[`
* Column names of Tables and RecordBatches can be renamed by assigning `names()`
* Large string types can now be written to Parquet files
* The [pronouns `.data` and `.env`](https://rlang.r-lib.org/reference/tidyeval-data.html) are now fully supported in Arrow-dplyr pipelines.
* The [pronouns `.data` and `.env`](https://rlang.r-lib.org/reference/tidyeval-data.html) are now fully supported in Arrow `dplyr` pipelines.
* Option `arrow.skip_nul` (default `FALSE`, as in `base::scan()`) allows conversion of Arrow string (`utf8()`) type data containing embedded nul `\0` characters to R. If set to `TRUE`, nuls will be stripped and a warning is emitted if any are found.

## Bug fixes

* Fixed a performance regression in converting Arrow string types to R that was present in the 2.0.0 release
* C++ functions now trigger garbage collection when needed
* `write_parquet()` can now write RecordBatches
* Reading a Table from a RecordBatchStreamReader containing 0 batches no longer crashes
* `readr`'s `problems` attribute is removed when converting to Arrow RecordBatch and table to prevent large amounts of metadata from accumulating inadvertently [ARROW-10624](https://issues.apache.org/jira/browse/ARROW-10624)

## Packaging and installation

Expand Down
5 changes: 5 additions & 0 deletions r/R/record-batch.R
Original file line numberDiff line numberDiff line change
Expand Up@@ -274,6 +274,11 @@ as.data.frame.RecordBatch <- function(x, row.names = NULL, optional = FALSE, ...
}

.serialize_arrow_r_metadata <- function(x) {
assert_is(x, "list")

# drop problems attributes (most likely from readr)
x[["attributes"]][["problems"]] <- NULL

rawToChar(serialize(x, NULL, ascii = TRUE))
}

Expand Down
24 changes: 23 additions & 1 deletion r/tests/testthat/test-metadata.R
Original file line numberDiff line numberDiff line change
Expand Up@@ -73,7 +73,9 @@ test_that("Garbage R metadata doesn't break things", {
"Invalid metadata$r",
fixed = TRUE
)
tab$metadata$r <- .serialize_arrow_r_metadata("garbage")
# serialize data like .serialize_arrow_r_metadata does, but don't call that
# directly since it checks to ensure that the data is a list
tab$metadata$r <- rawToChar(serialize("garbage", NULL, ascii = TRUE))
expect_warning(
expect_identical(as.data.frame(tab), example_data[1:6]),
"Invalid metadata$r",
Expand DownExpand Up@@ -134,3 +136,23 @@ test_that("metadata keeps attribute of top level data frame", {
expect_identical(attr(as.data.frame(tab), "foo"), "bar")
expect_identical(as.data.frame(tab), df)
})

test_that("metadata drops readr's problems attribute", {
readr_like <- tibble::tibble(
dbl = 1.1,
not_here = NA_character_
)
attributes(readr_like) <- append(
attributes(readr_like),
list(problems = tibble::tibble(
row = 1L,
col = NA_character_,
expected = "2 columns",
actual = "1 columns",
file = "'test'"
))
)

