Query Patterns & Best Practices

Query patterns represent proven, reusable solutions to common graph querying challenges. Understanding and applying effective query patterns is essential for writing performant, maintainable GQL queries in Geode. These patterns encode best practices learned from production deployments and help you avoid common pitfalls. Geode’s implementation of the ISO/IEC 39075:2024 GQL standard enables powerful pattern matching capabilities. By mastering query patterns, you can write concise, expressive queries that leverage Geode’s optimization engine effectively while maintaining code clarity and performance. This comprehensive guide explores essential query patterns, from basic node and relationship matching through advanced traversal strategies, aggregation patterns, and optimization techniques. <h3 id="fundamental-pattern-matching" class="position-relative d-flex align-items-center group"> Fundamental Pattern Matching <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="fundamental-pattern-matching" aria-haspopup="dialog" aria-label="Share link: Fundamental Pattern Matching"> Share link </button> </h3><div id="headingShareModal" class="heading-share-modal" role="dialog" aria-modal="true" aria-labelledby="headingShareTitle" hidden> <div class="hsm-dialog" role="document"> <div class="hsm-header"> <h2 id="headingShareTitle" class="h6 mb-0 fw-bold">Share this section</h2> <button type="button" class="hsm-close" aria-label="Close"> </button> </div> <div class="hsm-body"> <label for="headingShareInput" class="form-label small text-muted mb-1 text-uppercase fw-bold" style="font-size: 0.7rem; letter-spacing: 0.5px;">Permalink</label> <div class="input-group mb-4 hsm-url-group"> <input id="headingShareInput" type="text" class="form-control font-monospace" readonly aria-readonly="true" style="font-size: 0.85rem;" /> <button class="btn btn-primary hsm-copy" type="button" aria-label="Copy" title="Copy"> </button> </div> <div class="small fw-bold mb-2 text-muted text-uppercase" style="font-size: 0.7rem; letter-spacing: 0.5px;">Share via</div> <div class="hsm-share-grid"> <a id="share-twitter" class="btn btn-outline-secondary w-100" target="_blank" rel="noopener noreferrer"> Twitter </a> <a id="share-linkedin" class="btn btn-outline-secondary w-100" target="_blank" rel="noopener noreferrer"> LinkedIn </a> <a id="share-facebook" class="btn btn-outline-secondary w-100" target="_blank" rel="noopener noreferrer"> Facebook </a> </div> </div> </div> </div> <style> .heading-share-modal { position: fixed; inset: 0; display: flex; justify-content: center; align-items: center; background: rgba(0, 0, 0, 0.6); z-index: 1050; padding: 1rem; backdrop-filter: blur(4px); -webkit-backdrop-filter: blur(4px); } .heading-share-modal[hidden] { display: none !important; } .hsm-dialog { max-width: 420px; width: 100%; background: var(--bs-body-bg, #fff); color: var(--bs-body-color, #212529); border: 1px solid var(--bs-border-color, rgba(0,0,0,0.1)); border-radius: 1rem; box-shadow: 0 25px 50px -12px rgba(0, 0, 0, 0.25); overflow: hidden; animation: hsm-fade-in 0.2s ease-out; } @keyframes hsm-fade-in { from { opacity: 0; transform: scale(0.95); } to { opacity: 1; transform: scale(1); } } [data-bs-theme="dark"] .hsm-dialog { background: #1e293b; border-color: rgba(255,255,255,0.1); color: #f8f9fa; } .hsm-header { display: flex; justify-content: space-between; align-items: center; padding: 1rem 1.5rem; border-bottom: 1px solid var(--bs-border-color, rgba(0,0,0,0.1)); background: rgba(0,0,0,0.02); } [data-bs-theme="dark"] .hsm-header { background: rgba(255,255,255,0.02); border-color: rgba(255,255,255,0.1); } .hsm-close { background: transparent; border: none; color: inherit; opacity: 0.5; padding: 0.25rem 0.5rem; border-radius: 0.25rem; font-size: 1.2rem; line-height: 1; transition: opacity 0.2s; } .hsm-close:hover { opacity: 1; } .hsm-body { padding: 1.5rem; } .hsm-url-group { display: flex !important; align-items: stretch; } .hsm-url-group .form-control { flex: 1; min-width: 0; margin: 0; background: var(--bs-secondary-bg, #f8f9fa); border-color: var(--bs-border-color, #dee2e6); border-top-right-radius: 0; border-bottom-right-radius: 0; height: 42px; } .hsm-url-group .btn { flex: 0 0 auto; margin: 0; margin-left: -1px; border-top-left-radius: 0; border-bottom-left-radius: 0; height: 42px; display: flex; align-items: center; justify-content: center; padding: 0 1.25rem; z-index: 2; } [data-bs-theme="dark"] .hsm-url-group .form-control { background: #0f172a; border-color: #334155; color: #e2e8f0; } .hsm-share-grid { display: flex; flex-direction: column; gap: 0.5rem; } .hsm-share-grid .btn { display: flex; align-items: center; justify-content: center; font-size: 0.9rem; padding: 0.6rem; border-color: var(--bs-border-color); width: 100%; } [data-bs-theme="dark"] .hsm-share-grid .btn { color: #e2e8f0; border-color: #475569; } [data-bs-theme="dark"] .hsm-share-grid .btn:hover { background: #334155; border-color: #cbd5e1; } </style> <script> (function(){ const modal = document.getElementById('headingShareModal'); if(!modal) return; const input = modal.querySelector('#headingShareInput'); const copyBtn = modal.querySelector('.hsm-copy'); const twitter = modal.querySelector('#share-twitter'); const linkedin = modal.querySelector('#share-linkedin'); const facebook = modal.querySelector('#share-facebook'); const closeBtn = modal.querySelector('.hsm-close'); let lastFocus=null; let trapBound=false; function buildUrl(id){ return window.location.origin + window.location.pathname + '#' + id; } function isOpen(){ return !modal.hasAttribute('hidden'); } function hydrate(id){ const url=buildUrl(id); input.value=url; const enc=encodeURIComponent(url); const