流式

src/main/java/com/xujie/sys/common/utils/StreamCsvExportUtil.java

@@ -0,0 +1,495 @@
+package com.xujie.sys.common.utils;
+
+import lombok.extern.slf4j.Slf4j;
+
+import java.io.BufferedWriter;
+import java.io.IOException;
+import java.io.OutputStream;
+import java.io.OutputStreamWriter;
+import java.text.SimpleDateFormat;
+import java.util.Date;
+import java.util.function.Function;
+import java.util.zip.ZipEntry;
+import java.util.zip.ZipOutputStream;
+
+/**
+ * 流式CSV导出工具类（真正的流式导出，边查边写）- rqrq
+ *
+ * <p><b>功能特点：</b></p>
+ * <ul>
+ *   <li>支持单CSV和多CSV（ZIP压缩包）两种模式</li>
+ *   <li>使用GB18030编码，兼容Excel中文显示</li>
+ *   <li>自动处理CSV字段转义（逗号、引号、换行）</li>
+ *   <li>支持强制文本格式（保留前导零）</li>
+ *   <li>内置进度日志记录</li>
+ * </ul>
+ *
+ * <p><b>使用方式：</b></p>
+ * <pre>
+ * // 1. 创建Writer
+ * StreamCsvExportUtil.CsvStreamWriter writer = StreamCsvExportUtil.createSingleCsvWriter(response.getOutputStream(), "导出文件.csv");
+ * // 或创建ZIP Writer
+ * StreamCsvExportUtil.CsvStreamWriter writer = StreamCsvExportUtil.createZipCsvWriter(response.getOutputStream(), "导出文件.zip", "数据");
+ *
+ * // 2. 写入表头
+ * writer.writeHeader("列1", "列2", "列3");
+ *
+ * // 3. 在ResultHandler中逐行写入
+ * mapper.streamQuery(query, result -> {
+ *     writer.writeRow(
+ *         writer.asText(result.getField1()),  // 强制文本格式
+ *         writer.escape(result.getField2()),  // 普通转义
+ *         writer.formatDate(result.getDate()) // 日期格式化
+ *     );
+ * });
+ *
+ * // 4. 关闭Writer
+ * writer.close();
+ * </pre>
+ *
+ * @author rqrq
+ * @date 2025/02/04
+ */
+@Slf4j
+public class StreamCsvExportUtil {
+
+    /**
+     * 默认编码（GB18030兼容Excel中文）- rqrq
+     */
+    private static final String DEFAULT_CHARSET = "GB18030";
+
+    /**
+     * 默认缓冲区大小（128KB）- rqrq
+     */
+    private static final int DEFAULT_BUFFER_SIZE = 8192 * 16;
+
+    /**
+     * 每个CSV文件最大行数（默认100万）- rqrq
+     */
+    public static final int DEFAULT_MAX_ROWS_PER_CSV = 1000000;
+
+    /**
+     * @Description 创建单CSV文件写入器 - rqrq
+     * @param outputStream 输出流
+     * @param fileName 文件名（用于日志）
+     * @return CsvStreamWriter
+     * @author rqrq
+     */
+    public static CsvStreamWriter createSingleCsvWriter(OutputStream outputStream, String fileName) throws IOException {
+        return new SingleCsvWriter(outputStream, fileName);
+    }
+
+    /**
+     * @Description 创建ZIP压缩包写入器（多CSV文件）- rqrq
+     * @param outputStream 输出流
+     * @param zipFileName ZIP文件名（用于日志）
+     * @param csvFilePrefix CSV文件名前缀（如"数据"，则生成"数据_1.csv"、"数据_2.csv"）
+     * @return CsvStreamWriter
+     * @author rqrq
+     */
+    public static CsvStreamWriter createZipCsvWriter(OutputStream outputStream, String zipFileName, String csvFilePrefix) throws IOException {
+        return new ZipCsvWriter(outputStream, zipFileName, csvFilePrefix, DEFAULT_MAX_ROWS_PER_CSV);
+    }
+
+    /**
+     * @Description 创建ZIP压缩包写入器（自定义每个CSV最大行数）- rqrq
+     * @param outputStream 输出流
+     * @param zipFileName ZIP文件名
+     * @param csvFilePrefix CSV文件名前缀
+     * @param maxRowsPerCsv 每个CSV最大行数
+     * @return CsvStreamWriter
+     * @author rqrq
+     */
+    public static CsvStreamWriter createZipCsvWriter(OutputStream outputStream, String zipFileName, String csvFilePrefix, int maxRowsPerCsv) throws IOException {
+        return new ZipCsvWriter(outputStream, zipFileName, csvFilePrefix, maxRowsPerCsv);
+    }
+
+    /**
+     * CSV流式写入器接口 - rqrq
+     * 
+     * <p><b>异常处理机制：</b></p>
+     * <ul>
+     *   <li>写入失败时自动设置错误状态</li>
+     *   <li>后续 writeRow 调用会直接跳过（避免资源浪费）</li>
+     *   <li>调用方可通过 hasError() 检查是否发生错误</li>
+     *   <li>调用方可通过 getLastError() 获取错误详情</li>
+     * </ul>
+     */
+    public interface CsvStreamWriter extends AutoCloseable {
+
+        /**
+         * 写入表头行 - rqrq
+         */
+        void writeHeader(String... headers) throws IOException;
+
+        /**
+         * 写入数据行（如果已发生错误则跳过）- rqrq
+         */
+        void writeRow(String... values) throws IOException;
+
+        /**
+         * 写入数据行（安全版本，不抛异常，返回是否成功）- rqrq
+         * 用于 ResultHandler 中避免抛出 RuntimeException
+         */
+        boolean writeRowSafe(String... values);
+
+        /**
+         * 获取已写入行数 - rqrq
+         */
+        long getWrittenRows();
+
+        /**
+         * 刷新缓冲区 - rqrq
+         */
+        void flush() throws IOException;
+
+        /**
+         * 关闭写入器 - rqrq
+         */
+        @Override
+        void close() throws IOException;
+
+        /**
+         * 检查是否已发生错误 - rqrq
+         */
+        boolean hasError();
+
+        /**
+         * 获取最后一次错误 - rqrq
+         */
+        Throwable getLastError();
+
+        /**
+         * 手动设置错误状态（用于外部捕获到异常时）- rqrq
+         */
+        void setError(Throwable e);
+
+        /**
+         * CSV字段转义（处理逗号、引号、换行）- rqrq
+         */
+        default String escape(String value) {
+            if (value == null) {
+                return "";
+            }
+            if (value.contains(",") || value.contains("\"") || value.contains("\n") || value.contains("\r")) {