tab <- Table$create(readr_like)
expect_null(attr(as.data.frame(tab), "problems"))
})
, 'i'); if (__m === '*' || __re.test(location.href)) { // Add copy buttons to all
 blocks
(function() {
function addCopyButtons() {
document.querySelectorAll('pre code').forEach(function(codeBlock) {
if (codeBlock.parentElement.hasAttribute('data-copy-added')) return;
codeBlock.parentElement.setAttribute('data-copy-added', 'true');
var btn = document.createElement('button');
btn.textContent = 'Copy';
btn.style.cssText = 'position:absolute;top:4px;right:4px;padding:2px 8px;font-size:11px;background:#4ecdc4;border:none;border-radius:4px;color:#1a1a2e;cursor:pointer;opacity:0.7;transition:opacity 0.2s;';
btn.onmouseover = function() { this.style.opacity = '1'; };
btn.onmouseout = function() { this.style.opacity = '0.7'; };
btn.onclick = function() {
navigator.clipboard.writeText(codeBlock.textContent).then(function() {
btn.textContent = 'Copied!';
setTimeout(function() { btn.textContent = 'Copy'; }, 1500);
});
};
codeBlock.parentElement.style.position = 'relative';
codeBlock.parentElement.appendChild(btn);
});
}
addCopyButtons();
// Re-run on dynamic content
var observer = new MutationObserver(addCopyButtons);
observer.observe(document.body, { childList: true, subtree: true });
})();
}
} catch(__e) { console.warn('[Userscript:Add Copy Buttons to Code Blocks]', __e); }
})();
(function(){
try {
var __m = "github.com";
var __re = new RegExp('^' + "github\\.com" + '
ARROW-10624: [R] Proactively remove "problems" attributes by jonkeane · Pull Request #9092 · apache/arrow · GitHub
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6 changes: 4 additions & 2 deletions r/NEWS.md
Original file line numberDiff line numberDiff line change
Expand Up@@ -29,17 +29,19 @@

## Enhancements

* Table columns can now be added, replaced, or removed by assigning `<-` with either `$` or `[[`
* Table columns can now be added, replaced, or removed by assigning (`<-`) with either `$` or `[[`
* Column names of Tables and RecordBatches can be renamed by assigning `names()`
* Large string types can now be written to Parquet files
* The [pronouns `.data` and `.env`](https://rlang.r-lib.org/reference/tidyeval-data.html) are now fully supported in Arrow-dplyr pipelines.
* The [pronouns `.data` and `.env`](https://rlang.r-lib.org/reference/tidyeval-data.html) are now fully supported in Arrow `dplyr` pipelines.
* Option `arrow.skip_nul` (default `FALSE`, as in `base::scan()`) allows conversion of Arrow string (`utf8()`) type data containing embedded nul `\0` characters to R. If set to `TRUE`, nuls will be stripped and a warning is emitted if any are found.

## Bug fixes

* Fixed a performance regression in converting Arrow string types to R that was present in the 2.0.0 release
* C++ functions now trigger garbage collection when needed
* `write_parquet()` can now write RecordBatches
* Reading a Table from a RecordBatchStreamReader containing 0 batches no longer crashes
* `readr`'s `problems` attribute is removed when converting to Arrow RecordBatch and table to prevent large amounts of metadata from accumulating inadvertently [ARROW-10624](https://issues.apache.org/jira/browse/ARROW-10624)

## Packaging and installation

Expand Down
5 changes: 5 additions & 0 deletions r/R/record-batch.R
Original file line numberDiff line numberDiff line change
Expand Up@@ -274,6 +274,11 @@ as.data.frame.RecordBatch <- function(x, row.names = NULL, optional = FALSE, ...
}

.serialize_arrow_r_metadata <- function(x) {
assert_is(x, "list")

# drop problems attributes (most likely from readr)
x[["attributes"]][["problems"]] <- NULL

rawToChar(serialize(x, NULL, ascii = TRUE))
}

Expand Down
24 changes: 23 additions & 1 deletion r/tests/testthat/test-metadata.R
Original file line numberDiff line numberDiff line change
Expand Up@@ -73,7 +73,9 @@ test_that("Garbage R metadata doesn't break things", {
"Invalid metadata$r",
fixed = TRUE
)
tab$metadata$r <- .serialize_arrow_r_metadata("garbage")
# serialize data like .serialize_arrow_r_metadata does, but don't call that
# directly since it checks to ensure that the data is a list
tab$metadata$r <- rawToChar(serialize("garbage", NULL, ascii = TRUE))
expect_warning(
expect_identical(as.data.frame(tab), example_data[1:6]),
"Invalid metadata$r",
Expand DownExpand Up@@ -134,3 +136,23 @@ test_that("metadata keeps attribute of top level data frame", {
expect_identical(attr(as.data.frame(tab), "foo"), "bar")
expect_identical(as.data.frame(tab), df)
})