text=encodeURIComponent(document.title); if(twitter) twitter.href=`https://twitter.com/intent/tweet?url=${enc}&text=${text}`; if(linkedin) linkedin.href=`https://www.linkedin.com/sharing/share-offsite/?url=${enc}`; if(facebook) facebook.href=`https://www.facebook.com/sharer/sharer.php?u=${enc}`; } function openModal(id){ lastFocus=document.activeElement; hydrate(id); if(!isOpen()){ modal.removeAttribute('hidden'); } requestAnimationFrame(()=>{ input.focus(); }); trapFocus(); } function closeModal(){ if(!isOpen()) return; modal.setAttribute('hidden',''); if(lastFocus && typeof lastFocus.focus==='function') lastFocus.focus(); } function copyCurrent(){ try{ navigator.clipboard.writeText(input.value).then(()=>feedback(true),()=>fallback()); } catch(e){ fallback(); } } function fallback(){ input.select(); try{ document.execCommand('copy'); feedback(true);}catch(e){ feedback(false);} } function feedback(ok){ if(!copyBtn) return; const icon=copyBtn.querySelector('i'); if(!icon) return; const prev=copyBtn.getAttribute('data-prev')||icon.className; if(!copyBtn.getAttribute('data-prev')) copyBtn.setAttribute('data-prev',prev); icon.className= ok ? 'fa-duotone fa-clipboard-check':'fa-duotone fa-circle-exclamation'; setTimeout(()=>{ icon.className=prev; },1800); } function handleShareClick(e){ e.preventDefault(); const btn=e.currentTarget; const id=btn.getAttribute('data-share-target'); if(id) openModal(id); } function bindShareButtons(){ document.querySelectorAll('.h-share').forEach(btn=>{ if(!btn.dataset.hShareBound){ btn.addEventListener('click', handleShareClick); btn.dataset.hShareBound='1'; } }); } bindShareButtons(); if(document.readyState==='loading'){ document.addEventListener('DOMContentLoaded', bindShareButtons); } else { requestAnimationFrame(bindShareButtons); } document.addEventListener('click', function(e){ const shareBtn=e.target.closest && e.target.closest('.h-share'); if(shareBtn && !shareBtn.dataset.hShareBound){ handleShareClick.call(shareBtn, e); } }, true); document.addEventListener('click', e=>{ if(e.target===modal) closeModal(); if(e.target.closest && e.target.closest('.hsm-close')){ e.preventDefault(); closeModal(); } if(copyBtn && (e.target===copyBtn || (e.target.closest && e.target.closest('.hsm-copy')))) { e.preventDefault(); copyCurrent(); } }); document.addEventListener('keydown', e=>{ if(e.key==='Escape' && isOpen()) closeModal(); }); function trapFocus(){ if(trapBound) return; trapBound=true; modal.addEventListener('keydown', f=>{ if(f.key==='Tab' && isOpen()){ const focusable=[...modal.querySelectorAll('a[href],button,input,textarea,select,[tabindex]:not([tabindex="-1"])')].filter(el=>!el.hasAttribute('disabled')); if(!focusable.length) return; const first=focusable[0]; const last=focusable[focusable.length-1]; if(f.shiftKey && document.activeElement===first){ f.preventDefault(); last.focus(); } else if(!f.shiftKey && document.activeElement===last){ f.preventDefault(); first.focus(); } } }); } if(closeBtn) closeBtn.addEventListener('click', e=>{ e.preventDefault(); closeModal(); }); })(); </script>Basic Node Pattern: <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-gql" data-lang="gql">-- Match nodes by label MATCH (u:User) RETURN u.name, u.email; -- Match with property filter MATCH (u:User {status: 'active'}) RETURN u; -- Match with WHERE clause MATCH (u:User) WHERE u.created_at > '2024-01-01' RETURN u; </code></pre></div>Relationship Pattern: <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-gql" data-lang="gql">-- Match relationship by type MATCH (u:User)-[:FOLLOWS]->(other:User) RETURN u.name, other.name; -- Match with direction MATCH (u:User)<-[:FOLLOWS]-(follower:User) RETURN u.name, count(follower) as follower_count; -- Undirected relationship MATCH (u:User)-[:FRIENDS]-(friend:User) RETURN u.name, friend.name; </code></pre></div>Variable Length Paths: <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-gql" data-lang="gql">-- Friends of friends (2 hops) MATCH (u:User {id: 123})-[:FRIENDS*2]->(fof:User) RETURN DISTINCT fof.name; -- 1 to 3 hops MATCH (u:User {id: 123})-[:KNOWS*1..3]->(connection:User) RETURN connection.name, length(path) as degrees; -- Any length (use with caution!) MATCH path = (start:Node)-[:CONNECTED*]-(end:Node) WHERE start.id = 1 AND end.id = 999 RETURN path; </code></pre></div> <h3 id="pattern-combination-strategies" class="position-relative d-flex align-items-center group"> Pattern Combination Strategies <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="pattern-combination-strategies" aria-haspopup="dialog" aria-label="Share link: Pattern Combination Strategies"> Share link </button> </h3>Multiple Patterns (AND logic): <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-gql" data-lang="gql">-- User and their posts and comments MATCH (u:User {id: 123}) MATCH (u)-[:POSTED]->(p:Post) MATCH (u)-[:COMMENTED]->(c:Comment) RETURN u, collect(DISTINCT p) as posts, collect(DISTINCT c) as comments; </code></pre></div>OPTIONAL MATCH Pattern: <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-gql" data-lang="gql">-- Include users even if they haven't posted MATCH (u:User) OPTIONAL MATCH (u)-[:POSTED]->(p:Post) RETURN u.name, count(p) as post_count; </code></pre></div>UNION Pattern: <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-gql" data-lang="gql">-- Combine multiple patterns MATCH (u:User)-[:POSTED]->(content:Post) RETURN u.name, content.title, 'post' as type UNION ALL MATCH (u:User)-[:COMMENTED]->(content:Comment) RETURN u.name, content.text as title, 'comment' as type; </code></pre></div> <h3 id="aggregation-patterns" class="position-relative d-flex align-items-center group"> Aggregation Patterns <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="aggregation-patterns" aria-haspopup="dialog" aria-label="Share link: Aggregation Patterns"> Share link </button> </h3>Group and Count: <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-gql" data-lang="gql">-- Users