PostgreSQL은 가장 강력한 오픈소스 관계형 데이터베이스 중 하나다. JSON 지원, Full-Text Search, 파티셔닝 등 고급 기능들을 통해 다양한 요구사항을 충족할 수 있다. 이 글은 PostgreSQL의 고급 기능을 실전 예제와 함께 정리한다.
\n-- JSON 컬럼이 있는 테이블 생성\nCREATE TABLE products (\n id SERIAL PRIMARY KEY,\n name VARCHAR(100) NOT NULL,\n metadata JSON,\n attributes JSONB\n);\n\n-- JSON 데이터 삽입\nINSERT INTO products (name, metadata, attributes) VALUES\n('Laptop', \n '{\"brand\": \"Dell\", \"model\": \"XPS 13\", \"year\": 2024}',\n '{\"cpu\": \"Intel i7\", \"ram\": \"16GB\", \"storage\": \"512GB SSD\", \"price\": 1299}');\n\n-- JSON 데이터 조회\nSELECT name, metadata, attributes FROM products;\n\n-- JSON 필드 접근\nSELECT \n name,\n metadata->>'brand' AS brand,\n attributes->>'cpu' AS cpu,\n (attributes->>'price')::INTEGER AS price\nFROM products;-- JSONB 연산자들\nSELECT \n -- 필드 접근\n attributes->'cpu' AS cpu_json, -- JSON 반환\n attributes->>'cpu' AS cpu_text, -- 텍스트 반환\n \n -- 중첩 필드 접근\n attributes->'specs'->>'ram' AS ram,\n \n -- 배열 접근\n attributes->'tags'->0 AS first_tag,\n attributes->'tags'->>0 AS first_tag_text,\n \n -- 경로 접근\n attributes#>'{specs,ram}' AS ram_path,\n attributes#>>'{specs,ram}' AS ram_path_text,\n \n -- 키 존재 확인\n attributes ? 'cpu' AS has_cpu,\n attributes ?| ARRAY['cpu', 'ram'] AS has_any,\n attributes ?& ARRAY['cpu', 'ram'] AS has_all,\n \n -- JSONB 포함 확인\n attributes @> '{\"cpu\": \"Intel i7\"}' AS contains_cpu,\n '{\"cpu\": \"Intel i7\"}' <@ attributes AS is_contained\n \nFROM products;-- JSONB 함수들\nSELECT \n -- 키 추출\n jsonb_object_keys(attributes) AS keys,\n \n -- 값 추출\n jsonb_array_elements(attributes->'tags') AS tag,\n \n -- 객체 병합\n attributes || '{\"warranty\": \"2 years\"}'::jsonb AS merged,\n \n -- 키 제거\n attributes - 'price' AS without_price,\n attributes - ARRAY['price', 'warranty'] AS without_multiple,\n \n -- 배열 요소 제거\n attributes #- '{tags,0}' AS without_first_tag,\n \n -- 타입 변환\n jsonb_typeof(attributes->'price') AS price_type,\n \n -- JSONB 크기\n jsonb_array_length(attributes->'tags') AS tags_count\n \nFROM products;-- GIN 인덱스 생성 (전체 JSONB 검색용)\nCREATE INDEX idx_products_attributes_gin ON products USING GIN (attributes);\n\n-- 특정 키에 대한 인덱스\nCREATE INDEX idx_products_cpu ON products ((attributes->>'cpu'));\nCREATE INDEX idx_products_price ON products (((attributes->>'price')::INTEGER));\n\n-- JSONB 경로 인덱스\nCREATE INDEX idx_products_specs ON products USING GIN ((attributes->'specs'));\n\n-- 사용 예시\n-- GIN 인덱스를 활용한 쿼리\nSELECT * FROM products \nWHERE attributes @> '{\"cpu\": \"Intel i7\"}';\n\n-- 특정 키 인덱스를 활용한 쿼리\nSELECT * FROM products \nWHERE attributes->>'cpu' = 'Intel i7';-- JSONB 필드 업데이트\nUPDATE products \nSET attributes = attributes || '{\"warranty\": \"2 years\"}'::jsonb\nWHERE id = 1;\n\n-- 중첩 필드 업데이트\nUPDATE products \nSET attributes = jsonb_set(\n attributes,\n '{specs,ram}',\n '\"32GB\"',\n true -- 없으면 생성\n)\nWHERE id = 1;\n\n-- 배열에 요소 추가\nUPDATE products \nSET attributes = jsonb_set(\n attributes,\n '{tags}',\n COALESCE(attributes->'tags', '[]'::jsonb) || '\"new-tag\"'::jsonb\n)\nWHERE id = 1;\n\n-- 키 제거\nUPDATE products \nSET attributes = attributes - 'warranty'\nWHERE id = 1;-- Full-Text