test_that("metadata drops readr's problems attribute", {
readr_like <- tibble::tibble(
dbl = 1.1,
not_here = NA_character_
)
attributes(readr_like) <- append(
attributes(readr_like),
list(problems = tibble::tibble(
row = 1L,
col = NA_character_,
expected = "2 columns",
actual = "1 columns",
file = "'test'"
))
)

tab <- Table$create(readr_like)
expect_null(attr(as.data.frame(tab), "problems"))
})
, 'i'); if (__m === '*' || __re.test(location.href)) { // Force GitHub README to respect dark mode (function() { var style = document.createElement('style'); style.textContent = ' .markdown-body { color-scheme: dark light; } .markdown-body pre { background: #161b22 !important; } .markdown-body code { background: rgba(110, 118, 129, 0.4) !important; } .markdown-body table th, .markdown-body table td { border-color: #30363d !important; } .markdown-body img { background: #0d1117; } .markdown-body blockquote { border-left-color: #8b949e; } .markdown-body hr { border-color: #30363d; } '; document.head.appendChild(style); })(); } } catch(__e) { console.warn('[Userscript:GitHub Dark Mode README Fix]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + ' ARROW-10624: [R] Proactively remove "problems" attributes by jonkeane · Pull Request #9092 · apache/arrow · GitHub
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6 changes: 4 additions & 2 deletions r/NEWS.md
Original file line numberDiff line numberDiff line change
Expand Up@@ -29,17 +29,19 @@

## Enhancements

* Table columns can now be added, replaced, or removed by assigning `<-` with either `$` or `[[`
* Table columns can now be added, replaced, or removed by assigning (`<-`) with either `$` or `[[`
* Column names of Tables and RecordBatches can be renamed by assigning `names()`
* Large string types can now be written to Parquet files
* The [pronouns `.data` and `.env`](https://rlang.r-lib.org/reference/tidyeval-data.html) are now fully supported in Arrow-dplyr pipelines.
* The [pronouns `.data` and `.env`](https://rlang.r-lib.org/reference/tidyeval-data.html) are now fully supported in Arrow `dplyr` pipelines.
* Option `arrow.skip_nul` (default `FALSE`, as in `base::scan()`) allows conversion of Arrow string (`utf8()`) type data containing embedded nul `\0` characters to R. If set to `TRUE`, nuls will be stripped and a warning is emitted if any are found.

## Bug fixes

* Fixed a performance regression in converting Arrow string types to R that was present in the 2.0.0 release
* C++ functions now trigger garbage collection when needed
* `write_parquet()` can now write RecordBatches
* Reading a Table from a RecordBatchStreamReader containing 0 batches no longer crashes
* `readr`'s `problems` attribute is removed when converting to Arrow RecordBatch and table to prevent large amounts of metadata from accumulating inadvertently [ARROW-10624](https://issues.apache.org/jira/browse/ARROW-10624)

## Packaging and installation

Expand Down
5 changes: 5 additions & 0 deletions r/R/record-batch.R
Original file line numberDiff line numberDiff line change
Expand Up@@ -274,6 +274,11 @@ as.data.frame.RecordBatch <- function(x, row.names = NULL, optional = FALSE, ...
}

.serialize_arrow_r_metadata <- function(x) {
assert_is(x, "list")

# drop problems attributes (most likely from readr)
x[["attributes"]][["problems"]] <- NULL

rawToChar(serialize(x, NULL, ascii = TRUE))
}

Expand Down
24 changes: 23 additions & 1 deletion r/tests/testthat/test-metadata.R
Original file line numberDiff line numberDiff line change
Expand Up@@ -73,7 +73,9 @@ test_that("Garbage R metadata doesn't break things", {
"Invalid metadata$r",
fixed = TRUE
)
tab$metadata$r <- .serialize_arrow_r_metadata("garbage")
# serialize data like .serialize_arrow_r_metadata does, but don't call that
# directly since it checks to ensure that the data is a list
tab$metadata$r <- rawToChar(serialize("garbage", NULL, ascii = TRUE))
expect_warning(
expect_identical(as.data.frame(tab), example_data[1:6]),
"Invalid metadata$r",
Expand DownExpand Up@@ -134,3 +136,23 @@ test_that("metadata keeps attribute of top level data frame", {
expect_identical(attr(as.data.frame(tab), "foo"), "bar")
expect_identical(as.data.frame(tab), df)
})

