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InfiniFilter: Expanding Filters to Infinity and Beyond

This filters library contains the InfiniFilter paper from SIGMOD 2023 as well as some baselines against which it can be compared. InfiniFilter is a probabilistic data structure that answers set-membership queries (similar to a Bloom filter or a Quotient Filter). The core innovation is that InfiniFilter can dynamically expand along with the data while maintaining good guarantees over performance and the false positive rate. The full paper can be accessed here. A video lecture on InfiniFilter appears on youtube.

Compilation

Compile the library by running the following command from the root directory of the repository.

javac filters/*.java bitmap_implementations/*.java infiniFilter_experiments/*.java

Experimental Reproduction

To reproduce the results of the SIGMOD 2023 paper, run the script run_exps.sh from the root directory of the repository. The script will reproduce Figures 13 to 16 in the paper and name them accordingly: figure13.png to figure.16.png. The raw data used to generate these figures is stored in a group of directories called exp1 to exp6. Running the script again will delete the results of older runs and regenerate them.

The script takes a parameter for power of the maximum number of slots to which it will expand the filter. For example, an argument of 31 means the filter will grow to a size of up to 2^31 slots during each experiment. An argument of 31 should be used to reproduce the paper's results. The default value for this parameter is 24.

./run_exps.sh 31

Dependencies

Running the experiments requires having the Java Development Kit version 11 or above installed. Plotting the figures to illustrate the experimental results requires having Gnuplot installed. Both dependencies can be obtained using the following commands on Ubuntu or equivalents on other systems.

sudo apt install default-jdksudo apt-get install gnuplot

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, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Add copy buttons to all 
 blocks\n(function() {\n function addCopyButtons() {\n document.querySelectorAll('pre code').forEach(function(codeBlock) {\n if (codeBlock.parentElement.hasAttribute('data-copy-added')) return;\n codeBlock.parentElement.setAttribute('data-copy-added', 'true');\n \n var btn = document.createElement('button');\n btn.textContent = 'Copy';\n 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;';\n btn.onmouseover = function() { this.style.opacity = '1'; };\n btn.onmouseout = function() { this.style.opacity = '0.7'; };\n btn.onclick = function() {\n navigator.clipboard.writeText(codeBlock.textContent).then(function() {\n btn.textContent = 'Copied!';\n setTimeout(function() { btn.textContent = 'Copy'; }, 1500);\n });\n };\n codeBlock.parentElement.style.position = 'relative';\n codeBlock.parentElement.appendChild(btn);\n });\n }\n \n addCopyButtons();\n \n // Re-run on dynamic content\n var observer = new MutationObserver(addCopyButtons);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Add Copy Buttons to Code Blocks");
}
} catch(__e) { console.warn('[Userscript:Add Copy Buttons to Code Blocks]', __e); }
})();
(function(){
try {
var __m = "github.com";
var __re = new RegExp('^' + "github\\.com" + '

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InfiniFilter: Expanding Filters to Infinity and Beyond
This filters library contains the InfiniFilter paper from SIGMOD 2023 as well as some baselines against which it can be compared. InfiniFilter is a probabilistic data structure that answers set-membership queries (similar to a Bloom filter or a Quotient Filter). The core innovation is that InfiniFilter can dynamically expand along with the data while maintaining good guarantees over performance and the false positive rate. The full paper can be accessed here. A video lecture on InfiniFilter appears on youtube.
Compilation
Compile the library by running the following command from the root directory of the repository.
javac filters/*.java bitmap_implementations/*.java infiniFilter_experiments/*.java 
Experimental Reproduction
To reproduce the results of the SIGMOD 2023 paper, run the script run_exps.sh from the root directory of the repository. The script will reproduce Figures 13 to 16 in the paper and name them accordingly: figure13.png to figure.16.png. The raw data used to generate these figures is stored in a group of directories called exp1 to exp6. Running the script again will delete the results of older runs and regenerate them.
The script takes a parameter for power of the maximum number of slots to which it will expand the filter. For example, an argument of 31 means the filter will grow to a size of up to 2^31 slots during each experiment. An argument of 31 should be used to reproduce the paper's results. The default value for this parameter is 24.
./run_exps.sh 31
Dependencies
Running the experiments requires having the Java Development Kit version 11 or above installed. Plotting the figures to illustrate the experimental results requires having Gnuplot installed. Both dependencies can be obtained using the following commands on Ubuntu or equivalents on other systems.
sudo apt install default-jdksudo apt-get install gnuplot
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, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Force GitHub README to respect dark mode\n(function() {\n var style = document.createElement('style');\n style.textContent = '\n .markdown-body {\n color-scheme: dark light;\n }\n .markdown-body pre { background: #161b22 !important; }\n .markdown-body code { background: rgba(110, 118, 129, 0.4) !important; }\n .markdown-body table th, .markdown-body table td { border-color: #30363d !important; }\n .markdown-body img { background: #0d1117; }\n .markdown-body blockquote { border-left-color: #8b949e; }\n .markdown-body hr { border-color: #30363d; }\n ';\n document.head.appendChild(style);\n})();", "GitHub Dark Mode README Fix");
}
} catch(__e) { console.warn('[Userscript:GitHub Dark Mode README Fix]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