by country MATCH (u:User) RETURN u.country, count(*) as user_count ORDER BY user_count DESC; -- Posts per user MATCH (u:User)-[:POSTED]->(p:Post) RETURN u.name, count(p) as post_count ORDER BY post_count DESC LIMIT 10; </code></pre></div>Collect Pattern: <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-gql" data-lang="gql">-- Collect all followers MATCH (u:User {id: 123})<-[:FOLLOWS]-(follower:User) RETURN u.name, collect(follower.name) as followers; -- Collect with DISTINCT MATCH (u:User)-[:POSTED]->(p:Post)-[:HAS_TAG]->(t:Tag) RETURN u.name, collect(DISTINCT t.name) as tags; </code></pre></div>Statistical Aggregations: <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-gql" data-lang="gql">-- Compute statistics MATCH (u:User)-[:PURCHASED]->(p:Product) RETURN count(p) as total_purchases, sum(p.price) as total_spent, avg(p.price) as avg_price, min(p.price) as cheapest, max(p.price) as most_expensive; </code></pre></div> <h3 id="traversal-patterns" class="position-relative d-flex align-items-center group"> Traversal Patterns <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="traversal-patterns" aria-haspopup="dialog" aria-label="Share link: Traversal Patterns"> Share link </button> </h3>Depth-First Exploration: <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-gql" data-lang="gql">-- Explore social network depth-first MATCH path = (start:User {id: 123})-[:FOLLOWS*1..4]->(connected:User) WHERE connected.id <> 123 RETURN path, length(path) as depth ORDER BY depth; </code></pre></div>Breadth-First Shortest Path: <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-gql" data-lang="gql">-- Find shortest path between users MATCH path = shortestPath((u1:User {id: 123})-[:KNOWS*]-(u2:User {id: 456})) RETURN path, length(path) as distance; -- All shortest paths MATCH paths = allShortestPaths((u1:User {id: 123})-[:KNOWS*]-(u2:User {id: 456})) RETURN paths; </code></pre></div>Path Filtering Pattern: <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-gql" data-lang="gql">-- Paths avoiding specific nodes MATCH path = (start:User {id: 123})-[:FOLLOWS*1..5]->(end:User) WHERE NONE(node IN nodes(path) WHERE node.blocked = true) RETURN path; -- Paths with all relationships matching criteria MATCH path = (start)-[r:RATED*1..3]->(end) WHERE ALL(rel IN relationships(path) WHERE rel.rating >= 4) RETURN path; </code></pre></div> <h3 id="filtering-and-predicate-patterns" class="position-relative d-flex align-items-center group"> Filtering and Predicate Patterns <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="filtering-and-predicate-patterns" aria-haspopup="dialog" aria-label="Share link: Filtering and Predicate Patterns"> Share link </button> </h3>Property Comparison: <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-gql" data-lang="gql">-- Range filter MATCH (u:User) WHERE u.age BETWEEN 18 AND 65 AND u.country = 'US' AND u.verified = true RETURN u; -- String matching MATCH (u:User) WHERE u.email ENDS WITH '@example.com' OR u.name STARTS WITH 'John' RETURN u; -- Pattern matching MATCH (u:User) WHERE u.email =~ '.*@(gmail|yahoo)\.com' RETURN u; </code></pre></div>List Operations: <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-gql" data-lang="gql">-- IN operator MATCH (u:User) WHERE u.role IN ['admin', 'moderator'] RETURN u; -- List comprehension MATCH (u:User) WHERE ANY(tag IN u.tags WHERE tag STARTS WITH 'tech-') RETURN u; </code></pre></div>Existence Checks: <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-gql" data-lang="gql">-- Check relationship existence MATCH (u:User) WHERE EXISTS { (u)-[:VERIFIED]->(v:Verification) } RETURN u; -- Check property existence MATCH (u:User) WHERE u.email IS NOT NULL AND u.phone IS NOT NULL RETURN u; </code></pre></div> <h3 id="mutation-patterns" class="position-relative d-flex align-items-center group"> Mutation Patterns <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="mutation-patterns" aria-haspopup="dialog" aria-label="Share link: Mutation Patterns"> Share link </button> </h3>Create Pattern: <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-gql" data-lang="gql">-- Create with relationship CREATE (u:User {name: 'Alice', email: 'alice@example.com'}) CREATE (p:Post {title: 'First Post', content: '...'}) CREATE (u)-[:POSTED {timestamp: current_timestamp()}]->(p) RETURN u, p; -- Create from pattern MATCH (u:User {id: 123}) CREATE (u)-[:POSTED]->(p:Post {title: 'New Post'}) RETURN p; </code></pre></div>MERGE Pattern (upsert): <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-gql" data-lang="gql">-- Create or match user MERGE (u:User {email: 'alice@example.com'}) ON CREATE SET u.created_at = current_timestamp() ON MATCH SET u.last_login = current_timestamp() RETURN u; -- Merge relationship MATCH (u1:User {id: 123}), (u2:User {id: 456}) MERGE (u1)-[f:FOLLOWS]->(u2) ON CREATE SET f.since = current_timestamp() RETURN f; </code></pre></div>Conditional Update Pattern: <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-gql" data-lang="gql">-- Update with condition MATCH (u:User {id: 123}) WHERE u.login_count < 1000 SET u.login_count = u.login_count + 1 RETURN u; -- Batch update MATCH (p:Post) WHERE p.created_at < '2020-01-01' SET p.archived = true RETURN count(p) as archived_count; </code></pre></div> <h3 id="performance-optimization-patterns" class="position-relative d-flex align-items-center group"> Performance Optimization Patterns <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="performance-optimization-patterns" aria-haspopup="dialog" aria-label="Share link: Performance Optimization Patterns"> Share link </button> </h3>Index-Backed Lookups: <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-gql" data-lang="gql">-- Start with indexed lookup MATCH (u:User {email: 'user@example.com'}) -- Uses