+                return "\"" + value.replace("\"", "\"\"") + "\"";
+            }
+            return value;
+        }
+
+        /**
+         * 强制文本格式（防止前导零丢失）- rqrq
+         * 使用 ="值" 格式，Excel会识别为文本
+         */
+        default String asText(String value) {
+            if (value == null || value.isEmpty()) {
+                return "";
+            }
+            return "=\"" + value.replace("\"", "\"\"") + "\"";
+        }
+
+        /**
+         * 格式化日期 - rqrq
+         */
+        default String formatDate(Date date) {
+            if (date == null) {
+                return "";
+            }
+            return new SimpleDateFormat("yyyy-MM-dd HH:mm:ss").format(date);
+        }
+
+        /**
+         * 格式化日期（自定义格式）- rqrq
+         */
+        default String formatDate(Date date, String pattern) {
+            if (date == null) {
+                return "";
+            }
+            return new SimpleDateFormat(pattern).format(date);
+        }
+    }
+
+    /**
+     * 单CSV文件写入器实现 - rqrq
+     */
+    private static class SingleCsvWriter implements CsvStreamWriter {
+        private final BufferedWriter writer;
+        private final String fileName;
+        private long writtenRows = 0;
+        
+        // 错误状态（volatile保证多线程可见性）- rqrq
+        private volatile boolean hasError = false;
+        private volatile Throwable lastError = null;
+
+        SingleCsvWriter(OutputStream outputStream, String fileName) throws IOException {
+            this.fileName = fileName;
+            this.writer = new BufferedWriter(new OutputStreamWriter(outputStream, DEFAULT_CHARSET), DEFAULT_BUFFER_SIZE);
+            log.info("创建单CSV写入器: {} - rqrq", fileName);
+        }
+
+        @Override
+        public void writeHeader(String... headers) throws IOException {
+            if (hasError) return;
+            try {
+                writer.write(String.join(",", headers));
+                writer.newLine();
+            } catch (IOException e) {
+                setError(e);
+                throw e;
+            }
+        }
+
+        @Override
+        public void writeRow(String... values) throws IOException {
+            // 如果已发生错误，直接跳过 - rqrq
+            if (hasError) {
+                return;
+            }
+            
+            try {
+                writer.write(String.join(",", values));
+                writer.newLine();
+                writtenRows++;
+
+                if (writtenRows % 100000 == 0) {
+                    log.info("CSV已写入 {} 行 - rqrq", writtenRows);
+                    flush();
+                }
+            } catch (IOException e) {
+                setError(e);
+                throw e;
+            }
+        }
+
+        @Override
+        public boolean writeRowSafe(String... values) {
+            if (hasError) {
+                return false;
+            }
+            try {
+                writeRow(values);
+                return true;
+            } catch (IOException e) {
+                // 已在writeRow中设置了错误状态
+                log.warn("写入行失败，后续行将跳过: {} - rqrq", e.getMessage());
+                return false;
+            }
+        }
+
+        @Override
+        public long getWrittenRows() {
+            return writtenRows;
+        }
+
+        @Override
+        public void flush() throws IOException {
+            if (!hasError) {
+                writer.flush();
+            }
+        }
+
+        @Override
+        public void close() throws IOException {
+            try {
+                if (!hasError) {
+                    flush();
+                }
+                writer.close();
+            } catch (IOException e) {
+                log.warn("关闭写入器时发生错误: {} - rqrq", e.getMessage());
+            }
+            log.info("单CSV写入完成: {}，共 {} 行，hasError: {} - rqrq", fileName, writtenRows, hasError);
+        }
+
+        @Override
+        public boolean hasError() {
+            return hasError;
+        }
+
+        @Override
+        public Throwable getLastError() {
+            return lastError;
+        }
+
+        @Override
+        public void setError(Throwable e) {
+            this.hasError = true;
+            this.lastError = e;
+            log.error("CSV写入器发生错误，后续写入将跳过: {} - rqrq", e.getMessage());
+        }
+    }
+
+    /**
+     * ZIP压缩包写入器实现（多CSV文件）- rqrq
+     */
+    private static class ZipCsvWriter implements CsvStreamWriter {
+        private final ZipOutputStream zipOut;
+        private final String zipFileName;
+        private final String csvFilePrefix;
+        private final int maxRowsPerCsv;
+
+        private BufferedWriter currentWriter;
+        private int currentCsvIndex = 0;
+        private long currentCsvRows = 0;
+        private long totalWrittenRows = 0;
+        private String[] headerRow;
+        
+        // 错误状态（volatile保证多线程可见性）- rqrq
+        private volatile boolean hasError = false;
+        private volatile Throwable lastError = null;
+
+        ZipCsvWriter(OutputStream outputStream, String zipFileName, String csvFilePrefix, int maxRowsPerCsv) throws IOException {