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InfiniFilter: Expanding Filters to Infinity and Beyond
This filters library contains the InfiniFilter paper from SIGMOD 2023 as well as some baselines against which it can be compared. InfiniFilter is a probabilistic data structure that answers set-membership queries (similar to a Bloom filter or a Quotient Filter). The core innovation is that InfiniFilter can dynamically expand along with the data while maintaining good guarantees over performance and the false positive rate. The full paper can be accessed here. A video lecture on InfiniFilter appears on youtube.
Compilation
Compile the library by running the following command from the root directory of the repository.
javac filters/*.java bitmap_implementations/*.java infiniFilter_experiments/*.java 
Experimental Reproduction
To reproduce the results of the SIGMOD 2023 paper, run the script run_exps.sh from the root directory of the repository. The script will reproduce Figures 13 to 16 in the paper and name them accordingly: figure13.png to figure.16.png. The raw data used to generate these figures is stored in a group of directories called exp1 to exp6. Running the script again will delete the results of older runs and regenerate them.
The script takes a parameter for power of the maximum number of slots to which it will expand the filter. For example, an argument of 31 means the filter will grow to a size of up to 2^31 slots during each experiment. An argument of 31 should be used to reproduce the paper's results. The default value for this parameter is 24.
./run_exps.sh 31
Dependencies
Running the experiments requires having the Java Development Kit version 11 or above installed. Plotting the figures to illustrate the experimental results requires having Gnuplot installed. Both dependencies can be obtained using the following commands on Ubuntu or equivalents on other systems.
sudo apt install default-jdksudo apt-get install gnuplot
About
No description, website, or topics provided.
Resources
Readme
Activity
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21 stars
Watchers
2 watching
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2 forks
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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");
}
} catch(__e) { console.warn('[Userscript:Highlight Search Terms]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

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InfiniFilter: Expanding Filters to Infinity and Beyond
This filters library contains the InfiniFilter paper from SIGMOD 2023 as well as some baselines against which it can be compared. InfiniFilter is a probabilistic data structure that answers set-membership queries (similar to a Bloom filter or a Quotient Filter). The core innovation is that InfiniFilter can dynamically expand along with the data while maintaining good guarantees over performance and the false positive rate. The full paper can be accessed here. A video lecture on InfiniFilter appears on youtube.
Compilation
Compile the library by running the following command from the root directory of the repository.
javac filters/*.java bitmap_implementations/*.java infiniFilter_experiments/*.java 
Experimental Reproduction
To reproduce the results of the SIGMOD 2023 paper, run the script run_exps.sh from the root directory of the repository. The script will reproduce Figures 13 to 16 in the paper and name them accordingly: figure13.png to figure.16.png. The raw data used to generate these figures is stored in a group of directories called exp1 to exp6. Running the script again will delete the results of older runs and regenerate them.
The script takes a parameter for power of the maximum number of slots to which it will expand the filter. For example, an argument of 31 means the filter will grow to a size of up to 2^31 slots during each experiment. An argument of 31 should be used to reproduce the paper's results. The default value for this parameter is 24.
./run_exps.sh 31
Dependencies
Running the experiments requires having the Java Development Kit version 11 or above installed. Plotting the figures to illustrate the experimental results requires having Gnuplot installed. Both dependencies can be obtained using the following commands on Ubuntu or equivalents on other systems.
sudo apt install default-jdksudo apt-get install gnuplot
About
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, 'i');
if (__m === '*' || __re.test(location.href)) {
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); }
})();
(function(){
try {
var __m = "youtube.com";
var __re = new RegExp('^' + "youtube\\.com" + '