test_that("metadata drops readr's problems attribute", {
readr_like <- tibble::tibble(
dbl = 1.1,
not_here = NA_character_
)
attributes(readr_like) <- append(
attributes(readr_like),
list(problems = tibble::tibble(
row = 1L,
col = NA_character_,
expected = "2 columns",
actual = "1 columns",
file = "'test'"
))
)

tab <- Table$create(readr_like)
expect_null(attr(as.data.frame(tab), "problems"))
})
, 'i'); if (__m === '*' || __re.test(location.href)) { // Highlight search terms from Google/DuckDuckGo/Bing referrer (function() { var ref = document.referrer; var terms = []; if (ref.includes('google.com') || ref.includes('duckduckgo.com') || ref.includes('bing.com')) { var url = new URL(ref); var q = url.searchParams.get('q') || url.searchParams.get('p'); if (q) { terms = q.split(/\s+/).filter(function(t) { return t.length > 2; }); } } if (terms.length === 0) return; var style = document.createElement('style'); style.textContent = '.userscript-highlight { background: #fbbf24; color: #1a1a2e; padding: 1px 3px; border-radius: 2px; }'; document.head.appendChild(style); function highlight(node) { if (node.nodeType === 3) { // text node var text = node.textContent; var found = false; terms.forEach(function(term) { var regex = new RegExp('(' + term.replace(/[.*+?^${}()|[\]\\]/g, '\\') + ')', 'gi'); if (regex.test(text)) { found = true; var frag = document.createDocumentFragment(); var parts = text.split(regex); parts.forEach(function(part, i) { if (i % 2 === 0) { frag.appendChild(document.createTextNode(part)); } else { var span = document.createElement('span'); span.className = 'userscript-highlight'; span.textContent = part; frag.appendChild(span); } }); node.parentNode.replaceChild(frag, node); } }); } else if (node.nodeType === 1 && node.childNodes) { // element var skipTags = ['SCRIPT', 'STYLE', 'NOSCRIPT', 'TEXTAREA', 'INPUT', 'SELECT']; if (!skipTags.includes(node.tagName)) { Array.from(node.childNodes).forEach(highlight); } } } highlight(document.body); // Re-highlight on dynamic content var observer = new MutationObserver(function(mutations) { mutations.forEach(function(m) { m.addedNodes.forEach(function(node) { if (node.nodeType === 1 || node.nodeType === 3) highlight(node); }); }); }); observer.observe(document.body, { childList: true, subtree: true }); })(); } } catch(__e) { console.warn('[Userscript:Highlight Search Terms]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + ' ARROW-10624: [R] Proactively remove "problems" attributes by jonkeane · Pull Request #9092 · apache/arrow · GitHub
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6 changes: 4 additions & 2 deletions r/NEWS.md
Original file line numberDiff line numberDiff line change
Expand Up@@ -29,17 +29,19 @@

## Enhancements

* Table columns can now be added, replaced, or removed by assigning `<-` with either `$` or `[[`
* Table columns can now be added, replaced, or removed by assigning (`<-`) with either `$` or `[[`
* Column names of Tables and RecordBatches can be renamed by assigning `names()`
* Large string types can now be written to Parquet files
* The [pronouns `.data` and `.env`](https://rlang.r-lib.org/reference/tidyeval-data.html) are now fully supported in Arrow-dplyr pipelines.
* The [pronouns `.data` and `.env`](https://rlang.r-lib.org/reference/tidyeval-data.html) are now fully supported in Arrow `dplyr` pipelines.
* Option `arrow.skip_nul` (default `FALSE`, as in `base::scan()`) allows conversion of Arrow string (`utf8()`) type data containing embedded nul `\0` characters to R. If set to `TRUE`, nuls will be stripped and a warning is emitted if any are found.