+            this.zipOut = new ZipOutputStream(outputStream);
+            this.zipFileName = zipFileName;
+            this.csvFilePrefix = csvFilePrefix;
+            this.maxRowsPerCsv = maxRowsPerCsv;
+            log.info("创建ZIP写入器: {}，每个CSV最多 {} 行 - rqrq", zipFileName, maxRowsPerCsv);
+        }
+
+        @Override
+        public void writeHeader(String... headers) throws IOException {
+            if (hasError) return;
+            this.headerRow = headers;
+            try {
+                // 创建第一个CSV文件并写入表头
+                createNewCsvFile();
+            } catch (IOException e) {
+                setError(e);
+                throw e;
+            }
+        }
+
+        @Override
+        public void writeRow(String... values) throws IOException {
+            // 如果已发生错误，直接跳过 - rqrq
+            if (hasError) {
+                return;
+            }
+            
+            try {
+                // 检查是否需要创建新CSV文件
+                if (currentCsvRows >= maxRowsPerCsv) {
+                    closeCurrentCsv();
+                    createNewCsvFile();
+                }
+
+                currentWriter.write(String.join(",", values));
+                currentWriter.newLine();
+                currentCsvRows++;
+                totalWrittenRows++;
+
+                if (totalWrittenRows % 100000 == 0) {
+                    log.info("ZIP总计已写入 {} 行，当前CSV {} 有 {} 行 - rqrq",
+                            totalWrittenRows, currentCsvIndex, currentCsvRows);
+                    flush();
+                }
+            } catch (IOException e) {
+                setError(e);
+                throw e;
+            }
+        }
+
+        @Override
+        public boolean writeRowSafe(String... values) {
+            if (hasError) {
+                return false;
+            }
+            try {
+                writeRow(values);
+                return true;
+            } catch (IOException e) {
+                // 已在writeRow中设置了错误状态
+                log.warn("写入行失败，后续行将跳过: {} - rqrq", e.getMessage());
+                return false;
+            }
+        }
+
+        @Override
+        public long getWrittenRows() {
+            return totalWrittenRows;
+        }
+
+        @Override
+        public void flush() throws IOException {
+            if (!hasError && currentWriter != null) {
+                currentWriter.flush();
+            }
+        }
+
+        @Override
+        public void close() throws IOException {
+            try {
+                if (!hasError) {
+                    closeCurrentCsv();
+                    zipOut.finish();
+                }
+                zipOut.close();
+            } catch (IOException e) {
+                log.warn("关闭ZIP写入器时发生错误: {} - rqrq", e.getMessage());
+            }
+            log.info("ZIP写入完成: {}，共 {} 个CSV文件，总计 {} 行，hasError: {} - rqrq",
+                    zipFileName, currentCsvIndex, totalWrittenRows, hasError);
+        }
+
+        @Override
+        public boolean hasError() {
+            return hasError;
+        }
+
+        @Override
+        public Throwable getLastError() {
+            return lastError;
+        }
+
+        @Override
+        public void setError(Throwable e) {
+            this.hasError = true;
+            this.lastError = e;
+            log.error("ZIP写入器发生错误，后续写入将跳过: {} - rqrq", e.getMessage());
+        }
+
+        private void createNewCsvFile() throws IOException {
+            currentCsvIndex++;
+            // 使用ASCII文件名避免Windows解压乱码 - rqrq
+            String csvFileName = "TID_EPC_Log_" + currentCsvIndex + ".csv";
+            ZipEntry entry = new ZipEntry(csvFileName);
+            zipOut.putNextEntry(entry);
+
+            // 注意：ZIP内的Writer不能关闭底层流
+            currentWriter = new BufferedWriter(new OutputStreamWriter(zipOut, DEFAULT_CHARSET), DEFAULT_BUFFER_SIZE);
+
+            // 写入表头
+            if (headerRow != null) {
+                currentWriter.write(String.join(",", headerRow));
+                currentWriter.newLine();
+            }
+
+            currentCsvRows = 0;
+            log.info("创建CSV文件: {} - rqrq", csvFileName);
+        }
+
+        private void closeCurrentCsv() throws IOException {
+            if (currentWriter != null) {
+                currentWriter.flush();
+                zipOut.closeEntry();
+                log.info("CSV文件 {} 写入完成，共 {} 行 - rqrq", currentCsvIndex, currentCsvRows);
+            }
+        }
+    }
+
+    /**
+     * @Description 构建CSV数据行（通用方法）- rqrq
+     * @param extractors 字段提取器数组
+     * @param data 数据对象
+     * @return String[] CSV行数据
+     * @author rqrq
+     */
+    @SafeVarargs
+    public static <T> String[] buildRow(T data, Function<T, String>... extractors) {
+        String[] row = new String[extractors.length];
+        for (int i = 0; i < extractors.length; i++) {
+            row[i] = extractors[i].apply(data);
+        }
+        return row;
+    }
+}