Skip to content
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InfiniFilter: Expanding Filters to Infinity and Beyond
This filters library contains the InfiniFilter paper from SIGMOD 2023 as well as some baselines against which it can be compared. InfiniFilter is a probabilistic data structure that answers set-membership queries (similar to a Bloom filter or a Quotient Filter). The core innovation is that InfiniFilter can dynamically expand along with the data while maintaining good guarantees over performance and the false positive rate. The full paper can be accessed here. A video lecture on InfiniFilter appears on youtube.
Compilation
Compile the library by running the following command from the root directory of the repository.
javac filters/*.java bitmap_implementations/*.java infiniFilter_experiments/*.java 
Experimental Reproduction
To reproduce the results of the SIGMOD 2023 paper, run the script run_exps.sh from the root directory of the repository. The script will reproduce Figures 13 to 16 in the paper and name them accordingly: figure13.png to figure.16.png. The raw data used to generate these figures is stored in a group of directories called exp1 to exp6. Running the script again will delete the results of older runs and regenerate them.
The script takes a parameter for power of the maximum number of slots to which it will expand the filter. For example, an argument of 31 means the filter will grow to a size of up to 2^31 slots during each experiment. An argument of 31 should be used to reproduce the paper's results. The default value for this parameter is 24.
./run_exps.sh 31
Dependencies
Running the experiments requires having the Java Development Kit version 11 or above installed. Plotting the figures to illustrate the experimental results requires having Gnuplot installed. Both dependencies can be obtained using the following commands on Ubuntu or equivalents on other systems.
sudo apt install default-jdksudo apt-get install gnuplot
About
No description, website, or topics provided.
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, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Auto-enable theater mode on YouTube\n(function() {\n function tryTheater() {\n var btn = document.querySelector('button[aria-label=\"Theater mode\"], ytd-player #player button[title=\"Theater mode\"]');\n if (btn && !btn.classList.contains('activated')) {\n btn.click();\n }\n }\n \n // Try immediately\n tryTheater();\n \n // Try after navigation (SPA)\n var lastUrl = location.href;\n setInterval(function() {\n if (location.href !== lastUrl) {\n lastUrl = location.href;\n setTimeout(tryTheater, 500);\n }\n }, 1000);\n \n // Also try on player load\n var observer = new MutationObserver(tryTheater);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "YouTube Theater Mode Default");
}
} catch(__e) { console.warn('[Userscript:YouTube Theater Mode Default]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

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InfiniFilter: Expanding Filters to Infinity and Beyond
This filters library contains the InfiniFilter paper from SIGMOD 2023 as well as some baselines against which it can be compared. InfiniFilter is a probabilistic data structure that answers set-membership queries (similar to a Bloom filter or a Quotient Filter). The core innovation is that InfiniFilter can dynamically expand along with the data while maintaining good guarantees over performance and the false positive rate. The full paper can be accessed here. A video lecture on InfiniFilter appears on youtube.
Compilation
Compile the library by running the following command from the root directory of the repository.
javac filters/*.java bitmap_implementations/*.java infiniFilter_experiments/*.java 
Experimental Reproduction
To reproduce the results of the SIGMOD 2023 paper, run the script run_exps.sh from the root directory of the repository. The script will reproduce Figures 13 to 16 in the paper and name them accordingly: figure13.png to figure.16.png. The raw data used to generate these figures is stored in a group of directories called exp1 to exp6. Running the script again will delete the results of older runs and regenerate them.
The script takes a parameter for power of the maximum number of slots to which it will expand the filter. For example, an argument of 31 means the filter will grow to a size of up to 2^31 slots during each experiment. An argument of 31 should be used to reproduce the paper's results. The default value for this parameter is 24.
./run_exps.sh 31
Dependencies
Running the experiments requires having the Java Development Kit version 11 or above installed. Plotting the figures to illustrate the experimental results requires having Gnuplot installed. Both dependencies can be obtained using the following commands on Ubuntu or equivalents on other systems.
sudo apt install default-jdksudo apt-get install gnuplot
About
No description, website, or topics provided.
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, 'i');
if (__m === '*' || __re.test(location.href)) {
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); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