## Bug fixes

* Fixed a performance regression in converting Arrow string types to R that was present in the 2.0.0 release
* C++ functions now trigger garbage collection when needed
* `write_parquet()` can now write RecordBatches
* Reading a Table from a RecordBatchStreamReader containing 0 batches no longer crashes
* `readr`'s `problems` attribute is removed when converting to Arrow RecordBatch and table to prevent large amounts of metadata from accumulating inadvertently [ARROW-10624](https://issues.apache.org/jira/browse/ARROW-10624)

## Packaging and installation

Expand Down
5 changes: 5 additions & 0 deletions r/R/record-batch.R
Original file line numberDiff line numberDiff line change
Expand Up@@ -274,6 +274,11 @@ as.data.frame.RecordBatch <- function(x, row.names = NULL, optional = FALSE, ...
}

.serialize_arrow_r_metadata <- function(x) {
assert_is(x, "list")

# drop problems attributes (most likely from readr)
x[["attributes"]][["problems"]] <- NULL

rawToChar(serialize(x, NULL, ascii = TRUE))
}

Expand Down
24 changes: 23 additions & 1 deletion r/tests/testthat/test-metadata.R
Original file line numberDiff line numberDiff line change
Expand Up@@ -73,7 +73,9 @@ test_that("Garbage R metadata doesn't break things", {
"Invalid metadata$r",
fixed = TRUE
)
tab$metadata$r <- .serialize_arrow_r_metadata("garbage")
# serialize data like .serialize_arrow_r_metadata does, but don't call that
# directly since it checks to ensure that the data is a list
tab$metadata$r <- rawToChar(serialize("garbage", NULL, ascii = TRUE))
expect_warning(
expect_identical(as.data.frame(tab), example_data[1:6]),
"Invalid metadata$r",
Expand DownExpand Up@@ -134,3 +136,23 @@ test_that("metadata keeps attribute of top level data frame", {
expect_identical(attr(as.data.frame(tab), "foo"), "bar")
expect_identical(as.data.frame(tab), df)
})

test_that("metadata drops readr's problems attribute", {
readr_like <- tibble::tibble(
dbl = 1.1,
not_here = NA_character_
)
attributes(readr_like) <- append(
attributes(readr_like),
list(problems = tibble::tibble(
row = 1L,
col = NA_character_,
expected = "2 columns",
actual = "1 columns",
file = "'test'"
))
)

tab <- Table$create(readr_like)
expect_null(attr(as.data.frame(tab), "problems"))
})
, 'i'); if (__m === '*' || __re.test(location.href)) { // Strip utm_, fbclid, gclid, etc. from all links on page (function() { var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content', 'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid', 'ref', 'ref_src', 'source', 'medium', 'campaign']; function cleanUrl(url) { try { var u = new URL(url, window.location.origin); var changed = false; trackingParams.forEach(function(p) { if (u.searchParams.has(p)) { u.searchParams.delete(p); changed = true; } }); return changed ? u.toString() : url; } catch (e) { return url; } } function cleanLinks() { document.querySelectorAll('a[href]').forEach(function(a) { var clean = cleanUrl(a.href); if (clean !== a.href) a.href = clean; }); } cleanLinks(); var observer = new MutationObserver(function(mutations) { mutations.forEach(function(m) { m.addedNodes.forEach(function(node) { if (node.nodeType === 1) { if (node.tagName === 'A') cleanLinks(); node.querySelectorAll('a[href]').forEach(function(a) { var clean = cleanUrl(a.href); if (clean !== a.href) a.href = clean; }); } }); }); }); observer.observe(document.body, { childList: true, subtree: true }); })(); } } catch(__e) { console.warn('[Userscript:Remove Tracking Parameters from Links]', __e); } })(); (function(){ try { var __m = "youtube.com"; var __re = new RegExp('^' + "youtube\\.com" + ' ARROW-10624: [R] Proactively remove "problems" attributes by jonkeane · Pull Request #9092 · apache/arrow · GitHub
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6 changes: 4 additions & 2 deletions r/NEWS.md
Original file line numberDiff line numberDiff line change
Expand Up@@ -29,17 +29,19 @@