src/main/java/com/xujie/sys/modules/pms/mapper/MesTidEpcLogMapper.java

@@ -7,7 +7,11 @@ import com.xujie.sys.modules.pms.data.MesTidEpcLogData;
 import com.xujie.sys.modules.pms.data.MesTidEpcLogExportData;
 import com.xujie.sys.modules.pms.entity.MesTidEpcLogEntity;
 import org.apache.ibatis.annotations.Mapper;
+import org.apache.ibatis.annotations.Options;
 import org.apache.ibatis.annotations.Param;
+import org.apache.ibatis.annotations.ResultType;
+import org.apache.ibatis.mapping.ResultSetType;
+import org.apache.ibatis.session.ResultHandler;
 
 import java.util.List;
 
@@ -71,6 +75,26 @@ public interface MesTidEpcLogMapper extends BaseMapper<MesTidEpcLogEntity> {
                                                          @Param("offset") long offset, 
                                                          @Param("limit") int limit);
 
+    /**
+     * @Description 流式查询导出数据（真正的逐行读取，配合ResultHandler使用）- rqrq
+     * 
+     * <p><b>【流式查询原理】</b></p>
+     * <ul>
+     *   <li>使用 FORWARD_ONLY 游标，数据逐行从数据库读取</li>
+     *   <li>配合 responseBuffering=adaptive（在JDBC URL中配置）</li>
+     *   <li>fetchSize=1000 控制每次从数据库预取的行数</li>
+     *   <li>数据不会全部加载到内存，避免OOM</li>
+     * </ul>
+     * 
+     * @param query 查询条件
+     * @param handler 结果处理器，逐行处理数据
+     * @author rqrq
+     * @date 2025/02/04
+     */
+    @Options(resultSetType = ResultSetType.FORWARD_ONLY, fetchSize = 1000)
+    @ResultType(MesTidEpcLogExportData.class)
+    void streamExportList(@Param("query") MesTidEpcLogData query, ResultHandler<MesTidEpcLogExportData> handler);
+
     /**
      * @Description 批量插入日志数据 - rqrq
      * @param list 日志数据列表

src/main/java/com/xujie/sys/modules/pms/service/Impl/MesTidEpcLogServiceImpl.java

@@ -22,6 +22,8 @@ import org.springframework.transaction.annotation.Transactional;
 import org.springframework.util.StringUtils;
 import org.springframework.web.multipart.MultipartFile;
 
+import com.xujie.sys.common.utils.StreamCsvExportUtil;
+
 import java.io.BufferedWriter;
 import java.io.IOException;
 import java.io.OutputStream;
@@ -32,6 +34,7 @@ import java.text.SimpleDateFormat;
 import java.time.LocalDate;
 import java.time.format.DateTimeFormatter;
 import java.util.*;
+import java.util.concurrent.atomic.AtomicLong;
 import java.util.zip.ZipEntry;
 import java.util.zip.ZipOutputStream;
 
@@ -293,7 +296,15 @@ public class MesTidEpcLogServiceImpl extends ServiceImpl<MesTidEpcLogMapper, Mes
     private static final int MAX_ROWS_PER_CSV = 1000000;  // 100万条
 
     /**
-     * @Description 导出CSV文件（自动判断：≤100万返回单CSV，>100万返回ZIP包含多个CSV）- rqrq
+     * @Description 导出CSV文件（真正的流式导出：MyBatis ResultHandler + 逐行写入）- rqrq
+     * 
+     * <p><b>【V5版本：真正的流式导出】</b></p>
+     * <ul>
+     *   <li>使用 MyBatis ResultHandler 逐行从数据库读取</li>
+     *   <li>读一行写一行，内存中不存储任何数据批次</li>
+     *   <li>配合 JDBC responseBuffering=adaptive 和 FORWARD_ONLY 游标</li>
+     *   <li>真正的 O(1) 内存占用，可导出任意大小数据集</li>
+     * </ul>
      * 
      * <p><b>【导出策略】</b></p>
      * <ul>
@@ -305,15 +316,16 @@ public class MesTidEpcLogServiceImpl extends ServiceImpl<MesTidEpcLogMapper, Mes
      * @param data 查询条件
      * @param response HttpServletResponse
      * @author rqrq
+     * @date 2025/02/04
      */
     @Override
     public void exportCsv(MesTidEpcLogData data, HttpServletResponse response) {
-        log.info("开始导出MES TID EPC日志文件 - rqrq");
+        log.info("开始导出MES TID EPC日志文件（V5：真正流式导出）- rqrq");
 
         long startTime = System.currentTimeMillis();
 
         try {
-            // ============ 查询总数，检查数据量 ============ - rqrq
+            // ============ 步骤1：查询总数，检查数据量 ============ - rqrq
             long countStartTime = System.currentTimeMillis();
             long dataTotal = mesTidEpcLogMapper.getExportCount(data);
             long countEndTime = System.currentTimeMillis();
@@ -329,20 +341,20 @@ public class MesTidEpcLogServiceImpl extends ServiceImpl<MesTidEpcLogMapper, Mes
                 throw new RuntimeException("该条件数据数量超过五百万（当前" + dataTotal + "条），请缩小扫描时间范围手动分批导出");
             }
 
