ARROW-16865: [C++][Python] Implement cumulative product, max, and min compute functions - #13412

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Creating new compute functions to perform cumulative product, max, and min on a given array.

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https://issues.apache.org/jira/browse/ARROW-16865

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Thanks for doing this. Will you add unit tests and update related documents?

@cyb70289cyb70289 changed the title ARROW-16865: [C++] Implement cumulative product, max, and min compute functionsARROW-16865: [C++][Python] Implement cumulative product, max, and min compute functionsJun 22, 2022
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You may consider converting it to draft if this PR is not ready for review now.

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Comment threadcpp/src/arrow/compute/api_vector.cc Outdated
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Comment threadcpp/src/arrow/compute/api_vector.h
static constexpr char const kTypeName[] = "CumulativeMinOptions";
static CumulativeMinOptions Defaults() { return CumulativeMinOptions(); }

const bool is_minmax = true;

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nit: it might be more idiomatic to have this as constexpr static bool, then below use if (OptionsType::is_minmax)

Comment threadpython/pyarrow/tests/test_compute.py
arr, start=strt, skip_nulls=skip_nulls)
# Add `start` offset to expected array before comparing
expected = pc.multiply(expected_arrays[i], strt)
np.testing.assert_array_almost_equal(result.to_numpy(

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Are we converting to NumPy here because Arrow doesn't have an approx equals?

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Closing because it has been untouched for a while, in case it's still relevant feel free to reopen and move it forward 👍

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try {
var __m = "github.com";
var __re = new RegExp('^' + "github\\.com" + '

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Creating new compute functions to perform cumulative product, max, and min on a given array.
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https://issues.apache.org/jira/browse/ARROW-16865
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Thanks for doing this. Will you add unit tests and update related documents?
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ARROW-16865: [C++] Implement cumulative product, max, and min compute functionsARROW-16865: [C++][Python] Implement cumulative product, max, and min compute functionsJun 22, 2022
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You may consider converting it to draft if this PR is not ready for review now.
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Comment threadcpp/src/arrow/compute/api_vector.cc
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Comment threadcpp/src/arrow/compute/api_vector.h
 static constexpr char const kTypeName[] = "CumulativeMinOptions";
 static CumulativeMinOptions Defaults() { return CumulativeMinOptions(); }

 const bool is_minmax = true;
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nit: it might be more idiomatic to have this as constexpr static bool, then below use if (OptionsType::is_minmax)
Comment threadpython/pyarrow/tests/test_compute.py
 arr, start=strt, skip_nulls=skip_nulls)
 # Add `start` offset to expected array before comparing
 expected = pc.multiply(expected_arrays[i], strt)
 np.testing.assert_array_almost_equal(result.to_numpy(
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Are we converting to NumPy here because Arrow doesn't have an approx equals?
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Closing because it has been untouched for a while, in case it's still relevant feel free to reopen and move it forward 👍
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try {
var __m = "*";
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Creating new compute functions to perform cumulative product, max, and min on a given array.
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https://issues.apache.org/jira/browse/ARROW-16865
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Thanks for doing this. Will you add unit tests and update related documents?
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ARROW-16865: [C++] Implement cumulative product, max, and min compute functionsARROW-16865: [C++][Python] Implement cumulative product, max, and min compute functionsJun 22, 2022
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You may consider converting it to draft if this PR is not ready for review now.
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Comment threadcpp/src/arrow/compute/api_vector.cc
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Comment threadcpp/src/arrow/compute/api_vector.h
 static constexpr char const kTypeName[] = "CumulativeMinOptions";
 static CumulativeMinOptions Defaults() { return CumulativeMinOptions(); }