Search용 테이블 생성\nCREATE TABLE articles (\n id SERIAL PRIMARY KEY,\n title VARCHAR(200) NOT NULL,\n content TEXT NOT NULL,\n created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP\n);\n\n-- tsvector 컬럼 추가\nALTER TABLE articles ADD COLUMN search_vector tsvector;\n\n-- tsvector 생성 함수\nCREATE OR REPLACE FUNCTION update_search_vector() RETURNS TRIGGER AS $$\nBEGIN\n NEW.search_vector := \n setweight(to_tsvector('english', COALESCE(NEW.title, '')), 'A') ||\n setweight(to_tsvector('english', COALESCE(NEW.content, '')), 'B');\n RETURN NEW;\nEND;\n$$ LANGUAGE plpgsql;\n\n-- 트리거 생성\nCREATE TRIGGER update_articles_search_vector\n BEFORE INSERT OR UPDATE ON articles\n FOR EACH ROW\n EXECUTE FUNCTION update_search_vector();\n\n-- 샘플 데이터\nINSERT INTO articles (title, content) VALUES\n('Introduction to PostgreSQL', 'PostgreSQL is a powerful open-source database...'),\n('Advanced SQL Techniques', 'Learn advanced SQL techniques for data analysis...'),\n('Database Performance Optimization', 'Optimize your database queries for better performance...');\n\n-- Full-Text Search 쿼리\nSELECT title, content\nFROM articles\nWHERE search_vector @@ to_tsquery('english', 'PostgreSQL & database');\n\n-- 순위 기반 검색\nSELECT \n title,\n content,\n ts_rank(search_vector, to_tsquery('english', 'PostgreSQL & database')) AS rank\nFROM articles\nWHERE search_vector @@ to_tsquery('english', 'PostgreSQL & database')\nORDER BY rank DESC;-- GIN 인덱스 생성\nCREATE INDEX idx_articles_search_vector ON articles USING GIN (search_vector);\n\n-- 인덱스를 활용한 빠른 검색\nSELECT title, content\nFROM articles\nWHERE search_vector @@ to_tsquery('english', 'PostgreSQL & database');\n\n-- 여러 언어 지원\nCREATE INDEX idx_articles_search_korean ON articles \nUSING GIN (to_tsvector('korean', title || ' ' || content));\n\n-- 한국어 검색\nSELECT title, content\nFROM articles\nWHERE to_tsvector('korean', title || ' ' || content) \n @@ to_tsquery('korean', '데이터베이스 & 최적화');-- 사용자 정의 텍스트 검색 설정\nCREATE TEXT SEARCH CONFIGURATION english_custom (COPY = english);\n\n-- 동의어 사전 생성\nCREATE TEXT SEARCH DICTIONARY english_synonym (\n TEMPLATE = synonym,\n SYNONYMS = english_synonyms\n);\n\n-- 동의어 사전을 텍스트 검색 설정에 추가\nALTER TEXT SEARCH CONFIGURATION english_custom\n ALTER MAPPING FOR asciiword, word\n WITH english_synonym, english_stem;\n\n-- 사용자 정의 설정 사용\nSELECT title, content\nFROM articles\nWHERE to_tsvector('english_custom', title || ' ' || content)\n @@ to_tsquery('english_custom', 'database | DB');\n\n-- 하이라이트 검색 결과\nSELECT \n title,\n ts_headline(\n 'english',\n content,\n to_tsquery('english', 'PostgreSQL'),\n 'StartSel=<mark>, StopSel=</mark>'\n ) AS highlighted_content\nFROM articles\nWHERE search_vector @@ to_tsquery('english', 'PostgreSQL');-- 부분 인덱스 (NULL이 아닌 경우만 인덱싱)\nCREATE INDEX idx_articles_search_partial ON articles \nUSING GIN (search_vector)\nWHERE search_vector IS NOT NULL;\n\n-- 표현식 인덱스\nCREATE INDEX idx_articles_title_search ON articles \nUSING GIN (to_tsvector('english', title));\n\n-- 복합 인덱스\nCREATE INDEX idx_articles_title_content ON articles \nUSING GIN (\n to_tsvector('english', title),\n