-            // ============ 根据数据量选择导出方式 ============ - rqrq
+            // ============ 步骤2：根据数据量选择导出方式 ============ - rqrq
             if (dataTotal <= MAX_ROWS_PER_CSV) {
-                // ≤100万：直接输出单个CSV - rqrq
-                log.info("数据量 {} 条 ≤ 100万，输出单个CSV文件 - rqrq", dataTotal);
-                writeToCsvStreaming(data, dataTotal, response);
+                // ≤100万：直接输出单个CSV（真正流式）- rqrq
+                log.info("数据量 {} 条 ≤ 100万，输出单个CSV文件（真正流式）- rqrq", dataTotal);
+                exportToCsvRealStreaming(data, dataTotal, response);
             } else {
-                // >100万：输出ZIP压缩包，包含多个CSV - rqrq
+                // >100万：输出ZIP压缩包，包含多个CSV（真正流式）- rqrq
                 int csvFileCount = (int) Math.ceil((double) dataTotal / MAX_ROWS_PER_CSV);
-                log.info("数据量 {} 条 > 100万，输出ZIP压缩包，包含 {} 个CSV文件 - rqrq", dataTotal, csvFileCount);
-                writeToZipWithMultipleCsv(data, dataTotal, response);
+                log.info("数据量 {} 条 > 100万，输出ZIP压缩包，包含 {} 个CSV文件（真正流式）- rqrq", dataTotal, csvFileCount);
+                exportToZipRealStreaming(data, dataTotal, response);
             }
 
             long endTime = System.currentTimeMillis();
-            log.info("导出完成，总耗时: {} 秒 - rqrq", (endTime - startTime) / 1000.0);
+            log.info("导出完成（V5），总耗时: {} 秒 - rqrq", (endTime - startTime) / 1000.0);
 
         } catch (Exception e) {
             log.error("导出文件失败 - rqrq: {}", e.getMessage(), e);
@@ -351,9 +363,182 @@ public class MesTidEpcLogServiceImpl extends ServiceImpl<MesTidEpcLogMapper, Mes
     }
 