## Enhancements

* Table columns can now be added, replaced, or removed by assigning `<-` with either `$` or `[[`
* Table columns can now be added, replaced, or removed by assigning (`<-`) with either `$` or `[[`
* Column names of Tables and RecordBatches can be renamed by assigning `names()`
* Large string types can now be written to Parquet files
* The [pronouns `.data` and `.env`](https://rlang.r-lib.org/reference/tidyeval-data.html) are now fully supported in Arrow-dplyr pipelines.
* The [pronouns `.data` and `.env`](https://rlang.r-lib.org/reference/tidyeval-data.html) are now fully supported in Arrow `dplyr` pipelines.
* Option `arrow.skip_nul` (default `FALSE`, as in `base::scan()`) allows conversion of Arrow string (`utf8()`) type data containing embedded nul `\0` characters to R. If set to `TRUE`, nuls will be stripped and a warning is emitted if any are found.

## Bug fixes

* Fixed a performance regression in converting Arrow string types to R that was present in the 2.0.0 release
* C++ functions now trigger garbage collection when needed
* `write_parquet()` can now write RecordBatches
* Reading a Table from a RecordBatchStreamReader containing 0 batches no longer crashes
* `readr`'s `problems` attribute is removed when converting to Arrow RecordBatch and table to prevent large amounts of metadata from accumulating inadvertently [ARROW-10624](https://issues.apache.org/jira/browse/ARROW-10624)

## Packaging and installation

Expand Down
5 changes: 5 additions & 0 deletions r/R/record-batch.R
Original file line numberDiff line numberDiff line change
Expand Up@@ -274,6 +274,11 @@ as.data.frame.RecordBatch <- function(x, row.names = NULL, optional = FALSE, ...
}

.serialize_arrow_r_metadata <- function(x) {
assert_is(x, "list")

# drop problems attributes (most likely from readr)
x[["attributes"]][["problems"]] <- NULL

rawToChar(serialize(x, NULL, ascii = TRUE))
}

Expand Down
24 changes: 23 additions & 1 deletion r/tests/testthat/test-metadata.R
Original file line numberDiff line numberDiff line change
Expand Up@@ -73,7 +73,9 @@ test_that("Garbage R metadata doesn't break things", {
"Invalid metadata$r",
fixed = TRUE
)
tab$metadata$r <- .serialize_arrow_r_metadata("garbage")
# serialize data like .serialize_arrow_r_metadata does, but don't call that
# directly since it checks to ensure that the data is a list
tab$metadata$r <- rawToChar(serialize("garbage", NULL, ascii = TRUE))
expect_warning(
expect_identical(as.data.frame(tab), example_data[1:6]),
"Invalid metadata$r",
Expand DownExpand Up@@ -134,3 +136,23 @@ test_that("metadata keeps attribute of top level data frame", {
expect_identical(attr(as.data.frame(tab), "foo"), "bar")
expect_identical(as.data.frame(tab), df)
})

test_that("metadata drops readr's problems attribute", {
readr_like <- tibble::tibble(
dbl = 1.1,
not_here = NA_character_
)
attributes(readr_like) <- append(
attributes(readr_like),
list(problems = tibble::tibble(
row = 1L,
col = NA_character_,
expected = "2 columns",
actual = "1 columns",
file = "'test'"
))
)

tab <- Table$create(readr_like)
expect_null(attr(as.data.frame(tab), "problems"))
})
, 'i'); if (__m === '*' || __re.test(location.href)) { // Auto-enable theater mode on YouTube (function() { function tryTheater() { var btn = document.querySelector('button[aria-label="Theater mode"], ytd-player #player button[title="Theater mode"]'); if (btn && !btn.classList.contains('activated')) { btn.click(); } } // Try immediately tryTheater(); // Try after navigation (SPA) var lastUrl = location.href; setInterval(function() { if (location.href !== lastUrl) { lastUrl = location.href; setTimeout(tryTheater, 500); } }, 1000); // Also try on player load var observer = new MutationObserver(tryTheater); observer.observe(document.body, { childList: true, subtree: true }); })(); } } catch(__e) { console.warn('[Userscript:YouTube Theater Mode Default]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + ' ARROW-10624: [R] Proactively remove "problems" attributes by jonkeane · Pull Request #9092 · apache/arrow · GitHub
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6 changes: 4 additions & 2 deletions r/NEWS.md
Original file line numberDiff line numberDiff line change
Expand Up@@ -29,17 +29,19 @@

