> ## Documentation Index > Fetch the complete documentation index at: https://clickhouse.com/docs/llms.txt > Use this file to discover all available pages before exploring further. # Projections > Page describing what projections are, how they can be used to improve query performance, and how they differ from materialized views. export const RunnableCode = ({children, run = false, showStats = true}) => { const [results, setResults] = useState(null); const [error, setError] = useState(null); const [loading, setLoading] = useState(false); const [showResults, setShowResults] = useState(false); const [stats, setStats] = useState(null); const [isDark, setIsDark] = useState(false); const [hoveredRow, setHoveredRow] = useState(-1); const codeRef = useRef(null); useEffect(() => { if (typeof window !== 'undefined') { const check = () => setIsDark(document.documentElement.classList.contains('dark')); check(); const observer = new MutationObserver(check); observer.observe(document.documentElement, { attributes: true, attributeFilter: ['class'] }); return () => observer.disconnect(); } }, []); useEffect(() => { if (codeRef.current) { const block = codeRef.current.querySelector('.code-block'); if (block) { block.style.marginBottom = '0'; block.style.marginTop = '0'; block.style.borderBottomLeftRadius = '0'; block.style.borderBottomRightRadius = '0'; } } }); const getSqlText = () => { if (!codeRef.current) return ''; const code = codeRef.current.querySelector('code'); return (code || codeRef.current).textContent.trim(); }; const executeQuery = async () => { const sql = getSqlText(); if (!sql) return; setLoading(true); setError(null); setResults(null); setShowResults(true); try { const cleanQuery = sql.replace(/;$/, '').trim(); const params = new URLSearchParams({ query: cleanQuery, default_format: 'JSONCompact', result_overflow_mode: 'break', read_overflow_mode: 'break', allow_experimental_analyzer: '1' }); const res = await fetch(`https://sql-clickhouse.clickhouse.com/?${params.toString()}`, { method: 'POST', headers: { 'Authorization': `Basic ${btoa(`demo:`)}` } }); const text = await res.text(); if (!res.ok) { setError(text || `HTTP ${res.status}`); setLoading(false); return; } const json = JSON.parse(text); setResults(json); setStats(json.statistics || null); } catch (err) { setError(err.message || 'Query execution failed'); } setLoading(false); }; useEffect(() => { if (run) executeQuery(); }, []); const formatRows = n => { if (n >= 1e9) return `${(n / 1e9).toFixed(1)}B`; if (n >= 1e6) return `${(n / 1e6).toFixed(1)}M`; if (n >= 1e3) return `${(n / 1e3).toFixed(1)}K`; return String(n); }; const formatBytes = b => { if (b >= 1e9) return `${(b / 1e9).toFixed(2)} GB`; if (b >= 1e6) return `${(b / 1e6).toFixed(2)} MB`; if (b >= 1e3) return `${(b / 1e3).toFixed(2)} KB`; return `${b} B`; }; const isNumericType = type => { return (/^(UInt|Int|Float|Decimal)/).test(type); }; const isHyperlink = value => { return typeof value === 'string' && (/^https?:\/\//).test(value); }; const computeColumnExtremes = (meta, data) => { const extremes = {}; for (let i = 0; i < meta.length; i++) { if (isNumericType(meta[i].type)) { let min = Infinity, max = -Infinity; for (const row of data) { const v = Number(row[i]); if (!isNaN(v)) { if (v < min) min = v; if (v > max) max = v; } } if (max > -Infinity) { extremes[i] = { min, max }; } } } return extremes; }; const computeColumnWidths = (meta, data) => { const lengths = meta.map((col, i) => { const headerLen = col.name.length + col.type.length + 1; let maxData = 0; for (const row of data) { const v = row[i]; const len = v === null ? 