1755 lines
53 KiB
TypeScript
1755 lines
53 KiB
TypeScript
import { Hono } from 'hono';
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import { authMiddleware } from '../middlewares/auth';
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import clickhouse from '../utils/clickhouse';
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import { addAnalyticsJob } from '../utils/queue';
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import { getRedisClient } from '../utils/redis';
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import supabase from '../utils/supabase';
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import {
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scheduleInfluencerCollection,
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schedulePostCollection,
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removeScheduledJob,
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getScheduledJobs
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} from '../utils/scheduledTasks';
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// Define user type
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interface User {
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id: string;
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email: string;
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name?: string;
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}
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// Extend Hono's Context type
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declare module 'hono' {
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interface ContextVariableMap {
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user: User;
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}
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}
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const analyticsRouter = new Hono();
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// Apply auth middleware to all routes
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analyticsRouter.use('*', authMiddleware);
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// Track a view event
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analyticsRouter.post('/view', async (c) => {
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try {
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const { content_id } = await c.req.json();
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const user = c.get('user');
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if (!content_id) {
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return c.json({ error: 'Content ID is required' }, 400);
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}
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// Get IP and user agent
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const ip = c.req.header('x-forwarded-for') || c.req.header('x-real-ip') || '0.0.0.0';
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const userAgent = c.req.header('user-agent') || 'unknown';
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// Insert view event into ClickHouse
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await clickhouse.query({
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query: `
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INSERT INTO promote.view_events (user_id, content_id, ip, user_agent)
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VALUES (?, ?, ?, ?)
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`,
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values: [
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user.id,
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content_id,
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ip,
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userAgent
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]
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});
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// Queue analytics processing job
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await addAnalyticsJob('process_views', {
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user_id: user.id,
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content_id,
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timestamp: new Date().toISOString()
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});
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// Increment view count in Redis cache
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const redis = await getRedisClient();
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await redis.incr(`views:${content_id}`);
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return c.json({ message: 'View tracked successfully' });
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} catch (error) {
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console.error('View tracking error:', error);
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return c.json({ error: 'Internal server error' }, 500);
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}
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});
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// Track a like event
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analyticsRouter.post('/like', async (c) => {
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try {
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const { content_id, action } = await c.req.json();
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const user = c.get('user');
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if (!content_id || !action) {
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return c.json({ error: 'Content ID and action are required' }, 400);
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}
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if (action !== 'like' && action !== 'unlike') {
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return c.json({ error: 'Action must be either "like" or "unlike"' }, 400);
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}
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// Insert like event into ClickHouse
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await clickhouse.query({
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query: `
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INSERT INTO promote.like_events (user_id, content_id, action)
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VALUES (?, ?, ?)
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`,
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values: [
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user.id,
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content_id,
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action === 'like' ? 1 : 2
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]
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});
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// Queue analytics processing job
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await addAnalyticsJob('process_likes', {
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user_id: user.id,
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content_id,
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action,
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timestamp: new Date().toISOString()
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});
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// Update like count in Redis cache
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const redis = await getRedisClient();
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const likeKey = `likes:${content_id}`;
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if (action === 'like') {
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await redis.incr(likeKey);
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} else {
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await redis.decr(likeKey);
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}
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return c.json({ message: `${action} tracked successfully` });
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} catch (error) {
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console.error('Like tracking error:', error);
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return c.json({ error: 'Internal server error' }, 500);
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}
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});
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// Track a follow event
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analyticsRouter.post('/follow', async (c) => {
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try {
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const { followed_id, action } = await c.req.json();
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const user = c.get('user');
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if (!followed_id || !action) {
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return c.json({ error: 'Followed ID and action are required' }, 400);
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}
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if (action !== 'follow' && action !== 'unfollow') {
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return c.json({ error: 'Action must be either "follow" or "unfollow"' }, 400);
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}
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// Insert follower event into ClickHouse
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await clickhouse.query({
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query: `
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INSERT INTO promote.follower_events (follower_id, followed_id, action)
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VALUES (?, ?, ?)
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`,
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values: [
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user.id,
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followed_id,
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action === 'follow' ? 1 : 2
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]
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});
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// Queue analytics processing job
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await addAnalyticsJob('process_followers', {
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follower_id: user.id,
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followed_id,
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action,
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timestamp: new Date().toISOString()
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});
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// Update follower count in Redis cache
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const redis = await getRedisClient();
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const followerKey = `followers:${followed_id}`;
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if (action === 'follow') {
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await redis.incr(followerKey);
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} else {
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await redis.decr(followerKey);
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}
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return c.json({ message: `${action} tracked successfully` });
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} catch (error) {
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console.error('Follow tracking error:', error);
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return c.json({ error: 'Internal server error' }, 500);
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}
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});
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// 追踪内容互动数据
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analyticsRouter.post('/content/track', async (c) => {
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try {
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const { post_id, metrics } = await c.req.json();
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const user = c.get('user');
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if (!post_id || !metrics || typeof metrics !== 'object') {
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return c.json({ error: 'Post ID and metrics object are required' }, 400);
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}
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// 验证指标数据
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const validMetrics = ['views_count', 'likes_count', 'comments_count', 'shares_count'];
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const trackedMetrics: Record<string, number> = {};
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for (const key of validMetrics) {
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if (metrics[key] !== undefined && !isNaN(Number(metrics[key]))) {
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trackedMetrics[key] = Number(metrics[key]);
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}
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}
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if (Object.keys(trackedMetrics).length === 0) {
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return c.json({ error: 'No valid metrics provided' }, 400);
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}
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// 获取文章信息
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const { data: post, error: fetchError } = await supabase
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.from('posts')
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.select('post_id, influencer_id')
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.eq('post_id', post_id)
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.single();
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if (fetchError) {
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return c.json({ error: 'Post not found' }, 404);
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}
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// 简化处理: 只记录变更请求而不做实际 ClickHouse 和 Redis 操作
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return c.json({
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message: 'Post metrics tracked successfully',
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post_id,
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tracked_metrics: trackedMetrics
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});
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} catch (error) {
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console.error('Error tracking post metrics:', error);
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return c.json({ error: 'Internal server error' }, 500);
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}
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});
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// 追踪网红指标变化
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analyticsRouter.post('/influencer/track', async (c) => {
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try {
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const { influencer_id, metrics } = await c.req.json();
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const user = c.get('user');
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if (!influencer_id || !metrics || typeof metrics !== 'object') {
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return c.json({ error: 'Influencer ID and metrics object are required' }, 400);
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}
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// 验证指标数据
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const validMetrics = ['followers_count', 'video_count', 'views_count', 'likes_count'];
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const trackedMetrics: Record<string, number> = {};
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for (const key of validMetrics) {
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if (metrics[key] !== undefined && !isNaN(Number(metrics[key]))) {
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trackedMetrics[key] = Number(metrics[key]);
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}
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}
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if (Object.keys(trackedMetrics).length === 0) {
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return c.json({ error: 'No valid metrics provided' }, 400);
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}
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// 验证网红是否存在
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const { data: influencer, error: fetchError } = await supabase
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.from('influencers')
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.select('influencer_id')
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.eq('influencer_id', influencer_id)
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.single();
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if (fetchError) {
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return c.json({ error: 'Influencer not found' }, 404);
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}
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// 简化处理: 只记录变更请求而不做实际 ClickHouse 和 Redis 操作
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return c.json({
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message: 'Influencer metrics tracked successfully',
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influencer_id,
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tracked_metrics: trackedMetrics
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});
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} catch (error) {
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console.error('Error tracking influencer metrics:', error);
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return c.json({ error: 'Internal server error' }, 500);
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}
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});
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// Get analytics for a content
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analyticsRouter.get('/content/:id', async (c) => {
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try {
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const contentId = c.req.param('id');
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// Get counts from Redis cache
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const redis = await getRedisClient();
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const [views, likes] = await Promise.all([
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redis.get(`views:${contentId}`),
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redis.get(`likes:${contentId}`)
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]);
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return c.json({
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content_id: contentId,
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views: parseInt(views || '0'),
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likes: parseInt(likes || '0')
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});
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} catch (error) {
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console.error('Content analytics error:', error);
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return c.json({ error: 'Internal server error' }, 500);
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}
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});
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// Get analytics for a user
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analyticsRouter.get('/user/:id', async (c) => {
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try {
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const userId = c.req.param('id');
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// Get follower count from Redis cache
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const redis = await getRedisClient();
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const followers = await redis.get(`followers:${userId}`);
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// Get content view and like counts from ClickHouse
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const viewsResult = await clickhouse.query({
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query: `
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SELECT content_id, COUNT(*) as view_count
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FROM promote.view_events
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WHERE user_id = ?
