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package com.dsideal.base.AI;
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import com.dsideal.base.DataEase.Model.DataEaseModel;
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import com.dsideal.base.Util.LocalMysqlConnectUtil;
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import com.jfinal.plugin.activerecord.Db;
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import com.jfinal.plugin.activerecord.Record;
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import com.dsideal.base.Util.CallDeepSeek;
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import java.util.List;
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import java.util.Map;
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import java.util.Set;
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import java.util.LinkedHashSet;
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import java.util.ArrayList;
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import java.util.concurrent.CountDownLatch;
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import java.text.SimpleDateFormat;
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import java.util.Date;
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import cn.hutool.core.io.FileUtil;
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import java.io.File;
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public class TestMax32K {
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private static final int MAX_CHUNK_SIZE = 30000; // 30K字符限制
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public static void main(String[] args) {
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LocalMysqlConnectUtil.Init();
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// 直接调用生成综合报告
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String report = generateComprehensiveReport();
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System.out.println("\n=== 最终报告 ===");
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System.out.println(report);
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}
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/**
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* 分割过大的单表数据
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*/
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private static List<String> splitLargeTable(String tableName, Set<String> fieldNames,
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List<Record> allTableData, int maxSize) {
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List<String> chunks = new ArrayList<>();
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StringBuilder currentTableChunk = new StringBuilder();
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for (Record dataRecord : allTableData) {
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Map<String, Object> columns = dataRecord.getColumns();
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StringBuilder rowData = new StringBuilder();
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rowData.append("[");
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boolean first = true;
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for (String fieldName : fieldNames) {
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if (!first) rowData.append(",");
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Object value = columns.get(fieldName);
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if (value instanceof String) {
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rowData.append("\"").append(value).append("\"");
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} else {
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rowData.append(value);
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}
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first = false;
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}
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rowData.append("]\n");
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// 检查是否超过限制
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if (currentTableChunk.length() + rowData.length() > maxSize) {
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if (currentTableChunk.length() > 0) {
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chunks.add(currentTableChunk.toString());
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currentTableChunk = new StringBuilder();
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}
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}
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currentTableChunk.append(rowData);
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}
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if (currentTableChunk.length() > 0) {
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chunks.add(currentTableChunk.toString());
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}
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return chunks;
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}
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/**
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* 获取分块数据的方法（可供其他类调用）
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*/
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public static String[] getDataChunks() {
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// 这里可以将main方法中的逻辑提取出来，返回分块数据
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// 为了简化，这里只是示例
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return new String[]{"示例数据块1", "示例数据块2"};
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}
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public static String generateComprehensiveReport() {
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String[] regions = {"文山州", "楚雄州"};
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String sql = "select table_name as TABLE_NAME from core_dataset_table where dataset_group_id in (select id from core_dataset_group where pid='1036317909951057920')";
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List<Record> tableList = Db.use(DataEaseModel.DB_NAME).find(sql);
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// 获取分块数据
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String[] dataChunks = getDataChunks(regions, tableList);
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List<String> chunkAnalyses = new ArrayList<>();
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System.out.println("开始分析 " + dataChunks.length + " 个数据块...");
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// 第一阶段：流式分析各个数据块
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for (int i = 0; i < dataChunks.length; i++) {
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final int chunkIndex = i;
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final StringBuilder chunkResult = new StringBuilder();
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final CountDownLatch latch = new CountDownLatch(1);
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String prompt = "请对以下教育数据进行简要分析，重点关注关键指标和趋势，控制在500字以内：\n" + dataChunks[i];
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System.out.println("\n=== 正在分析第 " + (i + 1) + " 个数据块 ===");
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CallDeepSeek.callDeepSeekStream(prompt, new CallDeepSeek.SSEListener() {
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@Override
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public void onData(String data) {
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System.out.print(data);
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chunkResult.append(data);
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}
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@Override
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public void onComplete(String fullResponse) {
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System.out.println("\n--- 第 " + (chunkIndex + 1) + " 个数据块分析完成 ---\n");
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chunkAnalyses.add(chunkResult.toString());
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latch.countDown();
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}
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@Override
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public void onError(String error) {
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System.err.println("分析第 " + (chunkIndex + 1) + " 个数据块时出错: " + error);
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chunkAnalyses.add("分析失败: " + error);
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latch.countDown();
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}
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});
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try {
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// 等待当前块分析完成
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latch.await();
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Thread.sleep(1000); // 稍微延迟，避免API调用过于频繁
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} catch (InterruptedException e) {
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System.err.println("等待分析结果时被中断: " + e.getMessage());
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}
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}
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// 第二阶段：流式生成综合报告
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System.out.println("\n=== 开始生成综合分析报告 ===");
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StringBuilder combinedAnalysis = new StringBuilder();
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combinedAnalysis.append("基于以下分块分析结果，请生成一份完整的教育数据综合分析报告（3000字以内）：\n\n");
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for (int i = 0; i < chunkAnalyses.size(); i++) {
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combinedAnalysis.append("数据块").append(i + 1).append("分析：\n");
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combinedAnalysis.append(chunkAnalyses.get(i)).append("\n\n");
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}
