Table of Contents
Detailed explanation and solution for the problem of returning empty values ​​in batch query of RedisTemplate
Problem description
Analysis of the cause of the problem
The correct solution
Home Java javaTutorial Why is the return value empty when using RedisTemplate for batch query?

Why is the return value empty when using RedisTemplate for batch query?

Apr 19, 2025 pm 10:15 PM
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Why is the return value empty when using RedisTemplate for batch query?

Detailed explanation and solution for the problem of returning empty values ​​in batch query of RedisTemplate

When using RedisTemplate for batch queries, you often encounter the return result that is empty, even if the corresponding data exists in Redis. This is usually caused by the failure to properly handle the pipe operation. This article will explore this issue in depth and provide effective solutions.

Problem description

Suppose we have a method batchGetList , using RedisTemplate.executePipelined to batch get Redis data:

Question code example (code with problem):

 public<t> List<t> batchGetList(Collection<string> keys) {
    List<t> list = new ArrayList();
    if (CollectionUtil.isEmpty(keys)) {
        return list;
    }
    // ... (Incorrect pipeline operation code is omitted here) ...
    return list;
}</t></string></t></t>
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After executing the above code, the return result is empty. Even if the keys collection contains valid keys, corresponding data exists in Redis.

Analysis of the cause of the problem

The RedisTemplate.executePipelined method performs pipeline operations. The execution result of the Redis command will not be returned immediately, but will be returned together after batch execution. In the question code, trying to process the result of each command inside executePipelined , which is invalid because the result has not been returned at this time.

The correct solution

The correct way to do this is to process the returned result list after executePipelined . The following code shows the correct implementation:

 public<t> List<t> batchGetList(Collection<string> keys) {
    if (CollectionUtil.isEmpty(keys)) {
        return new ArrayList();
    }

    RedisSerializer<string> keySerializer = redisTemplate.getKeySerializer();
    List<object> results = redisTemplate.executePipelined((RedisConnection connection) -> {
        for (String key : keys) {
            connection.get(keySerializer.serialize(key));
        }
        return null; // executePipelined needs to return null
    });

    // Execute external processing results in the pipeline return results.stream()
                  .map(result -> (T) redisTemplate.getValueSerializer().deserialize((byte[]) result))
                  .filter(Objects::nonNull) //Filter out null value.collect(Collectors.toList());
}</object></string></string></t></t>
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Code description:

  1. RedisSerializer<string> keySerializer = redisTemplate.getKeySerializer();</string> : Get the key serializer of RedisTemplate to ensure the correct serialization of the key.

  2. redisTemplate.executePipelined((RedisConnection connection) -> { ... }); : Put all get commands into the pipeline to execute in batches. return null; is a requirement of the executePipelined method.

  3. results.stream().map(...)...collect(Collectors.toList()); : After the pipeline execution is completed, use the Java Stream API to process the result list. map operation deserializes the result of type byte[] to the target type T filter(Objects::nonNull) is used to filter out possible null values.

This method ensures that all get commands are sent as a batch operation and all results are processed at once after the operation is completed, avoiding the problem of empty return value. Note that this code assumes that the values ​​corresponding to all keys can be deserialized using the same deserializer. If different types of values ​​exist in your application scenario, more complex processing logic may be required to correctly deserialize them.

Through this improved code, the problem of RedisTemplate batch query returning empty values ​​can be effectively solved, and the code efficiency and reliability can be improved.

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