Implementing a cache with distributed compression using Apache Commons Compress and HashMap in Java

23 Oct 2023

In this blog post, we will explore how to implement a cache with distributed compression using Apache Commons Compress and HashMap in Java. Caching is an essential technique in software development that enables the storage of frequently accessed data in a fast and easily accessible manner. By compressing the cached data, we can optimize memory usage and reduce disk space requirements.

Introduction
Prerequisites
Implementing the Cache
Compressing the Cached Data
Retrieving and Decompressing the Cached Data
Conclusion
References

Introduction

Caching data helps improve the performance of applications by reducing the time needed to retrieve frequently accessed information from external sources such as databases or APIs. In this blog post, we will use Apache Commons Compress, a widely used compression library in Java, to implement a cache that not only stores data but also compresses it for efficient memory usage.

Prerequisites

Before proceeding, make sure you have the following prerequisites installed on your system:

Java Development Kit (JDK)
Apache Commons Compress library

Implementing the Cache

We will start by creating a cache using the HashMap data structure in Java. The HashMap will allow us to store key-value pairs, where the key represents the unique identifier of the cached data, and the value represents the compressed data.

import org.apache.commons.compress.compressors.CompressorStreamFactory;

import java.io.ByteArrayInputStream;
import java.io.ByteArrayOutputStream;
import java.io.IOException;
import java.util.HashMap;
import java.util.Map;

public class CompressedCache {
    private final Map<String, byte[]> cache;

    public CompressedCache() {
        cache = new HashMap<>();
    }

    public void put(String key, byte[] data) {
        try (ByteArrayOutputStream outputStream = new ByteArrayOutputStream()) {
            CompressorStreamFactory compressorFactory = new CompressorStreamFactory();
            compressorFactory.createCompressorOutputStream(outputStream).write(data);
            cache.put(key, outputStream.toByteArray());
        } catch (IOException e) {
            e.printStackTrace();
        }
    }

    public byte[] get(String key) {
        byte[] compressedData = cache.get(key);

        if (compressedData == null) {
            return null;
        }

        try (ByteArrayInputStream inputStream = new ByteArrayInputStream(compressedData)) {
            ByteArrayOutputStream outputStream = new ByteArrayOutputStream();
            CompressorStreamFactory compressorFactory = new CompressorStreamFactory();
            compressorFactory.createCompressorInputStream(inputStream).transferTo(outputStream);
            return outputStream.toByteArray();
        } catch (IOException e) {
            e.printStackTrace();
        }

        return null;
    }
}

The above code snippet shows the implementation of the CompressedCache class, which internally uses a HashMap to store the compressed data. The put method compresses the data using Apache Commons Compress and stores it in the cache, while the get method retrieves and decompresses the data using the same library.

Compressing the Cached Data

To compress the data before storing it in the cache, we use the CompressorStreamFactory class from Apache Commons Compress. This class provides various compression formats, such as GZIP, BZIP2, and ZIP. In our example, we will use the default compression format, which is GZIP.

import org.apache.commons.compress.compressors.CompressorStreamFactory;

// ...

CompressorStreamFactory compressorFactory = new CompressorStreamFactory();
compressorFactory.createCompressorOutputStream(outputStream).write(data);

In the above code snippet, we first create an instance of the CompressorStreamFactory. We then use it to create a CompressorOutputStream from the ByteArrayOutputStream (the output stream of our cache) and write the data to it. This will compress the data before storing it in the cache.

Retrieving and Decompressing the Cached Data

To retrieve and decompress the data from the cache, we follow a similar approach. We use the CompressorStreamFactory class to obtain a CompressorInputStream, which we read from and transfer the data to the ByteArrayOutputStream.

import org.apache.commons.compress.compressors.CompressorStreamFactory;

// ...

CompressorStreamFactory compressorFactory = new CompressorStreamFactory();
compressorFactory.createCompressorInputStream(inputStream).transferTo(outputStream);

In the above code snippet, we create an instance of CompressorStreamFactory and use it to create a CompressorInputStream from the ByteArrayInputStream (the input stream of our cache). We then transfer the data from the CompressorInputStream to the ByteArrayOutputStream, effectively decompressing the data.

Conclusion

In this blog post, we explored how to implement a cache with distributed compression using Apache Commons Compress and HashMap in Java. Caching data can significantly improve the performance of applications, and by compressing the cached data, we can optimize memory usage and reduce disk space requirements. Apache Commons Compress provides various compression formats, allowing developers to choose the most suitable format for their specific use cases.

By implementing a cache with distributed compression, we can achieve faster data retrieval and efficient memory usage, resulting in improved overall application performance.

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