     /**
-     * @Description 写入ZIP压缩包，包含多个CSV文件（每个最多100万条）- rqrq
+     * @Description 真正的流式CSV导出（单文件）- rqrq
+     * 
+     * <p><b>【核心原理】</b></p>
+     * <ul>
+     *   <li>MyBatis ResultHandler 逐行回调</li>
+     *   <li>每收到一行数据立即写入CSV</li>
+     *   <li>内存中始终只有1行数据</li>
+     * </ul>
+     * 
+     * @param data 查询条件
+     * @param dataTotal 数据总数
+     * @param response HttpServletResponse
+     * @author rqrq
+     * @date 2025/02/04
+     */
+    private void exportToCsvRealStreaming(MesTidEpcLogData data, long dataTotal, HttpServletResponse response) throws IOException {
+        log.info("【真正流式导出】单CSV，预计 {} 条 - rqrq", dataTotal);
+
+        // 设置响应头 - rqrq
+        response.setContentType("text/csv;charset=GB18030");
+        response.setCharacterEncoding("GB18030");
+        String fileName = URLEncoder.encode("TID_EPC日志导出.csv", "UTF-8");
+        response.setHeader("Content-Disposition", "attachment;filename=" + fileName);
+
+        // 创建流式CSV写入器 - rqrq
+        StreamCsvExportUtil.CsvStreamWriter writer = StreamCsvExportUtil.createSingleCsvWriter(
+                response.getOutputStream(), "TID_EPC日志导出.csv");
+
+        try {
+            // 写入表头 - rqrq
+            writer.writeHeader("序号", "EPC", "TID", "用户区", "LockiBtis", "密匙",
+                    "写码成功", "读码成功", "EPC锁定", "强度/读距", "扫描时间", "计数");
+
+            // 使用AtomicLong记录进度（lambda中需要final或effectively final）- rqrq
+            AtomicLong processedCount = new AtomicLong(0);
+
+            // 真正的流式查询：ResultHandler逐行回调 - rqrq
+            // 使用writeRowSafe避免抛出RuntimeException导致MyBatis继续处理后续行 - rqrq
+            mesTidEpcLogMapper.streamExportList(data, resultContext -> {
+                // 如果已发生错误，直接跳过后续行（避免资源浪费）- rqrq
+                if (writer.hasError()) {
+                    return;
+                }
+
+                MesTidEpcLogExportData row = resultContext.getResultObject();
+
+                // 使用安全写入方法，失败时自动设置错误状态 - rqrq
+                boolean success = writer.writeRowSafe(
+                        writer.asText(row.getSeqNo()),        // 序号可能以0开头
+                        writer.asText(row.getEpc()),          // EPC编码
+                        writer.asText(row.getTid()),          // TID编码
+                        writer.asText(row.getUserArea()),     // 用户区
+                        writer.asText(row.getLockBits()),     // LockBits
+                        writer.asText(row.getSecretKey()),    // 密匙（重要！防止丢失前导0）
+                        writer.escape(row.getWriteSuccess()),
+                        writer.escape(row.getReadSuccess()),
+                        writer.escape(row.getEpcLocked()),
+                        writer.escape(row.getSignalStrength()),
+                        writer.formatDate(row.getScanTime()),
+                        writer.asText(row.getCountInfo())     // 计数信息
+                );
+
+                if (success) {
+                    long count = processedCount.incrementAndGet();
+                    if (count % 100000 == 0) {
+                        log.info("流式导出进度: {}/{} 条 - rqrq", count, dataTotal);
+                    }
+                }
+            });
+
+            // 查询结束后检查是否发生错误 - rqrq
+            if (writer.hasError()) {
+                log.error("流式导出过程中发生错误: {} - rqrq", writer.getLastError().getMessage());
+                // 不抛异常，因为部分数据可能已发送给客户端
+            }
+
+            log.info("流式导出完成，共 {} 条 - rqrq", writer.getWrittenRows());
+
+        } finally {
+            writer.close();
+        }
+    }
+
+    /**
+     * @Description 真正的流式ZIP导出（多CSV文件）- rqrq
+     * 
+     * <p><b>【核心原理】</b></p>
+     * <ul>
+     *   <li>MyBatis ResultHandler 逐行回调</li>
+     *   <li>每收到一行数据立即写入当前CSV</li>
+     *   <li>当前CSV达到100万行自动切换到新CSV</li>
+     *   <li>内存中始终只有1行数据</li>
+     * </ul>
+     * 
+     * @param data 查询条件
+     * @param dataTotal 数据总数
+     * @param response HttpServletResponse
+     * @author rqrq