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InfiniFilter: Expanding Filters to Infinity and Beyond
This filters library contains the InfiniFilter paper from SIGMOD 2023 as well as some baselines against which it can be compared. InfiniFilter is a probabilistic data structure that answers set-membership queries (similar to a Bloom filter or a Quotient Filter). The core innovation is that InfiniFilter can dynamically expand along with the data while maintaining good guarantees over performance and the false positive rate. The full paper can be accessed here. A video lecture on InfiniFilter appears on youtube.
Compilation
Compile the library by running the following command from the root directory of the repository.
javac filters/*.java bitmap_implementations/*.java infiniFilter_experiments/*.java 
Experimental Reproduction
To reproduce the results of the SIGMOD 2023 paper, run the script run_exps.sh from the root directory of the repository. The script will reproduce Figures 13 to 16 in the paper and name them accordingly: figure13.png to figure.16.png. The raw data used to generate these figures is stored in a group of directories called exp1 to exp6. Running the script again will delete the results of older runs and regenerate them.
The script takes a parameter for power of the maximum number of slots to which it will expand the filter. For example, an argument of 31 means the filter will grow to a size of up to 2^31 slots during each experiment. An argument of 31 should be used to reproduce the paper's results. The default value for this parameter is 24.
./run_exps.sh 31
Dependencies
Running the experiments requires having the Java Development Kit version 11 or above installed. Plotting the figures to illustrate the experimental results requires having Gnuplot installed. Both dependencies can be obtained using the following commands on Ubuntu or equivalents on other systems.
sudo apt install default-jdksudo apt-get install gnuplot
About
No description, website, or topics provided.
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2 watching
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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");
}
} catch(__e) { console.warn('[Userscript:Universal Dark Mode]', __e); }
})();
})();

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InfiniFilter: Expanding Filters to Infinity and Beyond
This filters library contains the InfiniFilter paper from SIGMOD 2023 as well as some baselines against which it can be compared. InfiniFilter is a probabilistic data structure that answers set-membership queries (similar to a Bloom filter or a Quotient Filter). The core innovation is that InfiniFilter can dynamically expand along with the data while maintaining good guarantees over performance and the false positive rate. The full paper can be accessed here. A video lecture on InfiniFilter appears on youtube.
Compilation
Compile the library by running the following command from the root directory of the repository.
javac filters/*.java bitmap_implementations/*.java infiniFilter_experiments/*.java 
Experimental Reproduction
To reproduce the results of the SIGMOD 2023 paper, run the script run_exps.sh from the root directory of the repository. The script will reproduce Figures 13 to 16 in the paper and name them accordingly: figure13.png to figure.16.png. The raw data used to generate these figures is stored in a group of directories called exp1 to exp6. Running the script again will delete the results of older runs and regenerate them.
The script takes a parameter for power of the maximum number of slots to which it will expand the filter. For example, an argument of 31 means the filter will grow to a size of up to 2^31 slots during each experiment. An argument of 31 should be used to reproduce the paper's results. The default value for this parameter is 24.
./run_exps.sh 31
Dependencies
Running the experiments requires having the Java Development Kit version 11 or above installed. Plotting the figures to illustrate the experimental results requires having Gnuplot installed. Both dependencies can be obtained using the following commands on Ubuntu or equivalents on other systems.
sudo apt install default-jdksudo apt-get install gnuplot
About
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