to_tsvector('english', content)\n);\n\n-- 통계 정보 업데이트\nANALYZE articles;\n\n-- 쿼리 실행 계획 확인\nEXPLAIN ANALYZE\nSELECT title, content\nFROM articles\nWHERE search_vector @@ to_tsquery('english', 'PostgreSQL');-- 파티션된 테이블 생성\nCREATE TABLE sales (\n id SERIAL,\n sale_date DATE NOT NULL,\n product_id INTEGER,\n amount DECIMAL(10, 2),\n PRIMARY KEY (id, sale_date)\n) PARTITION BY RANGE (sale_date);\n\n-- 월별 파티션 생성\nCREATE TABLE sales_2024_01 PARTITION OF sales\n FOR VALUES FROM ('2024-01-01') TO ('2024-02-01');\n\nCREATE TABLE sales_2024_02 PARTITION OF sales\n FOR VALUES FROM ('2024-02-01') TO ('2024-03-01');\n\nCREATE TABLE sales_2024_03 PARTITION OF sales\n FOR VALUES FROM ('2024-03-01') TO ('2024-04-01');\n\n-- 기본 파티션 (나머지 모든 값)\nCREATE TABLE sales_default PARTITION OF sales DEFAULT;\n\n-- 데이터 삽입\nINSERT INTO sales (sale_date, product_id, amount) VALUES\n('2024-01-15', 1, 100.00),\n('2024-02-20', 2, 200.00),\n('2024-03-10', 3, 150.00);\n\n-- 파티션 프루닝 확인\nEXPLAIN ANALYZE\nSELECT * FROM sales\nWHERE sale_date >= '2024-01-01' AND sale_date < '2024-02-01';-- 리스트 파티셔닝\nCREATE TABLE products_by_region (\n id SERIAL,\n name VARCHAR(100),\n region VARCHAR(50) NOT NULL,\n price DECIMAL(10, 2),\n PRIMARY KEY (id, region)\n) PARTITION BY LIST (region);\n\n-- 지역별 파티션 생성\nCREATE TABLE products_north PARTITION OF products_by_region\n FOR VALUES IN ('Seoul', 'Incheon', 'Gyeonggi');\n\nCREATE TABLE products_south PARTITION OF products_by_region\n FOR VALUES IN ('Busan', 'Daegu', 'Ulsan');\n\nCREATE TABLE products_central PARTITION OF products_by_region\n FOR VALUES IN ('Daejeon', 'Gwangju', 'Jeonju');\n\n-- 데이터 삽입\nINSERT INTO products_by_region (name, region, price) VALUES\n('Product A', 'Seoul', 100.00),\n('Product B', 'Busan', 200.00),\n('Product C', 'Daejeon', 150.00);-- 해시 파티셔닝\nCREATE TABLE user_sessions (\n id SERIAL,\n user_id INTEGER NOT NULL,\n session_data JSONB,\n created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,\n PRIMARY KEY (id, user_id)\n) PARTITION BY HASH (user_id);\n\n-- 4개의 해시 파티션 생성\nCREATE TABLE user_sessions_0 PARTITION OF user_sessions\n FOR VALUES WITH (MODULUS 4, REMAINDER 0);\n\nCREATE TABLE user_sessions_1 PARTITION OF user_sessions\n FOR VALUES WITH (MODULUS 4, REMAINDER 1);\n\nCREATE TABLE user_sessions_2 PARTITION OF user_sessions\n FOR VALUES WITH (MODULUS 4, REMAINDER 2);\n\nCREATE TABLE user_sessions_3 PARTITION OF user_sessions\n FOR VALUES WITH (MODULUS 4, REMAINDER 3);-- 새 파티션 추가\nCREATE TABLE sales_2024_04 PARTITION OF sales\n FOR VALUES FROM ('2024-04-01') TO ('2024-05-01');\n\n-- 파티션 분할\nALTER TABLE sales_2024_01 \n SPLIT PARTITION sales_2024_01 INTO (\n PARTITION sales_2024_01_early FOR VALUES FROM ('2024-01-01') TO ('2024-01-15'),\n PARTITION sales_2024_01_late FOR VALUES FROM ('2024-01-15') TO ('2024-02-01')\n );\n\n-- 파티션 제거 (데이터 보존)\nALTER TABLE sales DETACH PARTITION sales_2024_01;\n\n-- 파티션 삭제 (데이터 삭제)\nDROP TABLE sales_2024_01;\n\n-- 파티션 통계 정보\nSELECT \n schemaname,\n tablename,\n pg_size_pretty(pg_total_relation_size(schemaname||'.'