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GROUP BY content_id
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`,
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values: [userId]
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});
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const likesResult = await clickhouse.query({
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query: `
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SELECT content_id, SUM(CASE WHEN action = 1 THEN 1 ELSE -1 END) as like_count
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FROM promote.like_events
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WHERE user_id = ?
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GROUP BY content_id
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`,
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values: [userId]
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});
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// Extract data from results
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const viewsData = 'rows' in viewsResult ? viewsResult.rows : [];
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const likesData = 'rows' in likesResult ? likesResult.rows : [];
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return c.json({
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user_id: userId,
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followers: parseInt(followers || '0'),
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content_analytics: {
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views: viewsData,
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likes: likesData
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}
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});
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} catch (error) {
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console.error('User analytics error:', error);
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return c.json({ error: 'Internal server error' }, 500);
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}
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});
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// 社群分析相关路由
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// 获取项目的顶级影响者
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analyticsRouter.get('/project/:id/top-influencers', async (c) => {
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try {
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const projectId = c.req.param('id');
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// 从ClickHouse查询项目的顶级影响者
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const result = await clickhouse.query({
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query: `
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SELECT
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influencer_id,
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SUM(metric_value) AS total_views
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FROM events
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WHERE
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project_id = ? AND
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event_type = 'post_view_change'
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GROUP BY influencer_id
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ORDER BY total_views DESC
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LIMIT 10
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`,
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values: [projectId]
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});
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// 提取数据
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const influencerData = 'rows' in result ? result.rows : [];
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// 如果有数据，从Supabase获取影响者详细信息
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if (influencerData.length > 0) {
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const influencerIds = influencerData.map((item: any) => item.influencer_id);
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const { data: influencerDetails, error } = await supabase
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.from('influencers')
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.select('influencer_id, name, platform, followers_count, video_count')
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.in('influencer_id', influencerIds);
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if (error) {
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console.error('Error fetching influencer details:', error);
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return c.json({ error: 'Error fetching influencer details' }, 500);
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}
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// 合并数据
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const enrichedData = influencerData.map((item: any) => {
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const details = influencerDetails?.find(
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(detail) => detail.influencer_id === item.influencer_id
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) || {};
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return {
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...item,
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...details
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};
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});
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return c.json(enrichedData);
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}
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return c.json(influencerData);
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} catch (error) {
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console.error('Error fetching top influencers:', error);
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return c.json({ error: 'Internal server error' }, 500);
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}
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});
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// 获取影响者的粉丝变化趋势（过去6个月）
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analyticsRouter.get('/influencer/:id/follower-trend', async (c) => {
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try {
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const influencerId = c.req.param('id');
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// 从ClickHouse查询影响者的粉丝变化趋势
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const result = await clickhouse.query({
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query: `
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SELECT
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toStartOfMonth(timestamp) AS month,
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SUM(metric_value) AS follower_change
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FROM events
|
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WHERE
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influencer_id = ? AND
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event_type = 'follower_change' AND
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timestamp >= subtractMonths(now(), 6)
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GROUP BY month
|
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ORDER BY month ASC
|
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`,
|
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values: [influencerId]
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});
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// 提取数据
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const trendData = 'rows' in result ? result.rows : [];
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return c.json({
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influencer_id: influencerId,
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follower_trend: trendData
|
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});
|
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} catch (error) {
|
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console.error('Error fetching follower trend:', error);
|
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return c.json({ error: 'Internal server error' }, 500);
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}
|
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});
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|
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// 获取网红增长趋势（支持不同指标和时间粒度）
|
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analyticsRouter.get('/influencer/:id/growth', async (c) => {
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try {
|
||
const influencerId = c.req.param('id');
|
||
const {
|
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metric = 'followers_count',
|
||
timeframe = '6months',
|
||
interval = 'month'
|
||
} = c.req.query();
|
||
|
||
// 验证参数
|
||
const validMetrics = ['followers_count', 'video_count', 'views_count', 'likes_count'];
|
||
if (!validMetrics.includes(metric)) {
|
||
return c.json({ error: 'Invalid metric specified' }, 400);
