The performance optimization skills of the JSON conversion framework in the Java library
The performance optimization skills of the JSON conversion framework in the Java library
Abstract: With the popularity of the front and back -end separation architecture, JSON has become an important form of data exchange.In Java development, the JSON conversion framework is one of the essential tools.However, due to a large amount of data conversion operation, performance has always been the focus of developers.This article will introduce some techniques to optimize performance in the JSON conversion framework in the Java library, and provide the corresponding Java code example.
1. Choose the right JSON conversion framework
In Java development, the commonly used JSON conversion frameworks include Jackson, GSON, and Fastjson.Different frameworks may be different in performance, so it is important to choose the right framework.Under normal circumstances, Jackson has excellent performance in performance and has good compatibility.In the scenario with high performance requirements, it can be the first choice.
2. Use the object pool
When performing a large number of JSON conversion operations, frequent creation and destruction objects may lead to decline in performance.An effective optimization method is to use the object pool to reuse the object required during the conversion process.Through the object pool, the creation and destruction of the object can be reduced, thereby improving performance.
Below is an example code for creating an object pool using the Apache Commons Pool Library:
GenericObjectPool<JsonParser> objectPool = new GenericObjectPool<>(new JsonParserFactory());
JsonParser jsonParser = objectPool.borrowObject();
// Execute JSON conversion operation
// ...
// Return the object to the object pool
objectPool.returnObject(jsonParser);
3. Configure the JSON conversion framework
The JSON conversion framework usually provides some configuration options, which can be optimized according to demand.For example, in Jackson, some attributes that configure the `ObjectMapper` can improve performance.Here are some commonly used configuration options:
-The configuration field visibility: Set the visibility of the object field, which can avoid unnecessary object field scan.
-Basion Disable Testing: Disable Cycling Testing can reduce performance overhead.
-Dappearing date formatting: If you do not need to formatting the date, you can disable the dated formatting function.
The following is a sample code that uses Jackson for configuration:
ObjectMapper objectMapper = new ObjectMapper();
objectMapper.setVisibility(PropertyAccessor.FIELD, JsonAutoDetect.Visibility.ANY);
objectMapper.disable(DeserializationFeature.FAIL_ON_UNKNOWN_PROPERTIES);
objectMapper.disable(SerializationFeature.FAIL_ON_EMPTY_BEANS);
objectMapper.disable(SerializationFeature.WRITE_DATES_AS_TIMESTAMPS);
// Other configurations ...
4. Batch conversion and asynchronous treatment
When a large amount of JSON data needs to be processed, batch conversion or asynchronous processing can be considered to optimize performance.Batch conversion can reduce the number of conversion operations and improve efficiency.Asynchronous treatment can use multi -threaded or asynchronous programming framework for concurrent processing to reduce waiting time and improve performance.
The following is an example code that uses Jackson for batch conversion and asynchronous processing:
List<MyObject> objects = new ArrayList<>();
// Add multiple MyObject objects to the list
// ...
ArrayNode arrayNode = objectMapper.valueToTree(objects);
// Batch conversion
List<MyObject> convertedObjects = objectMapper.readValue(arrayNode.traverse(), new TypeReference<List<MyObject>>() {});
// asynchronous treatment
CompletableFuture<List<MyObject>> future = CompletableFuture.supplyAsync(() -> {
try {
return objectMapper.readValue(arrayNode.traverse(), new TypeReference<List<MyObject>>() {});
} catch (IOException e) {
// Abnormal treatment
}
return null;
});
in conclusion:
By selecting the appropriate JSON conversion framework, the use of the object pool, the attributes of the configuration conversion framework, and the batch conversion and asynchronous processing, it can effectively improve the performance of using the JSON conversion framework in the Java class library.Developers should be appropriately optimized according to actual needs and rationally assess the trade -off between performance and code complexity.During the development process, the performance testing tools can be combined with performance assessment to ensure that the system has good performance.
references:
- "Jackson -Jackson Tutorial", tutorialspoint, [online link] (https://www.tutorialspoint.com/jackson/))))))
- "gson -gson user guide", Google Gson, [online link] (https://github.com/google/gson)
- "Alibaba Fastjson", alibaba github, [online link] (https://github.com/alibaba/fastjson)
- "Apache Commons Pool", Apache Commons, [Online Link] (https://commons.apache.org/proper/commons-pool/))))
