Initial commit of akmon project

doc_news/fulltext_search_alternative.sql

@@ -0,0 +1,108 @@
+-- 备选方案：不使用自定义函数的全文搜索索引
+-- 如果IMMUTABLE函数方法失败，可以使用此备选方案
+
+-- ===================================================================
+-- 方案1: 使用表达式索引 (推荐)
+-- ===================================================================
+
+-- 删除可能存在的有问题的索引
+DROP INDEX IF EXISTS public.idx_contents_fts_title;
+DROP INDEX IF EXISTS public.idx_contents_fts_content;
+
+-- 删除可能有问题的函数
+DROP FUNCTION IF EXISTS public.content_title_to_tsvector(TEXT);
+DROP FUNCTION IF EXISTS public.content_body_to_tsvector(TEXT);
+
+-- 方法1: 使用简单的表达式索引
+CREATE INDEX IF NOT EXISTS idx_contents_fts_title_simple 
+ON public.ak_contents USING gin((to_tsvector('simple', title)));
+
+CREATE INDEX IF NOT EXISTS idx_contents_fts_content_simple 
+ON public.ak_contents USING gin((to_tsvector('simple', content)));
+
+-- ===================================================================
+-- 方案2: 使用预计算列 (最佳性能)
+-- ===================================================================
+
+-- 添加预计算的tsvector列
+DO $$
+BEGIN
+    -- 检查列是否已存在
+    IF NOT EXISTS (
+        SELECT 1 FROM information_schema.columns 
+        WHERE table_name = 'ak_contents' 
+          AND column_name = 'title_search_vector'
+    ) THEN
+        ALTER TABLE public.ak_contents 
+        ADD COLUMN title_search_vector tsvector;
+    END IF;
+    
+    IF NOT EXISTS (
+        SELECT 1 FROM information_schema.columns 
+        WHERE table_name = 'ak_contents' 
+          AND column_name = 'content_search_vector'
+    ) THEN
+        ALTER TABLE public.ak_contents 
+        ADD COLUMN content_search_vector tsvector;
+    END IF;
+END
+$$;
+
+-- 更新现有数据的搜索向量
+UPDATE public.ak_contents SET 
+    title_search_vector = to_tsvector('simple', COALESCE(title, '')),
+    content_search_vector = to_tsvector('simple', COALESCE(content, ''))
+WHERE title_search_vector IS NULL OR content_search_vector IS NULL;
+
+-- 创建触发器自动更新搜索向量
+CREATE OR REPLACE FUNCTION public.update_content_search_vectors()
+RETURNS trigger AS $$
+BEGIN
+    NEW.title_search_vector := to_tsvector('simple', COALESCE(NEW.title, ''));
+    NEW.content_search_vector := to_tsvector('simple', COALESCE(NEW.content, ''));
+    RETURN NEW;
+END;
+$$ LANGUAGE plpgsql;
+
+-- 创建触发器
+DROP TRIGGER IF EXISTS trig_update_content_search_vectors ON public.ak_contents;
+CREATE TRIGGER trig_update_content_search_vectors
+    BEFORE INSERT OR UPDATE ON public.ak_contents
+    FOR EACH ROW EXECUTE FUNCTION public.update_content_search_vectors();
+
+-- 在预计算列上创建索引
+CREATE INDEX IF NOT EXISTS idx_contents_title_search_vector 
+ON public.ak_contents USING gin(title_search_vector);
+
+CREATE INDEX IF NOT EXISTS idx_contents_content_search_vector 
+ON public.ak_contents USING gin(content_search_vector);
+
+-- ===================================================================
+-- 查询示例
+-- ===================================================================
+
+-- 使用方案1的查询方式 (表达式索引)
+/*
+SELECT id, title FROM ak_contents 
+WHERE to_tsvector('simple', title) @@ to_tsquery('simple', 'AI');
+
+SELECT id, title FROM ak_contents 
+WHERE to_tsvector('simple', content) @@ to_tsquery('simple', 'technology');
+*/
+
+-- 使用方案2的查询方式 (预计算列)
+/*
+SELECT id, title FROM ak_contents 
+WHERE title_search_vector @@ to_tsquery('simple', 'AI');
+
+SELECT id, title FROM ak_contents 
+WHERE content_search_vector @@ to_tsquery('simple', 'technology');
+
+-- 组合搜索并按相关性排序
+SELECT 
+    id, title,
+    ts_rank(title_search_vector, query) + ts_rank(content_search_vector, query) as rank
+FROM ak_contents, to_tsquery('simple', 'AI & technology') query
+WHERE title_search_vector @@ query OR content_search_vector @@ query
+ORDER BY rank DESC;
+*/