index MATCH (u)-[:POSTED]->(p:Post) RETURN u, p; -- Avoid starting with unindexed scan -- Inefficient: MATCH (p:Post) MATCH (p)<-[:POSTED]-(u:User {email: 'user@example.com'}) RETURN u, p; </code></pre></div>Early Filtering Pattern: <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-gql" data-lang="gql">-- Filter early in the query MATCH (u:User) WHERE u.country = 'US' -- Reduce search space early MATCH (u)-[:POSTED]->(p:Post) WHERE p.created_at > '2024-01-01' RETURN u, p; </code></pre></div>WITH Clause for Pipeline: <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-gql" data-lang="gql">-- Break complex queries into stages MATCH (u:User) WHERE u.follower_count > 10000 WITH u ORDER BY u.follower_count DESC LIMIT 100 MATCH (u)-[:POSTED]->(p:Post) WHERE p.likes > 1000 RETURN u.name, count(p) as viral_posts; </code></pre></div>Avoid Cartesian Products: <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-gql" data-lang="gql">-- Bad: Cartesian product MATCH (u:User), (p:Post) -- Don't do this! WHERE u.id = p.author_id RETURN u, p; -- Good: Use relationship pattern MATCH (u:User)-[:POSTED]->(p:Post) RETURN u, p; </code></pre></div> <h3 id="analytical-patterns" class="position-relative d-flex align-items-center group"> Analytical Patterns <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="analytical-patterns" aria-haspopup="dialog" aria-label="Share link: Analytical Patterns"> Share link </button> </h3>Recommendation Pattern: <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-gql" data-lang="gql">-- Collaborative filtering MATCH (u:User {id: 123})-[:LIKED]->(item:Product) MATCH (similar:User)-[:LIKED]->(item) WHERE similar.id <> 123 MATCH (similar)-[:LIKED]->(recommendation:Product) WHERE NOT EXISTS { (u)-[:LIKED]->(recommendation) } RETURN recommendation.name, count(*) as score ORDER BY score DESC LIMIT 10; </code></pre></div>Influence Scoring Pattern: <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-gql" data-lang="gql">-- Calculate user influence MATCH (u:User) OPTIONAL MATCH (u)<-[:FOLLOWS]-(follower:User) OPTIONAL MATCH (u)-[:POSTED]->(p:Post) RETURN u.name, count(DISTINCT follower) as followers, count(DISTINCT p) as posts, count(DISTINCT follower) * 2 + count(DISTINCT p) as influence_score ORDER BY influence_score DESC; </code></pre></div>Community Detection Pattern: <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-gql" data-lang="gql">-- Find connected components MATCH (u:User {id: 123})-[:KNOWS*]-(connected:User) RETURN collect(DISTINCT connected.id) as community; -- Mutual connections MATCH (u1:User {id: 123})-[:KNOWS]->(mutual:User)<-[:KNOWS]-(u2:User {id: 456}) RETURN count(mutual) as mutual_friends, collect(mutual.name) as names; </code></pre></div> <h3 id="time-series-patterns" class="position-relative d-flex align-items-center group"> Time-Series Patterns <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="time-series-patterns" aria-haspopup="dialog" aria-label="Share link: Time-Series Patterns"> Share link </button> </h3>Temporal Filtering: <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-gql" data-lang="gql">-- Events in time window MATCH (e:Event) WHERE e.timestamp BETWEEN '2024-01-01' AND '2024-12-31' RETURN e ORDER BY e.timestamp; -- Time-based aggregation MATCH (o:Order) WHERE o.created_at > current_timestamp() - INTERVAL '30 days' RETURN date_trunc('day', o.created_at) as day, count(*) as order_count, sum(o.total) as revenue ORDER BY day; </code></pre></div>Trend Analysis Pattern: <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-gql" data-lang="gql">-- Growth over time MATCH (u:User) RETURN date_trunc('month', u.created_at) as month, count(*) as new_users ORDER BY month; </code></pre></div> <h3 id="anti-patterns-to-avoid" class="position-relative d-flex align-items-center group"> Anti-Patterns to Avoid <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="anti-patterns-to-avoid" aria-haspopup="dialog" aria-label="Share link: Anti-Patterns to Avoid"> Share link </button> </h3>Don’t Fetch Everything: <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-gql" data-lang="gql">-- Bad: Returns huge result set MATCH (n) RETURN n; -- Good: Use pagination MATCH (n:Node) RETURN n ORDER BY n.id LIMIT 100 OFFSET 0; </code></pre></div>Don’t Use Variable Length Without Bounds: <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-gql" data-lang="gql">-- Bad: Can explode MATCH path = (n)-[*]-(m) RETURN path; -- Good: Set reasonable limits MATCH path = (n)-[*1..4]-(m) RETURN path; </code></pre></div>Don’t Skip Relationship Direction When Possible: <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-gql" data-lang="gql">-- Less efficient MATCH (u:User)-[:FOLLOWS]-(other:User) RETURN u, other; -- More efficient (if direction is known) MATCH (u:User)-[:FOLLOWS]->(other:User) RETURN u, other; </code></pre></div> <h3 id="best-practices-summary" class="position-relative d-flex align-items-center group"> Best Practices Summary <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="best-practices-summary" aria-haspopup="dialog" aria-label="Share link: Best Practices Summary"> Share link </button> </h3><ol> <li>Start with indexed lookups to narrow search space early</li> <li>Filter aggressively before expensive operations like traversals</li> <li>Use LIMIT to prevent unbounded result sets</li> <li>Break complex queries into stages with WITH</li> <li>Leverage relationship direction when known</li> <li>Set bounds on variable-length paths to prevent explosions</li> <li>Use OPTIONAL MATCH for left-join semantics</li> <li>Profile queries with EXPLAIN and PROFILE to verify optimization</li> <li>Create appropriate indexes for frequently filtered properties</li> <li>Consider cardinality when ordering MATCH clauses</li> </ol> <h3 id="related-topics" class="position-relative d-flex