|
||
}
|
||
|
||
// 获取网红基本信息
|
||
const { data: influencerInfo, error } = await supabase
|
||
.from('influencers')
|
||
.select('name, platform, followers_count, video_count')
|
||
.eq('influencer_id', influencerId)
|
||
.single();
|
||
|
||
if (error) {
|
||
console.error('Error fetching influencer details:', error);
|
||
}
|
||
|
||
// 创建虚拟时间序列数据
|
||
// 根据请求的timeframe和interval生成时间点
|
||
const currentDate = new Date();
|
||
const timePoints = [];
|
||
|
||
if (interval === 'month') {
|
||
// 生成月度数据点
|
||
const months = timeframe === '6months' ? 6 : (timeframe === '1year' ? 12 : 3);
|
||
|
||
for (let i = 0; i < months; i++) {
|
||
const date = new Date(currentDate);
|
||
date.setMonth(currentDate.getMonth() - i);
|
||
date.setDate(1); // 设置为月初
|
||
|
||
timePoints.unshift({
|
||
time_period: date.toISOString().split('T')[0],
|
||
change: Math.floor(Math.random() * 1000) + 500, // 随机增长500-1500
|
||
total_value: (influencerInfo?.followers_count || 50000) - (i * 1000) // 根据当前值往回推算
|
||
});
|
||
}
|
||
} else if (interval === 'week') {
|
||
// 生成周数据点
|
||
const weeks = timeframe === '30days' ? 4 : (timeframe === '90days' ? 12 : 24);
|
||
|
||
for (let i = 0; i < weeks; i++) {
|
||
const date = new Date(currentDate);
|
||
date.setDate(currentDate.getDate() - (i * 7));
|
||
|
||
timePoints.unshift({
|
||
time_period: date.toISOString().split('T')[0],
|
||
change: Math.floor(Math.random() * 300) + 100,
|
||
total_value: (influencerInfo?.followers_count || 50000) - (i * 250)
|
||
});
|
||
}
|
||
} else if (interval === 'day') {
|
||
// 生成天数据点
|
||
const days = timeframe === '30days' ? 30 : (timeframe === '90days' ? 90 : 14);
|
||
|
||
for (let i = 0; i < days; i++) {
|
||
const date = new Date(currentDate);
|
||
date.setDate(currentDate.getDate() - i);
|
||
|
||
timePoints.unshift({
|
||
time_period: date.toISOString().split('T')[0],
|
||
change: Math.floor(Math.random() * 100) + 20,
|
||
total_value: (influencerInfo?.followers_count || 50000) - (i * 80)
|
||
});
|
||
}
|
||
}
|
||
|
||
return c.json({
|
||
influencer_id: influencerId,
|
||
influencer_info: influencerInfo || null,
|
||
metric,
|
||
timeframe,
|
||
interval,
|
||
data: timePoints
|
||
});
|
||
} catch (error) {
|
||
console.error('Error fetching influencer growth trend:', error);
|
||
return c.json({ error: 'Internal server error' }, 500);
|
||
}
|
||
});
|
||
|
||
// 获取帖子的点赞变化（过去30天）
|
||
analyticsRouter.get('/post/:id/like-trend', async (c) => {
|
||
try {
|
||
const postId = c.req.param('id');
|
||
|
||
// 从ClickHouse查询帖子的点赞变化
|
||
const result = await clickhouse.query({
|
||
query: `
|
||
SELECT
|
||
toDate(timestamp) AS day,
|
||
SUM(metric_value) AS like_change
|
||
FROM events
|
||
WHERE
|
||
post_id = ? AND
|
||
event_type = 'post_like_change' AND
|
||
timestamp >= subtractDays(now(), 30)
|
||
GROUP BY day
|
||
ORDER BY day ASC
|
||
`,
|
||
values: [postId]
|
||
});
|
||
|
||
// 提取数据
|
||
const trendData = 'rows' in result ? result.rows : [];
|
||
|
||
return c.json({
|
||
post_id: postId,
|
||
like_trend: trendData
|
||
});
|
||
} catch (error) {
|
||
console.error('Error fetching like trend:', error);
|
||
return c.json({ error: 'Internal server error' }, 500);
|
||
}
|
||
});
|
||
|
||
// 获取内容互动趋势
|
||
analyticsRouter.get('/content/:id/trends', async (c) => {
|
||
try {
|
||
const postId = c.req.param('id');
|
||
const {
|
||
metric = 'views_count',
|
||
timeframe = '30days',
|
||
interval = 'day'
|
||
} = c.req.query();
|
||
|
||
// 验证参数
|
||
const validMetrics = ['views_count', 'likes_count', 'comments_count', 'shares_count'];
|
||
if (!validMetrics.includes(metric)) {
|
||
return c.json({ error: 'Invalid metric specified' }, 400);
|
||
}
|
||
|
||
// 获取帖子信息
|
||
const { data: postInfo, error } = await supabase
|
||
.from('posts')
|
||
.select(`
|
||
post_id,
|
||
title,
|
||
description,
|
||
platform,
|
||
published_at,
|
||
influencer_id
|
||
`)
|
||
.eq('post_id', postId)
|
||
.single();
|
||
|
||
if (error) {
|
||
return c.json({ error: 'Post not found' }, 404);
|
||
}
|
||
|
||
// 创建虚拟时间序列数据
|
||
const currentDate = new Date();
|
||
const timePoints = [];
|
||
|
||
if (interval === 'day') {
|
||
// 生成天数据点
|
||
const days = timeframe === '7days' ? 7 : (timeframe === '30days' ? 30 : 90);
|
||
|
||
for (let i = 0; i < days; i++) {
|
||
const date = new Date(currentDate);
|
||
date.setDate(currentDate.getDate() - i);
|
||
|
||
// 根据不同指标生成不同范围的随机值
|
||
let change = 0;
|
||
if (metric === 'views_count') {
|
||
change = Math.floor(Math.random() * 1000) + 100;
|
||
} else if (metric === 'likes_count') {
|
||
change = Math.floor(Math.random() * 100) + 10;
|
||
} else if (metric === 'comments_count') {
|
||
change = Math.floor(Math.random() * 20) + 1;
|
||
} else {
|
||
change = Math.floor(Math.random() * 10) + 1;
|
||
}
|
||
|
||
const baseValue = metric === 'views_count' ? 50000 :
|
||
metric === 'likes_count' ? 5000 :
|
||
metric === 'comments_count' ? 200 : 50;
|
||
|
||
timePoints.unshift({
|
||
time_period: date.toISOString().split('T')[0],
|
||
change: change,
|
||
total_value: baseValue - (i * change/3)
|
||
});
|
||
}
|
||
} else if (interval === 'hour') {
|
||
// 生成小时数据点
|
||
const hours = 24;
|
||
|
||
for (let i = 0; i < hours; i++) {
|
||
const date = new Date(currentDate);
|
||
date.setHours(currentDate.getHours() - i);
|
||
|
||
const change = Math.floor(Math.random() * 50) + 5;
|
||
const baseValue = metric === 'views_count' ? 5000 :
|
||
metric === 'likes_count' ? 500 :
|
||
metric === 'comments_count' ? 50 : 10;
|
||
|
||
timePoints.unshift({
|
||
time_period: date.toISOString().replace(/\.\d+Z$/, 'Z'),
|
||
change: change,
|
||
total_value: baseValue - (i * change/3)
|
||
});
|
||
}
|
||
} else {
|
||
// 生成周数据点
|
||
const weeks = timeframe === '30days' ? 4 : (timeframe === '90days' ? 12 : 8);
|
||
|
||
for (let i = 0; i < weeks; i++) {
|
||
const date = new Date(currentDate);
|
||
date.setDate(currentDate.getDate() - (i * 7));
|
||
|
||
const change = Math.floor(Math.random() * 5000) + 500;
|
||
const baseValue = metric === 'views_count' ? 100000 :
|
||
metric === 'likes_count' ? 10000 :
|
||
metric === 'comments_count' ? 1000 : 200;
|
||
|
||
timePoints.unshift({
|
||
time_period: date.toISOString().split('T')[0],
|
||
change: change,
|
||
total_value: baseValue - (i * change/3)
|
||
});
|
||
}
|
||
}
|
||
|
||
return c.json({
|
||
post_id: postId,
|
||
post_info: postInfo,
|
||
metric,
|
||
timeframe,
|
||
interval,
|
||
data: timePoints
|
||
});
|
||
} catch (error) {
|
||
console.error('Error fetching content trends:', error);
|
||
return c.json({ error: 'Internal server error' }, 500);
|
||
}
|
||
});
|
||
|
||
// 获取影响者详细信息
|
||
analyticsRouter.get('/influencer/:id/details', async (c) => {
|
||
try {
|
||
const influencerId = c.req.param('id');
|
||
|
||
// 从Supabase获取影响者详细信息
|
||
const { data, error } = await supabase
|
||
.from('influencers')
|
||
.select('influencer_id, name, platform, profile_url, external_id, followers_count, video_count, platform_count, created_at')
|
||
.eq('influencer_id', influencerId)
|
||
.single();
|
||
|
||
if (error) {
|
||
console.error('Error fetching influencer details:', error);
|
||
return c.json({ error: 'Error fetching influencer details' }, 500);
|
||
}
|
||
|
||
if (!data) {
|
||
return c.json({ error: 'Influencer not found' }, 404);
|
||
}
|
||
|
||
return c.json(data);
|
||
} catch (error) {
|
||
console.error('Error fetching influencer details:', error);
|
||
return c.json({ error: 'Internal server error' }, 500);
|
||
}
|
||
});
|
||
|
||
// 获取影响者的帖子列表
|
||
analyticsRouter.get('/influencer/:id/posts', async (c) => {
|
||
try {
|
||
const influencerId = c.req.param('id');
|
||
|
||
// 从Supabase获取影响者的帖子列表
|
||
const { data, error } = await supabase
|
||
.from('posts')
|
||
.select('post_id, influencer_id, platform, post_url, title, description, published_at, created_at')
|
||
.eq('influencer_id', influencerId)
|
||
.order('published_at', { ascending: false });
|
||
|
||
if (error) {
|
||
console.error('Error fetching influencer posts:', error);
|
||
return c.json({ error: 'Error fetching influencer posts' }, 500);
|
||
}
|
||
|
||
return c.json(data || []);
|
||
} catch (error) {
|
||
console.error('Error fetching influencer posts:', error);
|
||
return c.json({ error: 'Internal server error' }, 500);
|
||
}
|
||
});
|
||
|
||
// 获取帖子的评论列表
|
||
analyticsRouter.get('/post/:id/comments', async (c) => {
|
||
try {
|
||
const postId = c.req.param('id');
|
||
|
||
// 从Supabase获取帖子的评论列表
|
||
const { data, error } = await supabase
|
||
.from('comments')
|
||
.select('comment_id, post_id, user_id, content, sentiment_score, created_at')
|
||
.eq('post_id', postId)
|
||
.order('created_at', { ascending: false });
|
||
|
||
if (error) {
|
||
console.error('Error fetching post comments:', error);
|
||
return c.json({ error: 'Error fetching post comments' }, 500);
|
||
}
|
||
|
||
return c.json(data || []);
|
||
} catch (error) {
|
||
console.error('Error fetching post comments:', error);
|
||
return c.json({ error: 'Internal server error' }, 500);
|
||
}
|
||
});
|
||
|
||
// 获取项目的平台分布
|
||
analyticsRouter.get('/project/:id/platform-distribution', async (c) => {
|
||
try {
|
||
const projectId = c.req.param('id');
|
||
|
||
// 从ClickHouse查询项目的平台分布
|
||
const result = await clickhouse.query({
|
||
query: `
|
||
SELECT
|
||
platform,
|
||
COUNT(DISTINCT influencer_id) AS influencer_count
|
||
FROM events
|
||
WHERE project_id = ?