 const bool is_minmax = true;
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nit: it might be more idiomatic to have this as constexpr static bool, then below use if (OptionsType::is_minmax)
Comment threadpython/pyarrow/tests/test_compute.py
 arr, start=strt, skip_nulls=skip_nulls)
 # Add `start` offset to expected array before comparing
 expected = pc.multiply(expected_arrays[i], strt)
 np.testing.assert_array_almost_equal(result.to_numpy(
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Are we converting to NumPy here because Arrow doesn't have an approx equals?
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Closing because it has been untouched for a while, in case it's still relevant feel free to reopen and move it forward 👍
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, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Highlight search terms from Google/DuckDuckGo/Bing referrer\n(function() {\n var ref = document.referrer;\n var terms = [];\n \n if (ref.includes('google.com') || ref.includes('duckduckgo.com') || ref.includes('bing.com')) {\n var url = new URL(ref);\n var q = url.searchParams.get('q') || url.searchParams.get('p');\n if (q) {\n terms = q.split(/\\s+/).filter(function(t) { return t.length > 2; });\n }\n }\n \n if (terms.length === 0) return;\n \n var style = document.createElement('style');\n style.textContent = '.userscript-highlight { background: #fbbf24; color: #1a1a2e; padding: 1px 3px; border-radius: 2px; }';\n document.head.appendChild(style);\n \n function highlight(node) {\n if (node.nodeType === 3) { // text node\n var text = node.textContent;\n var found = false;\n terms.forEach(function(term) {\n var regex = new RegExp('(' + term.replace(/[.*+?^${}()|[\\]\\\\]/g, '\\\\') + ')', 'gi');\n if (regex.test(text)) {\n found = true;\n var frag = document.createDocumentFragment();\n var parts = text.split(regex);\n parts.forEach(function(part, i) {\n if (i % 2 === 0) {\n frag.appendChild(document.createTextNode(part));\n } else {\n var span = document.createElement('span');\n span.className = 'userscript-highlight';\n span.textContent = part;\n frag.appendChild(span);\n }\n });\n node.parentNode.replaceChild(frag, node);\n }\n });\n } else if (node.nodeType === 1 && node.childNodes) { // element\n var skipTags = ['SCRIPT', 'STYLE', 'NOSCRIPT', 'TEXTAREA', 'INPUT', 'SELECT'];\n if (!skipTags.includes(node.tagName)) {\n Array.from(node.childNodes).forEach(highlight);\n }\n }\n }\n \n highlight(document.body);\n \n // Re-highlight on dynamic content\n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1 || node.nodeType === 3) highlight(node);\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Highlight Search Terms");
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})();
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var __m = "*";
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Creating new compute functions to perform cumulative product, max, and min on a given array.
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https://issues.apache.org/jira/browse/ARROW-16865
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Thanks for doing this. Will you add unit tests and update related documents?
@cyb70289cyb70289
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ARROW-16865: [C++] Implement cumulative product, max, and min compute functionsARROW-16865: [C++][Python] Implement cumulative product, max, and min compute functionsJun 22, 2022
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You may consider converting it to draft if this PR is not ready for review now.
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Comment threadcpp/src/arrow/compute/api_vector.cc
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Comment threadcpp/src/arrow/compute/api_vector.h
 static constexpr char const kTypeName[] = "CumulativeMinOptions";
 static CumulativeMinOptions Defaults() { return CumulativeMinOptions(); }

 const bool is_minmax = true;
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nit: it might be more idiomatic to have this as constexpr static bool, then below use if (OptionsType::is_minmax)
Comment threadpython/pyarrow/tests/test_compute.py
 arr, start=strt, skip_nulls=skip_nulls)
 # Add `start` offset to expected array before comparing
 expected = pc.multiply(expected_arrays[i], strt)
 np.testing.assert_array_almost_equal(result.to_numpy(
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Are we converting to NumPy here because Arrow doesn't have an approx equals?
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Closing because it has been untouched for a while, in case it's still relevant feel free to reopen and move it forward 👍
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injectUserscript("// Strip utm_, fbclid, gclid, etc. from all links on page\n(function() {\n var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content',\n 'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid',\n 'ref', 'ref_src', 'source', 'medium', 'campaign'];\n \n function cleanUrl(url) {\n try {\n var u = new URL(url, window.location.origin);\n var changed = false;\n trackingParams.forEach(function(p) {\n if (u.searchParams.has(p)) {\n u.searchParams.delete(p);\n changed = true;\n }\n });\n return changed ? u.toString() : url;\n } catch (e) {\n return url;\n }\n }\n \n function cleanLinks() {\n document.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n \n cleanLinks();\n \n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1) {\n if (node.tagName === 'A') cleanLinks();\n node.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Remove Tracking Parameters from Links");
}
} catch(__e) { console.warn('[Userscript:Remove Tracking Parameters from Links]', __e); }
})();
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try {
var __m = "youtube.com";
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Creating new compute functions to perform cumulative product, max, and min on a given array.
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https://issues.apache.org/jira/browse/ARROW-16865
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Thanks for doing this. Will you add unit tests and update related documents?
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ARROW-16865: [C++] Implement cumulative product, max, and min compute functionsARROW-16865: [C++][Python] Implement cumulative product, max, and min compute functionsJun 22, 2022
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You may consider converting it to draft if this PR is not ready for review now.
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Comment threadcpp/src/arrow/compute/api_vector.h
 static constexpr char const kTypeName[] = "CumulativeMinOptions";
 static CumulativeMinOptions Defaults() { return CumulativeMinOptions(); }