align-items-center group"> Related Topics <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="related-topics" aria-haspopup="dialog" aria-label="Share link: Related Topics"> Share link </button> </h3><ul> <li><a href="/tags/query-optimization/" >Query Optimization</a> </li> <li><a href="/tags/performance/" >Performance Tuning</a> </li> <li><a href="/tags/indexing/" >Indexing Strategies</a> </li> <li><a href="/tags/pattern-matching/" >Pattern Matching</a> </li> <li><a href="/tags/gql/" >GQL Query Language</a> </li> <li><a href="/tags/best-practices/" >Best Practices</a> </li> </ul> <h3 id="further-reading" class="position-relative d-flex align-items-center group"> Further Reading <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="further-reading" aria-haspopup="dialog" aria-label="Share link: Further Reading"> Share link </button> </h3><ul> <li>GQL Pattern Matching Specification</li> <li>Query Performance Optimization Guide</li> <li>Graph Algorithm Patterns</li> <li>Advanced Traversal Techniques</li> <li>Production Query Patterns</li> </ul> <h3 id="production-grade-query-patterns" class="position-relative d-flex align-items-center group"> Production-Grade Query Patterns <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="production-grade-query-patterns" aria-haspopup="dialog" aria-label="Share link: Production-Grade Query Patterns"> Share link </button> </h3> <h4 id="pagination-with-cursors" class="position-relative d-flex align-items-center group"> Pagination with Cursors <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="pagination-with-cursors" aria-haspopup="dialog" aria-label="Share link: Pagination with Cursors"> Share link </button> </h4>Efficient pagination for large result sets: <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-gql" data-lang="gql">-- Offset-based pagination (simple but slower for deep pages) MATCH (p:Post) WHERE p.status = 'published' RETURN p.post_id, p.title, p.created_at ORDER BY p.created_at DESC SKIP $offset LIMIT $page_size -- Cursor-based pagination (faster, more scalable) MATCH (p:Post) WHERE p.status = 'published' AND ($cursor IS NULL OR p.created_at < $cursor) RETURN p.post_id, p.title, p.created_at ORDER BY p.created_at DESC LIMIT $page_size -- Keyset pagination (best performance for sorted data) MATCH (p:Post) WHERE p.status = 'published' AND (p.created_at, p.post_id) < ($last_timestamp, $last_id) RETURN p.post_id, p.title, p.created_at ORDER BY p.created_at DESC, p.post_id DESC LIMIT 20 </code></pre></div> <h4 id="conditional-query-building" class="position-relative d-flex align-items-center group"> Conditional Query Building <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="conditional-query-building" aria-haspopup="dialog" aria-label="Share link: Conditional Query Building"> Share link </button> </h4>Dynamic queries based on filters: <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-python" data-lang="python"># Python: Build query dynamically based on filters def build_user_query(filters): clauses = ["u.active = true"] # Base filter params = {} if filters.get('email'): clauses.append("u.email =~ $email_pattern") params['email_pattern'] = f".*{filters['email']}.*" if filters.get('min_age'): clauses.append("u.age >= $min_age") params['min_age'] = filters['min_age'] if filters.get('country'): clauses.append("u.country = $country") params['country'] = filters['country'] where_clause = " AND ".join(clauses) query = f""" MATCH (u:User) WHERE {where_clause} RETURN u.user_id, u.name, u.email, u.age ORDER BY u.created_at DESC LIMIT $limit """ params['limit'] = filters.get('limit', 100) return query, params # Usage query, params = build_user_query({ 'email': 'alice', 'min_age': 18, 'country': 'USA', 'limit': 50 }) result, _ = await client.query(query, params) </code></pre></div> <h4 id="batch-operations" class="position-relative d-flex align-items-center group"> Batch Operations <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="batch-operations" aria-haspopup="dialog" aria-label="Share link: Batch Operations"> Share link </button> </h4>Efficiently process multiple operations: <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-gql" data-lang="gql">-- Batch insert with UNWIND UNWIND $users AS user_data CREATE (u:User { user_id: user_data.id, name: user_data.name, email: user_data.email, created_at: datetime() }) -- Batch relationship creation UNWIND $friendships AS friendship MATCH (a:User {user_id: friendship.user_a}) MATCH (b:User {user_id: friendship.user_b}) MERGE (a)-[:FRIENDS_WITH {since: datetime()}]->(b) -- Batch update with conditional logic UNWIND $updates AS update_data MATCH (p:Product {product_id: update_data.id}) SET p.price = update_data.new_price, p.updated_at = datetime() WHERE p.price <> update_data.new_price // Only update if changed </code></pre></div> <h4 id="hierarchical-queries-with-recursion" class="position-relative d-flex align-items-center group"> Hierarchical Queries with Recursion <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="hierarchical-queries-with-recursion" aria-haspopup="dialog" aria-label="Share link: Hierarchical Queries with Recursion"> Share link </button> </h4>Navigate tree structures efficiently: <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-gql" data-lang="gql">-- Find all descendants of a category MATCH path = (root:Category {cat_id: $root_id})-[:SUBCATEGORY_OF*0..]