Compression Techniques in Apache Spark

Apache Spark supports several light-weight compression techniques that can significantly reduce the size of your data, making it faster and more efficient to process. Here are some of the key techniques:

➡️ Dictionary Encoding

✅ When the values in a dataset are large and repetitive, a dictionary is created that contains the mapping information of the large values to some numeric key. This can drastically reduce memory utilization.
✅ For example, consider a column with repeated string values. Instead of storing this string multiple times, we can store a numeric key in the data and keep a dictionary that maps the key to the string.

➡️ Bit Packing

📌 Bit packing is a simple compression technique that uses as few bits as possible to store a piece of data. If done the right way, it can significantly reduce the data size.
📌 When used along with dictionary encoding, it gives the best compression.
📌 For instance, a numeric value that would typically require 32 bits for storage could be stored in fewer bits if the range of values is limited.

➡️ Delta Encoding

1️⃣ Delta encoding, also known as delta compression, is a compression technique that stores the data in the form of deltas (differences) between sequential data rather than the complete value.
2️⃣ For example, consider a sequence of timestamps or a sequence of increasing integer values. With Delta Encoding, it stores only the difference values and thereby drastically reduces the storage memory required.

➡️ Run-length Encoding

✅ Run-length encoding is a loss-less compression technique where data sequences having redundant data are stored as a single value along with the count of the number of times the redundant data appears in the sequence.
✅ For instance, a sequence of repeated characters or numbers can be stored as a single character or number along with the count, significantly reducing the storage space.

By understanding and effectively using these compression techniques, we can optimize Spark applications for better performance and efficiency.

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