4 : String(v).length; if (len > maxData) maxData = len; } return Math.max(headerLen, maxData); }); const total = lengths.reduce((s, l) => s + l, 0); return lengths.map(l => `${(l / total * 100).toFixed(1)}%`); }; const copyResultsAsTSV = () => { if (!results || !results.meta || !results.data) return; const header = results.meta.map(col => col.name).join('\t'); const rows = results.data.map(row => row.map(cell => cell === null ? 'NULL' : String(cell)).join('\t')); const tsv = [header, ...rows].join('\n'); navigator.clipboard.writeText(tsv); }; const borderColor = isDark ? 'rgba(255,255,255,0.15)' : '#e5e7eb'; const bgColor = isDark ? 'rgba(255,255,255,0.05)' : '#f9fafb'; const headerBg = isDark ? '#2a2a2a' : '#f3f4f6'; const textColor = isDark ? '#e5e7eb' : '#1f2937'; const mutedColor = isDark ? '#d1d5db' : '#6b7280'; const accentColor = isDark ? '#FAFF69' : '#323232'; const accentTextColor = isDark ? '#000' : '#fff'; const barColor = isDark ? '#35372f' : '#d2d2d2'; const cellBg = isDark ? '#1f201b' : '#ffffff'; const cellBgHover = isDark ? 'lch(15.8 0 0)' : '#f0f0f0'; const extremes = results && results.meta && results.data ? computeColumnExtremes(results.meta, results.data) : {}; const colWidths = results && results.meta && results.data ? computeColumnWidths(results.meta, results.data) : []; const getCellBarStyle = (cell, ci, ri) => { if (cell === null) return null; const colMeta = results.meta[ci]; if (!isNumericType(colMeta.type) || !extremes[ci] || results.data.length <= 1 || extremes[ci].max <= 0) return null; const ratio = 100 * Number(cell) / extremes[ci].max; const bg = ri === hoveredRow ? cellBgHover : cellBg; return { background: `linear-gradient(to right, ${barColor} 0%, ${barColor} ${ratio}%, ${bg} ${ratio}%, ${bg} 100%)` }; }; const renderCell = (cell, ci) => { if (cell === null) { return NULL; } const value = String(cell); if (isHyperlink(value)) { return {value} ; } return value; }; return
{}
{children}
{}
{results && } {showStats && stats && Read {formatRows(stats.rows_read)} rows, {formatBytes(stats.bytes_read)} in {stats.elapsed.toFixed(3)}s }
{} {showResults &&
{loading &&
Executing query...
} {error &&
{error}
} {results && results.meta && results.data &&
{results.meta.map((col, i) =>
1 ? 'right' : 'left', backgroundColor: headerBg, borderBottom: `1px solid ${borderColor}`, color: textColor, fontWeight: 600, fontSize: '12px', whiteSpace: 'nowrap', overflow: 'hidden', textOverflow: 'ellipsis' }}> {col.name} {col.type}
)} {results.data.map((row, ri) => row.map((cell, ci) =>
setHoveredRow(ri)} onMouseLeave={() => setHoveredRow(-1)} style={{ padding: '4px 12px', color: textColor, whiteSpace: 'nowrap', overflow: 'hidden', textOverflow: 'ellipsis', textAlign: isNumericType(results.meta[ci].type) && results.meta.length > 1 ? 'right' : 'left', borderBottom: `1px solid ${borderColor}`, backgroundColor: ri === hoveredRow ? cellBgHover : ri % 2 === 0 ? 'transparent' : bgColor, transition: 'background-color 0.1s', ...getCellBarStyle(cell, ci, ri) }}> {renderCell(cell, ci)}
))}
} {results && results.data &&
{results.rows} row{results.rows !== 1 ? 's' : ''}
}
}
; }; export const Image = ({img, alt, size = "lg"}) => { const normalizedSize = ["sm", "md", "lg"].includes(size) ? size : "lg"; return
{alt}
; };

Introduction

ClickHouse offers various mechanisms of speeding up analytical queries on large amounts of data for real-time scenarios. One such mechanism to speed up your queries is through the use of *Projections*. Projections help optimize queries by creating a reordering of data by attributes of interest. This can be: 1. A complete reordering 2. A subset of the original table with a different order 3. A precomputed aggregation (similar to a materialized view) but with an ordering aligned to the aggregation.