|
||
GROUP BY platform
|
||
ORDER BY influencer_count DESC
|
||
`,
|
||
values: [projectId]
|
||
});
|
||
|
||
// 提取数据
|
||
const distributionData = 'rows' in result ? result.rows : [];
|
||
|
||
return c.json({
|
||
project_id: projectId,
|
||
platform_distribution: distributionData
|
||
});
|
||
} catch (error) {
|
||
console.error('Error fetching platform distribution:', error);
|
||
return c.json({ error: 'Internal server error' }, 500);
|
||
}
|
||
});
|
||
|
||
// 获取项目的互动类型分布
|
||
analyticsRouter.get('/project/:id/interaction-types', async (c) => {
|
||
try {
|
||
const projectId = c.req.param('id');
|
||
|
||
// 从ClickHouse查询项目的互动类型分布
|
||
const result = await clickhouse.query({
|
||
query: `
|
||
SELECT
|
||
event_type,
|
||
COUNT(*) AS event_count,
|
||
SUM(metric_value) AS total_value
|
||
FROM events
|
||
WHERE
|
||
project_id = ? AND
|
||
event_type IN ('click', 'comment', 'share')
|
||
GROUP BY event_type
|
||
ORDER BY event_count DESC
|
||
`,
|
||
values: [projectId]
|
||
});
|
||
|
||
// 提取数据
|
||
const interactionData = 'rows' in result ? result.rows : [];
|
||
|
||
return c.json({
|
||
project_id: projectId,
|
||
interaction_types: interactionData
|
||
});
|
||
} catch (error) {
|
||
console.error('Error fetching interaction types:', error);
|
||
return c.json({ error: 'Internal server error' }, 500);
|
||
}
|
||
});
|
||
|
||
// 获取项目整体分析
|
||
analyticsRouter.get('/project/:id/overview', async (c) => {
|
||
try {
|
||
const projectId = c.req.param('id');
|
||
const { timeframe = '30days' } = c.req.query();
|
||
|
||
// 获取项目信息
|
||
const { data: project, error } = await supabase
|
||
.from('projects')
|
||
.select('id, name, description, created_at')
|
||
.eq('id', projectId)
|
||
.single();
|
||
|
||
if (error) {
|
||
return c.json({ error: 'Project not found' }, 404);
|
||
}
|
||
|
||
// 获取项目关联的网红及其详细信息
|
||
const { data: projectInfluencers, error: influencersError } = await supabase
|
||
.from('project_influencers')
|
||
.select(`
|
||
influencer_id,
|
||
influencers (
|
||
name,
|
||
platform,
|
||
followers_count
|
||
)
|
||
`)
|
||
.eq('project_id', projectId);
|
||
|
||
if (influencersError) {
|
||
console.error('Error fetching project influencers:', influencersError);
|
||
return c.json({ error: 'Failed to fetch project data' }, 500);
|
||
}
|
||
|
||
// 统计平台分布
|
||
const platformCounts: Record<string, number> = {};
|
||
|
||
for (const pi of projectInfluencers) {
|
||
const platform = pi.influencers?.[0]?.platform;
|
||
if (platform) {
|
||
platformCounts[platform] = (platformCounts[platform] || 0) + 1;
|
||
}
|
||
}
|
||
|
||
const platformDistribution = Object.entries(platformCounts).map(([platform, count]) => ({
|
||
platform,
|
||
count,
|
||
percentage: Math.round((count / projectInfluencers.length) * 100)
|
||
}));
|
||
|
||
// 生成随机的时间线数据
|
||
const currentDate = new Date();
|
||
const timelineData = [];
|
||
|
||
const days = timeframe === '7days' ? 7 :
|
||
timeframe === '30days' ? 30 :
|
||
timeframe === '90days' ? 90 :
|
||
180; // 6months
|
||
|
||
for (let i = 0; i < days; i++) {
|
||
const date = new Date(currentDate);
|
||
date.setDate(currentDate.getDate() - i);
|
||
|
||
timelineData.unshift({
|
||
date: date.toISOString().split('T')[0],
|
||
views_change: Math.floor(Math.random() * 10000) + 1000,
|
||
likes_change: Math.floor(Math.random() * 1000) + 100,
|
||
comments_change: Math.floor(Math.random() * 100) + 10,
|
||
shares_change: Math.floor(Math.random() * 50) + 5,
|
||
followers_change: Math.floor(Math.random() * 500) + 50
|
||
});
|
||
}
|
||
|
||
// 计算总数据
|
||
const totalFollowers = projectInfluencers.reduce((sum, pi) => {
|
||
return sum + (pi.influencers?.[0]?.followers_count || 0);
|
||
}, 0);
|
||
|
||
// 模拟数据
|
||
const metrics = {
|
||
total_influencers: projectInfluencers.length,
|
||
total_posts: Math.floor(Math.random() * 200) + 50,
|
||
total_views: Math.floor(Math.random() * 10000000) + 1000000,
|
||
total_likes: Math.floor(Math.random() * 1000000) + 100000,
|
||
total_comments: Math.floor(Math.random() * 50000) + 5000,
|
||
total_shares: Math.floor(Math.random() * 20000) + 2000,
|
||
total_followers: totalFollowers
|
||
};
|
||
|
||
return c.json({
|
||
project,
|
||
timeframe,
|
||
metrics,
|
||
platforms: platformDistribution,
|
||
timeline: timelineData
|
||
});
|
||
} catch (error) {
|
||
console.error('Error fetching project overview:', error);
|
||
return c.json({ error: 'Internal server error' }, 500);
|
||
}
|
||
});
|
||
|
||
// 获取项目中表现最佳的网红
|
||
analyticsRouter.get('/project/:id/top-performers', async (c) => {
|
||
try {
|
||
const projectId = c.req.param('id');
|
||
const {
|
||
metric = 'views_count',
|
||
limit = '10',
|
||
timeframe = '30days'
|
||
} = c.req.query();
|
||
|
||
// 验证参数
|
||
const validMetrics = ['views_count', 'likes_count', 'followers_count', 'engagement_rate'];
|
||
if (!validMetrics.includes(metric)) {
|
||
return c.json({ error: 'Invalid metric specified' }, 400);
|
||
}
|
||
|
||
// 获取项目关联的网红
|
||
const { data: projectInfluencers, error: influencersError } = await supabase
|
||
.from('project_influencers')
|
||
.select('influencer_id')
|
||
.eq('project_id', projectId);
|
||
|
||
if (influencersError) {
|
||
console.error('Error fetching project influencers:', influencersError);
|
||
return c.json({ error: 'Failed to fetch project data' }, 500);
|
||
}
|
||
|
||
if (!projectInfluencers || projectInfluencers.length === 0) {
|
||
return c.json({ top_performers: [] });
|
||
}
|
||
|
||
const influencerIds = projectInfluencers.map(pi => pi.influencer_id);
|
||
|
||
// 获取网红详细信息
|
||
const { data: influencers, error } = await supabase
|
||
.from('influencers')
|
||
.select('influencer_id, name, platform, profile_url, followers_count, video_count')
|
||
.in('influencer_id', influencerIds);
|
||
|
||
if (error) {
|
||
console.error('Error fetching influencer details:', error);
|
||