||tablename)) AS size\nFROM pg_tables\nWHERE tablename LIKE 'sales_%'\nORDER BY tablename;-- 기본 B-Tree 인덱스\nCREATE INDEX idx_users_email ON users (email);\n\n-- 복합 인덱스\nCREATE INDEX idx_orders_user_date ON orders (user_id, order_date DESC);\n\n-- 부분 인덱스\nCREATE INDEX idx_active_users ON users (email) \nWHERE is_active = true;\n\n-- 표현식 인덱스\nCREATE INDEX idx_users_lower_email ON users (LOWER(email));\n\n-- UNIQUE 인덱스\nCREATE UNIQUE INDEX idx_users_username_unique ON users (username);-- JSONB용 GIN 인덱스\nCREATE INDEX idx_products_attributes_gin ON products USING GIN (attributes);\n\n-- 배열용 GIN 인덱스\nCREATE INDEX idx_products_tags_gin ON products USING GIN (tags);\n\n-- Full-Text Search용 GIN 인덱스\nCREATE INDEX idx_articles_search_gin ON articles USING GIN (search_vector);-- 기하학적 데이터용 GiST 인덱스\nCREATE INDEX idx_locations_geom ON locations USING GIST (geom);\n\n-- 범위 타입용 GiST 인덱스\nCREATE INDEX idx_events_period ON events USING GIST (period);\n\n-- Full-Text Search용 GiST 인덱스 (GIN 대신)\nCREATE INDEX idx_articles_search_gist ON articles USING GIST (search_vector);-- 인덱스 사용 통계 확인\nSELECT \n schemaname,\n tablename,\n indexname,\n idx_scan AS index_scans,\n idx_tup_read AS tuples_read,\n idx_tup_fetch AS tuples_fetched\nFROM pg_stat_user_indexes\nORDER BY idx_scan;\n\n-- 사용되지 않는 인덱스 찾기\nSELECT \n schemaname,\n tablename,\n indexname,\n pg_size_pretty(pg_relation_size(indexrelid)) AS index_size\nFROM pg_stat_user_indexes\nWHERE idx_scan = 0\nORDER BY pg_relation_size(indexrelid) DESC;\n\n-- 인덱스 크기 확인\nSELECT \n tablename,\n indexname,\n pg_size_pretty(pg_relation_size(indexrelid)) AS index_size\nFROM pg_indexes\nWHERE schemaname = 'public'\nORDER BY pg_relation_size(indexrelid) DESC;\n\n-- 인덱스 재구성\nREINDEX INDEX CONCURRENTLY idx_users_email;\n\n-- 인덱스 통계 업데이트\nANALYZE users;-- EXPLAIN ANALYZE로 쿼리 계획 확인\nEXPLAIN ANALYZE\nSELECT * FROM orders\nWHERE user_id = 123\n AND order_date >= '2024-01-01'\nORDER BY order_date DESC\nLIMIT 10;\n\n-- 인덱스 힌트 (PostgreSQL 12+)\nSET enable_seqscan = off; -- 순차 스캔 비활성화 (테스트용)\n\n-- 통계 정보 업데이트\nANALYZE orders;\n\n-- 쿼리 통계 확인\nSELECT \n query,\n calls,\n total_exec_time,\n mean_exec_time,\n max_exec_time\nFROM pg_stat_statements\nORDER BY total_exec_time DESC\nLIMIT 10;-- 연결 수 제한\nALTER SYSTEM SET max_connections = 200;\n\n-- 공유 버퍼 크기 조정\nALTER SYSTEM SET shared_buffers = '256MB';\n\n-- 작업 메모리 조정\nALTER SYSTEM SET work_mem = '16MB';\n\n-- 설정 적용\nSELECT pg_reload_conf();-- 자동 VACUUM 설정\nALTER TABLE orders SET (\n autovacuum_vacuum_scale_factor = 0.1,\n autovacuum_analyze_scale_factor = 0.05\n);\n\n-- 수동 VACUUM\nVACUUM ANALYZE orders;\n\n-- 전체 VACUUM (테이블 잠금)\nVACUUM FULL orders;\n\n-- VACUUM 통계 확인\nSELECT \n schemaname,\n tablename,\n n_dead_tup AS dead_tuples,\n last_vacuum,\n last_autovacuum,\n last_analyze,\n last_autoanalyze\nFROM pg_stat_user_tables\nORDER BY n_dead_tup DESC;-- 제품 테이블 (JSONB 사용)\nCREATE TABLE products (\n id SERIAL PRIMARY KEY,\n name VARCHAR(200) NOT NULL,\n description TEXT,\n price DECIMAL(10, 2) NOT NULL,\n attributes JSONB,\n created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP\n);\n\n-- 제품 속성 인덱스\nCREATE INDEX idx_products_attributes_gin ON products USING GIN (attributes);\nCREATE INDEX idx_products_price ON products (price);\n\n-- 주문 테이블 (파티셔닝)\nCREATE TABLE orders (\n id SERIAL,\n user_id INTEGER NOT NULL,\n order_date DATE NOT NULL,\n total_amount DECIMAL(10, 2) NOT NULL,\n status VARCHAR(50) NOT NULL,\n shipping_info JSONB,\n PRIMARY KEY (id, order_date)\n) PARTITION BY RANGE (order_date);\n\n-- 월별 파티션\nCREATE TABLE orders_2024_01 PARTITION OF orders\n FOR VALUES FROM ('2024-01-01') TO ('2024-02-01');\n\n-- 주문 검색 (Full-Text Search)\nCREATE TABLE order_notes (\n id SERIAL PRIMARY KEY,\n order_id INTEGER NOT NULL,\n note_text TEXT NOT NULL,\n search_vector tsvector,\n created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP\n);\n\nCREATE INDEX idx_order_notes_search ON order_notes USING GIN (search_vector);\n\n-- 검색 벡터 업데이트 트리거\nCREATE TRIGGER update_order_notes_search_vector\n BEFORE INSERT OR UPDATE ON order_notes\n FOR EACH ROW\n EXECUTE FUNCTION update_search_vector();-- JSONB와 Full-Text Search 조합\nSELECT \n p.id,\n p.name,\n p.price,\n p.attributes->>'brand' AS brand,\n ts_rank(n.search_vector, to_tsquery('english', 'quality')) AS rank\nFROM products p\nJOIN order_notes n ON n.order_id IN (\n SELECT id FROM orders WHERE product_id = p.id\n)\nWHERE p.attributes @> '{\"category\": \"electronics\"}'\n AND n.search_vector @@ to_tsquery('english', 'quality')\nORDER BY rank DESC, p.price\nLIMIT 10;\n\n-- 파티션 프루닝과 인덱스 활용\nSELECT \n o.id,\n o.total_amount,\n o.shipping_info->>'address' AS address\nFROM orders o\nWHERE o.order_date >= '2024-01-01'\n AND o.order_date < '2024-02-01'\n AND o.status = 'completed'\nORDER BY o.order_date DESC;-- 활성 쿼리 확인\nSELECT \n pid,\n usename,\n application_name,\n state,\n query,\n query_start,\n state_change\nFROM pg_stat_activity\nWHERE state != 'idle'\nORDER BY query_start;\n\n-- 테이블 통계\nSELECT \n schemaname,\n tablename,\n n_live_tup AS live_tuples,\n n_dead_tup AS dead_tuples,\n last_vacuum,\n last_autovacuum,\n last_analyze,\n last_autoanalyze\nFROM pg_stat_user_tables\nORDER BY n_dead_tup DESC;\n\n-- 인덱스 사용 통계\nSELECT \n schemaname,\n tablename,\n indexname,\n idx_scan,\n idx_tup_read,\n idx_tup_fetch\nFROM pg_stat_user_indexes\nWHERE idx_scan = 0\nORDER BY pg_relation_size(indexrelid) DESC;-- 데이터베이스 크기\nSELECT \n pg_database.datname,\n pg_size_pretty(pg_database_size(pg_database.datname)) AS size\nFROM pg_database\nORDER BY pg_database_size(pg_database.datname) DESC;\n\n-- 테이블 크기\nSELECT \n schemaname,\n tablename,\n pg_size_pretty(pg_total_relation_size(schemaname||'.'||tablename)) AS total_size,\n pg_size_pretty(pg_relation_size(schemaname||'.'||tablename)) AS table_size,\n pg_size_pretty(pg_total_relation_size(schemaname||'.'||tablename) - \n pg_relation_size(schemaname||'.'||tablename)) AS indexes_size\nFROM pg_tables\nWHERE schemaname = 'public'\nORDER BY pg_total_relation_size(schemaname||'.'||tablename) DESC;PostgreSQL의 고급 기능들을 적절히 활용하면 강력하고 효율적인 데이터베이스 시스템을 구축할 수 있다. 이 글에서 다룬 내용:
\n이러한 기능들을 조합하여 확장 가능하고 성능이 뛰어난 데이터베이스 애플리케이션을 개발할 수 있다.
\nPostgreSQL 고급 기능 - JSON, Full-Text Search, Partitioning
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