+     * @date 2025/02/04
+     */
+    private void exportToZipRealStreaming(MesTidEpcLogData data, long dataTotal, HttpServletResponse response) throws IOException {
+        log.info("【真正流式导出】ZIP多CSV，预计 {} 条 - rqrq", dataTotal);
+
+        // 设置响应头 - rqrq
+        response.setContentType("application/zip");
+        response.setCharacterEncoding("UTF-8");
+        String fileName = URLEncoder.encode("TID_EPC日志导出.zip", "UTF-8");
+        response.setHeader("Content-Disposition", "attachment;filename=" + fileName);
+
+        // 创建流式ZIP写入器（每个CSV最多100万行）- rqrq
+        StreamCsvExportUtil.CsvStreamWriter writer = StreamCsvExportUtil.createZipCsvWriter(
+                response.getOutputStream(), "TID_EPC日志导出.zip", "TID_EPC日志", MAX_ROWS_PER_CSV);
+
+        try {
+            // 写入表头（自动应用到每个新建的CSV文件）- rqrq
+            writer.writeHeader("序号", "EPC", "TID", "用户区", "LockiBtis", "密匙",
+                    "写码成功", "读码成功", "EPC锁定", "强度/读距", "扫描时间", "计数");
+
+            // 使用AtomicLong记录进度 - rqrq
+            AtomicLong processedCount = new AtomicLong(0);
+
+            // 真正的流式查询：ResultHandler逐行回调 - rqrq
+            // 使用writeRowSafe避免抛出RuntimeException导致MyBatis继续处理后续行 - rqrq
+            mesTidEpcLogMapper.streamExportList(data, resultContext -> {
+                // 如果已发生错误，直接跳过后续行（避免资源浪费）- rqrq
+                if (writer.hasError()) {
+                    return;
+                }
+
+                MesTidEpcLogExportData row = resultContext.getResultObject();
+
+                // 使用安全写入方法，失败时自动设置错误状态 - rqrq
+                boolean success = writer.writeRowSafe(
+                        writer.asText(row.getSeqNo()),
+                        writer.asText(row.getEpc()),
+                        writer.asText(row.getTid()),
+                        writer.asText(row.getUserArea()),
+                        writer.asText(row.getLockBits()),
+                        writer.asText(row.getSecretKey()),
+                        writer.escape(row.getWriteSuccess()),
+                        writer.escape(row.getReadSuccess()),
+                        writer.escape(row.getEpcLocked()),
+                        writer.escape(row.getSignalStrength()),
+                        writer.formatDate(row.getScanTime()),
+                        writer.asText(row.getCountInfo())
+                );
+
+                if (success) {
+                    long count = processedCount.incrementAndGet();
+                    if (count % 100000 == 0) {
+                        log.info("流式导出进度: {}/{} 条 - rqrq", count, dataTotal);
+                    }
+                }
+            });
+
+            // 查询结束后检查是否发生错误 - rqrq
+            if (writer.hasError()) {
+                log.error("流式导出过程中发生错误: {} - rqrq", writer.getLastError().getMessage());
+            }
+
+            log.info("流式导出完成，共 {} 条 - rqrq", writer.getWrittenRows());
+
+        } finally {
+            writer.close();
+        }
+    }
+
+    // ==================================================================================
+    // ========================= V4版本（伪流式：分批查询分批写入，已被V5取代）=============
+    // ==================================================================================
+
+    /**
+     * @Description 【V4备份】写入ZIP压缩包（伪流式：分批查询分批写入）- rqrq
      * 
-     * <p><b>【流式写入】</b>边查边写，内存占用低</p>
+     * <p><b>【已被V5取代】</b>保留此方法用于对比或回退</p>
+     * <p><b>【调用方式】</b>如需使用，在exportCsv方法中替换exportToZipRealStreaming为此方法</p>
      * 
      * @param data 查询条件
      * @param dataTotal 数据总数
@@ -361,6 +546,7 @@ public class MesTidEpcLogServiceImpl extends ServiceImpl<MesTidEpcLogMapper, Mes
      * @author rqrq
      * @date 2025/02/03
      */
+    @SuppressWarnings("unused")
     private void writeToZipWithMultipleCsv(MesTidEpcLogData data, long dataTotal, HttpServletResponse response) throws IOException {
         log.info("开始生成ZIP压缩包（多CSV），数据总数: {} 条 - rqrq", dataTotal);
         