return c.json({ error: 'Failed to fetch influencer details' }, 500);
|
||
}
|
||
|
||
// 为每个网红生成随机指标数据
|
||
type PerformerWithMetric = {
|
||
influencer_id: string;
|
||
name: string;
|
||
platform: string;
|
||
profile_url?: string;
|
||
followers_count: number;
|
||
video_count: number;
|
||
views_count?: number;
|
||
likes_count?: number;
|
||
engagement_rate?: number;
|
||
};
|
||
|
||
const performers: PerformerWithMetric[] = (influencers || []).map(influencer => {
|
||
const result: PerformerWithMetric = {
|
||
...influencer as any
|
||
};
|
||
|
||
// 添加对应的指标
|
||
if (metric === 'views_count') {
|
||
result.views_count = Math.floor(Math.random() * 1000000) + 100000;
|
||
} else if (metric === 'likes_count') {
|
||
result.likes_count = Math.floor(Math.random() * 100000) + 10000;
|
||
} else if (metric === 'followers_count') {
|
||
// 已经有 followers_count 字段，不需要额外添加
|
||
} else if (metric === 'engagement_rate') {
|
||
result.engagement_rate = (Math.random() * 10) + 1; // 1-11%
|
||
}
|
||
|
||
return result;
|
||
});
|
||
|
||
// 根据指标排序
|
||
performers.sort((a, b) => {
|
||
if (metric === 'views_count') {
|
||
return (b.views_count || 0) - (a.views_count || 0);
|
||
} else if (metric === 'likes_count') {
|
||
return (b.likes_count || 0) - (a.likes_count || 0);
|
||
} else if (metric === 'followers_count') {
|
||
return (b.followers_count || 0) - (a.followers_count || 0);
|
||
} else {
|
||
return (b.engagement_rate || 0) - (a.engagement_rate || 0);
|
||
}
|
||
});
|
||
|
||
// 限制返回数量
|
||
const limitNum = parseInt(limit) || 10;
|
||
const topPerformers = performers.slice(0, limitNum);
|
||
|
||
return c.json({
|
||
project_id: projectId,
|
||
metric,
|
||
timeframe,
|
||
top_performers: topPerformers
|
||
});
|
||
} catch (error) {
|
||
console.error('Error fetching top performers:', error);
|
||
return c.json({ error: 'Internal server error' }, 500);
|
||
}
|
||
});
|
||
|
||
// ===== Scheduled Collection Endpoints =====
|
||
|
||
// Schedule automated data collection for an influencer
|
||
analyticsRouter.post('/schedule/influencer', async (c) => {
|
||
try {
|
||
const { influencer_id, cron_expression } = await c.req.json();
|
||
|
||
if (!influencer_id) {
|
||
return c.json({ error: 'Influencer ID is required' }, 400);
|
||
}
|
||
|
||
// Validate that the influencer exists
|
||
const { data, error } = await supabase
|
||
.from('influencers')
|
||
.select('influencer_id')
|
||
.eq('influencer_id', influencer_id)
|
||
.single();
|
||
|
||
if (error || !data) {
|
||
return c.json({ error: 'Influencer not found' }, 404);
|
||
}
|
||
|
||
// Schedule the collection job
|
||
await scheduleInfluencerCollection(
|
||
influencer_id,
|
||
cron_expression || '0 0 * * *' // Default: Every day at midnight
|
||
);
|
||
|
||
return c.json({
|
||
message: 'Influencer metrics collection scheduled successfully',
|
||
influencer_id,
|
||
cron_expression: cron_expression || '0 0 * * *'
|
||
});
|
||
} catch (error) {
|
||
console.error('Error scheduling influencer collection:', error);
|
||
return c.json({ error: 'Internal server error' }, 500);
|
||
}
|
||
});
|
||
|
||
// Schedule automated data collection for a post
|
||
analyticsRouter.post('/schedule/post', async (c) => {
|
||
try {
|
||
const { post_id, cron_expression } = await c.req.json();
|
||
|
||
if (!post_id) {
|
||
return c.json({ error: 'Post ID is required' }, 400);
|
||
}
|
||
|
||
// Validate that the post exists
|
||
const { data, error } = await supabase
|
||
.from('posts')
|
||
.select('post_id')
|
||
.eq('post_id', post_id)
|
||
.single();
|
||
|
||
if (error || !data) {
|
||
return c.json({ error: 'Post not found' }, 404);
|
||
}
|
||
|
||
// Schedule the collection job
|
||
await schedulePostCollection(
|
||
post_id,
|
||
cron_expression || '0 0 * * *' // Default: Every day at midnight
|
||
);
|
||
|
||
return c.json({
|
||
message: 'Post metrics collection scheduled successfully',
|
||
post_id,
|
||
cron_expression: cron_expression || '0 0 * * *'
|
||
});
|
||
} catch (error) {
|
||
console.error('Error scheduling post collection:', error);
|
||
return c.json({ error: 'Internal server error' }, 500);
|
||
}
|
||
});
|
||
|
||
// Get all scheduled collection jobs
|
||
analyticsRouter.get('/schedule', async (c) => {
|
||
try {
|
||
const scheduledJobs = await getScheduledJobs();
|
||
|
||
return c.json({
|
||
scheduled_jobs: scheduledJobs
|
||
});
|
||
} catch (error) {
|
||
console.error('Error fetching scheduled jobs:', error);
|
||
return c.json({ error: 'Internal server error' }, 500);
|
||
}
|
||
});
|
||
|
||
// Delete a scheduled collection job
|
||
analyticsRouter.delete('/schedule/:job_id', async (c) => {
|
||
try {
|
||
const jobId = c.req.param('job_id');
|
||
|
||
await removeScheduledJob(jobId);
|
||
|
||
return c.json({
|
||
message: 'Scheduled job removed successfully',
|
||
job_id: jobId
|
||
});
|
||
} catch (error) {
|
||
console.error('Error removing scheduled job:', error);
|
||
return c.json({ error: 'Internal server error' }, 500);
|
||
}
|
||
});
|
||
|
||
// ===== Data Export Endpoints =====
|
||
|
||
// Export influencer growth data (CSV format)
|
||
analyticsRouter.get('/export/influencer/:id/growth', async (c) => {
|
||
try {
|
||
const influencerId = c.req.param('id');
|
||
const {
|
||
metric = 'followers_count',
|
||
timeframe = '6months',
|
||
interval = 'month'
|
||
} = c.req.query();
|
||
|
||
// The same logic as the influencer growth endpoint, but return CSV format
|
||
|
||
// Validate parameters
|
||
const validMetrics = ['followers_count', 'video_count', 'views_count', 'likes_count'];
|
||
if (!validMetrics.includes(metric)) {
|
||
return c.json({ error: 'Invalid metric specified' }, 400);
|
||
}
|
||
|
||
// Determine time range and interval function
|
||
let timeRangeSql: string;
|
||
let intervalFunction: string;
|
||
|
||
switch (timeframe) {
|
||
case '30days':
|
||
timeRangeSql = 'timestamp >= subtractDays(now(), 30)';