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final StringBuilder finalReport = new StringBuilder();
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final CountDownLatch finalLatch = new CountDownLatch(1);
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CallDeepSeek.callDeepSeekStream(combinedAnalysis.toString(), new CallDeepSeek.SSEListener() {
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@Override
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public void onData(String data) {
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System.out.print(data);
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finalReport.append(data);
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}
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@Override
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public void onComplete(String fullResponse) {
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System.out.println("\n\n=== 综合分析报告生成完成 ===");
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// 保存报告到文件
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try {
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String timestamp = new SimpleDateFormat("yyyyMMdd_HHmmss").format(new Date());
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String fileName = "教育数据综合分析报告_" + timestamp + ".txt";
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String filePath = "WebRoot/upload/" + fileName;
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FileUtil.writeString(finalReport.toString(), new File(filePath), "UTF-8");
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System.out.println("报告已保存到: " + filePath);
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} catch (Exception e) {
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System.err.println("保存报告时出错: " + e.getMessage());
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}
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finalLatch.countDown();
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}
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@Override
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public void onError(String error) {
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System.err.println("生成综合报告时出错: " + error);
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finalReport.append("生成失败: ").append(error);
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finalLatch.countDown();
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}
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});
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try {
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finalLatch.await();
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} catch (InterruptedException e) {
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System.err.println("等待最终报告时被中断: " + e.getMessage());
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}
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return finalReport.toString();
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}
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/**
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* 提取数据分块逻辑为独立方法
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*/
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private static String[] getDataChunks(String[] regions, List<Record> tableList) {
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List<String> dataChunks = new ArrayList<>();
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StringBuilder currentChunk = new StringBuilder();
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String header = "数据说明: 以下是云南省教育数据的压缩格式\n" +
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"格式: 表名 -> 字段列表 -> 数据行(数组格式)\n" +
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"地区范围: " + String.join(",", regions) + "\n\n";
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currentChunk.append(header);
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// 遍历所有相关数据表
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for (Record record : tableList) {
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String tableName = record.getStr("TABLE_NAME");
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// 为当前表收集所有数据
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List<Record> allTableData = new ArrayList<>();
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Set<String> fieldNames = new LinkedHashSet<>();
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// 为每个地区收集数据
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for (String region : regions) {
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String sql = "select * from `" + tableName + "` where `行政区划`=?";
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List<Record> listContent = Db.use(DataEaseModel.DB_NAME).find(sql, region);
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if (!listContent.isEmpty()) {
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allTableData.addAll(listContent);
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// 收集字段名（使用第一条记录的字段结构）
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if (fieldNames.isEmpty()) {
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fieldNames.addAll(listContent.get(0).getColumns().keySet());
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}
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}
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}
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if (!allTableData.isEmpty()) {
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// 构建当前表的完整数据块
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StringBuilder tableData = new StringBuilder();
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tableData.append("\n表: ").append(tableName).append("\n");
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tableData.append("字段: ").append(String.join(",", fieldNames)).append("\n");
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// 输出压缩格式的数据
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for (Record dataRecord : allTableData) {
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Map<String, Object> columns = dataRecord.getColumns();
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tableData.append("[");
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boolean first = true;
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for (String fieldName : fieldNames) {
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if (!first) tableData.append(",");
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Object value = columns.get(fieldName);
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if (value instanceof String) {
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tableData.append("\"").append(value).append("\"");
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} else {
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tableData.append(value);
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}
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first = false;
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}
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tableData.append("]\n");
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}
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// 检查是否需要分块
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String tableDataStr = tableData.toString();
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if (currentChunk.length() + tableDataStr.length() > MAX_CHUNK_SIZE) {
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// 当前块已满，保存并开始新块
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if (currentChunk.length() > header.length()) {
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dataChunks.add(currentChunk.toString());
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currentChunk = new StringBuilder();
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currentChunk.append(header);
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}
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// 如果单个表数据超过限制，需要进一步分割
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if (tableDataStr.length() > MAX_CHUNK_SIZE - header.length()) {
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List<String> tableChunks = splitLargeTable(tableName, fieldNames, allTableData, MAX_CHUNK_SIZE - header.length());
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for (int i = 0; i < tableChunks.size(); i++) {
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StringBuilder chunkBuilder = new StringBuilder();
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chunkBuilder.append(header);
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chunkBuilder.append("\n[续] 表: ").append(tableName).append(" (第").append(i + 1).append("部分)\n");
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chunkBuilder.append("字段: ").append(String.join(",", fieldNames)).append("\n");
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chunkBuilder.append(tableChunks.get(i));
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dataChunks.add(chunkBuilder.toString());
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}
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} else {
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currentChunk.append(tableDataStr);
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}
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} else {
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currentChunk.append(tableDataStr);
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}
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}
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}
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// 添加最后一个块
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if (currentChunk.length() > header.length()) {
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dataChunks.add(currentChunk.toString());
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}
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return dataChunks.toArray(new String[0]);
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}
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}
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