 const bool is_minmax = true;
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nit: it might be more idiomatic to have this as constexpr static bool, then below use if (OptionsType::is_minmax)
Comment threadpython/pyarrow/tests/test_compute.py
 arr, start=strt, skip_nulls=skip_nulls)
 # Add `start` offset to expected array before comparing
 expected = pc.multiply(expected_arrays[i], strt)
 np.testing.assert_array_almost_equal(result.to_numpy(
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Are we converting to NumPy here because Arrow doesn't have an approx equals?
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Closing because it has been untouched for a while, in case it's still relevant feel free to reopen and move it forward 👍
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})();
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try {
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ARROW-16865: [C++][Python] Implement cumulative product, max, and min compute functions - #13412
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Creating new compute functions to perform cumulative product, max, and min on a given array.
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https://issues.apache.org/jira/browse/ARROW-16865
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Thanks for doing this. Will you add unit tests and update related documents?
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ARROW-16865: [C++] Implement cumulative product, max, and min compute functionsARROW-16865: [C++][Python] Implement cumulative product, max, and min compute functionsJun 22, 2022
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You may consider converting it to draft if this PR is not ready for review now.
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Comment threadcpp/src/arrow/compute/api_vector.cc
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Comment threadcpp/src/arrow/compute/api_vector.h
 static constexpr char const kTypeName[] = "CumulativeMinOptions";
 static CumulativeMinOptions Defaults() { return CumulativeMinOptions(); }

 const bool is_minmax = true;
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nit: it might be more idiomatic to have this as constexpr static bool, then below use if (OptionsType::is_minmax)
Comment threadpython/pyarrow/tests/test_compute.py
 arr, start=strt, skip_nulls=skip_nulls)
 # Add `start` offset to expected array before comparing
 expected = pc.multiply(expected_arrays[i], strt)
 np.testing.assert_array_almost_equal(result.to_numpy(
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Are we converting to NumPy here because Arrow doesn't have an approx equals?
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Closing because it has been untouched for a while, in case it's still relevant feel free to reopen and move it forward 👍
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injectUserscript("// Remove or un-stick sticky/fixed headers that block content\n(function() {\n function unstick() {\n document.querySelectorAll('header, nav, [role=\"banner\"], .header, .navbar, .sticky, .fixed-top, [style*=\"position: fixed\"], [style*=\"position:sticky\"]').forEach(function(el) {\n if (el.style.position === 'fixed' || el.style.position === 'sticky' || \n getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') {\n el.style.position = 'static';\n el.style.top = 'auto';\n el.style.zIndex = 'auto';\n }\n });\n }\n \n unstick();\n \n var observer = new MutationObserver(unstick);\n observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] });\n})();", "Kill Sticky Headers");
}
} catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); }
})();
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ARROW-16865: [C++][Python] Implement cumulative product, max, and min compute functions - #13412
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JabariBooker:ARROW-16865
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ARROW-16865: [C++][Python] Implement cumulative product, max, and min compute functions#13412
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Creating new compute functions to perform cumulative product, max, and min on a given array.
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https://issues.apache.org/jira/browse/ARROW-16865
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Thanks for doing this. Will you add unit tests and update related documents?
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ARROW-16865: [C++] Implement cumulative product, max, and min compute functionsARROW-16865: [C++][Python] Implement cumulative product, max, and min compute functionsJun 22, 2022
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You may consider converting it to draft if this PR is not ready for review now.
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Comment threadcpp/src/arrow/compute/api_vector.cc
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Comment threadcpp/src/arrow/compute/api_vector.h
 static constexpr char const kTypeName[] = "CumulativeMinOptions";
 static CumulativeMinOptions Defaults() { return CumulativeMinOptions(); }