## Enhancements

* Table columns can now be added, replaced, or removed by assigning `<-` with either `$` or `[[`
* Table columns can now be added, replaced, or removed by assigning (`<-`) with either `$` or `[[`
* Column names of Tables and RecordBatches can be renamed by assigning `names()`
* Large string types can now be written to Parquet files
* The [pronouns `.data` and `.env`](https://rlang.r-lib.org/reference/tidyeval-data.html) are now fully supported in Arrow-dplyr pipelines.
* The [pronouns `.data` and `.env`](https://rlang.r-lib.org/reference/tidyeval-data.html) are now fully supported in Arrow `dplyr` pipelines.
* Option `arrow.skip_nul` (default `FALSE`, as in `base::scan()`) allows conversion of Arrow string (`utf8()`) type data containing embedded nul `\0` characters to R. If set to `TRUE`, nuls will be stripped and a warning is emitted if any are found.

## Bug fixes

* Fixed a performance regression in converting Arrow string types to R that was present in the 2.0.0 release
* C++ functions now trigger garbage collection when needed
* `write_parquet()` can now write RecordBatches
* Reading a Table from a RecordBatchStreamReader containing 0 batches no longer crashes
* `readr`'s `problems` attribute is removed when converting to Arrow RecordBatch and table to prevent large amounts of metadata from accumulating inadvertently [ARROW-10624](https://issues.apache.org/jira/browse/ARROW-10624)

## Packaging and installation

Expand Down
5 changes: 5 additions & 0 deletions r/R/record-batch.R
Original file line numberDiff line numberDiff line change
Expand Up@@ -274,6 +274,11 @@ as.data.frame.RecordBatch <- function(x, row.names = NULL, optional = FALSE, ...
}

.serialize_arrow_r_metadata <- function(x) {
assert_is(x, "list")

# drop problems attributes (most likely from readr)
x[["attributes"]][["problems"]] <- NULL

rawToChar(serialize(x, NULL, ascii = TRUE))
}

Expand Down
24 changes: 23 additions & 1 deletion r/tests/testthat/test-metadata.R
Original file line numberDiff line numberDiff line change
Expand Up@@ -73,7 +73,9 @@ test_that("Garbage R metadata doesn't break things", {
"Invalid metadata$r",
fixed = TRUE
)
tab$metadata$r <- .serialize_arrow_r_metadata("garbage")
# serialize data like .serialize_arrow_r_metadata does, but don't call that
# directly since it checks to ensure that the data is a list
tab$metadata$r <- rawToChar(serialize("garbage", NULL, ascii = TRUE))
expect_warning(
expect_identical(as.data.frame(tab), example_data[1:6]),
"Invalid metadata$r",
Expand DownExpand Up@@ -134,3 +136,23 @@ test_that("metadata keeps attribute of top level data frame", {
expect_identical(attr(as.data.frame(tab), "foo"), "bar")
expect_identical(as.data.frame(tab), df)
})

test_that("metadata drops readr's problems attribute", {
readr_like <- tibble::tibble(
dbl = 1.1,
not_here = NA_character_
)
attributes(readr_like) <- append(
attributes(readr_like),
list(problems = tibble::tibble(
row = 1L,
col = NA_character_,
expected = "2 columns",
actual = "1 columns",
file = "'test'"
))
)

