diff --git a/hutool-core/src/main/java/cn/hutool/core/thread/RecyclableBatchThreadPoolExecutor.java b/hutool-core/src/main/java/cn/hutool/core/thread/RecyclableBatchThreadPoolExecutor.java
index a2aba2eb8..df16985c2 100644
--- a/hutool-core/src/main/java/cn/hutool/core/thread/RecyclableBatchThreadPoolExecutor.java
+++ b/hutool-core/src/main/java/cn/hutool/core/thread/RecyclableBatchThreadPoolExecutor.java
@@ -5,6 +5,7 @@ import java.util.concurrent.*;
 import java.util.concurrent.atomic.AtomicBoolean;
 import java.util.concurrent.atomic.AtomicInteger;
 import java.util.function.Function;
+import java.util.function.Supplier;
 import java.util.stream.Collectors;
 import java.util.stream.Stream;
 
@@ -14,12 +15,18 @@ import java.util.stream.Stream;
  * 1.数据分批并行处理
  * 2.主线程、线程池混合执行批处理任务，主线程空闲时会尝试召回线程池队列中的任务执行
  * 3.线程安全，可用同时执行多个任务，线程池满载时，效率与单线程模式相当，无阻塞风险，无脑提交任务即可
- * 4.适合批量处理数据且需要同步结束的场景，能一定程度上提高吞吐量、防止任务堆积
+ * </pre>
+ *
+ * 适用场景：
+ * <pre>
+ * 1.批量处理数据且需要同步结束的场景，能一定程度上提高吞吐量、防止任务堆积 {@link #process(List, int, Function)}
+ * 2.普通查询接口加速 {@link #processByWarp(Warp[])}
  * </pre>
  *
  * @author likuan
  */
 public class RecyclableBatchThreadPoolExecutor {
+
 	private final ExecutorService executor;
 
 	public RecyclableBatchThreadPoolExecutor(int poolSize){
@@ -90,7 +97,6 @@ public class RecyclableBatchThreadPoolExecutor {
 	 * @param processor 单条数据处理函数
 	 * @return 处理结果集合
 	 */
-	@SuppressWarnings("unchecked")
 	public <T,R> List<R> process(List<T> data, int batchSize, Function<T,R> processor) {
 		if (batchSize < 1) {
 			throw new IllegalArgumentException("batchSize >= 1");
@@ -99,7 +105,7 @@ public class RecyclableBatchThreadPoolExecutor {
 		int batchCount = batches.size();
 		int minusOne = batchCount - 1;
 		ArrayDeque<IdempotentTask<R>> taskQueue = new ArrayDeque<>(minusOne);
-		Map<Integer,Future<ResultWarp<R>>> futuresMap = new HashMap<>();
+		Map<Integer,Future<TaskResult<R>>> futuresMap = new HashMap<>();
 		// 提交前 batchCount-1 批任务
 		for (int i = 0 ; i < minusOne ; i++) {
 			final int index = i;
@@ -107,15 +113,15 @@ public class RecyclableBatchThreadPoolExecutor {
 			taskQueue.add(task);
 			futuresMap.put(i,executor.submit(task));
 		}
-		Object[] arr = new Object[batchCount];
+		@SuppressWarnings("unchecked")
+		List<R>[] resultArr = new ArrayList[batchCount];
 		// 处理最后一批
-		arr[minusOne] = processBatch(batches.get(minusOne), processor);
+		resultArr[minusOne] = processBatch(batches.get(minusOne), processor);
 		// 处理剩余任务
-		processRemainingTasks(taskQueue, futuresMap,arr);
+		processRemainingTasks(taskQueue, futuresMap,resultArr);
 		//排序、过滤null
-		return Stream.of(arr)
+		return Stream.of(resultArr)
 				.filter(Objects::nonNull)
-				.map(p -> (List<R>) p)
 				.flatMap(List::stream)
 				.collect(Collectors.toList());
 	}
@@ -124,20 +130,20 @@ public class RecyclableBatchThreadPoolExecutor {
 	 * 处理剩余任务并收集结果
 	 * @param taskQueue 任务队列
 	 * @param futuresMap 异步任务映射
-	 * @param arr 结果存储数组
+	 * @param resultArr 结果存储数组
 	 */
-	private <R> void processRemainingTasks(Queue<IdempotentTask<R>> taskQueue, Map<Integer,Future<ResultWarp<R>>> futuresMap,Object[] arr) {
+	private <R> void processRemainingTasks(Queue<IdempotentTask<R>> taskQueue, Map<Integer,Future<TaskResult<R>>> futuresMap, List<R>[] resultArr) {
 		// 主消费未执行任务
 		IdempotentTask<R> task;
 		while ((task = taskQueue.poll()) != null) {
 			try {
-				ResultWarp<R> call = task.call();
+				TaskResult<R> call = task.call();
 				if (call.effective) {
 					// 取消被主线程执行任务
-					Future<ResultWarp<R>> future = futuresMap.remove(task.index);
+					Future<TaskResult<R>> future = futuresMap.remove(task.index);
 					future.cancel(false);
 					//加入结果集
-					arr[task.index] = call.result;
+					resultArr[task.index] = call.result;
 				}
 			} catch (Exception e) {
 				// 不处理异常
@@ -146,9 +152,9 @@ public class RecyclableBatchThreadPoolExecutor {
 		}
 		futuresMap.forEach((index,future)->{
 			try {
-				ResultWarp<R> resultWarp = future.get();
-				if(resultWarp.effective){
-					arr[index] = resultWarp.result;
+				TaskResult<R> taskResult = future.get();
+				if(taskResult.effective){
+					resultArr[index] = taskResult.result;
 				}
 			} catch (InterruptedException | ExecutionException e) {
 				throw new RuntimeException(e);
@@ -159,7 +165,7 @@ public class RecyclableBatchThreadPoolExecutor {
 	/**
 	 * 幂等任务包装类，确保任务只执行一次
 	 */
-	private static class IdempotentTask<R> implements Callable<ResultWarp<R>> {
+	private static class IdempotentTask<R> implements Callable<TaskResult<R>> {
 