->(descendant:Category) RETURN descendant.cat_id, descendant.name, length(path) AS depth ORDER BY depth, descendant.name -- Find all ancestors (path to root) MATCH path = (leaf:Category {cat_id: $leaf_id})-[:SUBCATEGORY_OF*]->(ancestor:Category) WHERE NOT EXISTS { MATCH (ancestor)-[:SUBCATEGORY_OF]->() } RETURN [node IN nodes(path) | node.name] AS path_to_root -- Limit recursion depth for safety MATCH path = (a:Category)-[:SUBCATEGORY_OF*1..5]->(b:Category) WHERE a.cat_id = $start_id RETURN b.name, length(path) AS depth ORDER BY depth </code></pre></div> <h4 id="aggregation-with-grouping-sets" class="position-relative d-flex align-items-center group"> Aggregation with Grouping Sets <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="aggregation-with-grouping-sets" aria-haspopup="dialog" aria-label="Share link: Aggregation with Grouping Sets"> Share link </button> </h4>Advanced aggregation patterns: <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-gql" data-lang="gql">-- Multi-level aggregation (rollup pattern) MATCH (o:Order)-[:CONTAINS]->(item:OrderLineItem)-[:FOR_PRODUCT]->(p:Product) WHERE o.created_at >= datetime().minusDays(30) RETURN p.category AS category, p.brand AS brand, COUNT(DISTINCT o.order_id) AS order_count, SUM(item.quantity) AS units_sold, SUM(item.total) AS revenue ORDER BY revenue DESC -- Compute subtotals at multiple levels MATCH (o:Order) WHERE o.created_at >= datetime().minusDays(30) WITH date_trunc('day', o.created_at) AS day, o.status AS status, o.total AS amount RETURN day, status, COUNT(*) AS order_count, SUM(amount) AS daily_revenue ORDER BY day DESC, status -- Pivot-like aggregations MATCH (u:User)-[r:RATED]->(p:Product) WITH p.product_id AS product, SUM(CASE WHEN r.rating = 5 THEN 1 ELSE 0 END) AS five_star, SUM(CASE WHEN r.rating = 4 THEN 1 ELSE 0 END) AS four_star, SUM(CASE WHEN r.rating = 3 THEN 1 ELSE 0 END) AS three_star, SUM(CASE WHEN r.rating = 2 THEN 1 ELSE 0 END) AS two_star, SUM(CASE WHEN r.rating = 1 THEN 1 ELSE 0 END) AS one_star RETURN product, five_star, four_star, three_star, two_star, one_star </code></pre></div> <h4 id="subquery-patterns" class="position-relative d-flex align-items-center group"> Subquery Patterns <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="subquery-patterns" aria-haspopup="dialog" aria-label="Share link: Subquery Patterns"> Share link </button> </h4>Complex filtering with correlated subqueries: <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-gql" data-lang="gql">-- Users who have purchased from ALL specified categories MATCH (u:User) WHERE ALL(cat IN $required_categories WHERE EXISTS { MATCH (u)-[:PURCHASED]->(p:Product)-[:IN_CATEGORY]->(c:Category) WHERE c.name = cat }) RETURN u.user_id, u.name -- Find users with above-average activity MATCH (u:User) WITH u, COUNT{MATCH (u)-[:POSTED]->(:Post)} AS post_count WITH AVG(post_count) AS avg_posts MATCH (active:User) WITH active, COUNT{MATCH (active)-[:POSTED]->(:Post)} AS user_posts, avg_posts WHERE user_posts > avg_posts RETURN active.name, user_posts, avg_posts -- Lateral joins (correlated subqueries) MATCH (category:Category) CALL { WITH category MATCH (category)<-[:IN_CATEGORY]-(p:Product) RETURN p ORDER BY p.price DESC LIMIT 3 } RETURN category.name, COLLECT(p.name) AS top_products </code></pre></div> <h4 id="window-functions-ranking-and-analytics" class="position-relative d-flex align-items-center group"> Window Functions (Ranking and Analytics) <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="window-functions-ranking-and-analytics" aria-haspopup="dialog" aria-label="Share link: Window Functions (Ranking and Analytics)"> Share link </button> </h4>Advanced analytical queries: <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-gql" data-lang="gql">-- Rank products within each category MATCH (p:Product)-[:IN_CATEGORY]->(c:Category) WITH c.name AS category, p.name AS product, p.price AS price, p.sales AS sales, RANK() OVER (PARTITION BY c.name ORDER BY p.sales DESC) AS sales_rank WHERE sales_rank <= 10 RETURN category, product, sales, sales_rank ORDER BY category, sales_rank -- Running totals MATCH (o:Order) WHERE o.created_at >= datetime('2025-01-01') WITH o ORDER BY o.created_at RETURN o.order_id, o.created_at, o.total, SUM(o.total) OVER ( ORDER BY o.created_at ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW ) AS running_total -- Percentile calculations MATCH (p:Product) WITH p.price AS price, PERCENTILE_CONT(0.5) OVER () AS median_price, PERCENTILE_CONT(0.25) OVER () AS q1_price, PERCENTILE_CONT(0.75) OVER () AS q3_price RETURN DISTINCT median_price, q1_price, q3_price </code></pre></div> <h3 id="performance-optimization-patterns-1" class="position-relative d-flex align-items-center group"> Performance Optimization Patterns <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="performance-optimization-patterns-1" aria-haspopup="dialog" aria-label="Share link: Performance Optimization Patterns"> Share link </button> </h3> <h4 id="query-plan-analysis" class="position-relative d-flex align-items-center group"> Query Plan Analysis <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="query-plan-analysis" aria-haspopup="dialog" aria-label="Share link: Query Plan Analysis"> Share link </button> </h4>Systematic performance tuning: <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-gql" data-lang="gql">-- Step 1: Explain the query plan EXPLAIN MATCH (u:User {email: $email})-[:PURCHASED]->(p:Product) WHERE p.price > 100 RETURN p.name -- Look for: -- - Full table scans (should use indexes) -- - Cartesian products (accidental cross joins) -- - Large intermediate result sets -- - Missing index usage -- Step 2: Profile actual execution PROFILE MATCH (u:User {email: $email})-[:PURCHASED]->(p:Product) WHERE p.price > 100 RETURN p.name -- Check: -- - db hits per operator -- - rows processed vs. returned -- - execution time per operator </code></pre></div> <h4 id="index-strategy-patterns" class="position-relative d-flex align-items-center group"> Index Strategy Patterns <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="index-strategy-patterns" aria-haspopup="dialog" aria-label="Share link: Index Strategy Patterns"> Share link </button> </h4>Optimize with targeted indexes: <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-gql" data-lang="gql">-- Create indexes for lookup patterns CREATE INDEX FOR (u:User) ON (u.email); CREATE INDEX FOR (p:Product) ON (p.price); CREATE INDEX FOR (o:Order) ON (o.created_at); -- Composite index for multi-column filters CREATE INDEX FOR (u:User) ON (u.country, u.status, u.created_at); -- Use index hints when planner needs help MATCH (u:User) USING INDEX u:User(email) WHERE u.email = $email RETURN u -- Full-text search optimization CREATE TEXT INDEX FOR (p:Post) ON (p.title, p.content); MATCH (p:Post) WHERE p.content CONTAINS $search_term RETURN p </code></pre></div> <h4 id="caching-strategies" class="position-relative d-flex align-items-center group"> Caching Strategies <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="caching-strategies" aria-haspopup="dialog" aria-label="Share link: Caching Strategies"> Share link </button> </h4>Reduce database load with smart caching: <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-python" data-lang="python"># Application-level query result caching class GeodeCachedClient: def __init__(self, client, cache_ttl=300): self.client = client self.cache = {} self.cache_ttl = cache_ttl async def execute_cached(self, query, params=None, cache_key=None): if cache_key is None: cache_key = hash((query, json.dumps(params, sort_keys=True))) if cache_key in self.cache: result, timestamp = self.cache[cache_key] if time.time() - timestamp < self.cache_ttl: return result # Cache hit # Cache miss - execute query result, _ = await self.client.query(query, params) self.cache[cache_key] = (result, time.time()) return result # Usage cached_client = GeodeCachedClient(client, cache_ttl=300) # Frequently accessed data is cached user_count = await cached_client.execute_cached( "MATCH (u:User) WHERE u.active = true RETURN COUNT(u)", cache_key="active_user_count" ) </code></pre></div> <h3 id="advanced-pattern-techniques" class="position-relative d-flex align-items-center group"> Advanced Pattern Techniques <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="advanced-pattern-techniques" aria-haspopup="dialog" aria-label="Share link: Advanced Pattern Techniques"> Share link </button> </h3> <h4 id="graph-algorithm-implementations" class="position-relative d-flex align-items-center group"> Graph Algorithm Implementations <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="graph-algorithm-implementations" aria-haspopup="dialog" aria-label="Share link: Graph Algorithm Implementations"> Share link </button> </h4>Implement custom algorithms: <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-gql" data-lang="gql">-- PageRank-like influence scoring MATCH (u:User) OPTIONAL MATCH (u)<-[:FOLLOWS]-(follower:User) WITH u, COUNT(follower) AS follower_count, COLLECT(follower) AS followers OPTIONAL MATCH (u)<-[:FOLLOWS]-()-[:FOLLOWS]->(influenced:User) WHERE influenced <> u WITH u, follower_count, follower_count + COUNT(DISTINCT influenced) * 0.5 AS influence_score RETURN u.user_id, u.name, influence_score ORDER BY influence_score DESC LIMIT 20 -- Community detection via label propagation // Initialize: Each node has own community ID MATCH (u:User) SET u.community = u.user_id // Iteration 1: Adopt most common neighbor community MATCH (u:User)-[:KNOWS]-(neighbor:User) WITH u, neighbor.community AS neighbor_community, COUNT(*) AS frequency ORDER BY u, frequency DESC WITH u, COLLECT(neighbor_community)[0] AS most_common_community SET u.community = most_common_community // Repeat iteration multiple times, then analyze: MATCH (u:User) RETURN u.community, COUNT(*) AS community_size ORDER BY community_size DESC </code></pre></div> <h4 id="recommendation-engine-patterns" class="position-relative d-flex align-items-center group"> Recommendation Engine Patterns <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="recommendation-engine-patterns" aria-haspopup="dialog" aria-label="Share link: Recommendation Engine Patterns"> Share link </button> </h4>Build recommendation systems: <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-gql" data-lang="gql">-- Collaborative filtering MATCH (user:User {user_id: $user_id})-[:PURCHASED]->(product:Product) <-[:PURCHASED]-(other:User) WHERE other.user_id <> $user_id WITH other, COUNT(product) AS common_purchases ORDER BY common_purchases DESC LIMIT 10 MATCH (other)-[:PURCHASED]->(recommendation:Product) WHERE NOT EXISTS { MATCH (user)-[:PURCHASED]->(recommendation) } WITH recommendation, COUNT(other) AS recommender_count RETURN recommendation.product_id, recommendation.name, recommender_count ORDER BY recommender_count DESC LIMIT 5 -- Content-based filtering MATCH (user:User {user_id: $user_id})-[:PURCHASED]->(liked:Product) WITH user, COLLECT(liked.category) AS liked_categories MATCH (candidate:Product) WHERE candidate.category IN liked_categories AND NOT EXISTS { MATCH (user)-[:PURCHASED]->(candidate) } WITH candidate, SIZE([cat IN candidate.tags WHERE cat IN $user_interests]) AS tag_match_score WHERE tag_match_score > 0 RETURN candidate.product_id, candidate.name, tag_match_score ORDER BY tag_match_score DESC LIMIT 10 </code></pre></div> <h4 id="real-time-analytics-patterns" class="position-relative d-flex align-items-center group"> Real-Time Analytics Patterns <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="real-time-analytics-patterns" aria-haspopup="dialog" aria-label="Share link: Real-Time Analytics Patterns"> Share link </button> </h4>Stream processing with materialized views: <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-gql" data-lang="gql">-- Maintain real-time aggregates // Trigger on insert to Order ON INSERT INTO Order AS new_order DO MATCH (product:Product {product_id: new_order.product_id}) SET product.total_sales = product.total_sales + new_order.quantity, product.revenue = product.revenue + new_order.total, product.last_sold_at = new_order.created_at -- Real-time leaderboards MATCH (u:User) WITH u, COUNT{MATCH (u)-[:POSTED]->(:Post)} AS post_count, COUNT{MATCH (u)<-[:FOLLOWS]-(:User)} AS follower_count WITH u, post_count, follower_count, post_count * 1.0 + follower_count * 2.0 AS score RETURN u.user_id, u.name, score ORDER BY score DESC LIMIT 100 </code></pre></div> <h3 id="pattern-anti-patterns-and-pitfalls" class="position-relative d-flex align-items-center group"> Pattern Anti-Patterns and Pitfalls <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="pattern-anti-patterns-and-pitfalls" aria-haspopup="dialog" aria-label="Share link: Pattern Anti-Patterns and Pitfalls"> Share link </button> </h3> <h4 id="cartesian-product-prevention" class="position-relative d-flex align-items-center group"> Cartesian Product Prevention <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="cartesian-product-prevention" aria-haspopup="dialog" aria-label="Share link: Cartesian Product Prevention"> Share link </button> </h4>Avoid accidental cross joins: <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-gql" data-lang="gql">-- ANTI-PATTERN: Cartesian product MATCH (u:User), (p:Product) WHERE u.country = p.shipping_country // Millions of combinations! RETURN u, p -- CORRECT: Use relationship path MATCH (u:User)-[:INTERESTED_IN]->(c:Category)<-[:IN_CATEGORY]-(p:Product) WHERE u.country = p.shipping_country RETURN u, p -- OR: Add early filtering MATCH (u:User) WHERE u.country = $country WITH u LIMIT 100 // Limit early MATCH (p:Product) WHERE p.shipping_country = $country RETURN u, p </code></pre></div> <h4 id="variable-length-path-limits" class="position-relative d-flex align-items-center group"> Variable-Length Path Limits <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="variable-length-path-limits" aria-haspopup="dialog" aria-label="Share link: Variable-Length Path Limits"> Share link </button> </h4>Always bound path lengths: <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-gql" data-lang="gql">-- DANGEROUS: Unbounded path traversal MATCH path = (a:User)-[:KNOWS*]-(b:User) RETURN path // Can explode! -- SAFE: Bounded traversal MATCH path = (a:User)-[:KNOWS*1..4]-(b:User) WHERE a.user_id = $user_id RETURN path LIMIT 100 -- SAFER: Early termination MATCH path = shortestPath((a:User)-[:KNOWS*..8]-(b:User)) WHERE a.user_id = $user_a AND b.user_id = $user_b RETURN path </code></pre></div> <h4 id="unnecessary-optional-match" class="position-relative d-flex align-items-center group"> Unnecessary OPTIONAL MATCH <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="unnecessary-optional-match" aria-haspopup="dialog" aria-label="Share link: Unnecessary OPTIONAL MATCH"> Share link </button> </h4>Only use when needed: <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-gql" data-lang="gql">-- INEFFICIENT: Unnecessary OPTIONAL MATCH (u:User) OPTIONAL MATCH (u)-[:POSTED]->(p:Post) RETURN u, COUNT(p) // Every user always has 0+ posts -- EFFICIENT: Regular MATCH with aggregation handles missing MATCH (u:User) WITH u, COUNT{MATCH (u)-[:POSTED]->(:Post)} AS post_count RETURN u, post_count // Simpler and faster </code></pre></div> <h3 id="testing-and-validation-patterns" class="position-relative d-flex align-items-center group"> Testing and Validation Patterns <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="testing-and-validation-patterns" aria-haspopup="dialog" aria-label="Share link: Testing and Validation Patterns"> Share link </button> </h3> <h4 id="query-correctness-validation" class="position-relative d-flex align-items-center group"> Query Correctness Validation <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="query-correctness-validation" aria-haspopup="dialog" aria-label="Share link: Query Correctness Validation"> Share link </button> </h4><div class="highlight"><pre tabindex="0" class="chroma"><code class="language-python" data-lang="python"># Test query results with expected data async def test_user_recommendation(): # Setup: Create test data await client.execute(""" CREATE (alice:User {user_id: 'alice'}) CREATE (bob:User {user_id: 'bob'}) CREATE (carol:User {user_id: 'carol'}) CREATE (p1:Product {product_id: 'p1', name: 'Laptop'}) CREATE (p2:Product {product_id: 'p2', name: 'Mouse'}) CREATE (alice)-[:PURCHASED]->(p1) CREATE (bob)-[:PURCHASED]->(p1) CREATE (bob)-[:PURCHASED]->(p2) """) # Execute: Run recommendation query result, _ = await client.query(""" MATCH (alice:User {user_id: 'alice'})-[:PURCHASED]->(p:Product) <-[:PURCHASED]-(other:User) MATCH (other)-[:PURCHASED]->(rec:Product) WHERE NOT EXISTS { MATCH (alice)-[:PURCHASED]->(rec) } RETURN rec.product_id, rec.name """) # Assert: Verify expected recommendations assert len(result.rows) == 1 assert result.rows[0]['rec.product_id'] == 'p2' assert result.rows[0]['rec.name'] == 'Mouse' # Cleanup await client.execute("MATCH (n) DETACH DELETE n") </code></pre></div> <h3 id="related-topics-and-integration" class="position-relative d-flex align-items-center group"> Related Topics and Integration <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="related-topics-and-integration" aria-haspopup="dialog" aria-label="Share link: Related Topics and Integration"> Share link </button> </h3>Query patterns integrate deeply with: <ul> <li>Query Optimization: Plan analysis and index strategy</li> <li>Performance Tuning: Execution optimization</li> <li>Data Modeling: Schema design for query efficiency</li> <li>GQL Language: Standard syntax and semantics</li> <li>Indexing: Strategic index creation</li> <li>Caching: Application-level result caching</li> </ul> Browse the tagged content below to discover comprehensive pattern documentation, query examples, and optimization guides.

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