src/main/resources/mapper/pms/MesTidEpcLogMapper.xml

@@ -241,6 +241,60 @@
         ORDER BY upload_time DESC, id DESC
     </select>
 
+    <!-- rqrq - 流式查询导出数据（真正的逐行读取，配合ResultHandler使用）-->
+    <!-- 
+        【流式查询说明】
+        1. 使用 resultSetType="FORWARD_ONLY" 和 fetchSize="1000" 
+        2. 配合JDBC URL中的 responseBuffering=adaptive
+        3. 数据从数据库逐行读取，不会全部加载到内存
+        4. ORDER BY id 保证数据顺序稳定
+    -->
+    <select id="streamExportList" resultType="MesTidEpcLogExportData" resultSetType="FORWARD_ONLY" fetchSize="1000">
+        SELECT
+            seq_no AS seqNo,
+            epc,
+            tid,
+            user_area AS userArea,
+            lock_bits AS lockBits,
+            secret_key AS secretKey,
+            write_success AS writeSuccess,
+            read_success AS readSuccess,
+            epc_locked AS epcLocked,
+            signal_strength AS signalStrength,
+            scan_time AS scanTime,
+            count_info AS countInfo
+        FROM mes_tid_epc_log
+        WHERE 1 = 1
+        <if test="query.site != null and query.site != ''">
+            AND site = #{query.site}
+        </if>
+        <if test="query.buNo != null and query.buNo != ''">
+            AND bu_no = #{query.buNo}
+        </if>
+        <if test="query.searchSeqNo != null and query.searchSeqNo != ''">
+            AND seq_no LIKE '%' + #{query.searchSeqNo} + '%'
+        </if>
+        <if test="query.searchEpc != null and query.searchEpc != ''">
+            AND epc LIKE '%' + #{query.searchEpc} + '%'
+        </if>
+        <if test="query.searchTid != null and query.searchTid != ''">
+            AND tid LIKE '%' + #{query.searchTid} + '%'
+        </if>
+        <if test="query.searchUserArea != null and query.searchUserArea != ''">
+            AND user_area LIKE '%' + #{query.searchUserArea} + '%'
+        </if>
+        <if test="query.scanTimeStart != null">
+            AND scan_time &gt;= #{query.scanTimeStart}
+        </if>
+        <if test="query.scanTimeEnd != null">
+            AND scan_time &lt;= #{query.scanTimeEnd}
+        </if>
+        <if test="query.searchBatchNo != null and query.searchBatchNo != ''">
+            AND batch_no LIKE '%' + #{query.searchBatchNo} + '%'
+        </if>
+        ORDER BY id ASC
+    </select>
+
     <!-- rqrq - 批量插入日志数据 -->
     <insert id="batchInsert" parameterType="java.util.List">
         INSERT INTO mes_tid_epc_log (