 		private final int index;
 		private final Callable<List<R>> delegate;
@@ -171,21 +177,21 @@ public class RecyclableBatchThreadPoolExecutor {
 		}
 
 		@Override
-		public ResultWarp<R> call() throws Exception {
+		public TaskResult<R> call() throws Exception {
 			if (executed.compareAndSet(false, true)) {
-				return new ResultWarp<>(delegate.call(), true);
+				return new TaskResult<>(delegate.call(), true);
 			}
-			return new ResultWarp<>(null, false);
+			return new TaskResult<>(null, false);
 		}
 	}
 
 	/**
 	 * 结果包装类，标记结果有效性
 	 */
-	private static class ResultWarp<R>{
+	private static class TaskResult<R>{
 		private final List<R> result;
 		private final boolean effective;
-		ResultWarp(List<R> result, boolean effective){
+		TaskResult(List<R> result, boolean effective){
 			this.result = result;
 			this.effective = effective;
 		}
@@ -197,7 +203,7 @@ public class RecyclableBatchThreadPoolExecutor {
 	 * @param batchSize 每批次数据量
 	 * @return 分片后的二维集合
 	 */
-	public static <T> List<List<T>> splitData(List<T> data, int batchSize) {
+	private static <T> List<List<T>> splitData(List<T> data, int batchSize) {
 		int batchCount = (data.size() + batchSize - 1) / batchSize;
 		return new AbstractList<List<T>>() {
 			@Override
@@ -220,8 +226,69 @@ public class RecyclableBatchThreadPoolExecutor {
 	 * @param processor 处理函数
 	 * @return 处理结果
 	 */
-	public static <T,R> List<R> processBatch(List<T> batch, Function<T,R> processor) {
+	private static <T,R> List<R> processBatch(List<T> batch, Function<T,R> processor) {
 		return batch.stream().map(processor).filter(Objects::nonNull).collect(Collectors.toList());
 	}
 