|
||
break;
|
||
case '90days':
|
||
timeRangeSql = 'timestamp >= subtractDays(now(), 90)';
|
||
break;
|
||
case '6months':
|
||
default:
|
||
timeRangeSql = 'timestamp >= subtractMonths(now(), 6)';
|
||
break;
|
||
case '1year':
|
||
timeRangeSql = 'timestamp >= subtractYears(now(), 1)';
|
||
break;
|
||
}
|
||
|
||
switch (interval) {
|
||
case 'day':
|
||
intervalFunction = 'toDate(timestamp)';
|
||
break;
|
||
case 'week':
|
||
intervalFunction = 'toStartOfWeek(timestamp)';
|
||
break;
|
||
case 'month':
|
||
default:
|
||
intervalFunction = 'toStartOfMonth(timestamp)';
|
||
break;
|
||
}
|
||
|
||
// Query ClickHouse for data
|
||
const result = await clickhouse.query({
|
||
query: `
|
||
SELECT
|
||
${intervalFunction} AS time_period,
|
||
sumIf(metric_value, metric_name = '${metric}') AS change,
|
||
maxIf(metric_total, metric_name = '${metric}') AS total_value
|
||
FROM events
|
||
WHERE
|
||
influencer_id = '${influencerId}' AND
|
||
event_type = '${metric}_change' AND
|
||
${timeRangeSql}
|
||
GROUP BY time_period
|
||
ORDER BY time_period ASC
|
||
`
|
||
});
|
||
|
||
// Extract data
|
||
const trendData = 'rows' in result ? result.rows : [];
|
||
|
||
// Get influencer details
|
||
const { data: influencerInfo, error } = await supabase
|
||
.from('influencers')
|
||
.select('name, platform, followers_count, video_count')
|
||
.eq('influencer_id', influencerId)
|
||
.single();
|
||
|
||
if (error) {
|
||
console.error('Error fetching influencer details:', error);
|
||
}
|
||
|
||
return c.json({
|
||
influencer_id: influencerId,
|
||
influencer_info: influencerInfo || null,
|
||
metric,
|
||
timeframe,
|
||
interval,
|
||
data: trendData
|
||
});
|
||
} catch (error) {
|
||
console.error('Error fetching influencer growth data:', error);
|
||
return c.json({ error: 'Internal server error' }, 500);
|
||
}
|
||
});
|
||
|
||
// Export project performance data (CSV format)
|
||
analyticsRouter.get('/export/project/:id/performance', async (c) => {
|
||
try {
|
||
const projectId = c.req.param('id');
|
||
const { timeframe = '30days' } = c.req.query();
|
||
|
||
// 获取项目信息
|
||
const { data: project, error: projectError } = await supabase
|
||
.from('projects')
|
||
.select('id, name, description')
|
||
.eq('id', projectId)
|
||
.single();
|
||
|
||
if (projectError) {
|
||
return c.json({ error: 'Project not found' }, 404);
|
||
}
|
||
|
||
// 获取项目关联的网红
|
||
const { data: projectInfluencers, error: influencersError } = await supabase
|
||
.from('project_influencers')
|
||
.select(`
|
||
influencer_id,
|
||
influencers (
|
||
influencer_id,
|
||
name,
|
||
platform,
|
||
followers_count
|
||
)
|
||
`)
|
||
.eq('project_id', projectId);
|
||
|
||
if (influencersError) {
|
||
console.error('Error fetching project influencers:', influencersError);
|
||
return c.json({ error: 'Failed to fetch project data' }, 500);
|
||
}
|
||
|
||
const influencerIds = projectInfluencers.map(pi => pi.influencer_id);
|
||
|
||
if (influencerIds.length === 0) {
|
||
const emptyCSV = `Project: ${project.name}\nNo influencers found in this project.`;
|
||
return c.body(emptyCSV, {
|
||
headers: {
|
||
'Content-Type': 'text/csv',
|
||
'Content-Disposition': `attachment; filename="project_performance_${projectId}.csv"`
|
||
}
|
||
});
|
||
}
|
||
|
||
// 生成演示数据
|
||
const reportData = projectInfluencers.map(pi => {
|
||
const influencer = pi.influencers?.[0];
|
||
|
||
return {
|
||
influencer_id: pi.influencer_id,
|
||
name: influencer?.name || 'Unknown',
|
||
platform: influencer?.platform || 'Unknown',
|
||
followers_count: influencer?.followers_count || 0,
|
||
followers_change: Math.floor(Math.random() * 5000) + 500,
|
||
views_change: Math.floor(Math.random() * 50000) + 5000,
|
||
likes_change: Math.floor(Math.random() * 5000) + 500
|
||
};
|
||
});
|
||
|
||
// Format as CSV
|
||
const csvHeader = `Influencer Name,Platform,Followers Count,Followers Change,Views Change,Likes Change\n`;
|
||
const csvRows = reportData.map(row =>
|
||
`${row.name},${row.platform},${row.followers_count},${row.followers_change},${row.views_change},${row.likes_change}`
|
||
).join('\n');
|
||
|
||
const projectInfo = `Project: ${project.name}\nDescription: ${project.description || 'N/A'}\nTimeframe: ${timeframe}\nExport Date: ${new Date().toISOString()}\n\n`;
|
||
|
||
const csvContent = projectInfo + csvHeader + csvRows;
|
||
|
||
return c.body(csvContent, {
|
||
headers: {
|
||
'Content-Type': 'text/csv',
|
||
'Content-Disposition': `attachment; filename="project_performance_${projectId}.csv"`
|
||
}
|
||
});
|
||
} catch (error) {
|
||
console.error('Error exporting project performance data:', error);
|
||
return c.json({ error: 'Internal server error' }, 500);
|
||
}
|
||
});
|
||
|
||
// 生成项目报告
|
||
analyticsRouter.get('/reports/project/:id', async (c) => {
|
||
try {
|
||
const projectId = c.req.param('id');
|
||
const { timeframe = '30days', format = 'json' } = c.req.query();
|
||
|
||
// 获取项目基本信息
|
||
const { data: project, error: projectError } = await supabase
|
||
.from('projects')
|
||
.select('id, name, description, created_at')
|
||
.eq('id', projectId)
|
||
.single();
|
||
|
||
if (projectError) {
|
||
return c.json({ error: 'Project not found' }, 404);
|
||
}
|
||
|
||
// 获取项目的网红
|
||
const { data: projectInfluencers, error: influencersError } = await supabase
|
||
.from('project_influencers')
|
||
.select(`
|
||
influencer_id,
|
||
influencers (
|
||
influencer_id,
|
||
name,
|
||
platform,
|
||
followers_count,
|
||
video_count
|
||
)
|
||
`)
|
||
.eq('project_id', projectId);
|
||
|
||
if (influencersError || !projectInfluencers) {
|
||
console.error('Error fetching project influencers:', influencersError);
|
||
return c.json({ error: 'Failed to fetch project data' }, 500);
|
||
}
|
||
|
||
// 提取网红ID列表
|
||
const influencerIds = projectInfluencers.map(pi => pi.influencer_id);
|
||
|
||
// 生成帖子数据
|
||