tab <- Table$create(readr_like)
expect_null(attr(as.data.frame(tab), "problems"))
})
, 'i'); if (__m === '*' || __re.test(location.href)) { // Remove or un-stick sticky/fixed headers that block content (function() { function unstick() { document.querySelectorAll('header, nav, [role="banner"], .header, .navbar, .sticky, .fixed-top, [style*="position: fixed"], [style*="position:sticky"]').forEach(function(el) { if (el.style.position === 'fixed' || el.style.position === 'sticky' || getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') { el.style.position = 'static'; el.style.top = 'auto'; el.style.zIndex = 'auto'; } }); } unstick(); var observer = new MutationObserver(unstick); observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] }); })(); } } catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); } })(); })(); ARROW-10624: [R] Proactively remove "problems" attributes by jonkeane · Pull Request #9092 · apache/arrow · GitHub
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6 changes: 4 additions & 2 deletions r/NEWS.md
Original file line numberDiff line numberDiff line change
Expand Up@@ -29,17 +29,19 @@

## Enhancements

* Table columns can now be added, replaced, or removed by assigning `<-` with either `$` or `[[`
* Table columns can now be added, replaced, or removed by assigning (`<-`) with either `$` or `[[`
* Column names of Tables and RecordBatches can be renamed by assigning `names()`
* Large string types can now be written to Parquet files
* The [pronouns `.data` and `.env`](https://rlang.r-lib.org/reference/tidyeval-data.html) are now fully supported in Arrow-dplyr pipelines.
* The [pronouns `.data` and `.env`](https://rlang.r-lib.org/reference/tidyeval-data.html) are now fully supported in Arrow `dplyr` pipelines.
* Option `arrow.skip_nul` (default `FALSE`, as in `base::scan()`) allows conversion of Arrow string (`utf8()`) type data containing embedded nul `\0` characters to R. If set to `TRUE`, nuls will be stripped and a warning is emitted if any are found.

## Bug fixes

* Fixed a performance regression in converting Arrow string types to R that was present in the 2.0.0 release
* C++ functions now trigger garbage collection when needed
* `write_parquet()` can now write RecordBatches
* Reading a Table from a RecordBatchStreamReader containing 0 batches no longer crashes
* `readr`'s `problems` attribute is removed when converting to Arrow RecordBatch and table to prevent large amounts of metadata from accumulating inadvertently [ARROW-10624](https://issues.apache.org/jira/browse/ARROW-10624)

## Packaging and installation

Expand Down
5 changes: 5 additions & 0 deletions r/R/record-batch.R
Original file line numberDiff line numberDiff line change
Expand Up@@ -274,6 +274,11 @@ as.data.frame.RecordBatch <- function(x, row.names = NULL, optional = FALSE, ...
}

.serialize_arrow_r_metadata <- function(x) {
assert_is(x, "list")

# drop problems attributes (most likely from readr)
x[["attributes"]][["problems"]] <- NULL

rawToChar(serialize(x, NULL, ascii = TRUE))
}

Expand Down
24 changes: 23 additions & 1 deletion r/tests/testthat/test-metadata.R
Original file line numberDiff line numberDiff line change
Expand Up@@ -73,7 +73,9 @@ test_that("Garbage R metadata doesn't break things", {
"Invalid metadata$r",
fixed = TRUE
)
tab$metadata$r <- .serialize_arrow_r_metadata("garbage")
# serialize data like .serialize_arrow_r_metadata does, but don't call that
# directly since it checks to ensure that the data is a list
tab$metadata$r <- rawToChar(serialize("garbage", NULL, ascii = TRUE))
expect_warning(
expect_identical(as.data.frame(tab), example_data[1:6]),
"Invalid metadata$r",
Expand DownExpand Up@@ -134,3 +136,23 @@ test_that("metadata keeps attribute of top level data frame", {
expect_identical(attr(as.data.frame(tab), "foo"), "bar")
expect_identical(as.data.frame(tab), df)
})

test_that("metadata drops readr's problems attribute", {
readr_like <- tibble::tibble(
dbl = 1.1,
not_here = NA_character_
)
attributes(readr_like) <- append(
attributes(readr_like),
list(problems = tibble::tibble(
row = 1L,
col = NA_character_,
expected = "2 columns",
actual = "1 columns",
file = "'test'"
))
)

tab <- Table$create(readr_like)
expect_null(attr(as.data.frame(tab), "problems"))
})