+	/**
+	 * 处理Warp集合
+	 *
+	 * <pre>{@code
+	 * Warp<String> warp1 = Warp.of(this::select1);
+	 * Warp<List<String>> warp2 = Warp.of(this::select2);
+	 * executor.processByWarp(warp1, warp2);
+	 * String r1 = warp1.get();
+	 * List<String> r2 = warp2.get();
+	 * }</pre>
+	 *
+	 * @param warps Warp集合
+	 * @return Warp集合,此方法返回结果为空的不会被过滤
+	 */
+	public List<Warp<?>> processByWarp(Warp<?>... warps) {
+		return process(Arrays.asList(warps), 1, Warp::execute);
+	}
+
+	/**
+	 * 处理逻辑包装类
+	 * @param <R> 结果类型
+	 */
+	public static class Warp<R>{
+
+		private Warp(Supplier<R> supplier){
+			Objects.requireNonNull(supplier);
+			this.supplier = supplier;
+		}
+
+		/**
+		 * 创建Warp
+		 * @param supplier 执行逻辑
+		 * @return Warp
+		 * @param <R> 结果类型
+		 */
+		public static <R> Warp<R> of(Supplier<R> supplier){
+			return new Warp<>(supplier);
+		}
+
+		private final Supplier<R> supplier;
+		private R result;
+
+		/**
+		 * 获取结果
+		 * @return 结果
+		 */
+		public R get() {
+			return result;
+		}
+
+		/**
+		 * 执行
+		 * @return this
+		 */
+		public Warp<R> execute() {
+			result = supplier.get();
+			return this;
+		}
+
+	}
+
 }
diff --git a/hutool-core/src/test/java/cn/hutool/core/thread/RecyclableBatchThreadPoolExecutorTest.java b/hutool-core/src/test/java/cn/hutool/core/thread/RecyclableBatchThreadPoolExecutorTest.java
index 3fde81eac..d8dc2f182 100644
--- a/hutool-core/src/test/java/cn/hutool/core/thread/RecyclableBatchThreadPoolExecutorTest.java
+++ b/hutool-core/src/test/java/cn/hutool/core/thread/RecyclableBatchThreadPoolExecutorTest.java
@@ -1,11 +1,9 @@
 package cn.hutool.core.thread;
 
+import cn.hutool.core.thread.RecyclableBatchThreadPoolExecutor.Warp;
 import org.junit.jupiter.api.Test;
 
-import java.util.ArrayList;
-import java.util.HashMap;
-import java.util.List;
-import java.util.Map;
+import java.util.*;
 import java.util.concurrent.ExecutionException;
 import java.util.concurrent.ExecutorService;
 import java.util.concurrent.Executors;
@@ -17,6 +15,11 @@ import java.util.function.Function;
  */
 public class RecyclableBatchThreadPoolExecutorTest {
 
+
+	/**
+	 * 批量处理数据
+	 * @throws InterruptedException
+	 */
 	@Test
 	public void test() throws InterruptedException {
 		int corePoolSize = 10;// 线程池大小
@@ -25,6 +28,24 @@ public class RecyclableBatchThreadPoolExecutorTest {
 		test(corePoolSize,batchSize,clientCount);
 	}
 
+	/**
+	 * 普通查询接口加速
+	 */
+	@Test
+	public void test2() {
+		RecyclableBatchThreadPoolExecutor executor = new RecyclableBatchThreadPoolExecutor(10);
+		long s = System.nanoTime();
+		Warp<String> warp1 = Warp.of(this::select1);
+		Warp<List<String>> warp2 = Warp.of(this::select2);
+		executor.processByWarp(warp1, warp2);
+		Map<String, Object> map = new HashMap<>();
+		map.put("key1",warp1.get());
+		map.put("key2",warp2.get());
+		long d = System.nanoTime() - s;
+		System.out.printf("总耗时：%.2f秒%n",d/1e9);
+		System.out.println(map);
+	}
+
 	public void test(int corePoolSize,int batchSize,int clientCount ) throws InterruptedException{
 		RecyclableBatchThreadPoolExecutor processor = new RecyclableBatchThreadPoolExecutor(corePoolSize);
 		// 模拟多个调用者线程提交任务
@@ -73,4 +94,22 @@ public class RecyclableBatchThreadPoolExecutorTest {
 		return list;
 	}
 
+	private String select1()  {
+		try {
+			Thread.sleep(3000);
+		} catch (InterruptedException e) {
+			throw new RuntimeException(e);
+		}
+		return "1";
+	}
+
+	private List<String> select2() {
+		try {
+			Thread.sleep(5000);
+		} catch (InterruptedException e) {
+			throw new RuntimeException(e);
+		}
+		return Arrays.asList("1","2","3");
+	}
+
 }