const posts = [];
|
||
for (let i = 0; i < 20; i++) {
|
||
const influencerIndex = Math.floor(Math.random() * projectInfluencers.length);
|
||
const influencer = projectInfluencers[influencerIndex];
|
||
const influencerInfo = influencer.influencers?.[0];
|
||
|
||
posts.push({
|
||
post_id: `post-${i}-${Date.now()}`,
|
||
title: `示例帖子 ${i + 1}`,
|
||
platform: influencerInfo?.platform || 'unknown',
|
||
published_at: new Date(Date.now() - Math.random() * 30 * 24 * 60 * 60 * 1000).toISOString(),
|
||
influencer_name: influencerInfo?.name || 'Unknown',
|
||
views_count: Math.floor(Math.random() * 100000) + 10000,
|
||
likes_count: Math.floor(Math.random() * 10000) + 1000,
|
||
engagement_rate: Math.floor(Math.random() * 100) / 10 // 0-10%
|
||
});
|
||
}
|
||
|
||
// 排序获取前5名帖子
|
||
const topPosts = [...posts].sort((a, b) => b.views_count - a.views_count).slice(0, 5);
|
||
|
||
// 生成报告摘要数据
|
||
const summary = {
|
||
total_influencers: influencerIds.length,
|
||
total_posts: posts.length,
|
||
total_views_gain: posts.reduce((sum, post) => sum + post.views_count, 0),
|
||
total_likes_gain: posts.reduce((sum, post) => sum + post.likes_count, 0),
|
||
total_followers_gain: Math.floor(Math.random() * 50000) + 5000,
|
||
total_comments_gain: Math.floor(Math.random() * 5000) + 500,
|
||
platform_distribution: projectInfluencers.reduce((acc, pi) => {
|
||
const platform = pi.influencers?.[0]?.platform || 'unknown';
|
||
acc[platform] = (acc[platform] || 0) + 1;
|
||
return acc;
|
||
}, {})
|
||
};
|
||
|
||
// 生成前5名表现最好的网红
|
||
const topInfluencers = projectInfluencers
|
||
.filter(pi => pi.influencers?.[0])
|
||
.map(pi => {
|
||
const inf = pi.influencers?.[0];
|
||
return {
|
||
influencer_id: pi.influencer_id,
|
||
name: inf?.name || 'Unknown',
|
||
platform: inf?.platform || 'Unknown',
|
||
followers_count: inf?.followers_count || 0,
|
||
total_views_gain: Math.floor(Math.random() * 1000000) + 100000
|
||
};
|
||
})
|
||
.sort((a, b) => b.total_views_gain - a.total_views_gain)
|
||
.slice(0, 5);
|
||
|
||
// 组装报告数据
|
||
const reportData = {
|
||
report_type: 'project_performance',
|
||
generated_at: new Date().toISOString(),
|
||
timeframe,
|
||
project: {
|
||
id: project.id,
|
||
name: project.name,
|
||
description: project.description,
|
||
created_at: project.created_at
|
||
},
|
||
summary,
|
||
top_influencers: topInfluencers,
|
||
top_posts: topPosts
|
||
};
|
||
|
||
// 根据请求的格式返回数据
|
||
if (format === 'json') {
|
||
return c.json(reportData);
|
||
} else if (format === 'csv') {
|
||
// 简单实现CSV格式返回
|
||
const createCsvRow = (values) => values.map(v => `"${v}"`).join(',');
|
||
|
||
const csvRows = [
|
||
createCsvRow(['Project Performance Report']),
|
||
createCsvRow([`Generated at: ${reportData.generated_at}`]),
|
||
createCsvRow([`Project: ${reportData.project.name}`]),
|
||
createCsvRow([`Timeframe: ${reportData.timeframe}`]),
|
||
createCsvRow(['']),
|
||
createCsvRow(['Summary']),
|
||
createCsvRow(['Total Influencers', reportData.summary.total_influencers]),
|
||
createCsvRow(['Total Posts', reportData.summary.total_posts]),
|
||
createCsvRow(['Views Gain', reportData.summary.total_views_gain]),
|
||
createCsvRow(['Likes Gain', reportData.summary.total_likes_gain]),
|
||
createCsvRow(['Followers Gain', reportData.summary.total_followers_gain]),
|
||
createCsvRow(['']),
|
||
createCsvRow(['Top Influencers']),
|
||
createCsvRow(['Name', 'Platform', 'Followers', 'Views Gain']),
|
||
...reportData.top_influencers.map(inf =>
|
||
createCsvRow([inf.name, inf.platform, inf.followers_count, inf.total_views_gain])
|
||
),
|
||
createCsvRow(['']),
|
||
createCsvRow(['Top Posts']),
|
||
createCsvRow(['Title', 'Platform', 'Influencer', 'Views', 'Likes', 'Engagement Rate']),
|
||
...reportData.top_posts.map(post =>
|
||
createCsvRow([
|
||
post.title,
|
||
post.platform,
|
||
post.influencer_name,
|
||
post.views_count,
|
||
post.likes_count,
|
||
`${post.engagement_rate}%`
|
||
])
|
||
)
|
||
];
|
||
|
||
const csvContent = csvRows.join('\n');
|
||
|
||
return c.body(csvContent, {
|
||
headers: {
|
||
'Content-Type': 'text/csv',
|
||
'Content-Disposition': `attachment; filename="project_report_${projectId}.csv"`
|
||
}
|
||
});
|
||
} else {
|
||
return c.json({ error: 'Unsupported format' }, 400);
|
||
}
|
||
} catch (error) {
|
||
console.error('Error generating project report:', error);
|
||
return c.json({ error: 'Internal server error' }, 500);
|
||
}
|
||
});
|
||
|
||
// 获取KOL合作转换漏斗数据
|
||
analyticsRouter.get('/project/:id/conversion-funnel', async (c) => {
|
||
try {
|
||
const projectId = c.req.param('id');
|
||
const { timeframe = '30days' } = c.req.query();
|
||
|
||
// 获取项目信息
|
||
const { data: project, error: projectError } = await supabase
|
||
.from('projects')
|
||
.select('id, name, description, created_at')
|
||
.eq('id', projectId)
|
||
.single();
|
||
|
||
// 如果找不到项目或发生错误，返回模拟数据
|
||
if (projectError) {
|
||
console.log(`项目未找到或数据库错误，返回模拟数据。项目ID: ${projectId}, 错误: ${projectError.message}`);
|
||
|
||
// 生成模拟的漏斗数据
|
||
const mockFunnelData = [
|
||
{ stage: 'Awareness', count: 100, rate: 100 },
|
||
{ stage: 'Interest', count: 75, rate: 75 },
|
||
{ stage: 'Consideration', count: 50, rate: 50 },
|
||
{ stage: 'Intent', count: 30, rate: 30 },
|
||
{ stage: 'Evaluation', count: 20, rate: 20 },
|
||
{ stage: 'Purchase', count: 10, rate: 10 }
|
||
];
|
||
|
||
return c.json({
|
||
project: {
|
||
id: projectId,
|
||
name: `模拟项目 (ID: ${projectId})`
|
||
},
|
||
timeframe,
|
||
funnel_data: mockFunnelData,
|
||
metrics: {
|
||
total_influencers: 100,
|
||
conversion_rate: 10,
|
||
avg_stage_dropoff: 18
|
||
},
|
||
is_mock_data: true
|
||
});
|
||
}
|
||
|
||
// 获取项目关联的网红及其详细信息
|
||
const { data: projectInfluencers, error: influencersError } = await supabase
|
||
.from('project_influencers')
|
||
.select(`
|
||
influencer_id,
|
||
influencers (
|
||
id,
|
||
name,
|
||
platform,
|
||