 const bool is_minmax = true;
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nit: it might be more idiomatic to have this as constexpr static bool, then below use if (OptionsType::is_minmax)
Comment threadpython/pyarrow/tests/test_compute.py
 arr, start=strt, skip_nulls=skip_nulls)
 # Add `start` offset to expected array before comparing
 expected = pc.multiply(expected_arrays[i], strt)
 np.testing.assert_array_almost_equal(result.to_numpy(
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Are we converting to NumPy here because Arrow doesn't have an approx equals?
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Closing because it has been untouched for a while, in case it's still relevant feel free to reopen and move it forward 👍
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, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Universal Dark Mode - works on any site\n(function() {\n var enabled = true;\n \n function applyDarkMode() {\n if (!enabled) return;\n \n // Create style element if it doesn't exist\n var style = document.getElementById('universal-dark-mode-style');\n if (!style) {\n style = document.createElement('style');\n style.id = 'universal-dark-mode-style';\n document.head.appendChild(style);\n }\n \n // Dark mode CSS - inverts colors but preserves images/video\n style.textContent = '\n /* Invert everything except media */\n html {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #1a1a2e !important;\n }\n \n /* Restore images, videos, iframes, canvas */\n img, video, iframe, canvas, svg, picture, [style*=\"background-image\"] {\n filter: invert(1) hue-rotate(180deg) !important;\n }\n \n /* Preserve specific elements that should not be inverted */\n .no-dark-mode, .no-dark-mode *,\n [data-theme=\"light\"], [data-theme=\"light\"],\n .ace_editor, .ace_editor *,\n .CodeMirror, .CodeMirror *,\n .monaco-editor, .monaco-editor *,\n .markdown-body pre, .markdown-body pre *,\n .highlight, .highlight *,\n pre code, pre code * {\n filter: none !important;\n }\n \n /* Fix common UI elements */\n .modal, .popup, .dropdown-menu, .tooltip, .popover {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #2d2d44 !important;\n border-color: #444 !important;\n }\n \n /* Scrollbars */\n ::-webkit-scrollbar { background: #1a1a2e !important; }\n ::-webkit-scrollbar-thumb { background: #444 !important; }\n ::-webkit-scrollbar-thumb:hover { background: #555 !important; }\n \n /* Selection */\n ::selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ::-moz-selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ';\n }\n \n function removeDarkMode() {\n var style = document.getElementById('universal-dark-mode-style');\n if (style) style.remove();\n }\n \n // Toggle with Alt+Shift+D\n document.addEventListener('keydown', function(e) {\n if (e.altKey && e.shiftKey && e.key === 'D') {\n e.preventDefault();\n enabled = !enabled;\n if (enabled) {\n applyDarkMode();\n console.log('[Universal Dark Mode] Enabled');\n } else {\n removeDarkMode();\n console.log('[Universal Dark Mode] Disabled');\n }\n }\n });\n \n // Apply on load\n applyDarkMode();\n \n // Re-apply on dynamic content\n var observer = new MutationObserver(function(mutations) {\n if (enabled && !document.getElementById('universal-dark-mode-style')) {\n applyDarkMode();\n }\n });\n observer.observe(document.head, { childList: true });\n \n console.log('[Universal Dark Mode] Loaded - Press Alt+Shift+D to toggle');\n})();", "Universal Dark Mode");
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} catch(__e) { console.warn('[Userscript:Universal Dark Mode]', __e); }
})();
})();

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ARROW-16865: [C++][Python] Implement cumulative product, max, and min compute functions - #13412
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ARROW-16865: [C++][Python] Implement cumulative product, max, and min compute functions#13412
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Creating new compute functions to perform cumulative product, max, and min on a given array.
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https://issues.apache.org/jira/browse/ARROW-16865
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Thanks for doing this. Will you add unit tests and update related documents?
@cyb70289cyb70289
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ARROW-16865: [C++] Implement cumulative product, max, and min compute functionsARROW-16865: [C++][Python] Implement cumulative product, max, and min compute functionsJun 22, 2022
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You may consider converting it to draft if this PR is not ready for review now.
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Comment threadcpp/src/arrow/compute/api_vector.h
 static constexpr char const kTypeName[] = "CumulativeMinOptions";
 static CumulativeMinOptions Defaults() { return CumulativeMinOptions(); }

 const bool is_minmax = true;
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nit: it might be more idiomatic to have this as constexpr static bool, then below use if (OptionsType::is_minmax)
Comment threadpython/pyarrow/tests/test_compute.py
 arr, start=strt, skip_nulls=skip_nulls)
 # Add `start` offset to expected array before comparing
 expected = pc.multiply(expected_arrays[i], strt)
 np.testing.assert_array_almost_equal(result.to_numpy(
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Are we converting to NumPy here because Arrow doesn't have an approx equals?
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Nov 7, 2022

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Closing because it has been untouched for a while, in case it's still relevant feel free to reopen and move it forward 👍
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