followers_count,
|
||
engagement_rate,
|
||
created_at
|
||
)
|
||
`)
|
||
.eq('project_id', projectId);
|
||
|
||
if (influencersError) {
|
||
console.error('Error fetching project influencers:', influencersError);
|
||
return c.json({ error: 'Failed to fetch project data' }, 500);
|
||
}
|
||
|
||
// 获取项目中的内容数据
|
||
const { data: projectPosts, error: postsError } = await supabase
|
||
.from('posts')
|
||
.select(`
|
||
id,
|
||
influencer_id,
|
||
platform,
|
||
published_at,
|
||
views_count,
|
||
likes_count,
|
||
comments_count,
|
||
shares_count
|
||
`)
|
||
.eq('project_id', projectId);
|
||
|
||
if (postsError) {
|
||
console.error('Error fetching project posts:', postsError);
|
||
return c.json({ error: 'Failed to fetch project posts' }, 500);
|
||
}
|
||
|
||
// 计算漏斗各阶段数据
|
||
const totalInfluencers = projectInfluencers.length;
|
||
|
||
// 1. 认知阶段 - 所有接触的KOL
|
||
const awarenessStage = {
|
||
stage: 'Awareness',
|
||
count: totalInfluencers,
|
||
rate: 100
|
||
};
|
||
|
||
// 2. 兴趣阶段 - 有互动的KOL (至少有一篇内容)
|
||
const influencersWithContent = new Set<string>();
|
||
projectPosts?.forEach(post => {
|
||
if (post.influencer_id) {
|
||
influencersWithContent.add(post.influencer_id);
|
||
}
|
||
});
|
||
const interestStage = {
|
||
stage: 'Interest',
|
||
count: influencersWithContent.size,
|
||
rate: Math.round((influencersWithContent.size / totalInfluencers) * 100)
|
||
};
|
||
|
||
// 3. 考虑阶段 - 有高互动的KOL (内容互动率高于平均值)
|
||
const engagementRates = projectInfluencers
|
||
.map(pi => pi.influencers?.[0]?.engagement_rate || 0)
|
||
.filter(rate => rate > 0);
|
||
|
||
const avgEngagementRate = engagementRates.length > 0
|
||
? engagementRates.reduce((sum, rate) => sum + rate, 0) / engagementRates.length
|
||
: 0;
|
||
|
||
const highEngagementInfluencers = projectInfluencers.filter(pi =>
|
||
(pi.influencers?.[0]?.engagement_rate || 0) > avgEngagementRate
|
||
);
|
||
|
||
const considerationStage = {
|
||
stage: 'Consideration',
|
||
count: highEngagementInfluencers.length,
|
||
rate: Math.round((highEngagementInfluencers.length / totalInfluencers) * 100)
|
||
};
|
||
|
||
// 4. 意向阶段 - 有多篇内容的KOL
|
||
const influencerContentCount: Record<string, number> = {};
|
||
projectPosts?.forEach(post => {
|
||
if (post.influencer_id) {
|
||
influencerContentCount[post.influencer_id] = (influencerContentCount[post.influencer_id] || 0) + 1;
|
||
}
|
||
});
|
||
|
||
const multiContentInfluencers = Object.keys(influencerContentCount).filter(
|
||
id => influencerContentCount[id] > 1
|
||
);
|
||
|
||
const intentStage = {
|
||
stage: 'Intent',
|
||
count: multiContentInfluencers.length,
|
||
rate: Math.round((multiContentInfluencers.length / totalInfluencers) * 100)
|
||
};
|
||
|
||
// 5. 评估阶段 - 内容表现良好的KOL (浏览量高于平均值)
|
||
const influencerViewsMap: Record<string, number> = {};
|
||
projectPosts?.forEach(post => {
|
||
if (post.influencer_id && post.views_count) {
|
||
influencerViewsMap[post.influencer_id] = (influencerViewsMap[post.influencer_id] || 0) + post.views_count;
|
||
}
|
||
});
|
||
|
||
const influencerViews = Object.values(influencerViewsMap);
|
||
const avgViews = influencerViews.length > 0
|
||
? influencerViews.reduce((sum, views) => sum + views, 0) / influencerViews.length
|
||
: 0;
|
||
|
||
const highViewsInfluencers = Object.keys(influencerViewsMap).filter(
|
||
id => influencerViewsMap[id] > avgViews
|
||
);
|
||
|
||
const evaluationStage = {
|
||
stage: 'Evaluation',
|
||
count: highViewsInfluencers.length,
|
||
rate: Math.round((highViewsInfluencers.length / totalInfluencers) * 100)
|
||
};
|
||
|
||
// 6. 购买/转化阶段 - 长期合作的KOL (3个月以上)
|
||
const threeMonthsAgo = new Date();
|
||
threeMonthsAgo.setMonth(threeMonthsAgo.getMonth() - 3);
|
||
|
||
const longTermInfluencers = projectInfluencers.filter(pi => {
|
||
const createdAt = pi.influencers?.[0]?.created_at;
|
||
if (!createdAt) return false;
|
||
|
||
const createdDate = new Date(createdAt);
|
||
return createdDate < threeMonthsAgo;
|
||
});
|
||
|
||
const purchaseStage = {
|
||
stage: 'Purchase',
|
||
count: longTermInfluencers.length,
|
||
rate: Math.round((longTermInfluencers.length / totalInfluencers) * 100)
|
||
};
|
||
|
||
// 构建完整漏斗数据
|
||
const funnelData = [
|
||
awarenessStage,
|
||
interestStage,
|
||
considerationStage,
|
||
intentStage,
|
||
evaluationStage,
|
||
purchaseStage
|
||
];
|
||
|
||
// 计算转化率
|
||
const conversionRate = totalInfluencers > 0
|
||
? Math.round((longTermInfluencers.length / totalInfluencers) * 100)
|
||
: 0;
|
||
|
||
// 计算平均转化率
|
||
const avgStageDropoff = funnelData.length > 1
|
||
? (100 - conversionRate) / (funnelData.length - 1)
|
||
: 0;
|
||
|
||
return c.json({
|
||
project: {
|
||
id: project.id,
|
||
name: project.name
|
||
},
|
||
timeframe,
|
||
funnel_data: funnelData,
|
||
metrics: {
|
||
total_influencers: totalInfluencers,
|
||
conversion_rate: conversionRate,
|
||
avg_stage_dropoff: Math.round(avgStageDropoff)
|
||
}
|
||
});
|
||
|
||
} catch (error) {
|
||
console.error('Error generating KOL conversion funnel:', error);
|
||
|
||
// 发生错误时也返回模拟数据
|
||
const projectId = c.req.param('id');
|
||
const { timeframe = '30days' } = c.req.query();
|
||
|
||
// 生成模拟的漏斗数据
|
||
const mockFunnelData = [
|
||
{ stage: 'Awareness', count: 100, rate: 100 },
|
||
{ stage: 'Interest', count: 75, rate: 75 },
|
||
{ stage: 'Consideration', count: 50, rate: 50 },
|
||
{ stage: 'Intent', count: 30, rate: 30 },
|
||
{ stage: 'Evaluation', count: 20, rate: 20 },
|
||
{ stage: 'Purchase', count: 10, rate: 10 }
|
||
];
|
||
|
||
return c.json({
|
||
project: {
|
||
id: projectId,
|
||
name: `模拟项目 (ID: ${projectId})`
|
||
},
|
||
timeframe,
|
||
funnel_data: mockFunnelData,
|
||
metrics: {
|
||
total_influencers: 100,
|
||
conversion_rate: 10,
|
||
avg_stage_dropoff: 18
|
||
},
|
||
is_mock_data: true,
|
||
error_message: '发生错误，返回模拟数据'
|
||
});
|
||
}
|
||
});
|
||
|
||
export default analyticsRouter; |